Rafael Almar

Thomas Stieglitz

• Kwasi

Appeaning Addo

Kader Ba

• Gregoire

Abessolo Ondoa

Erwin W J Bergsma

Frédéric Bonou

Olusegun Dada

Donatus Angnuureng

Olivier Arino

Coastal Zone Changes in West Africa: Challenges and Opportunities for Satellite Earth Observations

Keywords: Satellite Earth observations, Coastal hazards, Vulnerability, Monitoring, Coastal zone management

The West African coastal population and ecosystems are increasingly exposed to a multitude of hazards. These are likely to be exacerbated by global climate change and direct impacts from local human activities. Our ability to understand coastal changes has been limited by an incomplete understanding of the processes and the difficulty of obtaining detailed data. Recent advances in satellite techniques have made it possible to obtain rich coastal data sets that provide a solid foundation for improving climate change adaptation strategies for humanity and increasing the resilience of ecosystems for sustainable development. In this article, we review West African coastal layout and current socio-environmental challenges together with key parameters that can be monitored and several coastal management programs that rely on satellite techniques to monitor indicators at the regional level. The social, technical and scientific problems and difficulties that hinder the interest of coastal practitioners and decision-makers to use the satellite data are identified. We provide a roadmap to precisely respond to these difficulties and on how an improved satellite earth observation strategy can better support future coastal zone management in West Africa.

The West African Coastline: Layout and Drivers

The low-lying West African coast from Mauritania to Nigeria can be classified into three main sectors (Fig. 1; [START_REF] Ibe | Sea level rise impact on African coastal zones[END_REF][START_REF] Alves | A review on coastal erosion and flooding risks and best management practices in West Africa: what has been done and should be done[END_REF][START_REF] Dada | Towards West African coastal social-ecosystems sustainability: interdisciplinary approaches[END_REF]):

• The northwestern sector of Mauritania, Senegal, and the Gambia is characterized by a narrow continental shelf with sand dunes and their generally narrow spits delineating river arms (with the exception of the cliff-bound southern coast in the Gambia River estuary), • The western sector of sand and mud from Guinea-Bissau to Sierra Leone with estuaries rich in mangroves and a wide continental shelf favoring the amplification of the tides, • The Gulf of Guinea coast from Liberia to Nigeria with a narrow shelf and straight barrier of sandy beaches, river inlets and lagoons [START_REF] Anthony | Morpho-sedimentary evolution of a delta-sourced, drift-aligned sand barrier-lagoon complex, western Bight of Benin[END_REF][START_REF] Feka | Managing mangroves for coastal ecosystems change: A decade and beyond of conservation experiences and lessons for and from west-central Africa[END_REF][START_REF] Alves | A review on coastal erosion and flooding risks and best management practices in West Africa: what has been done and should be done[END_REF].

The West African coast has a subtropical to tropical climate, primarily influenced by the Atlantic Ocean and the Sahara Desert [START_REF] Lewis | Climate impacts in the sahel and west africa: the role of climate science in policy making[END_REF]. The West African monsoon, a seasonal low-level atmospheric circulation pattern, represents, along with the Harmattan system, the primary driver of climate variability in the region. The most important rivers originate in the Guinea highlands and include the Niger, Volta, and Senegal rivers [START_REF] Diop | The western and central africa land-sea interface: a vulnerable, threatened, and important coastal zone within a changing environment[END_REF][START_REF] Anthony | Patterns of sand spit development and their management implications on deltaic, driftaligned coasts: the cases of the Senegal and Volta River delta spits, West Africa[END_REF][START_REF] Anthony | Recent shoreline changes in the Volta River delta, West Africa: the roles of natural processes and human impacts[END_REF]. For hydroelectric power generation, irrigation, and flood control purposes, most of these large rivers as well as smaller ones have been dammed in recent decades, significantly altering their hydrology Fig. 1 The West African coast (from [START_REF] Dada | Towards West African coastal social-ecosystems sustainability: interdisciplinary approaches[END_REF] Surveys in Geophysics 1 3 and sediment flows, accelerating coastal erosion downstream [START_REF] Ly | The role of the Akosombo Dam on the Volta River in causing erosion in central and eastern Ghana (West Africa)[END_REF][START_REF] Anthony | Patterns of sand spit development and their management implications on deltaic, driftaligned coasts: the cases of the Senegal and Volta River delta spits, West Africa[END_REF][START_REF] Diop | The western and central africa land-sea interface: a vulnerable, threatened, and important coastal zone within a changing environment[END_REF][START_REF] Anthony | Recent shoreline changes in the Volta River delta, West Africa: the roles of natural processes and human impacts[END_REF][START_REF] Anthony | Response of the Bight of Benin (Gulf of Guinea, West Africa) coastline to anthropogenic and natural forcing, Part 2: sources and patterns of sediment supply, sediment cells, and recent shoreline change[END_REF][START_REF] Dada | Evolutionary trends of the Niger Delta shoreline during the last 100 Years: responses to rainfall and river discharge[END_REF]Dada et al. , 2016aDada et al. , b, 2018;;[START_REF] Abessolo | Modeling the Bight of Benin (Gulf of Guinea, West Africa) coastline response to natural and anthropogenic forcing[END_REF].

