Dr Adel M Sarea
email: adelsarea@yahoo.com

Dr Abdalmuttaleb M A Musleh Al-Sartawi
email: amasartawi@hotmail.com

Dr Azam Abdelhakeem Khalid

Electronic financial disclosure: Islamic banking vs conventional banking in GCC

Keywords: Financial accounting, Islamic banking vs conventional banking, Electronic Financial Disclosure, GCC

This paper examines electronic financial disclosure in Islamic banking vs conventional banking in Gulf cooperation council (GCC). A checklist was adopted to measure the level of electronic financial disclosure in Islamic banking vs conventional banking in GCC. The sample size consisted of total 90 banks in GCC (44 Islamic and 46 conventional) for the year 2017. The statistical analysis indicated that the overall level of of electronic financial disclosure (EFD) was 73 %, and 78.6% by Islamic banks and conventional banks respectively. The results also report a significant and positive relationship with firm size, and an insignificant relationship with profitability, and age. This paper should be particularly relevant to central banking authorities considering in banking sector in GCC for strategizing policies in the future of EFD as well as to serve as a guide for academic EFD in banking sector in GCC.

Introduction and Literature Review: Need for the Study

This study seeks to contribute significantly to all aspects of banking sector through the electronic financial disclosure (EFD) for both Islamic banking and conventional banking sector by determining the levels of disclosure of EFD. The need of disclosing more information through EFD are increasingly raised in the previous studies connected by different scholar from different countries including GCC countries, some of the most important of these incentives are: firstly, the need for the development of the appropriate institutional and regulatory framework. This is necessary to address the peculiar factors contributing to financial instability, while provide support and guide regarding the increasing globalization and liberalization with their potential crossborder effects. Secondly, it would enhance and facilitate timely, accurate and reliable information for investors [START_REF]The Effect of the Electronic Financial Reporting on the Market Value Added of the Islamic banks in Gulf Cooperation Council Countries[END_REF]Janifer, 2003).

Despite the numerous challenges currently facing Islamic financial system, there is no doubt that the Islamic financial institutions (IFIs) comprising mainly of Islamic banking has steadfastly lay a formidable foundation in term of Internationally recognized Islamic financial transactions (AL-Rawashdah, 2009).In this regard, the impacts on the levels of EFD for both Islamic banking and conventional banking sector in term of external and internal influence on Islamic banking such as, foreign investment, globalization, international capital markets, international accounting firms and multinational organizations are due to the internal influences such as socio-cultural, national economic development levels, local capital markets and accounting professional body (Warsame, 2006).

Islamic banking plays a major and important role in the Islamic economy system. The significance of this study emerges from the need of full information through EFD for both Islamic banking and conventional banking sector. Therefore, financial disclosure in Islamic banking is required to be prepared fairly and carefully. This will further enhance and improve the efficient operation of Islamic banks as an important player in the economies and an unambiguous source of a comprehensive development.

In this regard, this study attempts to evaluate the extent of the levels for both Islamic banking and conventional banking sector by determining the levels of disclosure of EFD. Furthermore, this study contributes to the accounting literature in terms of the impact of the changes in EFD on investors, regulators, accountants, and the media as well as on several other dimensions with expectation of assisting in the establishment of checklist for banking system in its operation.

The findings obtained from the current study are therefore expected to fill the gap in the literature review and contribute towards a better understanding and acceptability of the electronic financial disclosure for both Islamic banking and conventional banking sector. Therefore, as a result of the rapid increase in number of investors and shareholders in the financial markets, the need of disseminating financial statements has increased to fulfill the satisfaction of shareholders. Moreover, the disclosing of earning information by large firms requires being fair, it should be disseminated widely and simultaneously to the investors by internet [START_REF] Jorgensen | A Survey on the Dissemination of Earnings Information by Large Firms[END_REF].

Adopting EFD by companies has several benefits. Firstly, adopting internet financial disclosure enhances the companies' efficiency and attracts investors from all over the world. Secondly, EFD serves people who need to collect information about companies via internet. The users can easily access internet at any time, from anywhere and obtain efficient information inexpensively.

In addition, the adoption of EFD by the companies can enhance performance of these companies through the cooperating and exchanging of ideas, experiences and information between these companies. However, there are some factors that prevent companies from adopting EFD including: the necessity for a continuous updating of the information to benefit the users as much as possible, the illegality of requirements and the unwanted transparency in disclosing financial information. "Bin Au Khan & bin Ismail" (2012) summarize the advantages of the internet financial disclosure as: the globalism, investors' communication and timelines, whereas the disadvantages of exposing financial information electronic include the problems of privacy and security, cost and experiences. Based on the above discussion, it is clear that the investigation of the extant of adoption EFD by the listed banks in GCC is important in this study.

Recently, there have been too many researchers investigating the extent of disclosing financial reports electronic among firms all over the world. Researchers were interested in examining the effect of some selected characteristics (e.g. size, profitability, liquidity, leverage… etc.) on EFD companies. In related study, [START_REF] Khadaroo | Business disclosure on the internet in Malaysia and Singapore: A comparative study[END_REF] conducted a comparative study that compares the internet disclosure practices of Malaysian listed companies with those in Singapore. The study also examines the implications of web technology for business disclosure and the challenge it poses for standard-setting bodies. The results show that the companies listed in Singapore has more countenance than those in Malaysia. Moreover, the Singapore companies characterized more potential to use the Internet than those in Malaysia.

Electronic Financial Disclosure: A GCC Perspective

Several studies conducted in GCC discussing a number of issues related the EFD for both Islamic banking and conventional banking sector. For instance, the adoption of EFD to spread companies' information is a recent phenomenon and some studies consider its future implication. "Al-Motrafi" (2008) noted that the use of electronic financial disclosure in Saudi Arabia may involve rising the concerns of the accounting information disclosing, and this may lead users (such as auditors and regulators) to contribute in financial disclosure to extract regulations and moderate the use of EFD to fulfill statutory. Moreover, the researcher noted that firms may concentrate on innovation of EFD which may help companies induct a disclosure strategy to fulfill users satisfactory level (such as getting benefits by disseminating better information, and extant the companies communication). According to Al-Motrafi (2008) he examined the extent of using of EFD by Saudi public companies (113 companies); the researcher tested the influence of eight specific characteristics on disclosing financial disclosure attitudes. The study has found out that 95(84%) of the companies' own websites while only 51 companies (45%) are adopting EFD. Moreover, the findings of the study have noted that none of these companies possess comprehensive financial information. In addition, the study has also stated that firm's size and stock market are the main variables that affect the mount of corporate information posed.

Another study conducted by [START_REF] Oyelere | INTERNET FINANCIAL DISCLOSURE IN OMAN[END_REF] in Oman stock market, study showed that of the 142 firms, 59% (84 companies) had an accessible Web site, and of these 84 companies only 31(36.9%) provided financial information on their home page. In related study, Al-Moghaiwli (2009) conducted a study to investigate the extent of internet disclosure practices of Qatar listed companies on the Doha Securities Market (DSM). The results indicated that 90.6% (39 companies) had websites and a total of 28 (71.8%) of these companies provided complete form for financial disclosure via internet. the ownership, firm size, and profit ratio structure are the main factors influencing EFD adoption. Another study conducted in Kuwait by "Alanezi", (2009) A total number of 179 companies listed on Kuwaiti joint-stock (KSX) were investigated.

The variables of company size, type of auditors, profitability, liquidity, and leverage were examined. The study reported that 56% of the listed companies disclose financial information.

Momany and Pillai (2013) conducted an empirical study in the United Arab Emirates to investigate the extent of volunteer (EFD) among (UAE) firms listed on the Abu Dhabi finance market (ADX). 65 companies were examined, and the researchers used UAE electronic search engines to collect data. The researchers tested eight (8) characteristics including the effect of profit ratios, firm's volume, firm's age, the type of ownership and its concentration, debt ratios, corporate governance, and asset ratios.

The logistic regression analysis used as well as several statistical tests were done like correlation variance. The main results showed that 89% of the listed companies had special sites on the Internet whereas the other 11% did not have any sites. The study also found out that 60% of the firms on Abu Dhabi possessed web-sites provided financial information electronic while 40% of the firms did not provide corporate finance information online. In addition, the results showed that 91% of the companies provided comprehensive financial statements whereas 9% provided partial financial statements. In addition to that, the findings showed that profitability and corporate governance were the significant factors that affect the adoption of EFD.

A similar study conducted by Miniaoui & Oyelere in UAE (2013) to investigate the determinants of disclosing corporate financial information online. The study stated that the firm size, industry sector, the leverage, and profitability were the most important variables of volunteer EFD. The study results showed, "larger companies with greater leverage are more likely to set up a website and use it for EFD than smaller less leveraged ones". The logistic regression analysis used to examine the significant factors of EFD by the firms. The study noted that the banking sectors, investment and finance sectors and insurance sector had the major portion (62%) of EFD companies.

In addition to that, Joshi & Al-Modhahki (2003) conducted study in Bahrain and Kuwait to determine the extent of disclosing corporate financing information. A sample of 75 companies (Kuwait 42 and Bahrain 33) was selected. Six (6) characteristics were tested; company size, profitability, debt ratio, industry type, auditor size, and country effect. The researchers analyzed the collected data about these companies and deduced that 47.6% of Kuwait companies owned website, while 48.5% of Bahrain companies did. They also concluded that the size and industry were the most significant variables that affect adopting EFD. Another study was carried out by Mohamad & Oyelere (2008) to examine the practices of disclosing corporate information via internet in Bahrain.

