Khalid

DeepRes-UpwellNet: A Robust Framework for Coastal Upwelling Monitoring Along the Moroccan Atlantic Coast 1 st Belmajdoub

Keywords: convolutional neural network, DeepRes-UpwellNet, Sea surface temperature, chlorophyll-a, Upwelling, Atlantic coast of Morocco

Upwelling, a pivotal oceanic process, serves as a crucial mechanism for transporting nutrients from the ocean depths to the surface, playing a fundamental role in enhancing primary productivity and bearing immense significance for coastal ecosystems. Within the scope of this study, we introduce a novel deep learning tool tailored to the monitoring of upwelling in the Moroccan coastal waters, utilizing satellite images encompassing both biological and physical attributes. Recent years have witnessed substantial advancements in the field of deep learning, particularly in the domain of segmentation techniques. These methods have proven their efficacy across a spectrum of ocean remote sensing applications, encompassing image segmentation, classification, and detection. Notably, the U-Net architecture has gained widespread recognition for its effectiveness in these tasks. In the context of our investigation, we present DeepRes-UpwellNet, a fully convolutional deep neural network architecture explicitly engineered to automate the detection and precise localization of upwelling regions in sea surface temperature (SST) and chlorophyll-a (chl-a) images. Our primary objective revolves around assessing the performance of deep learning in the accurate identification of upwelling regions. To achieve this, DeepRes-UpwellNet is meticulously trained and optimized using a database of satellite-derived SST and chlorophyll-a data sourced from the Moderate Resolution Imaging Spectroradiometer (MODIS). The empirical results, as obtained from experiments conducted along the Atlantic coast of Morocco, clearly underscore the superior performance of our proposed model in comparison to conventional segmentation methods. By harnessing deep learningbased upwelling detection systems, we usher in a cost-effective, precise, and practical approach to objectively analyze this pivotal oceanic phenomenon.

I. INTRODUCTION

The Canary Current Upwelling System (CCUS) is situated in the central region of Northwest Africa (NWA) and is renowned as one of the world's most productive marine ecosystems [START_REF] Carr | Production regimes in four eastern boundary current systems[END_REF]. This system is a part of the extensive upwelling system running along the coast of North-West Africa, encompassing countries such as Morocco, Mauritania, Gambia, and Senegal. The remarkable productivity of this region results in a significant fish biomass, primarily comprising small pelagic species [START_REF] El Aouni | Physical and biological satellite observations of the northwest african upwelling: Spatial extent and dynamics[END_REF]. The upwelling phenomenon in this area persists throughout most of the year, exhibiting continuous variability [START_REF] Hanae | A new upwelling index for the moroccan atlantic coast for the period between 1982-2021[END_REF]. The driving force behind the upwelling in the North West Sea region is predominantly the equatorial trade winds, which facilitate the upward movement of cold, nutrient-rich intermediate waters [START_REF] Bakun | Coastal upwelling indices, west coast of north america[END_REF]. As a consequence, a dominant surface current is observed along the coast, extending from north to south, with seasonal fluctuations in cold, nutrient-rich coastal waters being a prominent feature [START_REF] Walfrid | On the influence of the earth's rotation on ocean-currents[END_REF].

Within the scientific literature, various techniques and algorithms have been proposed for the automated identification of upwelling regions in SST images. For instance, [START_REF] Cayula | Edge detection algorithm for sst images[END_REF] introduced an unsupervised classification method utilizing neural networks trained with k-means clustering [START_REF] Hartigan | Algorithm as 136: A k-means clustering algorithm[END_REF]. Another approach, presented by [START_REF] Nieto | Mesoscale frontal structures in the canary upwelling system: New front and filament detection algorithms applied to spatial and temporal patterns[END_REF] , relied on a histogram-based separation method, interpreting the bimodality of the SST histogram as indicative of distinct water masses. In a similar context, [START_REF] Sousa | Identification of upwelling areas on sea surface temperature images using fuzzy clustering[END_REF] developed a specialized algorithm for extracting upwelling regions in the coastal waters of Portugal, using fuzzy clustering to achieve accurate segmentation in that specific area. More recent advancements by Tamim et [START_REF] Tamim | A simple and efficient approach for coarse segmentation of moroccan coastal upwelling[END_REF], [START_REF] Tamim | An efficient tool for automatic delimitation of moroccan coastal upwelling using sst images[END_REF] and [START_REF] Aouni | An improved method for accurate computation of coastal upwelling index using sea surface temperature images[END_REF] improved upon these algorithms, delivering favorable results for the southern part of the Moroccan Atlantic coast. However, these methods exhibited limitations when applied to the entire Moroccan coast, including the central and northern regions. The primary challenge arose from the substantial variability in the latitudinal temperature distribution. To address this issue, [START_REF] Aouni | Robust detection of the north-west african upwelling from sst images[END_REF] introduced a robust approach for identifying upwelling regions in SST images along the central part of the Canary Islands upwelling ecosystem. Their method relies on nonlinear normalization of SST images, offering a straightforward implementation and addressing the limitations encountered in the methodology proposed by [START_REF] Tamim | A simple and efficient approach for coarse segmentation of moroccan coastal upwelling[END_REF], [START_REF] Tamim | An efficient tool for automatic delimitation of moroccan coastal upwelling using sst images[END_REF].

The variability of upwelling in the Canary Current upwelling system has also been explored in the scientific literature using satellite images of ocean color. For example, studies by [START_REF] Aouni | Surface mixing and biological activity in the north african upwelling[END_REF] and [START_REF] Rossi | Comparative study of mixing and biological activity of the benguela and canary upwelling systems[END_REF] delved into the non-linear correlation between surface mixing and biological productivity in the 979-8-3503-4415-8/23/$31.00 ©2023 IEEE upwelling phenomenon. Additionally, with a specific focus on Morocco's Atlantic coast, authors such as [START_REF] Aouni | Detection of moroccan coastal upwelling using sea surface chlorophyll concentration[END_REF], [START_REF] Khalid | A simple tool for automatic extraction of the moroccan coastal upwelling from sea surface chlorophyll images[END_REF] and [START_REF] Belmajdoub | Automatic detection of moroccan coastal upwelling from chlorophyll-a concentration images using the expectation-maximization method[END_REF] employed ocean color images to detect upwelling, utilizing hard clustering, fuzzy clustering, and expectation maximization algorithms, respectively.

In addition to the existing literature, authors in [START_REF] Abidi | An efficient detection of moroccan coastal upwelling based on fusion of chlorophyll-a and sea surface temperature images with a new validation index[END_REF], [START_REF] El | An improved fusion method for detecting upwelling off the coast of northwest africa from chlorophyll-a and sea surface temperature satellite images[END_REF] introduced alternative methodologies for identifying Moroccan coastal upwelling, using both SST and chl-a images. More specifically, they used the concept of image fusion to detect the upwelling region along the Moroccan Atlantic coast.

However, the aforementioned studies mainly use traditional image processing methods, which have two main limitations. Firstly, these methods are time-consuming, as they rely on optimization techniques. Secondly, they are highly dependent on the specific format of the input data. In this paper, we present a new deep learning approach that overcomes these limitations and enables effective upwelling monitoring, regardless of the characteristics of the input data.

Deep learning has emerged as a transformative approach to the segmentation of satellite-derived datasets [START_REF] Thiria | Downscaling of ocean fields by fusion of heterogeneous observations using deep learning algorithms[END_REF], including SST and chl-a images. The integration of deep learning techniques with remote sensing data offers enormous potential for advancing our understanding of oceanographic processes and ecosystem dynamics [START_REF] Zheng | Purely satellite data-driven deep learning forecast of complicated tropical instability waves[END_REF]. By exploiting the power of deep neural networks, we are able to automatically extract and classify important features and patterns from SST and chla images. This enables the precise and efficient identification and delineation of regions of interest such as upwelling zones, frontal boundaries and phytoplankton blooms, as well as a better understanding of ecosystem dynamics. The application of deep learning to SST and chl-a segmentation facilitates the characterization of dynamic ocean phenomena at different spatial and temporal scales. It also offers the way for improved monitoring, analysis and modeling of marine ecosystems.