The West African coast is generally considered a storm-free environment, dominated by North Atlantic distant swells [START_REF] Sadio | Shoreline changes on the wave-influenced Senegal River delta, West Africa: the roles of natural processes and human interventions[END_REF][START_REF] Almar | On the key influence of remote climate variability from Tropical Cyclones, North and South Atlantic mid-latitude storms on the Senegalese coast (West Africa)[END_REF][START_REF] Ndour | On the natural and anthropogenic drivers of the Senegalese (West Africa) low coast evolution: Saint Louis Beach 2016 COASTVAR experiment and 3D modeling of short term coastal protection measures[END_REF] with their interannual fluctuation described by the North Atlantic Oscillation [START_REF] Almar | On the key influence of remote climate variability from Tropical Cyclones, North and South Atlantic mid-latitude storms on the Senegalese coast (West Africa)[END_REF]. The wave regime in the Gulf of Guinea area is mainly driven by extratropical storms, and their variability is modulated by the South Atlantic Annular Mode (SAM) [START_REF] Almar | Response of the Bight of Benin (Gulf of Guinea, West Africa) coastline to anthropogenic and natural forcing. Part 1: Wave Climate variability and impacts on the longshore sediment transport[END_REF][START_REF] Melet | What dominates sea level at the coast : a case study for the Gulf of Guinea[END_REF][START_REF] Abessolo | Beach adaptation to intraseasonal sea level changes[END_REF]. The evolution of the sandy coast is controlled by strong longshore sediment drift resulting from oblique waves. [START_REF] Laibi | Longshore drift cell development on the human-impacted Bight of Benin sand barrier coast[END_REF][START_REF] Almar | Response of the Bight of Benin (Gulf of Guinea, West Africa) coastline to anthropogenic and natural forcing. Part 1: Wave Climate variability and impacts on the longshore sediment transport[END_REF][START_REF] Almar | On the key influence of remote climate variability from Tropical Cyclones, North and South Atlantic mid-latitude storms on the Senegalese coast (West Africa)[END_REF]Giardino et al. 2017a;[START_REF] Anthony | Response of the Bight of Benin (Gulf of Guinea, West Africa) coastline to anthropogenic and natural forcing, Part 2: sources and patterns of sediment supply, sediment cells, and recent shoreline change[END_REF]). Tidal amplitude is typically micro-to meso-tidal, with the highest amplitudes recorded in Guinea, Guinea-Bissau and Sierra Leone (2.8-4.7 m; [START_REF] Diop | The western and central africa land-sea interface: a vulnerable, threatened, and important coastal zone within a changing environment[END_REF].