The study was preparatory and limited since it didn't investigate an in-depth view of the potential practices. The researchers collected data available about all the 49 listed companies in Bahrain Stock Exchange (BSE). They used Google and Yahoo engines and telephone calls to investigate whether the listed companies own websites or not.

The study reported that 40(81.6%) of the companies possess websites while only 27(67.5%) of these companies were adopting EFD. Moreover, the findings showed that 34 companies provided historical information about themselves and 34 provided information about their services and products, whereas 31 companies provided financial information. In addition, the researchers stated that only 25 companies posed both annual reports and financial highlights.

Theory of Voluntary Disclosure: The Agency Theory

The agency theory interprets why organizations voluntarily disclose information primarily for stakeholders and public in general. The organizations believe that contact with agents is a good means for monitoring actions and this contact can be best achieved by disclosure of proper information. According to agency theory, there are conflicts of interest between two parties; outsiders and insiders. These conflicts are more likely to occur in larger organizations [START_REF] Mohammad | The voluntary disclosure of internet disclosure (EFD) in an emerging economy: a case of digital Bangladesh[END_REF]. This indicates that the advantage of disclosing information is correspondingly greater. The managers (insiders) usually need to be trustworthy to the shareholders (outsiders) through the reduction of agency cost by disclosing more information about the organization (Sweiti, and Attayah, 2013).

"Francis et al"; (2002) has argued that less outsider ownership results in less information asymmetry between the insider and outsider shareholders; therefore, ownership concentration reduces the need for strong corporate governance and transparency. According to "Zimbwa", (2005) companies with a greater concentration of shareholding are likely to have lower levels of transparency and thus not disclosing information whereas companies with higher leverage ratios are more likely to have higher levels of transparency and disclose more information as a result. This leads to the assumption that there is a relation between the firm's size, leverage and cost and benefits on the one hand and the disclosure of information on the other.

Research Design and Methodology

Sample Selection

The empirical study of the current research depends on a population which consists of all the listed banks in the GCC bourses for the year 2017. However, the required data were gathered from 90 banks (44 Islamic, and 46 conventional) out of 110 banks listed in the GCC bourses. Some of the banks were excluded from the study because they are suspended and closed, some of them their website was not functioning and some of them did not have an investor relations section on their websites. Moreover, the researchers used the banks' websites and the GCC Bourses websites to gather the data required for this study.

Measuring the level of Electronic financial disclosure:

For the current study the researchers have adopted a checklist used by Al-Sartawi (2016) Alrawahi & Sarea (2016) & Al jawder & Sarea (2016) consisting of 90 items (71 items for content and 19 items for presentation) to measure the EFD. Therefore, the EFD index is based on binary, that is, if a bank reported an item which was included in the checklist it received a score of 1 and if the bank did not report an item, a score of 0 was allocated. Accordingly, the Index for each bank was calculated by dividing the total earned scores of the bank by the total maximum possible score appropriate for the bank.

Below formula shows the way of calculating the EFD index.

𝐸𝐹𝐷 = ∑ 𝑑𝑖 𝑛 𝑖=1

Where: di: disclosed item equals One if the bank meets the checklist item and Zero otherwise. n: equals maximum score each bank can obtain.

Research Design and Methodology

Dependent Variable

Several research studies have addressed the issue of electronic disclosure in the GCC countries (Al-Sartawi, 2016, and Al-Sartawi, 2018). These studies have investigated the effect of several variables on EFD like corporate governance, and institutional investor. Yet there are negligible studies that actually investigate the association of firm characteristics with EFD Accordingly, this study would be an important contribution in filling the gap in the current literature by determining whether there is a relationship between the level of EFD and the type of banks that are listed in the GCC Bourses.

Independent Variables

Type of Bank

Previous studies conducted in several countries are used "type of bank" as independent variable, for instance, Heffernan & Fue (2008) they used dummy for type of bank: whether national joint stocks, city commercials and rural commercials. This bank dummy variable will provide a measure of the relative performance of the selected banks. This study could help in filling the gap in the literature by determining whether there is a postive relationship between the level of EFD and the type of banks in GCC.

Control Variables

Profitability (ROA)

However, based on Singhvi and Desai (1971) companies disclose more information when its profitability is above industry average in order to signal to the owners about its strong position to survive. Many studies have examined the relationship between profitability and the level of EFD (Oyelere et 2012), larger companies are more perceptible, and as a result, may be more likely to disclose more information. Similarly, Adebimpe and Ikenna (2013) argue that large companies usually operate over wide geographical areas and undertake many products along with several divisional units. Hence, it is assumed that they have wellbuilt information systems that enable them to trace both financial and non-financial information for operational, tactical and strategic purposes. Moreover, Agboola and Salawu claim that the arguments in the literature lend support to higher disclosure by larger firms.

Age

Finally, with regards to age, previous studies reveal that there is a positive relationship with the level of EFD: Akhtaruddin (2005), Al-Shammari (2007). Older companies may be more motivated to disclose such information, as the disclosure is less likely to hurt their competitive position (Agboola and Salawu, 2012) Therefore, older companies might have better and established reporting systems than newer companies. Therefore, based on the signaling theory, and theoretical and empirical literature, this paper establishes the following hypothesis as: H1: There is a positive relationship between the type of the banks (Islamic or conventional) listed in the GCC Bourse and the level of EFD.

Model:

The following regression model was used to test the hypothesis. The regression model was developed using the EFD as dependent variable, the type of banking as independent variable, and the firm characteristics as control variables. 𝐸𝐹𝐷 𝑖 = 𝛽 0 + 𝛽 The difference between the establishing date of the firm and the report date εi Error

6 Research Findings

Descriptive Analysis

As mentioned earlier, the level of EFD is measured by dividing the total score of every bank by the maximum probable scores. In 2000, the Financial accounting standards board (FASB) identified the two dimensions of financial reporting as both the content and presentation of information disclosed by companies' websites. Consequently, based on the adopted index, the maximum score of the EFD was 90 items constituting content dimensions of reporting and presentation dimensions. Where the content dimension included 71 items, the presentation dimension included 19 items.

The results shown in table [START_REF] Adebimpe | Internet financial reporting and company characteristics: A case of quoted companies in Nigeria[END_REF] suggest that the level of EFD was differed between Islamic and Conventional Banks. The conventional banks level was 78.6% and the Islamic banks level was 73%. This could be due to the characteristics and the regulation of conventional banks comparing to the Islamic banks, both types are working in GCC countries, but the Islamic banks still did not have its separate standers for disclosures. Overall, the results show that the level of electronic financial disclosure by the two types of banks can be considered as a fairly good level of reporting since the differences between them were not significant at the level of 5%.

Validity

To test the validity, the model of the study was checked for multicollinearity which involved conducting the Variance Inflation Factor (VIF). The VIF should be lower than 10 and tolerance should not be below 0.2 (Field, 2005). The VIF scores for each variable are reported in Table [START_REF] Agboola | The Determinants of Internet Financial Disclosure: Empirical Evidence from Nigeria[END_REF]. The results indicate that since no VIF score exceeded 10 for any variable in the model, while no Tolerance score was below 0.2. So, it was concluded that there is no threat of multicollinearity.

Testing the Hypotheses

Table [START_REF] Agyei-Mensah | Corporate financial reporting: Firm characteristics and the use of internet as a medium of communication by listed firms in Ghana[END_REF] reports the findings of the regression analysis of the model. These findings show that the value of calculated F-Statistic for the model is 2.799 at a confidence level 95%, where the p-value for the model is less than 5% at 0.022. This finding supports the significance of the regression model statistically. The results as shown in the above table indicate a negative relationship between the level of EFD and the type of bank (Islamic or conventional), which could be due to Islamic banks disclosing less electronic financial information when compared to conventional banks as indicated by the overall levels of EFD. Reasons for this could be due to the high experience and age associated with conventional banks. Moreover, there is no clear regulation for disclosure in Islamic banks, and at the same time the Islamic banks follow double regulations which include both the Islamic standards and the central banks standards.

The firm characteristics such as profitability indicate that there is a positive but insignificant association with EFD, as the significance levels of the Return on Assets (ROA) variable is 0.154. This result is in line with the results reported by [START_REF] Ashbaugh | Corporate Reporting on the Internet[END_REF], and Xiao et al. (2004). Thus, could be due to the profit and loss sharing (PLS) principle in Islamic banking when compared to conventional banks, where Islamic banks are protected and have more stable profits. Another reason could be related to the Islamic principle of trusteeship (Amanah) i.e. due to the trust between managers and investors, managers might not have the need to signal their justification for their compensation packages.

Regarding size, the study found a significant and positive relationship with EFD, i.e. significant at 0.004 as larger firms tend to have more resources than smaller firms, and therefore it is expected that they have efficient information systems that enable them to easily trace information for operational, tactical, and strategic purposes. This study also failed to find an association between age and EFD at a significance level of 0.817. This is in line with the results of Adebimpe & Ikenna, (2013), and Yusuf, (2013) who also found an insignificant relationship with age. The insignificance of age shows that experience with investor relations does not necessarily encourage banks to undertake more advanced means of financial reporting such as EFD. One reason for this could be that when compared to conventional banks, Islamic banks in the GCC are relatively young.

Consequently, we can summarize that the level of EFD by the GCC banks has a positive relationship with size and a negative relationship with bank type. Moreover, it has a positive yet insignificant relationship with profitability and age.