Recently, authors in [START_REF] Belmajdoub | Convolutional neural networks for coastal up-welling monitoring along the atlantic coast of morocco[END_REF] proposed to train the U-Net encoder/decoder network using both SST and chl-a images encompassing the entire Moroccan Atlantic coast. The main objective of this approach was to accurately identify upwelling regions within the same geographical area. Our study uses the DeepRes-UpwellNet, a modified version of the U-Net Encoder/Decoder network, for the segmentation of Moroccan upwelling regions. The use of the DeepRes-UpwellNet architecture offers significant advantages over previous methodologies. It facilitates efficient feature extraction, enabling the network to recognize the high-level features essential for accurate identification of upwelling regions. In addition, the DeepRes-UpwellNet is robust to the noise and variability commonly encountered in satellite images of the ocean. This robustness is particularly important for the accurate segmentation of upwelling regions, as the ocean environment can exhibit significant fluctuations and disturbances. In addition, the DeepRes-UpwellNet is capable of processing large datasets, a critical aspect when processing the many satellite images needed to segment upwelling regions. Its ability to process large volumes of data efficiently contributes to improved performance, and enables comprehensive analysis of the dynamic and extensive nature of upwelling phenomena.

The structure of this paper is as follows: Section II presents the dataset and the specific area of interest used in this study. Section III presents an overview of the proposed methodology for the detection and extraction of upwelling zones from SST and chl-a images. Section IV focuses on the experimental results. Finally, Section V concludes the study.

II. REGION OF INTEREST AND DATASET

In our research, we utilized a comprehensive training dataset for our deep neural network framework, employing remote sensing images of SST and chl-a. The dataset covered a substantial temporal span of a decade, from 2012 to 2021, focusing on coastal upwelling occurrences along the Moroccan Atlantic coast. The region of interest was meticulously delimited, encompassing geographical coordinates spanning from 21 • N to 36 • N latitude and from 6 • E to 19 • E longitude. The SST and chl-a images employed in our study were sourced from the MODIS sensor, hosted aboard the TERRA satellites, a mission overseen by NASA (National Aeronautics and Space Administration). Figure . 1 visually portrays the characteristic upwelling conditions captured in the images, distinctly highlighting the presence of a well-defined upwelling main front. The precision of the upwelling front's demarcation is uniformly evident across the entire study area, as exemplified in the chl-a image.

The data harnessed in this study encompassed 8-day MODIS-TERRA mapped products, extending spatial coverage at a resolution of 4 × 4 km. These data sets were publicly accessible through a dedicated database hosted at http://oceancolor.gsfc.nasa.gov/. To ensure comprehensive spatio-temporal coverage, we selected an 8-day temporal resolution for our analysis, a choice supported by previous work [START_REF] Hanae | A new upwelling index for the moroccan atlantic coast for the period between 1982-2021[END_REF].

Each image within the SST/chl-a dataset was structured as 384 × 384 pixels, where SST pixels conveyed temperature values in degrees Celsius ( • C), and chl-a pixels represented chlorophyll concentration ((mgm -3 )). To accommodate potential challenges posed by terrestrial, cloudy, or sparsely populated regions, we opted to replace the standard fill value with zero, a modification designed to effectively mitigate the influence of outliers. Importantly, this adjustment does not interfere with the upwelling detection process, as upwelling typically manifests in regions characterized by nonzero SST/chl-a values.

It is crucial to highlight that the creation of segmentation masks for training and testing our deep learning model relies on a training database comprising SST and chl-a images coupled with upwelling detection and segmentation outcomes (as illustrated in Fig. 1). We adopted a method developed by [START_REF] Aouni | Robust detection of the north-west african upwelling from sst images[END_REF], chosen for its track record of successfully identifying and delineating upwelling regions along the Moroccan coast, drawing on physical and biological satellite observations. Consequently, pixels were systematically labeled as "0" to represent areas devoid of upwelling, zones with no available data, or terrestrial regions, while "1" was designated for areas exhibiting upwelling. For a visual representation of the segmentation map derived from the training dataset, (refer to Fig. 1).

III. METHODS

The aim of this paper is to identify and extract upwelling zones from SST and chl-a images using the DeepRes-UpwellNet architecture. In this section, we provide details of the network architecture used.

A. Architecture

The proposed model, DeepRes-UpwellNet, represents a state-of-the-art end-to-end fully convolutional neural network meticulously engineered to identify upwelling regions in SST and chl-a satellite images. It is designed to improve upon the U-Net structure [START_REF] Sivagami | Unet architecture based dental panoramic image segmentation[END_REF] by incorporating enhancements to handle more complex and deeper networks.

DeepRes-UpwellNet consists of two primary pathways: an encoder path, responsible for extracting features related to upwelling from the input SST and chl-a images, and a decoder path, which reconstructs these features to match the original input SST and chl-a map dimensions.

Deep neural networks with numerous stacked layers can enhance their discriminatory capabilities but are susceptible to the issue of vanishing gradients, which can impede training convergence. To combat this problem, the model employs residual units, as depicted in Figure . 2(b). These residual units facilitate the direct propagation of gradients during backpropagation, leading to improved accuracy and convergence [START_REF] Yu | Automated melanoma recognition in dermoscopy images via very deep residual networks[END_REF]. Additionally, a Softmax layer is integrated at the network's end to generate the final binary segmentation map. For a more comprehensive understanding of DeepRes-UpwellNet's architectural details,( refer to Figure . 3).

The input layer of DeepRes-UpwellNet receives SST and chl-a satellite images, which contain temperature data in Celsius or chlorophyll concentration in mgm -3 . The output layer generates a binary segmentation map, where white pixels indicate upwelling regions, and black pixels represent nonupwelling areas, which may include cloud and land pixels.

The design of DeepRes-UpwellNet follows a symmetric structure akin to U-Net but distinguishes itself by employing residual network units instead of simple convolutional units. Each residual unit comprises a 3 × 3 convolutional layer, followed by batch normalization (BN) [START_REF] Ioffe | Batch normalization: Accelerating deep network training by reducing internal covariate shift[END_REF] and a ReLU activation function [START_REF] Harrison | Machine learning applications of convolutional neural networks and unet architecture to predict and classify demosponge behavior[END_REF] to effectively capture non-linear features. The utilization of residual units ensures a smooth information flow through the network and mitigates the vanishing gradient problem, as depicted in Figure . 2(b).

Mathematically, the residual unit can be represented as follows:

Let's consider a neural network block, as shown in Figure. 2(a), with 'x' as the input and 'M(x)' as the true underlying distribution. The network learns the mapping from 'x' to 'y,' represented as:

M (x) = Y (1)
The residual function captures the difference between the mapping applied to 'x' (i.e., M(x)) and the original input 'x' instead of directly learning a direct mapping. This can be expressed as:

F (x) = M (x) -x (2)
The concept of shortcut connections is integral to this approach, represented by:

M (x) = F (x) + x (3)
In this architecture, feature extraction from input SST and chl-a images is achieved using convolutional layers. To enhance the training process, batch normalization is applied after each convolutional layer. The convolution operations employ a 3 × 3 filter with a stride of one, resulting in convolved feature maps.

To downsample the feature maps obtained from the residual units in the encoder path, a 2 × 2 max-pooling operation is employed. This downsampling reduces the feature map size, reducing computational complexity while preserving input transformation invariance.

For the decoder path, transposed convolutions are used to restore the original resolution of the feature maps. The final layer of the network comprises a 1 × 1 convolutional layer, followed by a Softmax activation function, which converts the multi-channel feature maps into the ultimate binary segmentation map. In this segmentation map, pixels are labeled as '1' and '0' for upwelling and background regions, respectively.

The DeepRes-UpwellNet model represents a significant leap forward in upwelling region detection from SST and chl-a satellite images. It combines the power of residual units with a symmetric U-Net architecture to deliver more accurate and reliable results when compared to traditional methodologies.

B. Training the Model

The segmentation model employed for the extraction and identification of upwelling regions in SST and chl-a images was developed using Python, TensorFlow, and Keras, serving as a high-level neural network API, operates seamlessly on top of TensorFlow. Leveraging Keras facilitates rapid experimentation without the need for extensive code development.

The training dataset utilized in this study comprises original SST and chl-a images alongside manually segmented mask images. Specifically, the dataset consists of 450 sets of both masked and unmasked SST/chl-a images, which were partitioned into training and validation subsets. The training subset encompassed (70%) of the images, while the remaining (30%) were reserved for validation purposes. We use ADAM optimization function, with an initial learning rate of 0.0001, and 300 epochs.