There is a wide variety of ecosystems and habitats along the West African coast. The richness of estuaries, deltas, coastal lagoons, and nutrient-rich cold water upwelling contributes greatly to the diversity of fish life in this region. These habitats include (1) wetlands, particularly those surrounding mangroves in a succession of deltas and estuaries, providing key habitats for migratory birds [START_REF] Diop | The western and central africa land-sea interface: a vulnerable, threatened, and important coastal zone within a changing environment[END_REF]); (2) coastal freshwater lagoons, deltas and estuaries, and a wide range of tidal marshes and seasonal swamps, also counting with seagrass beds located off some estuaries, archipelagos and deltas; (3) sandy beaches, considered important nesting ecosystems, especially for sea turtles.

The dominant factor affecting the waters of the continental shelf is coastal upwelling, which is the source of the rich fish production of the region (Fig. 2).

Socio-Environmental Threats

The rapid emergence of new infrastructure, urban expansion and densification, superimposed on the effects of climate change, is rapidly accelerating the deterioration of coastal ecosystems and their ecological service functions. Today, there is increasing demand for natural hazard management in coastal areas [START_REF] Goussard | West African coastal area: challenges and outlook[END_REF][START_REF] Alves | A review on coastal erosion and flooding risks and best management practices in West Africa: what has been done and should be done[END_REF][START_REF] Dada | Towards West African coastal social-ecosystems sustainability: interdisciplinary approaches[END_REF]. Lowlying coastal areas, estuaries, and deltas are most vulnerable to coastal flooding (Nicholls and Tol 2006;World Bank 2020;Duku et al. 2021). Sea-level rise, coupled with an increase in the intensity or frequency of extreme events, will have severe effects on coastal development (IPCC report, Oppenheimer et al. 2019). Many coastal and island areas will be submerged or subject to increasingly frequent flooding, causing considerable damage [START_REF] Goussard | West African coastal area: challenges and outlook[END_REF][START_REF] Dada | Recent coastal sea-level variations and flooding events in the Nigerian Transgressive Mud coast of Gulf of Guinea[END_REF].

Along the West African coast, a rise above the global average is expected (World Bank 2020; [START_REF] Marti | Altimetry-based sea level trends along the coasts of Western Africa[END_REF]). This could have dramatic consequences for some coastal areas located just above current sea level. Major coastal cities and historical heritage in the region are at great risk [START_REF] Ouikotan | Evolution récente du trait de côte dans le golfe du Bénin Exemples du Togo et du Bénin[END_REF][START_REF] Vousdoukas | African heritage sites threatened as sea-level rise accelerates[END_REF]. Saltwater intrusion into coastal aquifers will be more frequent and could gradually render aquifers unsuitable for consumption and agriculture. The assumption of a 1 m rise in sea level would lead to a considerable increase in coastal hazards, mainly affecting low-lying sandy and muddy coasts and mangroves. Major lagoon systems will also be affected [START_REF] Chaigneau | From seasonal flood pulse to seiche: multi-frequency water-level fluctuations in a large shallow tropical lagoon (Nokoué Lagoon, Benin)[END_REF].

Some areas of the region, especially along deltas and megacities, are progressively subsiding due to human activities such as oil and gas development, freshwater extraction for agriculture, and urban densification, exacerbating the effects of sea-level change there. Subsidence and mangrove clearing have increased erosion to about -30 m/yr in Nigeria [START_REF] Ebisemiju | An Evaluation of factors controlling present rate of shoreline retrogradation in the Western Niger Delta Nigeria[END_REF]Dada et al. 2016b[START_REF] Dada | Effect of coastal land use change on coastline dynamics along the Nigerian transgressive Mahin mud coast[END_REF][START_REF] Anthony | Response of the Bight of Benin (Gulf of Guinea, West Africa) coastline to anthropogenic and natural forcing, Part 2: sources and patterns of sediment supply, sediment cells, and recent shoreline change[END_REF][START_REF] Alves | A review on coastal erosion and flooding risks and best management practices in West Africa: what has been done and should be done[END_REF]. Indeed, the main source for smoking fish and shrimp is mangrove wood.