Conclusion and Recommendations

This research study set out to examine and report on the extent and firm characteristics that determine the practices of EFD by Islamic banks vs conventional banks in the GCC countries. This paper is an important contribution to filling the gap in the literature, as there are a limited number of studies which deal with EFD from such a perspective. The paper creates awareness regarding EFD that might prove beneficial to the various stakeholders including investors, regulators and preparers of financial statements. Data was collected using the websites of 90 banks listed on the stock markets in the GCC countries for 2017. A checklist was adopted from Al-Sartawi (2016), Alrawahi & Sarea (2016) & Al jawder & Sarea (2016) to compute the total level of EFD.

The index measured both the content and presentation dimensions of the websites and online reports. This study found that the overall level of EFD in the GCC by Islamic banks is 73 %, while the level of EFD by conventional banks was 78.6%. The results report a significant negative relationship with bank type, and a positive relationship with firm size. On the other hand, the results show an insignificant relationship with profitability (ROA), and age. It can be concluded that that larger banks disclosed more financial information on their websites due to the availability of resources where they can benefit from the resulting lower costs. This is consistent with the agency theory that large firms attempt to reduce the high agency costs associated with information asymmetry between the management and investors by disclosing a large amount of information.

This study recommends that Islamic banks use the internet to improve their exposure and the availability of financial information when compared to conventional banks. For example, based on Agoobala and Salawu (2012) many of the processes that occur in remote places can be automated and fed into a firm-wide information system or intranet. Moreover, to promote the uniformity in disclosure by Islamic banks, both regulatory and professional bodies should jointly provide a template for EFD.

  This result is similar to Agboola and Salawu (2012), Hossain et al. (2012), and Omran and Ramdhony (2016).

  1 𝐵_𝑇𝑦𝑝𝑒 𝑖 + 𝛽 2 𝑅𝑂𝐴 𝑖 + 𝛽 3 𝐿𝐹𝑆𝑍 𝑖 + 𝛽 4 𝐴𝐺𝐸 𝑖 + 𝜀 𝑖

	Where:
	Code	Variable Name	Operationalization
	Dependent variable -:
	EFD	Electronic Financial Disclosure %	Total scored items by the company/Total maximum scores
	Independent Variables -:
			This is a binary Wherein 1 means
	B_Type Bank Type	that the bank is Islamic and 0
			conventional
	Control Variables-:
	ROA	Returned on assets	Net income / Total assets
	LFSZ	Firm size	Natural logarithm of Total Assets
	AGE	Firm Age

  Difference is significant at the 0.10 level.Additionally, the descriptive statistics for control variables, i.e. the firm characteristics, in table[START_REF] Agboola | The determinants of internet financial reporting: Empirical evidence from Nigeria[END_REF] show that the mean of ROA is 0.10. As for the mean of firm size, i.e. Total Assets, it was 1.49 million, with a minimum of 367246 million and a maximum 1719741907. The normality distributions of total assets were skewed. Hence, natural logarithm was used in the regression analysis to reduce skewness and bring the distribution of the variables nearer to normality. Finally, the bank age ranges from 4 to 62 with a mean of 19, indicating fairly young banks.

			Table (1)
		Level of electronic financial disclosure
	Bank Type	N.	EFD		Independent Samples Test
			Mean S. D	t-value	Sig
	Islamic	44	.7308	.19341
	Conventional	46	.7857	.19341
	Total	90	.7588	.18130	-1.444	0.076*

*

Table ( 2) Descriptive statistics for dependent and control variables

 (

	Variable	Min.	Max	Mean	S. D
	ROA	-.05	.85	.0997	.12438
	Size	367246	1719741907	1.49E8	2.669E8
	Age	4	62	19.14	14.471

Table ( 3) Collinearity Statistics Test

 (

	Variable	Tolerance	VIF
	Type	.933	1.072
	ROA	.739	1.354
	Size	.992	1.008
	Age	.771	1.297
	Additionally, the researchers conducted the Pearson correlation test to measure the
	correlation between the dependent and independent variables. The results of the
	pairwise correlation presented in table (4) below demonstrate a weak correlation
	between the variables where the correlation does not exceed 0.449.


George Chimowa

Lin Yang

Pierre Lonchambon

Teresa Hungria

Lucien Datas

Christophe Vieu

Emmanuel Flahaut

Tailoring of DWNTs for formaldehyde sensing through encapuslation of selected materials

Keywords: Carbon nanotubes, Metal encapsulation, Chemo-resistive sensor, Formaldehyde

Tailoring carbon nanomaterials for specific applications is of great importance in the quest to improve the properties of these materials and hence increase their functionality. Using a simple and easy to apply technique Zinc, Zinc oxide and Iodine were encapsulated and confined within double walled carbon nanotubes whose internal diameter ranges from 1.2 to 2.5 nm. The simultaneous confinement of Zinc and Iodine was shown to improve the sensitivity by 100 times while at the same time enhancing the selectivity of DWNTs towards formaldehyde. By exploiting the p-doping effect of Iodine, CNTs networks were engineered to differentiate formaldehyde from ethanol and acetone, some of the common volatile organic compounds. The ability to tune the chemical selectivity and sensitivity of carbon nanotubes based sensors through inner encapsulation of a specific material thus appears as a new possible route compared to more conventional outer surface functionalization.

1 Introduction: Formaldehyde is one of the most common and well known indoor air pollutants [1]. It has also been classified as a group one carcinogen for human beings even at low concentration of 0.1 ppm and yet it is found in many household products such as cleaning and building materials [2][3][4]. There is therefore a need for a cheap, sensitive and selective, sensor that can be used for real time monitoring of this volatile organic compound in houses and factories.

Carbon nanotubes have emerged as potential good candidates for the fabrication of cheap chemoresistive sensors for room temperature gas sensing [5]. This is because of their intrinsic electrical properties and their large s p e c i f i c surface area making them sensitive t o g as m olec u les a ds orp t i on . Their e a s y i n t e g r a t i o n a t t h e nano-scale makes them ideal for large sensor array miniaturisation. However, despite these positive attributes, metallic CNTs still suffer from poor selectivity and stability when compared to metal oxide based gas sensors [6]. Furthermore pristine CNTs have been shown to be poorly sensitive, when compared to metal oxides [7]. The gas sensing mechanism and selectivity of pristine CNTs is somewhat complicated because of a number of issues such as the mixture of semiconducting and metallic tubes, resulting in resistance modulation due to the different inter-tube junctions and different charge carrier mechanisms such as hole (p-type) and or electron (n-type) transport. Another factor is the wide varying levels of defect states due to different purification methods.

The sensitivity of pristine CNTs can however be improved greatly by either surface functionalisation or metal incorporation or encapsulation as has been shown by many researchers [8][9][10][11]. Vanadium encapsulated in multi-walled CNTs with 10 to 15 inner walls was shown to improve the sensitivity by about 1.5 % [12]. This suggests that using CNTs with fewer walls such as single, double or triple walled CNTs would induce an even higher sensitivity improvement. This is expected because the in-direct gas interaction with the encapsulated metal would be greater. In this work we propose to investigate the role of selected compounds, encapsulated inside double walled CNTs (DWNTs) with the objective to tailor them for Formaldehyde gas detection.

Metal oxides have been the dominant material of choice for chemo-resistive sensors because of their high sensitivity and stability but their drawback is the need to operate at high temperatures (between 120 to 300 o C) in addition to the slow response/recovery times when compared to CNTs [13][14][15]. Zinc oxide in particular has been one of the most popular materials for designing gas sensors and is able to detect low levels of formaldehyde down to 1 ppb with "detectable response" of 7.4 (ratio of electrical resistance with and without gas) [16]. Therefore it makes sense to suggest that a combination of DWNTs and ZnO materials would make a good sensor combining high level of sensitivity, fast response and recovery times, able to work at room temperature. This is the main hypothesis tested in this work.

Encapsulating metals in CNTs can boost electronic transport in CNTs without reducing the carbon active sites at their surface responsible for their sensitivity [17][18][19]. In other previous works (Ref 12), it has been shown that metal and /or metal oxide encapsulation increases the density of states around the Fermi level, which helps to improve sensitivity.

The tuneable density of states and the extended π -conjugation bonding in CNTs (which accounts for most of their electronic properties) makes it possible to tailor the gas adsorption properties of CNTs. Furthermore confinement of metal oxides at nanometer scale inside, 1D spaces is expected to promote new and original phases of the material [20] which in some way may enhance selectivity as certain phases should respond better to certain gases than others. More work on this aspect is still on-going [21].

In this work we however focus on improving the sensitivity of DWNTs towards gases by encapsulating Zinc and Zinc oxide inside the tubes.

We also attempt to tune the selectivity by introducing Iodine into the ensemble, which results in p-doping of the CNTs making p o s s i b l e semiconducting tubes to exhibit metallic behaviour at room temperature.

In a nutshell this work highlights our attempts to tailor DWNTs so that they can be used as sensitive and selective sensors of f o r m a l d e h yd e vapour.

From high r e s o l u t i o n TEM and STEM, EDX, XPS as well as electrical resistance measurements, the influence and role of Zinc and / or Zinc oxide or Iodine encapsulated in DWNTs is discussed. We assess the selectivity aspect by c o m p a r i n g t h e r e s p o n s e o f o u r m a t e r i a l t o other g a s e s vapours such as ethanol and acetone. This article is organised as follows, section 2 details the experimental setup. In section 3.1, we present the results from the structural characterisation of the material while the results on the vapour sensing in nitrogen atmosphere are discussed in section 3.2. The last section discusses gas sensing in air, and illustrates the competition between n-type and p-type conductivity in DWNTs that occurs in air. After this some discussion on selectivity is presented. We also give a brief discussion on the sensing mechanisms that strongly consolidates the results. The article concludes by some general discussion on future work.