C. Results and Discussion

In this section, we describe the results obtained from our experiments. To evaluate the effectiveness of our method, we have chosen to compare it with the method developed by [START_REF] Aouni | Robust detection of the north-west african upwelling from sst images[END_REF] and and by [START_REF] Belmajdoub | Convolutional neural networks for coastal up-welling monitoring along the atlantic coast of morocco[END_REF].

The results of the visual inspection reveal that the DeepRes-UpwellNet outperforms the other two methods in terms of performance evaluation. Figure . 4 provides a clear illustration of the DeepRes-UpwellNet's remarkable ability to accurately extract the primary upwelling area along the Moroccan Atlantic coast. In the realm of detecting upwelling in both SST To establish the quantitative validity of our proposed method, we computed the upwelling validation index (Vup) on 92 SST images and 92 chl-a images collected over two consecutive years (2020-2021). The results for Vup are presented in Table I and are compared with the findings from previous works, as reported in [START_REF] Belmajdoub | Convolutional neural networks for coastal up-welling monitoring along the atlantic coast of morocco[END_REF] and [START_REF] Aouni | Robust detection of the north-west african upwelling from sst images[END_REF].

time Vup DeepRes-UpwellNet 3s SST= 79.18%; chl-a= 79.34% Methodology of [START_REF] Belmajdoub | Convolutional neural networks for coastal up-welling monitoring along the atlantic coast of morocco[END_REF] 3s SST= 78.30%; chl-a= 78.97% Methodology of [START_REF] Aouni | Robust detection of the north-west african upwelling from sst images[END_REF] 1min9s SST= 76.74%; chl-a= 77.88% The calculated index substantiates the effectiveness of our approach in accurately delineating the primary Moroccan upwelling fronts. Notably, for both chl-a and SST, our method exhibits a significant improvement of over 1.5% in V up compared to the approaches developed in the previous works. This substantial enhancement underscores the superior upwelling detection capabilities of the DeepRes-UpwellNet, as it adeptly identifies more upwelling regions than the conventional U-Net method.

IV. CONCLUSION

In this study, we have introduced a novel deep learning tool called the DeepRes-UpwellNet, specifically designed for accurately detecting and localizing upwelling regions in satellite images of SST and chl-a along the Moroccan Atlantic coast. The performance evaluation demonstrated that the proposed model surpasses traditional segmentation methods, offering an effective and objective analysis of this oceanic phenomenon. Additionally, a comparative analysis was conducted between the segmentation results obtained by the DeepRes-UpwellNet and the U-Net. The DeepRes-UpwellNet model outperformed the U-Net framework, showcasing its enhanced capability in identifying even the smallest areas of upwelling that were not detectable by the U-Net. To quantitatively validate our proposed method, we computed the V up index over the years between 2020 and 2021. The results confirm the effectiveness and reliability of our approach to detecting upwelling.

Fig. 1 .

 1 Fig. 1. Example of 8-day: (a) SST and its mask (b) chl-a and its mask selected from our database showing a typical upwelling scenario in the study area.The white color in the mask represent the upwelling region, and black color represent the non-upwelling region.

Fig. 2 .

 2 Fig. 2. Comparing Neural Network Building Blocks: (a): Original Plain Block in the Classic U-Net Architecture. (b): Residual Unit with Shortcut connections in the Proposed Network.

Fig. 3 .

 3 Fig. 3. DeepUpwell Res-Net Architecture: Binary Segmentation from SST Images. Input layer contains temperature values in ( • C) or chlorophyllconcentration in (mgm -3 )). The left part depicts the Encoder Path, while the right part represents the Decoder Path.

Fig. 4 .

 4 Fig. 4. Comparative visualization of upwelling segmentation results using three approaches to (a) SST and (b) chl-a image.

TABLE I RESULTS

 I OF Vup ON THE PROPOSED METHODOLOGY ON SST AND CHL-A IMAGES FROM 2020 TO 2021.


domain: shs sde

text:
Fatma Fourati-Jamoussi

Michel J F Dubois

Maxime Agnès

Valérie Leroux

Loïc Sauvée

Our aim is to keep in mind all these theoretical constructions and observations and to study how to evaluate the integration of SD in a case study of engineering education, and even more how to use this integration as a driver for educational innovation. We define educational innovation 1 as novel practices, tools or technologies used in curricula, course materials and pedagogy.

Following previous research (Fourati-Jamoussi et al. 2015a) this article attempts to answer these questions: i) how has Sustainable Development (SD) been introduced in some curricula? ii) what are the reasons for innovating in an engineer training programme ? iii) can we identify a link or an interaction between the reasons for integrating SD and innovation in training programmes?

The attempt to evaluate the integration of academic SD initiatives in universities suffers from a dual mismatch: i) Most studies only focus on the environmental pillar (Davis and Elliott 2003; Thomas 2004) while they should also take into account the economic and social dimensions (Olszak 2012); ii) We observe an increasing number of scientific works that examines SD initiatives in higher education (teaching and curricula) and research. For instance, Urbanski and Rowland (2014) evaluated academic SD initiatives by using 'STARS as a multi-purpose tool' in the campus sustainability movement. This tool was released by the Higher Education Associations Sustainability Consortium (HEASC) in 2006, and 'would address all the dimensions of sustainability and all the sectors and functions of a university'. In 2009, the use of STARS allowed colleges and universities to measure their 'sustainability performance'. Rowe and Hiser (2016) consider that 'effective strategies for blending service learning and sustainability pedagogies are beginning to emerge'.

On the basis of this statement, our hypothesis is that the implementation of SD in its entirety, in a higher education engineering school, should lead to educational innovation, taking into account its relationship with research. We present a case study at 'Institut Polytechnique UniLaSalle' focused on the education of engineers (geology, agriculture, and environmental sciences, biomass and food production, food transformation and distribution in relation to health).

For an independent organisation of higher education such as the 'Institut Polytechnique UniLaSalle', the challenge of SD is a potential driver for differentiation,

Introduction

Since 2000, many studies have dealt with sustainable development and innovation, technological transitions, evolutionary processes, based on the idea that innovation is a key factor for SD [START_REF] Mulder | Innovation for Sustainable Development: From Environmental Design to Transition Management[END_REF]. Innovation networks could be set up using new methods to search for sustainable technological solutions [START_REF] Weaver | Sustainable Technology Development[END_REF]. Innovation or technological transitions could be considered as evolutionary processes [START_REF] Geels | Technological Transitions as Evolutionary Reconfiguration Processes: A Multi-Level Perspective and a Case-Study[END_REF][START_REF] Geels | Typology of Sociotechnical Transition Pathways[END_REF][START_REF] Ziman | Technological Innovation as an Evolutionary Process[END_REF]. Conceptual work has dealt with SD for engineers (Mulder 2006, 2017; Mulder and Francoeur 2009; Mulder, Segalàs, and Ferrer-Balas 2012; Segalàs-Coral 2009). The relationship between sustainable development and innovation has been explored [START_REF] Hall | The Challenges of Innovating for Sustainable Development[END_REF][START_REF] Mulder | Innovation for Sustainable Development: From Environmental Design to Transition Management[END_REF], and also what should be learnt, in engineering curricula, for sustainability [START_REF] Segalàs-Coral | Engineering Education for a Sustainable Future[END_REF], with a tension between nature sciences and technology, on the one hand, and public welfare commitment involving interdisciplinarity and transdisciplinarity education on the other hand (Cech 2014).

Interdisciplinarity creates dialogue and exchanges between disciplines. It is no longer a fragmented vision but an enrichment from different disciplines. Transdisciplinarity works on objects that do not belong to one discipline. It aims to achieve a project through the use of different disciplinary activities.

It appeared necessary to think about the integration of SD in educational programmes as well as innovation for a sustainable educational system [START_REF] Mulder | Sustainable Development for Engineers: A Handbook and Resource Guide[END_REF][START_REF] Quendler | Sustainable Development in Education: are we Ready for Change? System Innovation and Higher Education in Life Sciences[END_REF].