The African population is the fastest growing in the world [START_REF] Denis | Urban growth in West Africa: from explosion to proliferation[END_REF]. The coastal fringe accounts for about 56% of the gross domestic product (GDP) of West African countries (UEMOA/WAEMU 2011; [START_REF] Goussard | West African coastal area: challenges and outlook[END_REF][START_REF] Diop | The western and central africa land-sea interface: a vulnerable, threatened, and important coastal zone within a changing environment[END_REF]. The highest population density hotspots are located in some key megacities along the coast, including Dakar, Abidjan, Accra, Lomé, Cotonou, and Lagos.

Due to rapidly changing environmental conditions, the increasingly dense human population now faces the challenge of adapting its habitats and activities, but public governance generally fails to support it [START_REF] Dada | Towards West African coastal social-ecosystems sustainability: interdisciplinary approaches[END_REF]). The situation is further exacerbated by the lack of a legal framework for land use, planning and coordination for environmental protection. These heavily and densely populated West African coastal areas depend on the biological resources of the marine and coastal areas. Coastal fisheries are an important source of income in the region, employing 6.7 million people [START_REF] Thomas | Saving West African Fisheries[END_REF]). However, overexploitation of marine resources and degradation of nurseries will likely lead to gradual and significant depletion of fish stocks [START_REF] Diop | The western and central africa land-sea interface: a vulnerable, threatened, and important coastal zone within a changing environment[END_REF].

Water pollution is also a major aspect of environmental degradation in marine, coastal, and freshwater areas of the West African coast [START_REF] Diop | The western and central africa land-sea interface: a vulnerable, threatened, and important coastal zone within a changing environment[END_REF]World Bank 2020;[START_REF] Croitoru | The cost of coastal zone degradation in West Africa: Benin, Côte d'Ivoire, Senegal and Togo[END_REF]. Agricultural runoff from irrigation, including elevated nutrient and pesticide concentrations, contributes to increased eutrophication of estuaries, deltas, coastal and freshwater environments [START_REF] Diop | The western and central africa land-sea interface: a vulnerable, threatened, and important coastal zone within a changing environment[END_REF]. There are occurrences of seasonal invasive aquatic weeds in most freshwater aquatic areas, including coastal lagoons [START_REF] Diop | The western and central africa land-sea interface: a vulnerable, threatened, and important coastal zone within a changing environment[END_REF][START_REF] Ndour | Management strategies for coastalerosion problems in West Africa: analysis, issues, and constraints drawn from examples from Senegal and Benin[END_REF]. Sargassum beach landings are becoming an increasingly prevalent problem in the region [START_REF] Gower | Satellite images suggest a new Sargassum source region in 2011[END_REF][START_REF] Franks | Pelagic sargassum in the tropical North Atlantic. Gulf and Caribbean Research[END_REF][START_REF] Wang | Mapping and quantifying Sargassum distribution and coverage in the Central West Atlantic using MODIS observations[END_REF].

3

Coastal erosion is widespread in the region, with significant effects on coastal ecosystem functioning and livelihood support. Although the coastline is highly sensitive to natural erosion and sedimentation processes due to natural changes in wave regime, strong longshore drift transport, and river flow due to rainfall variability, human activities have intensified coastal erosion, including sand mining, disruption of hydrological cycles, construction of dams on rivers, construction of ports, dredging and deforestation of mangroves, etc., 2009;[START_REF] Laibi | Longshore drift cell development on the human-impacted Bight of Benin sand barrier coast[END_REF]Ozer et al. 2017;[START_REF] Sadio | Shoreline changes on the wave-influenced Senegal River delta, West Africa: the roles of natural processes and human interventions[END_REF][START_REF] Angnuureng | Influence of sea level variability on a microtidal beach[END_REF][START_REF] De Boer | Mapping the sandy beach evolution around seaports at the scale of the African Continent[END_REF]Giardino et al. 2017a;[START_REF] Ndour | Management strategies for coastalerosion problems in West Africa: analysis, issues, and constraints drawn from examples from Senegal and Benin[END_REF][START_REF] Almar | On the key influence of remote climate variability from Tropical Cyclones, North and South Atlantic mid-latitude storms on the Senegalese coast (West Africa)[END_REF][START_REF] Anthony | Response of the Bight of Benin (Gulf of Guinea, West Africa) coastline to anthropogenic and natural forcing, Part 2: sources and patterns of sediment supply, sediment cells, and recent shoreline change[END_REF][START_REF] Abessolo | Modeling the Bight of Benin (Gulf of Guinea, West Africa) coastline response to natural and anthropogenic forcing[END_REF].