Experimental

Synthesis and filling of DWNTs

Double walled carabon nanotubes were synthesized as described in Ref [22]. Molten Zinc compounds were used to fill the DWNTs after synthesis as outlined in Ref [23]. One batch was filled using Zinc acetate (bought from Sigma Aldrich) producing Zinc and / or Zinc oxide filled DWNTs after an appropriate heat treatment [23], while another one was filled by Zi nc iodide (ZnI 2 ) (also bought from Sigma Aldrich) l i k e l y resulting in a mixture of ZnI ging was done using a Hitachi S -4800. Figure 2 shows the HRTEM images of unfilled and filled DWNTs. The identity of the filler material was further confirmed using XPS, see Fig. 4(a andb). From Fig. 4(b (i)) the unusual double peak of the O1s, suggest that the Zinc is in the Zn(OH) 2 environment, but more studies are needed to confirm this hypothesis [25]. The presence of the Auger peak associated with the Zn2p peak at 992 eV might be taken as an indication of Zinc buried under carbon supporting the HRTEM analysis which confirmed that the Zinc is encapsulated inside CNTs.

Results and Discussions

Gas response in Nitrogen atmosphere

After confirming the identity and the amount of the filler material, two probes electrical resistance measurements were performed at various mass concentrations of formaldehyde and other volatile gases ranging from 1.8 to 4 % as calculated using

Gas response in synthetic air atmosphere

When the same tests using formaldehyde were performed in synthetic air (Fig.

The role of Iodine on the gas response

To confirm that Iodine and not Zinc was responsible for the doping effect and the peculiar response of the Zinc Iodide filled nanotubes, Iodine only filled DWNTs were also tested with formaldehyde and ethanol and the results confirmed that the peculiar response of Zinc Iodide was likely due to Iodine doping as shown in Fig. 7. As observed earlier the introduction of the formaldehyde vapour results in a decrease in resistance/response for the Iodine only filled DWNTs. This confirms that the gas sensing mechanism for this sample and that of ZnI 2 filled sample is similar. Be-cause the response of the Iodine (only) filled tubes was weaker we only showed results at higher mass concentration greater than 2.8 % to illustrate the question about the mechanism. We also compared it with the response to ethanol which showed a different sensing mechanism, in which the resistance increases as this was the case with Zinc Iodide doped sample (Fig. 7). The graph (Fig. 8) shows that the response mechanism of the Zinc Iodide -filled DWNTs to ethanol and acetone is different to its response to water or formaldehyde vapour. In this regard this material is exhibiting some selectivity. Ethanol and water are very similar solvents but however the Zinc Iodide -filled sensors showed relative selectivity which we might attribute to the difference in the electron affinities of water (0.8 eV [29]) and ethanol (1.82 eV) [30]. With this background, water vapour then appears as the only competing gas with formaldehyde.

Since formaldehyde was dissolved in water, we then sought to establish if the observed response was due to water or formaldehyde. Different solutions (by concentration) of formaldehyde in water solution were prepared and tested. From Fig. 9, the response of the more dilute solutions was higher than for the more concentrated. This observation can be attributed to either the increased volatility of the dilute solutions, which means that more molecules of the formaldehyde are carried onto the DWNTs by the nitrogen gas or that the higher water content in dilute solutions was increasing the response. However the second argument was then ruled out, when we compared the 0.04 g/L to the 0.004 g/L solution. If the water content was the main driving factor then the 0.04 g/L solution would be expected to lead to a higher response, which is not the case and therefore supporting the first argument. In this regard it was observed that our sensors were stable within the four months of the experiments.

However for commercialisation more dedicated studies on stability and detection limit would be needed.

Conclusions

  2, Z n O and possibly iodine f i l l e d DW N T s . T h e l a s t b a t c h c o n t a i n e d DWNTs filled with only Iodine as follows: solid Iodine was mixed with raw DWNTs in a mortar in the ratio 3:1 respectively. The mixture was sealed under vacuum in an ampoule after nitrogen purge. The sealed ampoule was heated from room temperature (at this temperature for 24 hours. It was cooled at a slow rate of 0.1 o C/min and then washed in absolute ethanol until the filtrate was colorless. 2.2 Fabrication of sensing devices The sensor devices were fabricated by liquid stencil lithography using PDMS (Poly-DiMethylSiloxane) stencils and liquid phase pipetting of a suspension of the DWNTs of interest in ethanol. To remove the organic solvent, the deposited films were heated at 80 C for 30 min in an oven. To ensure repeatability and reproducibility of the devices a constant concentration of 0.1 mg/L of CNTs in ethanol was used. The PDMS stencil was previously aligned on gold microelectrodes deposited on oxidised silicon substrates by conventional optical lithography and lift-off process. Each device (1 cm x 2 cm) is equipped with a set of 7 DWNT based resistors. Each resistor can accommodate a different suspension of DWNTs (either obtained from pristine DWNTs or from filled DWNTs using the different compounds previously mentioned), allowing a multiplexed (up to 7) detection see diagram Fig 1. Four different devices were tested per each sample batch. Formaldehyde, ethanol, acetone and water vapors, were used as the gases for two probe resistance measurements which were performed at room temperature using the setup illustrated in Fig.1. As shown in figure 1 the different gases injected inside the sensing chamber were obtained after controlled bubbling of a gas carrier (dry Nitrogen or Air) inside an aqueous solution of controlled concentration. The liquid solutions used in our experiments were brought from Sigma Aldrich and used in their absolute state with at acetone and ethanol at 99.95% and 99.98% purity respectively. However formaldehyde was intentionally diluted in deionized water at volume concentration of 0.04g/L or 0.004g/L.

Fig 1 :

 1 Fig 1: Illustration of the gas sensing system with LABVIEW software used for controlling the Keithley source meter and recording the data. Inset, a,b and c, typical SEM micrographs of sensing area of the device showing (a) the connection of DWNT networks to the gold electrode and (b, and c) entangled DWNTs between electrodes at different magnifications.

  purification of the four kinds of DWNTs, structural characterisation of the nanotubes was performed using High Resolution Transmission Electron Microscopy (HRTEM) and Scanning Transmission Electron Microscopy (STEM) performed using a JEOL cold-FEG JEM-ARM200F operated at 200 kV and equipped with a probe Cs corrector reaching a spatial resolution of 0.078 nm. EDX spectra were recorded on a JEOL Centrurio SDD detector from which we obtained an estimate of the elementary mass composition of the filled CNTs. SEM ima-

Fig 2 :

 2 Fig 2: (a) (i and ii) HRTEM images of empty DWNTs showing individual and bundled DWNTs (b) STEM (i) High-angle annular dark field (HAADF) image of Zinc Acetate filled

Fig 3 :

 3 Fig 3: HAADF-STEM image and EDX analysis of the filled DWNTS (a) Zinc acetate filled DWNTs (b) Zinc iodide filled DWNTs.

equation 1 .

 1 The vapour to be detected was diluted in nitrogen gas or dry synthetic air and its relative concentration was controlled by adjusting the mass flow rate in the different branches of the experimental set-up shown in figure 1. The percentage mass concentration (C %) was calculated using equation 1. , where the symbols stand for the partial pressure of the vapour at 25 o C, , the total input pressure which was kept at 1.2 Bar, the mass flow rate inside the bubbling branch, the mass flow rate inside the pure gas carrier branch. The sensor's response is defined as , where is the resistance in the presence of the vapour, while is the resistance in the carrier gas (air or nitrogen). In most of the discussions the sensor's response was used instead of the actual resistance (nonethless highlighted in the supplimentary data, Fig. S1) so as to enable easy comparison of the different samples. As a matter of fact, CNT network devices are well known to have different resistance values due to non-uniformity, which jusitfies the use of response for easy comparison.

Fig 4 :Fig 5 :

 45 Fig 4: (a)(i) XPS survey spectra of raw DWNTs (ii) XPS survey spectra of Zinc acetate filled DWNTs (iii) XPS survey spectra of Zinc iodide filled DWNTs (b) (i) The O1s peaks of ZnI2 filled DWNTs (ii) The I3d peaks for iodine filled DWNTs.

Fig 6 :

 6 Fig 6: Schematic of the sensing mechanism as envisioned for different DWNTs samples under investigation. An approaching formaldehyde molecule will draw electrons from the DWNTs; this will push the Fermi level (Ef) down when the n-type DWNTs dominate the conduction (a and b) or push the Fermi level up when p-type DWNTs dominate (c).

  Fig. 5(b)) the response increases initially upon formaldehyde introduction but as more air increases (which is the carrier gas) in the chamber the response begins to decrease whilst still on the same cycle. This is clear evidence of competition between n-type and p-type conductivity. The initial increase in response is due the dominate n-type conduction in mixed DWNTs but as more air (oxygen) increases in the chamber it p -dopes the DWNTs, resulting in the decrease in response. Increasing vapour concentrations to 2.8 and 3.2 % (i.e. first and second cycle respectively of Fig. S2, supplementary data), results in more air into the chamber. It was observed that the initial increase in response upon vapour introduction disappeared and replaced by a decrease with some small steps in response. This is supports the ex-

Fig 7 :

 7 Fig 7: Response of iodine (only) -incorporated DWNTs to 2.8 % mass concentration of ethanol or 3.2 % of formaldehyde in nitrogen atmosphere (as calculated using equation 1). The second cycle is when vapour concentration was increased by 0.4 % by increasing the flow rate of the carrier gas. The olive green dotted vertical lines show when the respective vapour was introduced and the red lines indicate when the vapour was closed.