Moreover, the way SD competences were introduced into technological universities has been studied Ferrer-Balas, and Mulder 2010); the results show that 'a more communityoriented and constructive, active learning pedagogical approach increases students' knowledge of SD'.

for singularity, and is consequently an innovation process as an answer to this issue. In the French context, with a very strong dominance of public institutions in research and higher education, our hypothesis is that autonomy is not always an advantage neither in terms of legitimacy nor in terms of financial resources. A balanced development, according to economic necessities, social issues and environmental concerns, remains fragile; but precisely this fragility requires a path that must be taken in accordance with Spinozian principle that the order and connection of thoughts should be the same as the order and connection of things. Moreover, we suggest here that an autonomous institution, like UniLaSalle, devoted to teaching and research, in order to be itself sustainable, must also face the three conditions of this sustainability (environment, economic and social), in its own functioning. This autonomy in its development, which is a cause of fragility, is also a condition of its own sustainability. This specific situation increases the need for coherence in terms of SD principles. This case study is not an overview of higher education institutions, although the results could be used in other higher education institutions.

Meeting the challenge of SD by applying it directly to governance, operation teaching and research is of a different nature than teaching SD to students. It is one thing to define the external purpose of organizing training and research, but another to develop methods of internal operation consistent with its purpose. If the purpose of an organisation is to train actors highly concerned by SD, strategic choices should be in coherence with this educational objective. Operations, i.e. courses taught, have to be adapted to this objective. However, the case study of such a transformation is interesting in an Institute which is positioned as a trainer and producer of knowledge in areas at the heart of sustainability: mineral and energy resources, soils, water, biodiversity, adaptation to climate' change, farming systems, food production and food quality [START_REF] Quendler | Sustainable Development in Education: are we Ready for Change? System Innovation and Higher Education in Life Sciences[END_REF].

In education, the study of each stage of incremental transformation becomes a strategic priority for the integration of SD (Mulder, Segalàs, and Ferrer-Balas 2012). The change should begin with the educational leaders and then spread to the teaching staff. In addition, reflexivity on the relationship between actions and their purpose, in the short, medium or long term, should be accessible, since the Institute includes research teams that are able to enforce it. Most of them are well informed about scientific data on climate change, energy resources, biodiversity, etc., but also on economic constraints and social sustainability. The Institute can become, de facto, a 'living Lab' offering the ability to study its evolution towards more SD for its own research team.

The challenge of this work is to study the impact of one Institute's finality as explained by Management, i.e. to train responsible actors for SD, in its operational methods. This particular reflexivity, both from outside and from within, can bring valuable insights in the assistance and support for any organisation that sincerely wishes to reach more social responsibility in its own development.

Finally, the aim of this article is not to describe the sustainability of UniLaSalle only through the campus infrastructure and operational activities, although it is important for educational reasons, but to focus on the sustainability of the teaching itself, that means on its ability to move and to transmit to the students the ability to meet their own needs without compromising the following generations to meet their own. Before any comparison with other peer institutions (engineering schools), it is necessary to understand and modelise the interaction of innovation and sustainability processes in our particular case institution.

The previous paper (Fourati-Jamoussi et al. 2015a) focused on the study of sustainability by using two perspectives: integration and evaluation by the Executive Management team. This paper tends to extend this idea of sustainability through the use of two other perspectives: reflections of the researcher and the perception of Management and educational managers [START_REF] Lönngren | Dealing with the Multidimensionality of Sustainability Through the use of Multiple Perspectives -A Theoretical Framework[END_REF].

The main contributions of this paper are: i) the analysis in UniLaSalle of the staff and curricula man-agers' educational programmes; ii) The production of a model which describes the interrelationship in a perception and integration perspective. Such a model could then be broadened to students and to other schools. This study cannot be completely anonymous. In living research approach, 'users' are the con-cerned people who want to participate to the study. For the recruitment of 'users' according to the context of a 'living Lab' project, we reached the directly concerned people in our network of trust. Paradoxically, it is a question of ethics, since the model can only be built from a real engagement of the respondents.

Subsequently, when the model is used on a larger scale, anonymous methods for recruitment can be used [START_REF] Dubé | Montréal: UMVELT[END_REF][START_REF] Leminen | Coordination and Participation in Living Lab Networks[END_REF]. This aspect, which breaks with the traditional practices of academic research, probably explains the small number, although increasing, of publications on 'living Labs'.

There are now more than 400 'living Labs' (EnoLL Network) around the world that help to better understand social innovation [START_REF] Bergvall-Kareborn | Concept Design with a Living Lab Approach, System Sciences[END_REF]Bergvall-Kareborn and Stahlbrost 2009).

The structure of this article is as follows: section 2 presents a brief literature on SD and innovation; section 3 articulates the relationship between SD and innovation in higher education; presents the research questions and provides the methodology of our empirical study on the dynamic capacity of innovation in UniLaSalle; section 4 presents the results of the study; the discussion and research limits and section 5 concludes this paper.

A brief literature review on SD and innovation in education and training

We adopt the traditional definition of SD, from the Brundtland Report (1987) that specifically emphasises the requirement to 'meet the needs of the present without compromising the ability of future generations to meet their own needs'. If it is necessary to meet current needs, the important thing is not only to anticipate the needs of the future but to participate in the development of the capacity of future generations to meet their needs. UniLaSalle aims at training young engineers or managers for the very near future, that is to say, those that will meet the needs for a short-term future without compromising the ability of 'their future children'. This vision led to teaching methods which, in fact, are both focused on the present -making young people able to meet their needs, but also look to the future -enable them to act while thinking about the effects of their actions on tomorrow's society.

The « three pillars of sustainability » is a metaphoric way to visualise their needs to reach sustain-ability, like three Greek columns carrying the pediment of a temple. Of course, each pillar should be as high and as strong as the others. Another way is to use the Euler diagram generalised by [START_REF] Venn | On the Employment of Geometrical Diagrams for the Sensible Representation of Logical Propositions[END_REF]; in this representation, sustainability is achieved when the three 'pillars' are merged into one. Truly the number of three pillars is a minimum; they are economic, social and environmental issues. A global adapted policy is needed to obtain three pillars of sustainability at an equivalent level. Until now, a clear definition of this equality was not achievable, but it could be shown through pragmatic actions. The major point to understand is that sustainability is a process of perpetual adaptation and that actions should concern the three pillars. [START_REF] Moldavska | Development of Manufacturing Sustainability Assessment Using Systems Thinking[END_REF] insist on the fact that the three pillars of SD should be addressed equally. Here, we focus our attention on how teaching could be transformed in order to be in adequacy with the global aim of SD. In accordance with [START_REF] Van Bellen | Sustainability Indicators -A Comparative Analysis[END_REF], who explained that the construction of indicators in order to measure sustainability must establish a connection from past to present and from present to future, we defined indicators to follow the evolution of SD teaching practices.

These indicators could have a practical utility, as a support for instructional decisions and for evaluating degrees of success in new educational tools. [START_REF] Lozano | Teaching Organisational Change Management for Sustainability: Designing and Delivering a Course at the University of Leeds to Better Prepare Future Sustainability Change Agents[END_REF] presented five main approaches for incorporating SD into higher education curricula: i) coverage of some environmental issues in an existing course or courses; ii) a specific SD course; iii) SD intertwined as a concept in regular disciplinary courses; iv) SD as a possibility for specialisation within the framework of each faculty; v) SD as an undergraduate or post-graduate programme.

UniLaSalle has followed the third approach as SD is adapted to the nature of each specific course (Abdul-Wahab, Abdulraheem, and Hutchinson 2003; Ceulemans and De Prins 2010; Kamp 2006; Peet, Mulder, and Bijma 2004; Thomas 2004). No specific courses on SD were defined for one major reason: all the curricula need SD, profoundly, depending on the type of know-how (expertise) the future engineers are trained for.

They will work on energy production, in mining or public works, in agriculture and biomass production, in environmental protection, or in the food industry. 2 [START_REF] Cros | L'innovation en éducation et en Formation[END_REF] presented the theoretical works about the concept of innovation in social sciences and asked how this research could encourage reflection on innovation in education and training. She thought that 'this innovation is a relatively recent subject of reflection. It has interested social scientists since 1960 (Bashi and Zass 1992) and often in operating terms'. Later, she discussed 'innovation in education and training as presented by the works of researchers in education'. She showed the complexity and the difficulties of 'attachment' to academic disciplines. She proposed to conceptual-ise this specific innovation because this field is one that didn't have theories, models or strategies to improve the work of teachers and researchers.