Finally, tourism is also an important industry in some West African countries, with its impacts on coastal areas. The construction of infrastructure such as ports, hotels, and other recreational facilities directly on the coast has been responsible for clearing coastal vegetation, filling wetlands, and increasing sewage and solid waste loads (Giardino et al. 2017a) and, in some cases, has contributed to accelerated coastal erosion [START_REF] Appeaning | Detection of coastal Erosion hotspots in Accra, Ghana[END_REF][START_REF] Andrieu | Land cover changes on the West-African coastline from the Saloum Delta (Senegal) to Rio Geba (Guinea-Bissau) between 1979 and 2015[END_REF][START_REF] Angnuureng | Application of shore-based video and unmanned aerial vehicles (drones): complementary tools for beach studies[END_REF][START_REF] Dada | Towards West African coastal social-ecosystems sustainability: interdisciplinary approaches[END_REF].

Satellite Observation to Support the Management of Coastal Areas and Marine Activities

Coastal areas are notoriously expensive and difficult to measure and monitor using in situ techniques [START_REF] Benveniste | Requirements for a coastal hazards observing system[END_REF][START_REF] Melet | Earth331observations for monitoring marine coastal hazards and their drivers[END_REF][START_REF] Cesbron | Pan-European satellite-derived coastal bathymetry-Review user needs and future services[END_REF]. Due to the lack of consistent mapping regimes, the evolution of West African coasts is partially known and the processes driving these dynamics are poorly described (i.e., global climate change is still perceived as the dominant driver of coastal evolution, while local human pressure is often dominant and rather poorly documented; [START_REF] Dada | Towards West African coastal social-ecosystems sustainability: interdisciplinary approaches[END_REF]). Thus, it is in these regions that EO data have a particularly vital role to play; in many cases, there are few viable and cost-effective alternatives for assessing critical information for decision making and management. Satellite Earth observation (EO) represents a powerful tool for generating regionally consistent information. It provides a unique source of information that can help monitor and link hazards, exposure, vulnerability factors, and a wide range of potential risks. Most EO programs are moving toward free and open source policies so that the data generated can be used without restriction, making it more accessible today [START_REF] Traon | From observation to information and users : the Copernicus Marine Service Perspective[END_REF]. EO data can provide unprecedented understanding of the coastal environment. EO also provides valuable information in support of risk and disaster management, such as exposure mapping in support of preparedness and mitigation, early warning, and response; tracking of up-to-date, synoptic, and objective information on the infrastructure of assets at risk; early warning and tracking of a range of natural hazards, disaster response, and support for crisis mapping and damage assessment; and support for recovery/reconstruction/rehabilitation. Despite the high potential for coastal practitioners and scientists, these EO data are still only minimally used. We list the main EO geo-environmental variables that can be monitored and discuss the social, technical, and scientific issues or challenges that hinder the interest of these actors in using satellite data and how satellite observation of these geo-environmental variables can better support coastal zone management in West Africa (Table 1). Below, we briefly review the main EO-derived observations used in coastal research today, illustrating each parameter with an example from West Africa. 1 3

Land Cover-Land Use

EO land cover algorithms (reviewed in [START_REF] Pandey | Land use/land cover in view of earth observation: data sources, input dimensions, and classifiers-a review of the state of the art[END_REF]) can be used to determine the status of beaches/dunes, forests, and other vegetation types such as crops and mangroves, land artificialization [START_REF] Zanaga | [END_REF]. Many EO programs such as Landsat, Sentinel, SPOT, and Pleiades produce a huge volume of medium to high-resolution multispectral images every day that can be organized into time series. These time series provide a powerful tool for detecting and measuring spatial and temporal changes in anthropogenic and natural features. In addition, the temporal information provided by image time series allows for increased accuracy in land cover classification, producing up-to-date maps that can help identify changes in land over time and space.