Figure 8 ,

 8 Figure 8, investigates in more details the changes of sensing mechanism of ZnI 2 filled DWNTs as a function of the stimulant gas (i.e. acetone, ethanol, formaldehyde and water) in nitrogen atmosphere. The stimulant solvents for this particular investigation were used in their original commercial concentration in water solution from the supplier with the exception of formaldehyde that was diluted to 0.04 g/L in water from the original 0.4 g/L.

Fig 9 :

 9 Fig 9:Response of Zinc Iodide filled DWNTs to 2.8 % (as calculated using equation 1) of formaldehyde diluted at different concentrations in deionised water. The second cycle is when vapour concentration was increased by 0.4 % by increasing the flow rate of the carrier gas. The olive green dotted vertical lines show when the respective vapour was introduced and the red lines indicate when the vapour was closed.

  In conclusion, we have managed to tailor or tune the response of DWNTs towards formaldehyde sensing in two ways but using one salt, Zinc Iodide. Filling DWNTs using, Zinc Iodide results in encapsulation of both Zinc and Iodine in the nanotubes. The enclosed Zinc improves the sensitivity by two orders of magnitude while the iodine enhances the selectivity towards formaldehyde by making the DWNT ensemble (network) predominantly metallic from a state of mixture of metallic and semiconducting DWNTs. Our main observation is that metal encapsulation has been shown to be another ideal route to enhance response sensitivity of DWNTs without compromising the response time as there is no direct interaction between the gas and the encapsulated material. It therefore offers an alternative route for manipulating the electronic properties of DWNTs for a desired application. In this regard we have laid a strong foundation for the application of DWNTs in formaldehyde sensing and thus increasing the functionality of the material.

Table 1 ,

 1

summarizes the elementary composition of the filled CNTs and it shows that Zinc content in ZnI 2 filled DWNTs is less compared to that in Zinc acetate filled DWNTs. This probably has a significant effect on the sensitivity of the material as shall be discussed later.

Empty individual tubes

Empty bundled tubes

Table 1

 1 Elementary composition of the filled DWNTs, obtained by EDX as an average of data from three different spots probed with same number of counts.

	Element	Zinc acetate	Zinc Iodide Filled
		Filled DWNTs	DWNTs
		Mass %	Mass %
	C	93.1	89.3
	O	1.8	0.7
	Zn	4.3	1.8
	I	(Not Present)	6.3

Acknowledgements

The research leading to these results has received funding from the European Union Sev-enth Framework Programme under grant agreement n°604391 Graphene Flagship. We would like to also acknowledge the technical support from Mr Frank Carcenac in developing the wafers substrates for the gas sensing devices.


Guillaume Touya
email: guillaume.touya@ign.fr

Andreas Reimer
email: andreas.reimer@geog.uni-heidelberg.de

G Touya Cogit

Inferring the Scale of OpenStreetMap Features

Keywords: Generalization, Scale, Data Quality, Level of Detail, OpenStreetMap 1

Traditionally, national mapping agencies produced datasets and map products for a low number of specified and internally consistent scales, i.e. at a common level of detail (LoD). With the advent of projects like OpenStreetMap, data users are increasingly confronted with the task of dealing with heterogeneously detailed and scaled geodata. Knowing the scale of geodata is very important for mapping processes such as for generalization of label placement or land-cover studies for instance. In the following chapter, we review and compare two concurrent approaches at automatically assigning scale to OSM objects. The first approach is based on a multi-criteria decision making model, with a rationalist approach for defining and parameterizing the respective criteria, yielding five broad LoD classes. The second approach attempts to identify a single metric from an analysis process, which is then used to interpolate a scale equivalence. Both approaches are combined and tested against well-known Corine data, resulting in an improvement of the scale inference process. The chapter closes with a presentation of the most pressing open problems

Introduction

Studying the quality of OpenStreetMap (OSM) data has been a hot research topic in recent years, as OSM has grown and applications flourished. OSM quality can be assessed by comparisons with a reference dataset [START_REF] Haklay | How good is volunteered geographical information? a comparative study of OpenStreetMap and ordnance survey datasets[END_REF][START_REF] Girres | Quality assessment of the french Open-StreetMap dataset[END_REF][START_REF] Zielstra | A comparative study of proprietary geodata and volunteered geographic information for germany[END_REF], with intrinsic measurements [START_REF] Barron | Towards intrinsic quality analysis of OpenStreetMap datasets[END_REF], with contributor trust inference [START_REF] Skarlatidou | Trust in web GIS: the role of the trustee attributes in the design of trustworthy web GIS applications[END_REF], Kessler et al. 2013), or in a fitness for use context, like pedestrian routing [START_REF] Mondzech | Quality analysis of OpenStreetMap data based on application needs[END_REF]. The latter method is the concern of this chapter, particularly the assessment of the fitness of OSM data for high-quality cartography [START_REF] Sester | Integrating and Generalising Volunteered Geographic Information[END_REF]. Besides being crucial for automated derivation of cartographic products, scale evaluation also touches issues for the appraisal of OSM data for geographic analyses, linking the issue with the bigger problem of scale in Volunteered Geographic Information (VGI) (Jokar 2014, Feick and[START_REF] Feick | A multi-scale approach to exploring urban places in geotagged photographs[END_REF].

OSM data can be very rich in the regions with good completeness, but the level of detail of objects is very heterogeneous [START_REF] Touya | What is the level of detail of OpenStreetMap?[END_REF]. For instance, Figure 1 shows three very complex religious buildings: the first one is captured with many details while the others are captured coarsely. This heterogeneity is a major obstacle for automated cartography, as existing automatic processes, like map generalization processes, are parameterized for a given homogeneous input scale. As a consequence, producing smaller scale maps by automatic generalization requires the inference of the initial scale or level of detail for every object as it can be different for each. Even for the production of large-scale maps (e.g. city plans) where map generalization is not necessary, level of detail is important. By introducing confusion in the spatial relations between detailed and less-detailed objects, such inconsistency may mislead the map reader. Whether a building is actually in a clearing or in a patch of woodland that was imported from a generalized source or even incompletely mapped is undecidable without some information on scale [START_REF] Touya | Detecting Level-of-Detail inconsistencies in volunteered geographic information data sets[END_REF]. Apart from cartographic communication, investigations into land cover/land use obviously face similar problems. Two concurrent methods have been proposed to infer the scale/LoD of OSM objects individually [START_REF] Touya | What is the level of detail of OpenStreetMap?[END_REF]Brando 2013, Reimer et al. 2014). In this chapter, we review and compare both methods to improve the quality of scale/LoD inference for OSM. The second section discusses the cartographic and geographic notions of scale and level of detail. The third section briefly presents both scale inference methods, while Section 4 explores how these methods can be combined to improve the scale inference of OSM data. Section 5 describes how scale inference can be used to enhance the automated mapping techniques for OSM data, to illustrate the usefulness of the research. After a discussion in the sixth section, the chapter is concluded and further research is proposed.

Scale and Level of Detail

All scientific modelling approaches implicitly or explicitly must deal with the question of the conceptual and numerical relationships between reality and the model being created. In the most straightforward interpretation, a numerical relationship between reality and the model is the ratio of values in reality to values in the model. For all spatial sciences and endeavors, be they model railroads or traffic simulations, informative numerical ratios as an expression of the reality-model relationship are based on geometries. For maps as graphical models of geographic phenomena, the ratio between distances as measured on the map and as measured in reality is called "scale" (International Cartographic Association 1972). As it has so far been inefficient to provide maps at an arbitrary scale, mapping agencies have prepared maps and map series at certain scale groups. Furthermore, in cartography, scale has become shorthand for usage environment for the map and conceptual organization of the subject matter depicted. Freitag (1962) writes: "The scale of a map is one of its constitutive elements; it determines information density, readability, significant contents and area of application." Due to this historical development, the seemingly objective and quantifiable numerical scale has become attached to precepts about the conceptual relations between geographic reality and its graphical model (Freitag 1962, Bollmann andKoch 2002). This was driven by and is congruent with developments in geography [START_REF] Sudgen | Scale, systems and regional geography[END_REF] and other geosciences such as ecology [START_REF] Steinhardt | Die Theorie der geographischen Dimensionen in der Angewandten Landschaftsökologie[END_REF][START_REF] Levin | The problem of Pattern and Scale in Ecology[END_REF][START_REF] Chave | The problem of pattern and scale in ecology: what have we learned in 20 years?[END_REF]). In all cases, ranges of numerical scales are grouped into conceptual hierarchies. Consequentially, each level of the hierarchy is understood to be the realm of certain phenomena and specialized research methods only applicable within the bounds of that level. [START_REF] Haggett | Scale Standards in Geographical Research: A new Measure of Areal Magnitude[END_REF] proposed normalization over the surface of the earth as the basis for a logarithmic subdivision as a "yardstick" (G-scale) for a continuous hierarchy of modelling perspectives. Without any direct connection to the geosciences or cartography, computer graphics research saw itself confronted with the problem of "enhancing performance and realism" of "computer produced pictures" for graphical models of reality [START_REF] Clark | Hierarchical Geometric Models for Visible Surface Algorithms[END_REF]. It is not surprising that one of the most enduring solutions was to devise hierarchical geometric models, which came to be known as "Levels of Detail" (LoD) [START_REF] Clark | Hierarchical Geometric Models for Visible Surface Algorithms[END_REF]). As such, LoD and the hierarchical models of space in the geosciences are quite similar in purpose and argumentation. Both approaches also share the need for a concretization for specific use cases. [START_REF] Touya | Detecting Level-of-Detail inconsistencies in volunteered geographic information data sets[END_REF] define the LoD of a geographical dataset as the conjunction of several factors, namely the conceptual schema of the data, the semantic resolution, the geometric resolution, the geometric precision, and the granularity. The conceptual schema component is the way ground truth is represented in the geographical database: polygonal features representing forests or point features representing individual trees are conceptual schemas that correspond to different LoDs. The semantic resolution is the quantity of details in the attribute data attached to geographical features. By analogy with raster resolution, the geometric resolution of vector features is approximately the minimum distance between two vertices of the geometry. The geometric precision is simply the positional shift between ground truth and the represented feature. Finally, granularity describes the size of the smallest shapes of features, such as the smallest protrusions of buildings or the smallest width for sharp bends in a road. [START_REF] Biljecki | Formalisation of the level of detail in 3D city modelling[END_REF] proposed a formal framework to measure LoD, but it is applicable for 3D city models.