In the same article, [START_REF] Cros | L'innovation en éducation et en Formation[END_REF] presented the development of innovation in education and train-ing according to eight entries to, or views on, innovation. In this study, our problematic refers to the fifth and the seventh issues respectively focused on:

• The evaluation of innovations either by a fine analysis of the objectives or by the analysis of tea-cher's performances and their attitude towards innovation.

• The place and the role of different categories of stakeholders in the educational system: students, teachers, and academic staff.

In the same vein, [START_REF] Huberman | Innovation up Close. How School Improvement Works[END_REF] adopted an empirical approach and analysed the attitudes of teachers through representative case studies, and changes in terms of restriction and effects on students when several innovations were applied in different contexts. This work uses such studies and their results as the basis for an empirical study of the perception of the interrelation-ship between SD and innovation in education.

2. Methods to analyse and discuss the problem 2.1. Articulating the relationship between SD and innovation in higher education

Operationalisation of SD requires strategic thinking. It is, therefore, necessary to innovate in the content of training courses but also probably in their organisation and their pedagogical modalities. But this relationship is probably not deterministic since it goes through representations of what SD requires. between the epistemology of various disciplines and the history of education in their domains [START_REF] Sonntag | Les Questions de Formation Dans les Ecoles D'ingénieurs. Un Débat Reconnu[END_REF].

In agriculture sciences, in France, for the last fifty-six years, training in HSS has been considered as necessary, due to the age and the importance of agricultural law, the recognition of close links between agriculture and society, and the importance of territorial management and development. Agriculture is at the origin of civilisations.

All higher education engineering schools in agriculture, even in the seventies, included training courses in humanities and social sciences. Food science engineers also need knowledge on the social and cultural basis of human consumption of food, more and more related to the internationalisation of the food business. Generally speaking, engineers in agriculture and food sciences need some basic knowledge of HSS.

According to [START_REF] Sonntag | Les Questions de Formation Dans les Ecoles D'ingénieurs. Un Débat Reconnu[END_REF], a better adaptation of individuals to professional activities and economic realities is due to the increase in teaching of humanities and social sciences. We believe that HSS should be thought as a useful knowledge for students, to acquire skills or 'competencies' and to be able to adapt themselves to work in companies, and/or to be also able to change them. An integrated sustainable approach should involve the evolution of the academic programmes in a transversal way.

2.1.2. Context of UniLaSalle and its choice about SD and innovation

On the campus, the students stay during five years and they often have a behaviour of consumers of campus facilities. To learn that they have to be involved in the sustainability of their Institute is a novelty for them. In addition to engineering degrees, some masters (Management of Urban Food Security, Plant Breeding, Data

Management in Agriculture) train future actors, coming from inter-national networks, to work in areas directly engaged with the issues of SD. Insofar, UniLaSalle pro-vides training which is at the heart of SD issues and also specific and applied courses which are answers to SD. It is obvious that the whole Institute has to take the choice of SD at all levels. The context in which the Institute evolves seems favourable:

international networks of Lasallian universities; international networks of universities in agriculture/agronomy/geology, accurate insertion in the regional territory and numerous partnerships with industry. After fifteen years of continuous growth, with now more than 2500 students, and about 450 graduated engineers every year, the institute has begun to acquire a new but real recognition in France.

A strategy of development of teaching and research chairs in partnership with companies and ter-ritorial institutions has been undertaken on three subjects: Risks in Agriculture, Agro-Equipment & New Technologies, and Plant Breeding. A fourth one is being considered: all the other chairs make it possible to work on many questions induced by the choice of SD. Therefore, the choice to set up a teaching strategy, research, and governance consistent with the imperatives of SD seem 'natural'. In this context, as presented in the previous article (Fourati-Jamoussi et al. 2015a), the question was: how to place an integrated approach of SD in the strategy of UniLaSalle? The Institute implemented many actions at all levels from an evaluation perspective [START_REF] Lönngren | Dealing with the Multidimensionality of Sustainability Through the use of Multiple Perspectives -A Theoretical Framework[END_REF], the first results of the dimensions, or axes of SD, and the choice of strategic variables were published in the cited article above.

We analysed these actions and their new perspectives on management, practices in teaching and research about sustainability in an engineer higher school.

To compare the evolution of UniLaSalle with roughly comparable structures [START_REF] Lima | A Sustainability Evaluation Framework for Science and Technology Institutes: an International Comparative Analysis[END_REF]) raises many problems, as the chosen indicators can experience biases that are difficult to assess: different financial resources, specific student populations, diverse academic programmes, specific and non-comparable business activities of graduate students.

Problematic and research questions

The question is now the following: does the strategic choice of SD promote innovation in education? We, therefore, undertook a study on the importance of SD as an Innovation vector for higher education, from the teachers' point of view. To the extent that SD requires the acquisition of capacities/skills and to take into account, in education, the necessary capacities/skills of future technical and economic actors, it seemed consistent that SD could be an innovation vector.

Very few studies investigated the ways in which education and SD have evolved or what is the impact of the choice of SD in higher education on the overall content of education and teaching methods [START_REF] Crofton | Educating for Sustainability: Opportunities in Undergraduate Engineering[END_REF][START_REF] Quist | Backcasting for Sustainability in Engineering Education: the Case of Delft University of Technology[END_REF]. [START_REF] Sterling | Higher Education, Sustainability, and the Role of Systemic Learning[END_REF] argues that 'the sustainability does not simply require an 'add-on' to existing structures analysing 2513 studies published between 2000 and 2015; their findings show that 'the transdisciplinarity can be considered as an epistemic transgression that relates societal issues with scientific problems'. This study offered 'an alternative approach related to the lack of comprehensive research works on how to organize diverse assets involved in Sustainability in Higher Education'.

We focused more on the last two years of the curricula (Master level), as these are the ones leading to professional practice. The Institute follows the Bologna process, but it follows also the French system for engineer training in five years. The strategic and operational directions of the Institute are underpinned by the integration of a vision of SD and therefore should bring both opportunities and constraints involving creativity and innovation. In practice, does SD promote or restrict innovation?

Furthermore, for students learning a trade, they must think about it in the framework of SD. Concerning SD, we defend the idea according to which there is a teaching specificity that requires a change in perspective. It seems that integrating SD in higher education, which leads to new useful skills for a professional activity, should be a source of innovation. SD comes from different awareness of our responsibility towards future generations (Brundtland 1987;[START_REF] Jonas | Le principe responsabilité : une éthique pour la civilisation technologique[END_REF][START_REF] Jonas | Le Principe Responsabilité. Une éthique Pour la Civilisation Technologique[END_REF]. The reasons which led to the construction of the concept of SD are thus derived from philosophical reflections on human becoming and from our responsibility in the evolution of the biosphere. This is indeed a new ethical dimension. This responsibility, which guides economic decisions, takes the environment into account and should lead to innovations in the structure of education as well as in the content of theoretical courses.

Methodology

To understand precisely how SD is articulated with educational innovation, both in content and in method, we pursued the examination of [START_REF] Holmberg | Embedding Sustainability in Higher Education Through Interaction with Lecturers: Case Studies From Three European Technical Universities[END_REF] about the integration of SD into educational programmes in three universities to show the difference of their activities and to describe the methods used to achieve the embeddedness of sustainability in curricula with teachers and other actors. We chose a qualitative methodology [START_REF] Wacheux | Méthodes Qualitatives et Recherche en Gestion[END_REF][START_REF] Yin | Case Study Research. Design and Methods[END_REF] based on a single case study of UniLaSalle, in order to place the Institute in its role of 'living Lab'. This study uses 1 type of nonnumerical data that were collected from 27 semi-structured interviews (during 45 min)

with 2 groups: the Executive Management Team and the Curricula Management Team.

The first one includes the Vice-President, the Director of studies, the student life Director, the Directors of each specialisation pathway, the previous and the new Director of SD, the Manager of the master in management of urban food security, the professional integration Manager, the Information Technology and Communication in Education manager, the Scientific Director and one research unit Manager. The role of this team is to guide the strategic decisions of teaching and research. The second one is composed of 14 Curricula Managers including three academic advisors. Their role is to implement the programmes of the different courses. As interviewees did not answer the same item for each theme (e.g. Figure 2), we have less than 27 answers for each item. SD and innovation in engineering education? All the answers to the questions were openended questions that were recorded. To analyse qualitative data, we used NVivo 9 4 that allowed us to: i) organise, classify and analyse responses more effectively, ii) examine relationships between data and themes, iii) visualise our project and draw models and charts.