Coastal land cover types can be generated by combining optical data (Sentinel-2, Landsat-8) and SAR data (Sentinel-1). A supervised classification method can then be applied to several spectral band indices derived from the optical data and backscatter information statistics from several SAR acquisitions [START_REF] Thomas | Mapping mangrove extent and change: a globally applicable approach[END_REF]). An illustration is given in the West African Coast 2020 Assessment Report of the Schéma Directeur d'Aménagement du Littoral Ouest Africain (SDLAO)/West African Economic and Monetary Union (UEMOA/ WAEMU) in a study of land use on the coast of Benin, with the aim of differentiating mangroves, forests, and agriculture for vegetated areas (Fig. 3). This information can be linked to in situ observations such as information on water quality, e.g., turbidity or the occurrence of algal blooms.

Urban area detection, in particular, benefits from combining optical and radar data into a common classification system. Especially in areas where cloud cover limits the acquisition of suitable optical data, radar data have a great advantage because they are independent of cloud conditions [START_REF] Parker | Discover the Benefits of Radar Imaging[END_REF]. Further research and experience in combination with ground truth data would provide better results and therefore a better basis for change detection analyses. A primary objective in the Benin example in Fig. 3 is the identification of mangroves. Differentiating them from forests remains difficult, especially for very dense vegetation (because the water below cannot be seen). However, advances in satellite technology, as well as the availability of freely available datasets and open-source software, have produced increasingly accurate and comprehensive datasets on the extent, structure, and condition of mangroves, which can contribute to ecosystem service assessments and stimulate conservation and rehabilitation efforts [START_REF] Worthington | Harnessing big data to support the conservation and rehabilitation of mangrove forests globally[END_REF].

The European Space Agency's Earth Observation for Sustainable Development (EO4SD) disaster risk reduction (DRR) product-mapping the condition and evolution of built-up areas for Greater Banjul-provides discrete information on the spatial distribution and shape of human settlements and urban expansion. New settlements are increasingly located in hazard-prone areas and are sometimes occupied by dwellings with building typologies that are particularly vulnerable to hazards. The EO4SD DRR products provide information on features at risk, which can be used to estimate exposure to a given hazard. A methodology for extracting built-up areas from Copernicus Sentinel-2 imagery is illustrated here by a processing chain using a deep learning model [START_REF] De Teyou | Deep neural networks for automatic extraction of features in time series optical satellite images[END_REF][START_REF] James | Convolutional neural networks for water segmentation using sentinel-2 red, green, blue (RGB) composites and derived spectral indices[END_REF]. It uses a semantic segmentation algorithm based on convolutional neural networks as a central piece of decision making on an annual time series of Copernicus Sentinel-2 images with 10 m resolution (channels: R, G, B, NIR). It is particularly interesting to see how the model can detect built-up areas from 10-m resolution images in areas virtually impossible for a human interpreter to grasp: The model sees beyond what is observable to the naked eye in the imagery (Fig. 4). The model is adaptable to the computation of entire regions due to its processing efficiency. It can be customized for certain geographic contexts and can learn and improve its accuracy with each new area analyzed and extracted.