As CityGML standard did for 3D city models [START_REF] Kolbe | Representing and exchanging 3D city models with CityGML[END_REF], LoD categories can be defined for maps. [START_REF] Touya | Detecting Level-of-Detail inconsistencies in volunteered geographic information data sets[END_REF] proposed five LoD categories that would be used in this chapter, from the more detailed to the less detailed: street, city, county, region, and country. The street LoD contains features represented for parcel management or street orientation. For example, the British Ordnance Survey MasterMap can be considered as a street LoD dataset. The city LoD contains features to describe what is visible on the ground (buildings, roads, rivers, forests, etc.). It is the LoD of classical 1:25k topographic maps. The county LoD contains features that represent a small region to allow tourist-like displacements (e.g., visits, hiking, cycle rides). The regional LoD is related to the representation of a large region and only contains important roads and geographic features. Finally, the country LoD is even less detailed, for the representation of countries or very large regions.

In order to compare LoD and scale inferences, we have to match the LoD categories used in this chapter with scale values. Table 1 summarizes an attempt at such a matching. Although this matching is somewhat subjective, it was used in the remainder of the chapter to compare scale and LoD inferences.

Table 1. Matching the LoD categories from Touya and Brando (2013) with map scale ranges, i.e. the objects with a given LoD category can be mapped within this scale range, without significant generalization.

Two Methods for the Automatic Inference of Scale

As we have noted before, information on the scale/LoD of a given dataset is crucial for further geoprocessing operations such as automated generalization. Before the rise of datasets like OSM, information on scale/LoD was just part of the metadata, but with user generated geodata, capture or intended scale/LoD are not documented. To address these problems, we present two different data enrichment approaches that attempt to infer the scale/LoD of OSM-data. The first approach can be understood as a rationalist [START_REF] Touya | Detecting Level-of-Detail inconsistencies in volunteered geographic information data sets[END_REF], the second as an empiricist approach [START_REF] Reimer | Assigning Scale Equivalencies to OpenStreetMap Polygons[END_REF].

Scale Inference with a Multiple Criteria Decision Technique

Measuring Level of Detail

The definition of LoD presented in Section 2 showed that it is more complex than geometric resolution alone, as many aspects are involved in its characterization.

Assuming that LoD inference is the aim, rather than scale, several measures have to be used to properly infer LoD. Following the definition given in Section 2, measures can be used to infer LoD while covering all its aspects [START_REF] Touya | Detecting Level-of-Detail inconsistencies in volunteered geographic information data sets[END_REF].

Measuring the conceptual schema:

The feature type of the object, in the Open Geospatial Consortium sense, can help us to measure the schema aspect of the level of detail. For instance, buildings or points of interest have a higher LoD than built-up areas. Although the Resource Description Framework (RDF) structure of OSM data prevents deriving of the feature type from classes, it can be derived from the main tags of objects like highway, building, or amenity.

Measuring the semantic resolution:

The annotation process to add semantic information on objects improves the level of detail of OSM objects by giving specifications on the object, but OSM is sparsely tagged [START_REF] Mooney | The annotation process in OpenStreetMap[END_REF] and only a few objects contain several tags. A very simple measure that counts tags is used. Metadata-like tags, such as source, or created_by, are counted as well as property tags like name, and language specific tags, such as species:fr that gives the French name of a tree species while the generic tag species gives the Latin name.

Measuring the geometric resolution:

Geometric resolution can be measured by assessing the density of vertices in relation to the length of objects. Indeed, we assume that a higher frequency of vertices denotes a digitization of objects at a larger scale or level of detail. The vertex density measure has been empirically normalized between 0 and 1 using the maximum and minimum values found in French authoritative datasets at different LoDs (1:25k, 1:100k and 1:250k). However, such a measure penalizes curvy lines that require more vertices to digitize than a straight line. So, curved objects (e.g. rivers) may be artificially considered as more detailed. So, we added a measure, the median of edge lengths (Figure 2), to better capture the resolution of curved objects. It has been proved more effective than vertices density on mountain roads by [START_REF] Girres | An evaluation of the impact of cartographic generalisation on length measurement computed from linear vector databases[END_REF]. This measure is also empirically normalized using the same authoritative datasets.

Measuring the geometric precision:

Intrinsically assessing the geometric precision is a complex task and previous research giving a geometric precision for OSM objects used a reference dataset (Haklay 2010, Girres and[START_REF] Girres | Quality assessment of the french Open-StreetMap dataset[END_REF]. However, the source tag in OSM informs on where the contribution comes from (e.g. GPS survey, Bing imagery, imported from open datasets). Knowledge on the rough precision of such sources can give us a vague but useful insight on geometric precision. The main possible values for the source tag have been listed from the TagInfo tool, and a rough LoD equivalency was derived when possible: a GPS survey is usually quite precise (value set to city) while digitization from Landsat creates imprecise objects (value set to region).

Measuring granularity:

Granularity captures the minimum size of details in an object shape. The detail can be the whole shape, a simple protrusion, or a bend in a linear object. To capture granularity in all three cases, three measures are proposed: size, smallest edge, and coalescence. First, small areas indicate a high granularity for small-sized objects but do not indicate anything about the granularity of large objects. The measure was calibrated with the smallest sizes found in the authoritative datasets at several LoDs used before. The size criterion is only applied to polygons. Then, the smallest edge criterion analyzes the length of the shortest edge between two vertices to infer granularity. This criterion is a classical measure to assess building granularity in cartographic generalization [START_REF] Stoter | Methodology for evaluating automated map generalization in commercial software[END_REF]. Note that when used on raw data, shortest edge values can become infinitesimally small due to nighdouble clicks and other digitization errors. A clean-up step is suggested when used on OSM data, for example. Finally, the coalescence (i.e. symbol overlap in a curve) criterion is used for the inference of linear features' granularity. This crite-rion is based on the principle that if a linear feature symbol coalesces at a given symbol width, the feature cannot be displayed at a scale that requires such a width for eye perception [START_REF] Girres | An evaluation of the impact of cartographic generalisation on length measurement computed from linear vector databases[END_REF]. It could also be used on polygons but it has not been tested.

To summarize, eight criteria can be used to infer LoD in OpenStreetMap:

 Feature type (conceptual schema).  Number of tags (semantic resolution).  Vertex density (geometric resolution).  Median edge length (geometric resolution).  Capture source (geometric precision).  Size (granularity).  Smallest edge (granularity).  Coalescence (granularity).

Combining Criteria to Infer a LoD Category

The eight proposed criteria are quite diverse, and hardly comparable, so their aggregation to infer a LoD category is challenging. Multiple-criteria decisionmaking is a computer science domain that researches methods to that are able to cope with diverse and intuitively hard-to-compare measurements (Figueira et al. 2005a). Such techniques can help us to infer LoD from the eight proposed criteria. Among the large number of existing techniques, we chose the ELECTRE TRI method (Figueira et al. 2005b) as its properties match our needs:

 The decision is a classification into categories.  There are more than three criteria.  The criteria are hardly comparable (i.e. how to compare the vertex density measure with the capture source criterion?).  The criteria give fuzzy results that may be insignificant taken individually.

In ELECTRE TRI, the comparison between two vectors of measures (that gather the measures for all criteria) is not made by aggregating the measures. Comparisons are made criterion by criterion, and according to this comparison, each criterion votes for or against the assertion that "vector u outranks vector v". To make a classification, each category is assigned a lower-bound vector and an upper-bound vector to which the vectors to classify are compared. Therefore, we had to define, the lower-bound and upper-bound vectors for each category: e.g., the feature type "building" is the feature type criterion value for the lower-bound vector of the category City LoD. The bounds definition is based on the authoritative datasets. The criteria are able to vote indifference when the criterion alone is not sufficient to decide what outranks what. For instance, the criterion "feature type" is indifferent when the values up for comparison are "footpath" and "residential road". The criteria are also able to vote a veto, i.e. the outranking decision is based only on this criteria. For instance, the granularity criterion will put a veto if a 1-m smallest edge is compared to a 500-m smallest edge.