We summarised the 'coding process' of Philip Adu 5 to conduct this qualitative analysis with NVivo 9: 'we identify and code relevant information and put them in their respective nodes'. Figure 1 shows each node that contains the number of relevant information coded; they are called 'node references' (code Frequencies). For each new node, 'we are expected to label and describe it'. We have two kinds of nodes: 'Parent to represent a theme (defined during the phase of building the survey) and Child to represent a category (the sub-themes were defined after the transcription phase)'. To generate and label nodes/codes, 'we assigned a word or phrase (a concept) that best represents the relevant information' [START_REF] Bazely | Qualitative Data Analysis with NVivo[END_REF]. After reviewing the characteristics of the research questions, 'we used the answer to code (create a node) and represented the information' [START_REF] Kane | Concept Mapping for Planning and Evaluation[END_REF]. The processing of the collected data with those discussions (from June 2015 to March 2016) allowed us to better understand the dynamics of the innovation process in Uni-LaSalle for the past two years, and the role of SD in the events of creating new courses, masters and new teaching practices in a specific situation. The following section details the results of these interviews. (d) Social innovation, seen as a systematic sharing of experiences (monthly) between teachers helps increasing reflexivity. These formal meetings are not merely discussions, but imply sharing teachers' experience.

Results analysis and discussion

The most frequently cited innovation by the respondents is the innovation in teaching methods because this type is central to the strategy of the Institute, we must support practices and all innovations … We are in a systemic approach; we innovate in pedagogy for each teacher. To really get a dynamic approach, we designed a 'support cell'. It is a group designed to offer exchanges between teachers which are presentations and explanations followed by a collective discussion. We can be innovative if we adopt a reflexive posture both personal and collective. (Director of studies). [START_REF] Sonntag | Les Formations D'ingénieurs. Des Formations Professionnelles et Professionnalisantes. Orientations, Contenus, Contextes[END_REF] highlighted the dynamism of the teaching in educational programmes. He found a promotion of interactive educational methods (by projects, by problems, simulations) in opposition to traditional pedagogical methods (based on the transmission of knowledge)

which is reputed as passive by students.

This categorisation of innovation in engineer training and the definition of SD have been communicated in a paper at the Ingenium Symposium (Fourati-Jamoussi et al. 2015b).

We develop the results of the interviews below, regarding the reasons to innovate in engineering education and the relationship between this innovation and SD.

(1) What are the main reasons to innovate?

Figure 2 shows the distribution of the answers to the question on the reasons to innovate by execu-tive and management teams (executive managers and managers of Master or research unit …). The first cited reason refers to the constraints of natural or global environment change. Three other reasons are mentioned: to adapt training to the engineer's profile; to stimulate the collective effort and favour sharing between teachers; the evolution of education. This global presentation requires a comparative analysis: see Figures 3 and4.

Figure 3 shows that the reasons to innovate, as the curricula managers or the academic advisors say, are quite different. The two first answers are focused on the needs of the manufacturers and companies and on the demands and motivation of the students, meaning the constraints connected with their professional and social environment. The constraints of the natural or global environment change come after.

Directors are more concerned with the issue of global environment and education while teachers in charge of final curricula look for the best compromise between companies' needs and students' needs and wants (Figure 4). For the operational actors, economic problems and companies needs are considered as a priority. This is in tune with their activities; the first group has a strategic view, and the second a tactic one.

(2) Reasons to integrate SD in the courses Regulatory and environmental issues are also important as they establish rules, Responsibility is just evoked. For all of these respondents, the European dimension seems to have nothing to do with the reasons to integrate SD in courses (Figure 7). Figure 6. Reasons of SD integration by the Curricula Managers Team.

(3) SD, a three or four pillar concept?

Figure 8 shows that, unsurprisingly, the three pillars of SD are well integrated, although environ-mental issues are a little more considered. An important element of our results is the emergence of a fourth pillar. The three respondents who insisted on this fourth dimension came from three different horizons: the previous Director of Agronomy speciality, two curricula managers one is a geologist and the other is an agricultural ecologist. They affirm that the governance of energy and mineral resources is specific and different from environmental issues which are more connected to the natural living world. This new pillar is said to describe fundamental technical needs, less connected with the living world but more with minerals and physics, and to involve strong geopolitical components; this is close to [START_REF] Vatin | La Pensée Agronomique de Jean-Edmond Briaune : Pragmatisme, énergétisme et Calcul économique[END_REF] point of view:

he considers that engineering in agronomy and geology contributed to the genesis of the thought on energy. Environment is globally to be protected, and this protection should be local. Energy and minerals are to be found, extracted, trans-formed and produced; sources can be local and spread nearly randomly, but the needs are universal and increase with economic development; and it appears that they carry heavy geopolitical stakes. Energy is lost with use, but minerals, metals and their products can be produced and recycled through energy consumption. (4) Potential relationships between Innovation and SD It appears that there is a large consensus that SD is both a restriction and a stimulation for innovation when analysing Figure 9. But stimulation for innovation is considered to be more important for directors and for curricula managers. This means that, beyond the difference in positioning, the reference to SD is now perceived as a stimulus to innovation for the majority of respondents (85%). This is an important result, because, two years before, there was no real consensus. This change can have occurred as a consequence of the overall commitment of the Institute, but also with the evolution of a collective representation of SD. Nevertheless, it appears that the rate of people who consider SD as both a constraint and a stimulus for innovation is somewhat stronger among managers (no exception). It seems as if they had understood more than the others that 'contradictory' could be 'complementary', and that the axiom/principle of the 'excluded middle', in this case, could not be applied. These two results, as described in Figure 9, indicate an implicit recognition of complexity and that a constraint can be good for innovation, and sometimes can promote it although it could together restrict it. A constraint as SD could be thought as a selective system for innovation; it has a steering effect. It is not a simple result of the interviews as the answers are open-ended. Some specific and unpredictable items appeared, like the one concerning the European dimension. This is an important element of the strategy of many higher education institutions in Europe.

We keep it to check if some evolution could appear in the future and if it can be different when broadening to the students.

After the analysis of all the Figures (2-9), Figure 10 summarises the points raised in this analysis. This model is more oriented in a perspective of perception and integration [START_REF] Lönngren | Dealing with the Multidimensionality of Sustainability Through the use of Multiple Perspectives -A Theoretical Framework[END_REF] than of impact, which could be studied later. The outcomes show that three major reasons are considered when integrating SD. It is interesting to note that very few respondents refer to the European dimension, although most of the regulation originates from European directives (for example, the Energy Performance of Buildings Directive). Our model shows that the reasons to integrate SD in training courses lead to a process of continuous improvement in which promotion and restrictions are mixed, although promotion is stronger [START_REF] Deardorff | Outcomes Assessment in the Internationalization of Higher Education[END_REF][START_REF] Geels | Technological Transitions as Evolutionary Reconfiguration Processes: A Multi-Level Perspective and a Case-Study[END_REF][START_REF] Koehn | Evaluating Sustainability Education: Lessons From International Development Experience[END_REF].

According to [START_REF] Cros | L'innovation en éducation et en Formation[END_REF], the process of innovation is more essential than the content. Although our study does not aim at distinguishing process innovation and content innovation, these results offer the possibility to distinguish four types of relevant innovations, according to a mix of Huberman's typology (1973). The 'materials' used by teachers have evolved with information and communication technologies that have boosted the potential for teachers to implement new teaching strategies [START_REF] Bridgland | Perspectives On … Information Literacy in the "E" Environment: An Approach for Sustainability[END_REF][START_REF] Konting | Leadership Development for Sustainability of e-Learning[END_REF][START_REF] Viegas | Critical Attributes of Sustainability in Higher Education: a Categorisation From Review[END_REF][START_REF] Wang | Professional Development to Enhance Teachers' Practices in Using Information and Communication Technologies (ICTs) as Cognitive Tools: Lessons Learned From a Design-Based Research Study[END_REF]). The 'concepts' correspond to content innovation about the programme change (integration of SD). But in this study, the innovation in teaching is defined as a specific association of materials and teaching methods; so it is a mix of 'materials' and 'concepts'. Hence, 'interpersonal relationships' correspond to the social innovation that concerns exchanges of experiences between teachers and we can add the roles of teachers who act as students' coaches. Finally, the specificity of SD could have some impact on the nature of innovation, through a higher responsibility of engineers in tomorrow's society (Baillie and Catalano 2009; Bell 2011). Innovation in SD integrates necessarily means and aims in a retroactive loop.