Multispectral optical and Synthetic Aperture Radar (SAR) satellite data (e.g., PALSAR or Sentinel-1) are used to map and monitor coastal mangrove forests worldwide, including in West Africa [START_REF] Bunting | The global mangrove watch-A new 2010 global baseline of mangrove extent[END_REF][START_REF] Giri | Status and distribution of mangrove forests of the world using earth observation satellite data[END_REF][START_REF] Goldberg | Global declines in human-driven mangrove loss[END_REF][START_REF] Nwobi | Rapid mangrove forest loss and nipa palm (nypa fruticans) expansion in the niger delta, 2007-2017[END_REF][START_REF] Thomas | Mapping mangrove extent and change: a globally applicable approach[END_REF]). However, significant inconsistencies remain among the mangrove extent data products. Sargassum beach landings are also becoming an increasingly prevalent problem in the region. Since 2011, innovative satellite remote sensing analyses have provided strong evidence for the growth and spreading of Sargassum in the equatorial Atlantic [START_REF] Gower | Satellite images suggest a new Sargassum source region in 2011[END_REF][START_REF] Franks | Pelagic sargassum in the tropical North Atlantic. Gulf and Caribbean Research[END_REF][START_REF] Wang | Mapping and quantifying Sargassum distribution and coverage in the Central West Atlantic using MODIS observations[END_REF]. For example, based on an "alternative floating algal index" (AFAI), "FA density" maps are now provided daily as an average of the previous 7 days. [START_REF] Marsh | Seasonal predictions of holopelagic sargassum across the tropical Atlantic accounting for uncertainty in drivers and processes: the SART RAC ensemble forecast system[END_REF].

Geo-Morphology

Shoreline

A number of methods can be used to monitor the location of shorelines from space, all using optical or radar data processing techniques. For country-scale mapping (e.g., as requested by the West African Coastal Area Management (WACA) program), annual median cloud minimum optical data composites can be downloaded from Google Earth Engine and used to delineate shoreline changes using open-source tools such as Coastsat (Vos et al. 2019a;Bergsma et al. 2020;[START_REF] Almeida | Coastal analyst system from space imagery engine (CASSIE): shoreline management module[END_REF]) and the Digital Shoreline Analysis System (DSASv5) [START_REF] Himmelstoss | Alarming coastal vulnerability of the deltaic and sandy beaches of North Africa[END_REF].

For example, along the coast of Benin, shorelines are synthesized through a classification and thresholding process using Landsat 7, 8, and Sentinel-2 pan-sharpened images between 2000 and 2020 (Fig. 5). A baseline is extracted using the first shorelines to plot transects at 50 m intervals along the coast. The process can be repeated over many regions of interest along the coast to allow for rapid large-scale (i.e., country/region-wide) analysis over a period of several decades.

Topography-Digital Elevation Model (DEM)

Remote sensing techniques now offer a good alternative for constructing digital elevation models (DEMs) over large spatial areas with sufficient resolution (< 100 m). They include global DEMs such as the 90 m resolution Shuttle Radar Topography Mission (SRTM) collected in the early 2000s [START_REF] Farr | The Shuttle radar topography mission[END_REF]; widely used for large-scale flood modeling, e.g., [START_REF] Ettritch | Enhancing digital elevation models for hydraulic modelling using flood frequency detection[END_REF][START_REF] Neumann | Future coastal population growth and exposure to sea-level rise and coastal flooding-a global assessment[END_REF][START_REF] Kulp | CoastalDEM: a global coastal digital elevation model improved from SRTM using a neural network[END_REF], as well as the commercial 5 m ALOS AW3D30 DEMs (JAXA, [START_REF] Tadono | Generation of the 30 M-MESH global digital surface model by alos prism[END_REF]; 30 m free resolution used for coastal overtopping in [START_REF] Dada | Effect of coastal land use change on coastline dynamics along the Nigerian transgressive Mahin mud coast[END_REF]Almar et al. 2021a), and 8 m resolution WorldDEM (Airbus, on request). However, these DEMs are often several years old and do not reflect rapidly changing coastal areas.

By analyzing stereo pairs of optical satellite images using photogrammetry [START_REF] Tateishi | Relative DEM production from SPOT data without GCP[END_REF][START_REF] Youssefi | Cars: A photogrammetry pipeline using dask graphs to construct a global 3d model[END_REF], it is possible to construct large-area DEMs, including the key intertidal zone, with vertical errors less than 0.5 m [START_REF] Collin | High resolution topobathymetry using a Pleiades-1 triplet: Moorea Island in 3D[END_REF][START_REF] Almeida | Deriving high spatial-resolution coastal topography from sub-meter satellite stereo imagery[END_REF][START_REF] Taveneau | Observing and predicting coastal erosion at the Langue de Barbarie Sand Spit around Saint Louis (Senegal, West Africa) through Satellite-Derived Digital Elevation Model and Shoreline[END_REF])-see Fig. 6.