As the importance of any single criterion in the global method is hard to assess, a sensitivity analysis was conducted. We compared the global result (i.e. with all criteria) with results derived from only a subset of the criteria. The sensitivity analysis shows stability for some objects (e.g. building and forest), i.e. whatever the criteria used, the LoD category is the same. Other objects show more variability: for the tested streets or rivers, the choice of the criteria among the eight available significantly impacts the LoD category that is inferred.

As a strategy to make the method more robust against such feature typedependent sensitivity, we compute the LoD for all the possible permutations of criteria (with at least four criteria to all criteria). The geometric mean of all the inferred categories is used as the new LoD value, robust against outliers and changing sensitivity.

The multiple criteria decision method and all the criteria have been implemented in the open source research platform GeOxygene [START_REF] Grosso | GEOXYGENE: an interoperable platform for geographical application development[END_REF], which is able to load OSM datasets. Some results automatically computed on built-up areas, like in [START_REF] Reimer | Assigning Scale Equivalencies to OpenStreetMap Polygons[END_REF], are presented in Figure 3.

Empiric Scale Inference

The empiric approach as presented in [START_REF] Reimer | Assigning Scale Equivalencies to OpenStreetMap Polygons[END_REF] is based on an inversion of Töpfer's radical law [START_REF] Töpfer | The principle of selection[END_REF]. The basic idea is to create a specific radical law applicable to a specific class of objects by empirically determining a measurable constant and inverting it, to determine the scale equivalency of a given object. The scale equivalency is then expressed as if it was a cartographic scale. This empiric scale inference method is thus divided into three phases:

1. Identification of a suitable measure. 2. Determination of the specific constant. 3. Automated application.

Phases 1 and 2 are currently not fully automated, but conceivably could be automated, assuming some further work in defining criteria for selecting suitable measures. Note that phase 2 needs to be informed by the relation of the selected measure to the object, potentially modifying the degree of power of the equation. Area-based measures will most likely be of third degree and linear measures of second-degree complexity, disregarding other factors such as a drop or increase in apparent density. For a detailed discussion of the determination of the exponent x in the equation:

n F =n A• √( M A M F ) x ,
where n_F is a measure in the follow-up scale, n_A is a measure at the original scale and M_A and M_F are the scale factors at original and follow-up scale respectively, please see Töpfer (1979, pp. 43).

For the case of urban area polygons, the vertex frequency was identified from many other potential measures generated for urban area polgyons for 1:250k scale map products from three different national mapping agencies. Note that vertex frequency was used for a related purpose by [START_REF] Dutton | Scale, sinuosity and point selection in digital line generalization[END_REF]. Other potential measures such as minimum edge length, area, vertex per area, angular resolution, minimum angle, etc. were tested and discarded either due to being too different across the tested maps or due to being statistically dependent on the area of the polygon. The vertex frequency tested negatively for dependence on the area of the polygon, i.e. there is no statistically significant correlation between frequency and polygon size. Furthermore, the measure showed very stable distributions with low standard deviations around a concrete value of 1 vertex per millimeter drawing space across a wide range of maps of the same scale produced by different organizations. We thus set up the scale equivalency S_E as:

S E =250000• ( 1.0 v mm n F ) 2 .
Note how this is equivalent to the 1st degree (x = 1) selection equation based on [START_REF] Töpfer | Kartographische Generalisierung, 2nd Edition[END_REF]:

M F =M A • ( n A n F ) 2 .
Contrary to common experience, no significant numerical difference could be detected whether curvy rivers and coastlines were part of the urban area polygons or not. We highlight this as an example of the conceptual difference compared to the multi-criteria analysis, where the choice of criteria is made a priori, i.e. without a preceding statistical-empirical analysis. Whereas intuition and expert knowledge suggest that there is a strong influence on the artificial/natural form dichotomy of polygons on vertex frequency, these effects are not measurable for this specific object type and scale range.

Combining Both Methods to Improve Scale Inference

Compared Evaluation of Both Inference Methods

To compare both methods, scale was used and the improved LoD inference (the mean of category inferences when criteria vary) was interpolated to scale, using the scale ranges from Table 1, and a linear interpolation inside each category (i.e. a 2.5 LoD mean corresponds to a 1:50000 scale). Then, five test areas were selected with only built-up areas as the empiric scale inference is only tuned for such objects. Four of the test areas come from areas of interest highlighted in [START_REF] Reimer | Assigning Scale Equivalencies to OpenStreetMap Polygons[END_REF]: Africa, western Ukraine, Australia, and Belgium. A test area in France, where the multiple criteria method was initially tested, was also added. Figure 4 clearly highlights the general trend on all tested datasets, that both methods do not infer scale the same way. The scale equivalency (SE) tends to infer larger scale than the multiple criteria method (SL). The results are summarized for all built-up areas of all five test datasets in Table 2. Occasionally, SL is larger than S E , but the mean scale gap is around 40 in most datasets (the gap is only significantly bigger in the French dataset). However, both methods are quite consistent in assessing the wide diversity of scales for built-up areas across the test datasets. When such a difference is measured, it is necessary to assess which one is closer to some form of ground truth. For this purpose, we used the French dataset where almost all built-up areas are derived from an automatic import of the Corine Land Cover European dataset, which is confirmed by the source tag on the objects. Corine Land Cover is produced by remote sensing for a scale of 1:100k. So, the both scale inferences should tend to 1:100k on the French dataset. S E appears to be the more accurate scale: it slightly underestimates the scale with a mean scale of 1:43k, while S L is much further with a mean scale of 1:2.5M.

The large bias of S L may have several explanations. First, the multiple criteria method was not intended to infer scale but LoD, being a different and fuzzier notion (see Section 2). Measurements on geometry are balanced with measures on feature type, or metadata, which significantly impacts the inferred scale. Moreover, the geometry measurements were not calibrated on built-up areas but mostly on roads and buildings [START_REF] Touya | Detecting Level-of-Detail inconsistencies in volunteered geographic information data sets[END_REF], and they were not changed for this comparison to see if it mattered. Finally, the interpolation between LoD categories and scales is quite fuzzy and inaccurate. The ranges used for each category could be tuned and a non-linear interpolation could be used for small scales, where the scale-range is very large compared to the scale ranges of street and city categories. On the other hand, the scale equivalency also appears to be biased, as the only consideration of vertex density tends to increase scale equivalency too much. Taking granularity into account would maybe make S L more accurate. Although the exemplary scale equivalency was calibrated with built-up areas in authoritative datasets, it was computed on other map types of objects, as well as the multiple criteria LoD inference, in order to further explore both methods. Such evaluations can help us to know if the scale equivalency really has to be calibrated several times for several types of objects, which is the baseline assumption. Tests were carried out on rivers (tag waterway = river), forest (tag landuse = forest) that are geographically far from built-up areas and industrial areas (tag landuse = industrial), which is a type of object close to built-up areas (Figure 5). Two areas with good completeness in France and Germany were selected.

In all three cases, the scale gap between S L and S E is less pronounced, particularly on rivers that are quite different objects, while forest and industrial areas are considered as land use areas. The gap decrease is partly due to the inference of smaller scales by S L compared to the inference for built-up areas. Indeed, vertex density is correlated to the shape of objects, and curved shapes like forests and rivers tend to be composed of more vertices than built-up or industrial areas with the same length

Mixing Both Inference Methods

The exemplary scale equivalency for polygons as a function of the vertex density measure is naturally quite similar to the vertex density criterion used by [START_REF] Touya | Detecting Level-of-Detail inconsistencies in volunteered geographic information data sets[END_REF], normalized by benchmarking on existing datasets. Hence, we tried to compute the multiple criteria scale inference replacing the vertex density criterion by the scale equivalency measure. The previous section showed that the multiple criteria method tended to yield much smaller scales compared to Reimer et al.'s (2014) scale equivalency, so adding the scale equivalency as a criterion could plausibly improve inference results. The scale inference was computed with the vertex density criterion and with the scale equivalency instead on the same datasets of built-up areas (Table 3). The comparison was also computed on three buildings datasets (Table 4) in different parts of the world in order to assess the impact of the scale equivalency criterion on geographical data it was not calibrated for. The result for built-up areas shows that replacing the vertex density criterion clearly influences the LoD inference with a mean decrease of the LoD of 1 category, giving a mean scale of approximately 1:90k, which is consistent with the computation of scale equivalency on the same datasets. As most built-up areas in the tested datasets are imported from Corine Land Cover, a dataset specified for 1:100k scale, the scale inference is more accurate with Reimer et al.'s (2014) scale equivalency for these objects.

On the contrary, the LoD inference on building remains nearly the same with or without Reimer et al.'s (2014) scale equivalency, which means that the calibration of both measures for small and detailed features like buildings produce quite similar results.

LoD Harmonization for Large-Scale Automatic Mapping

When OSM is an input for the automatic derivation of large-scale maps (e.g. 1:10k), highly detailed objects are displayed with less detailed objects. When these objects share spatial relation (e.g. inclusion) in reality, the LoD difference may alter this spatial relation and blur the map readability [START_REF] Touya | What is the level of detail of OpenStreetMap?[END_REF]. In this case, the automatic inference of scale/LoD for individual objects is very useful. It helps identifying those spatial relations that are damaged because of LoD difference [START_REF] Touya | Detecting Level-of-Detail inconsistencies in volunteered geographic information data sets[END_REF]. The spatial relations are identified by spatial rela-tions algorithms and stored as complex objects of the dataset. Then, the LoD inference is a required input for an automatic LoD harmonization process that could restore the spatial relation [START_REF] Touya | Harmonizing Level of Details in OpenStreetMap Based Maps[END_REF]; here spatial relations could be made explicit as map objects in order to assure their restoration.