From this analysis, we discovered a real collective awareness, but both some requests for faster progress and some obstacles against progress. SD appeared to be a differentiation strategy with added value for the Institute and for the teaching programme. It is therefore a long-term strategy that depends on continuous involvement. It is necessary to simultaneously modify the contents and the posture, the governance and the behaviour.

Discussion and research limits

The integration of SD in higher education is of utmost importance to understand how it is taking place and how it could be possible to promote it. Authors have shown that introducing SD requires teaching innovations. But it is far from certain that the educational innovations required are SD' specific. There is a systemic effect between a SD strategic positioning and the content of knowledge. Consequently, there is a need for more consistency in interdisciplinarity within the pedagogical methods. For example, it has been at least 40 years since we know that interdisciplinarity is a source of innovation, regardless of the concepts of sustainability. At the UniLaSalle Institute, strategic choices for growth, the implementation of a quality system, the increasing use of digital and video, SD, transformation of teaching content, promotion of innovation and entrepreneurship, work on teaching innovation, have all been taken practically at the same time. It is not certain that the SD choices were the driving forces, because systemic analysis, interdisciplinarity, and even flipped classroom were set up independently and often before SD education. In other words, it is not because the incorporation of the SD can transform teaching, that the transformation of the latter cannot take place in the absence of SD teaching. Thus it is important to acknowledge the fact that this hypothesis would necessitate further investigation about the links between SD choices and innovation in teaching. It turns out that the concerns of sustainability in agriculture and living sciences are much older than the political conceptualisation of SD. This research was motivated by the perception that the integration of the SD evolved less quickly than the curricula.

The study of innovation in education and training requires an intersection of disciplines and there-fore a pluridisciplinarity approach (Cros 1997). Pluridisciplinarity addresses an object of study according to the juxtaposition of multiple specialised looks. The problem lies in the fragmentation of approaches, although it is a way of approaching all aspects.

The difficulty is to conceptualise innovation in this field; it is a reflexive research which includes innovation in knowledge contents in permanent interaction with innovation in pedagogy, teaching and learning. These latter were found to be attributes of knowledge assets [START_REF] Viegas | Critical Attributes of Sustainability in Higher Education: a Categorisation From Review[END_REF].

Alike [START_REF] Roby | Place et fonction des SHS dans les Ecoles d'ingénieurs en France : état des lieux, enjeux et perspectives épistémiques[END_REF], we think that innovation as well as SD could be considered as good opportunities to integrate HSS alongside engineer sciences curricula. The objective of the Institute is to train 'operating' engineers in a world of competitive education to enable students to understand the logic and strategies of actors in this context of life sciences, earth and environment. To focus on the development of young skills at the end of basic training, education should be thought as an action for present needs and also for the development of capabilities or skills [START_REF] Wiek | Key Competencies in Sustainability: a Reference Framework for Academic Program Development[END_REF], in the medium and long-term.

Pedagogy can be considered more as a technique than a science; it is a skill that combines objectivity and subjectivity, because its object is the art to transmit knowledge, know-how, methods and also expertise, and so it depends on the field in which knowledge is transmitted. It can be defined also as accompanying somebody for the acquisition of new skills. [START_REF] Mintz | Education for Sustainability in Higher Education: A Multiplecase Study of Three Courses[END_REF] defined 'pedagogies as teaching strategies to improve students' skills'. This very strong entanglement between science and techniques, so present in 'post-modern' times, can lead to confusion; but innovation itself is a process that is in fact an epistemic transgression, by relating phenomena that refer to different sciences. Even scientists can commit epistemic transgression when they discover something new through an analogy with other concept in another discipline. Discovery, invention, innovation are in general epistemic transgression [START_REF] Simondon | Imagination et Invention[END_REF].

Among the research limits we raise, we must mention the following: i) one engineering education school was studied; therefore it could be seen as a case that cannot necessarily be generalised; ii) the perceptions of institutional actors may change and not correspond to the practice of the institution;

iii) the opinion of students would also have been interesting to understand how teaching has an impact of their perceptions of SD and SD values. Does teaching change values and students' SD behaviour and attitudes in the future? What is the impact of SD teaching in real life?

Conclusion

Integrating SD in engineering education is not only adding material. The task is also to transform teaching, to make students more inclusive and more open to multidimensional issues concerning social and environmental responsibility while meeting economic criteria. It appears that for most teachers, it is really a discovery which should have an important impact, on the medium term, on their activity; they have to learn by themselves a different language. Comparatively, the students listen to the SD goals and learn some tools, as much new materials. Although higher management is aware of the need to have a holistic and complex approach of SD, curricula managers are even more concerned by economic requirements.

The results of our research suggest that people in charge of the strategic choices consider that the SD is a major reason to innovate, either is in the economic action or in the education. Teachers closer to the actual job opportunities of future engineer's place more emphasis on the economic reasons and on motivations of students in situation to be soon engineers. In this case, the SD, as a reason to innovate, is a more strategic than tactical choice. The strategic approach is associated with the ethics of responsibility, while the concern for the professional integration of young people brings them closer to an ethics of attitude.

Executive Management Team is more concerned with the issue of global environment and education while teachers in charge of final curricula look for the best compromise between companies' needs and students' needs and wants (Figure 4). For the Curricula Managers, economic problems and companies needs are considered as a priority.

This is in tune with their activities; the first group has a strategic view, and the second a tactic one. This is confirmed by the figure 7; regulation is also directly linked with tactic point of view.

The assessment of a possible fourth pillar in SD should be established and elaborated European dimension could also be developed. The signal is lower, but is more typical of the Institute' strategic choices'.

The link between research and teaching seems very important. It is possible that the number of publications, reflexive research and teachers/researchers' and managers/directors' attitude towards innovation and SD in UniLaSalle have all had an impact on SD adoption by teachers and on its integration in the Institute.

This research, although based on previous theoretical analysis (Fourati-Jamoussi et al. 2015a), is an empirical study. We attempt to understand how SD is really implemented into engineering school. This is the reason we used a 'living Lab' approach, in order to specify teachers' and managers' perception and reflexivity.

Indeed, SD is more a posture, a way of being and living, than a specific discipline such as mathematics, physics or biology. It could be thought as a new designing approach or a new 'value': how to act in a global system on which my action has an effect? I am in the system, and whatever I do, I change the system. In this point of view, goals and tools to achieve the goals could be classified as similar categories: something which changes the system. In that case, to be able to listen to the whole environment is a new and important skill to develop. Here is probably the most important innovation to implement in pedagogy, teaching, and training: the ability to listen and to perceive even very weak but persistent signals.

SD challenges reveal some specific stakes, and, as an answer, a posture forcing the Institute to create its own SD model that could be really specific. It is now known that the more complex a system is, the more numerous the possible representations of it could be.

Our model leads to new possibilities to broaden this research at different levels. First, we have to implement this research at the students' level, and more quantitative results would be useful. This could help to better understand the relationship between Topdown incentives and Bottom-up proposals. We have already designed a first survey for students, in order to validate this model, based on the responses of about 300 students, specifically in master level. Depending on the result, it could be broaden to different situations, e.g. after a six month training course in foreign institutions.

Another survey for teachers is underway. Second, it would be insightful to test the model on other peer engineering schools, and then on other academic institutions.

Such a methodology could be used to study other relationships between SD and specific educational innovations.