For instance, OSM built-up areas are often poorly detailed (see experiments above, Section 4.1) while buildings are quite detailed in France (imported from cadastral data). So, buildings may lie just outside built-up areas. The harmonization process extends the geometries of built-up areas to include those buildings, restoring the spatial relation of buildings included in a built-up area (Figure 6). Figure 6. Automatic harmonization of a built-up area (in red), extended (in grey) to include buildings with higher LoD.

6 Open Problems

Scale Inference for Point Objects

Both methods rely on some kind of point density estimation based on the series of vertices that describe objects' geometry, which is not immediately applicable to point objects (Dutton 1999, Bereuter and[START_REF] Bereuter | Real-time Generalization of Point Data in Mobile and Web Mapping Using Quadtrees[END_REF]. So, how can we infer the scale or LoD of point objects?

In the multiple criteria method, all criteria related to geometric resolution and granularity become meaningless, and the conceptual schema, semantic resolution and geometric precision criteria remain. We tested the method with the remaining criteria on several point features in OSM: trees, aerial way pylons, bicycle_rental, bus stops, towers, peaks, and power poles. These features are diverse in terms of real extent and geographical neighborhood. A fourth criterion, called version number, was added to assess the features with a crowdsourcing approach (Goodchild and Li 2012): although the Linus' law (i.e. quality increases with the number of active contributors) has not been completely proved for VGI [START_REF] Haklay | How many volunteers does it take to map an area well? the validity of linus's law to volunteered geographic information[END_REF], the number of versions of a feature gives hints on the number of times a feature has been improved by OSM contributors. This criterion assesses the objects with many versions as detailed objects.

As the source tag is seldom filled, the most differentiating criterion is the feature type criterion. The point objects that represent a small object like a tree, bus stop or a pylon are attributed to a detailed LoD, while objects representing a large (and fuzzy) extent like peaks or bicycle rental places are given less detailed LoD. Within a feature type, the three other criteria (source, number of tags, and version number) make the objects more or less detailed: for instance, a peak captured by GPS with elevation and name tags is given a higher LoD than a peak captured from Bing imagery (Figure 7). These results show that the LoD inference of point objects could be improved. First, the version number criterion only uses the version number, so there is no information about the number of contributors that improved the object, and it may be a single contributor. However, the wisdom of crowd theory assumes that better decisions can be made when there are multiple independent contributors [START_REF] Surowiecki | The Wisdom of Crowds[END_REF]). Using the full history OSM database, as proposed by [START_REF] Barron | Towards intrinsic quality analysis of OpenStreetMap datasets[END_REF], could further enhance the version number criterion with the number of different contributors involved in the object improvement. Moreover, the peaks example is the ideal case for introducing what [START_REF] Goodchild | Assuring the quality of volunteered geographic information[END_REF] call the geographic approach of VGI quality assurance. If we could cross the peaks with digital terrain model information, it would be easy to assess the proximity of the feature and a peak in the relief as modelled in the DTM.

Does Feature Density Alter Scale Level?

Inferring the LoD of objects individually is sometimes insufficient, as the legibility of the object can be affected by the local density of objects. It is plausible to assume that certain dense patterns alter the LoD/scale of its composite object, potentially raising partonomic questions. Figure 8 shows the example of a crosscountry ski resort in the Pyrenees. Individually, the paths are approximately inferred as 1:100k scale objects by the improved multiple criteria method. However, the density of such paths prevents any legible display at this scale (Figure 8c). In this case, the scale inferred is not the scale at which the paths could be mapped, but the scale at which they could be individually mapped. Regarding the multiple criteria method, two kinds of criterion could be added to integrate such density issues. First, clutter measures [START_REF] Rosenholtz | Measuring visual clutter[END_REF]) at several scales could be made to assess at which scales the density of objects from one feature type causes clutter problems. Then, the principles from the coalescence criterion could be extended to the neighborhood of objects: as symbol size increases when scale decreases, when does the object symbol overlap with symbols from its neighbors?

The Scale of Objects with Simple Shapes

In a dataset with a homogeneous scale, simple objects like rectangular-shaped buildings are captured with simple geometries, but we know the scale is similar to all the other buildings that may have complex shapes. In OpenStreetMap, if an object has a very simple shape, it is hard to know if its scale is small, or if it is just a simple geometry that has been accurately captured. The scale equivalency measure will infer that such simple objects have a small scale, as the number of vertices to capture them is small (Figure 9). Within the empirical scale equivalency approach one must come up with coping strategies for individual object types separately, as was done for city blocks [START_REF] Reimer | Assigning Scale Equivalencies to OpenStreetMap Polygons[END_REF]. LoD inference too, provides quite different results for buildings depending on the complexity of their original shape [START_REF] Touya | Detecting Level-of-Detail inconsistencies in volunteered geographic information data sets[END_REF]. When the application is the production of small-scale maps with a generalization process, this issue will not alter the generalization result. Indeed, if the inferred scale is small, the impact will only be a slight generalization, but if the shape is simple, it does not require as much generalization as a building with a complex shape. However, this can be an issue when the application is the production of a large-scale map, with LoD consistency checking (see Section 5). Then, objects with simple shapes should be identified before consistency checking, for instance, by analysis of the neighbors of the objects: if only one has a low resolution, the shape is probably simple. This analysis can be related to the geographic approach of quality of [START_REF] Goodchild | Assuring the quality of volunteered geographic information[END_REF].

Conclusions

Until the widespread availability and success of VGI and OSM specifically, scale was an easily determined metadatum. With non-government grassroots geodata becoming more encompassing by the day, users are confronted with rich but scale-wise inhomogeneous data. This is as true for geometries as it is on a conceptual level. This chapter reviewed the first two attempts at automatized scale inference for OSM and showed their relative strengths and weaknesses and ways to improve both by combining them. Both approaches currently and purposefully work on an individual object level. The open problems such as point features and feature density could plausibly be approached with meso-regions as intermediate steps, as it has been done in agent-based automated generalization. A more fundamental problem seems to be the further automation of parameterization. The current approaches make extensive use of tacit and explicit cartographic knowledge in selecting the measures and/or criteria. It is unclear at the moment how or if automation of these fundamental steps is attainable at all in the near future.

Figure 1 .

 1 Figure 1. Different levels of detail for three very complex religious buildings with similar granularity. (a) Is captured from cadastre data while (b) and (c) are captured from Bing images.

Figure 2 .

 2 Figure 2. The median of edge lengths gives a clearer idea of geometric resolution for curved objects like mountain roads or rivers.

Figure 3 .

 3 Figure 3. LoD inference results for built-up areas in France: LoD is globally low because built-up areas are imported from Corine Land Cover.

Figure 4 .

 4 Figure 4. (a) Reimer et al.'s (2014) scale equivalency on built-up areas in Tunisia. (b) Interpolated scale from multiple criteria LoD inference on the same dataset.

Figure 5 .

 5 Figure 5. LoD inference on industrial areas in (a) Germany, (b) forests in France, and (c) rivers in Germany.

Figure 7 .

 7 Figure 7. Peaks (triangle symbols) and passes (square symbols) extracted from OSM in the French Alps. Scale inference (computed from the multiple criteria method) varies according to the tags on the objects.

Figure 8 .

 8 Figure 8. (a) Multiple paths in a cross-country ski resort in the Pyrenees. (b) Individual scale inference tells that paths should be mapped at 1:100k, but (c) there are too many close paths at this scale.

Figure 9 .

 9 Figure 9. Two buildings captured from the source (French cadastre) by the same contributor with quite different scale equivalency because the upper one has a much simpler shape.When the application is the production of small-scale maps with a generalization process, this issue will not alter the generalization result. Indeed, if the inferred scale is small, the impact will only be a slight generalization, but if the shape is simple, it does not require as much generalization as a building with a complex shape. However, this can be an issue when the application is the production of a large-scale map, with LoD consistency checking (see Section 5). Then, objects with simple shapes should be identified before consistency checking, for instance, by analysis of the neighbors of the objects: if only one has a low resolution, the shape is probably simple. This analysis can be related to the geographic approach of quality of[START_REF] Goodchild | Assuring the quality of volunteered geographic information[END_REF].

Table 2 .

 2 Comparison of scale inferences from both methods in all five datasets (17402 objects).

		LoD	Scale from LoD	Scale from equivalency	Scale gap
		Mean	(SL)	(SE)	(SL/SE)
	mean	3.94	1:18996375	1:81368	638.9
	max	5.00	1:75375000	1:32017460	11499.7
	min	1.93	1:14475	1:5	0.3
	median 3.94	1:411549	1:11149	61.1

Table 3 .

 3 Comparison of LoD inference with and withoutReimer et al.'s (2014) scale equivalency as a criterion, on 4858 built-up areas from the French and African datasets (tag landuse = residential).

		Mean LoD with vertex	Mean LoD with Scale Equiva-	LoD differ-
		density	lency	ence
	mean	4.18	3.12	1.06
	max	5.00	4.20	1.72
	min	1.98	1.98	-0.03
	median 4.64	3.06	0.94

Table 4 .

 4 Comparison of LoD inference with and withoutReimer et al.'s (2014) scale equivalency as a criterion, on 9153 buildings from the three chosen datasets.

		Mean LoD with vertex	Mean LoD with Scale Equiva-	LoD differ-
		density	lency	ence
	mean	2.05	1.99	0.05
	max	4.66	3.95	1.48
	min	1.64	1.61	-0.25
	median 2.02	2.00	0.03