  Entrepreneurship and Innovation. Research areas ('Agroecology' Unit, 'Quality of Agricultural Resources and Processing' Unit, 'Process Innovation, Competitiveness in the Agriculture and Rural Territories' Unit, 3 'Basin, Resources and Tanks' Unit) associated with

  and curricula, but implies a change of the fundamental epistemology in our culture and in our educational thinking and practice […], sustainability is a gateway to a different view of curriculum, of pedagogy, of organisational change … '. Multiple inter-national declarations[START_REF] Wright | Definitions and Frameworks for Environmental Sustainability in Higher Education[END_REF] refer to the need to include SD across the curriculum and to develop interdisciplinarity and transdisciplinarity research as well as public outreach.[START_REF] Viegas | Critical Attributes of Sustainability in Higher Education: a Categorisation From Review[END_REF] identified attributes of sustainability in Higher Education by

  innovation in engineer training, as described by the respondents of the interviews, reveal four different types of innovation that could be named as: a) Educational innovation; b) Content innovation; c) Training Teacher's innovation; d) Social innovation.

Figure 1 .

 1 Figure 1. NVIVO data figure for coding process. All sub themes are not presented in this screen capture (+ in a node means that the sub themes are not visible).

  (a) Educational innovation concerns the teaching methods and the new tools involved in teaching. It can be described according to different formalised situations and implies a change in the relationship between students, their involvement, and the teacher: flipped classroom[START_REF] Bergmann | Flip Your Classroom: Reach Every Student in Every Class Every Day[END_REF]; project approach, inductive method; tools and materials used to make this type of innovation (Mooc, Videos, boxes, podcast, audio, digital tablets …); 'reverse professionalization' (It is the used terms for an adapted project training, build on the request of a sponsor, which is interested in a project to be realised by the students. We have no references about such project training courses) and coffee meetings between students and entrepreneurs to share experience stories.According to the Vice-President of UniLaSalle, 'The curricula innovation is a state of mind, to share with teachers: try and test new practices for the transmission of knowledge, not only through IT tools but also with traditional tools. Innovation in courses may be promoted through transdisciplinarity'. (b) Content innovation for student engineers and the creation of new courses and Master degrees are due to close relationship between research and education and the adaptation to external changes in higher education and the business environment. The innovation in the content is directly connected to the evolution of knowledge, know-how, or specific tools developed for engineers.(c) Training teacher's innovation: joined in the strategy of the Institute, we can consider that this training helps to maintain optimum consistency between teachers' conceptions and behaviour when engaging in curricula innovation (Béchard and Grégoire 2005). It is not just more training. It is a radical change in the contents and the ways of training, considering that teachers are adults who can have reflexive thinking on their own practices, their own behaviour, and their own representation about what is teaching. This falls within an all-round personal development approach.

Figure 2 .

 2 Figure 2. Reasons to innovate for Executive Management Team.

Figure 3 .

 3 Figure 3. Reasons to innovate by Curricula Managers Team.

Figure 5

 5 Figure5clearly shows that for directors, the first reason for integrating SD is to train Responsible Engineers. Ethics per se seems not to be considered; the meaning of such answers is that Ethics is directly considered as responsibility. Even if they do not mention this, they clearly follow the distinction of Max Weber between the 'ethics of responsibility' [in German: Verantwortungsethik] and the ethics of attitude [in German: Gesinnungsethik] through the affirmation: 'engineers should respond for the consequences of their actions'.In contrast, as Figure6depicts, teachers in charge of professional-qualification curriculum modules and academic advisors, precisely focus on ethics. During interviews, ethics was specifically linked to the rules of the technical profession, which is more connected to ethics of attitude [Gesinnungsethik], according to Max Weber.

Figure 4 .

 4 Radar fusion of Figures2 and 3

Figure 5 .

 5 Figure 5. Reasons of SD integration by Executive Management Team.

Figure 7 .

 7 Figure 7. Radar fusion of Figures 5 and 6.

Figure 8 .

 8 Figure 8. Pillars of SD integration by Executive Management and Curricula Managers Teams.

Figure 9 .

 9 Figure 9. The potential relationship between innovation and SD by Executive Management and Curricula Managers Teams.

Figure 10

 10 Figure 10 presents the model which has been built from the analysis of the answers.

  She based herself on the work of[START_REF] Huberman | Comment S'opèrent les Changements en éducation : Contribution à L'étude de L'innovation[END_REF] who identified three types of 'products': the 'materials', which belong to the textbook; the 'concepts', which means the change in programmes or teaching methods; and changes in 'interpersonal relationships' which are related to the mutual roles of teachers and students.

Figure 10 .

 10 Figure 10. Actual Model of UniLaSalle: Potential relationship between SD integration and innovation process in Engineering Education

  in a future research project. It would be interesting to validate it by an additional research. A global governance for energy and minerals is really different from climate change and environmental protection issues. The first point to check is the following: is it not already included in Social / Economic / Environmental Pillars? The second point could be to analyse whether if a definition of such a fourth pillar would help geopolitics governance as the distribution and consumption of mineral resources are very specific.

  The third group corresponds to HSS training embedded in professional situations; this group takes into account engineering trades to try to detect the skills needed in their professional practices. Educational research can help to better understand the evolution of engineer training courses. A link can be made

2.1.1. Theoretical analysis In France, there are different models of engineering schools; integrating SD approaches differs from one institution to another because of the importance of Humanities and Social Sciences (HSS) is variable. In her thesis,

[START_REF] Roby | Place et fonction des SHS dans les Ecoles d'ingénieurs en France : état des lieux, enjeux et perspectives épistémiques[END_REF]

presented the communication of

[START_REF] Béraud | Les sciences humaines et sociales dans les Écoles d'ingénieurs, tentative de typologie[END_REF]

who proposed three categories of higher education engineering schools: the first group isn't interested in HSS, the trained engineer is a 'one-dimensional' expert whose missions are purely technical. Organisational missions are considered only in connection with their technical aspects; the second group whose archetype is 'Ecole Polytechnique', considered that business techniques are learned after school: HSS are part and parcel of general training as well as fundamental sciences.

  The interview guide was built on six themes/questions: i) what is the definition of innovation in engineering education?; ii) what are the different types of innovations?; iii) what are the reasons to innovate at UniLaSalle?; iv) what is the definition of SD?; v) what are the reasons for integrating SD in the engineer training?; vi) what is the link between

Acknowledgments

We thank Gaëlle Kotbi, Associate Professor at UniLaSalle, for her participation in the reflection of the guide interview, Marie Chedru, Associate Professor at UniLaSalle, and Sylvie Lupton, Associate Professor at UniLaSalle, for the second reading and revision of the final version. We also thank all interviewees for providing the time to answer our questions; these answers have enriched the empirical part of this research.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Fatma Fourati-Jamoussi, Associate Professor in Marketing and Strategic Intelligence at UniLaSalle, PhD. in Management Sciences at the University Paris Dauphine. Member of INTERACT Research Unit UP 2018.C102 (Innovation Territoire Agri-culture et Agroindustrie, Connaissance et Technologie). She teaches mainly the Economic and Business Intelligence. Her research interests concern the evaluation of business intelligence tools, and technology intelligence process, Sustainable Development in Higher Engineering Education. Michel J.F. Dubois, Expert in Agriculture Sciences at UniLaSalle, PhD in Plant Molecular Biology and in Philosophy and Habilitation to supervise research (HDR). Member of INTERACT Research Unit UP 2018.C102 (Innovation Territoire Agri-culture et Agroindustrie, Connaissance et Technologie). He teaches Agriculture History and its challenges of today, Epistemology, History of technology. His main domains are Sustainable Development and Human and Technology Relationships in Agriculture Maxime Agnès, Assignment Manager for Sustainable Development at UniLaSalle, Sustainable Development Direction. Engineer (MSc in Agriculture), he is responsible for the implementation of the sustainable development. He also works in network with other education institutions in order to share good practices and to build a SD label. Finally he is involved in SD lessons and supervises student projects. Valérie Leroux, Vice-President at UniLaSalle, PhD. in Management Sciences. Member of INTERACT Research Unit. Her field interests deal with strategy, finance and entrepreneurship especially in agrifood sector and for SME's. Loïc Sauvée, Professor in Management Sciences at UniLaSalle, PhD and Habilitation to supervise research (HDR), Head of INTERACT Research Unit UP 2018.C102 (Innovation Territoire Agriculture et Agroindustrie, Connaissance et Technologie) and expert in applied social sciences, Scientific Direction. His teaching fields are: business organisation and marketing in agrifood sectors. His research fields are: governance of innovation processes in agrifood competitiveness cluster, alignment of quality management systems in agrifood chains and networks, implementation of CSR in food SMEs, dynamics of network governance; member of editorial board of the Journal on Chain and Network Science. Notes