Bathymetry, Toward a Shoreface Land-Sea Coastal Morphology Continuum

To derive nearshore bathymetry, ocean color can be derived from optical missions such as Sentinel-2 and Landsat, from which water depth, seafloor features, and turbidity can be derived simultaneously or independently [START_REF] Caballero | Retrieval of nearshore bathymetry from sentinel-2A and 2B satellites in South Florida coastal waters[END_REF][START_REF] Salameh | Monitoring beach topography and nearshore bathymetry using spaceborne remote sensing: A review[END_REF][START_REF] Monteys | Spatial prediction of coastal bathymetry based on multispectral satellite imagery and multibeam data[END_REF][START_REF] Li | Automated global shallow water bathymetry mapping using google earth engine[END_REF][START_REF] Cesbron | Pan-European satellite-derived coastal bathymetry-Review user needs and future services[END_REF]. The calculated bathymetry is not the depth of the consolidated sediment bedrock, but the depth of the suspended sediment layers in the mud. On muddy coasts, the data provide information on both constant suspended sediment and fluid sediment layers. As an alternative, bathymetry can be derived from satellite wave kinematics (Fig. 7), which has the potential to be independent of the water column and bottom spectral characteristics [START_REF] Bergsma | Radon-augmented sentinel-2 satellite imagery to derive wave-patterns and regional bathymetry[END_REF][START_REF] Daly | The new era of regional coastal bathymetry from space: a showcase for West Africa using sentinel-2 imagery[END_REF][START_REF] Baba | Deriving large-scale coastal bathymetry from sentinel-2 images using an high-performance cluster: a case study covering North Africa's coastal zone[END_REF]Almar et al. 2021b) to depths of 35-50 m, depending on wave conditions (Bergsma andAlmar 2020, Daly et al. 2021). The nearshore of coastal areas includes within the same cell and morphological profile both emergent and submerged portions that rapidly exchange sediment. This is a critical area to monitor to reduce uncertainty in predicting the impact of storms and climate change [START_REF] Ranasinghe | On the need for a new generation of coastal change models for the 21st century[END_REF]Almar et al. 2021a, b). New opportunities are provided by on-demand satellite video (e.g., Planet, Jilin, Pleiades, etc.) that allows for combined topography and bathymetry in a single pass [START_REF] Bergsma | Coastal morphology from space: a showcase of monitoring the topography-bathymetry continuum[END_REF][START_REF] Almar | Coastal topo-bathymetry from a single-pass satellite video: insights in space-videos for coastal monitoring at Duck Beach (NC, USA)[END_REF]. This unlocks the problem of lack of decades-old data or surveys in West Africa, with significant potential in coastal engineering (coastal infrastructure designsee [START_REF] Turner | Satellite optical imagery in coastal engineering[END_REF]).

Vertical Land Motion-Subsidence

In the context of increasing intensity and frequency of disasters related to soil instability, it is important to accurately assess the potential impact of events such as landslides and subsidence [START_REF] Dealbera | Disentangling vertical land motion and waves from coastal sea level altimetry and tide gauges[END_REF]Nicholls et al. 2021a, b). To achieve this goal, cost-effective techniques can be useful for monitoring soil and infrastructure stability over a wide area (regional and global), avoiding large initial investments and increasing risk management capabilities to reduce losses.

As an example, the Geologic Risk Operations Platform (GEP-https:// geoha zards-tep. eu) is a cloud-based environment that provides a set of EO processing services to map hazard-prone land surfaces and monitor ground deformation. The platform is constantly expanding and includes a wide range of systematic and on-demand products and services to help EO practitioners and end users better understand geohazards and their impact [START_REF] Foumelis | Monitoring geohazards using on -demand and systematic services on ESA's geohazards exploitation platform[END_REF]. The GEP aims to improve the acceptance of online EO services and products for geohazard assessment and their adoption in decision making. Being a collaborative platform, it allows users to control how they engage and interact with other users, to share and promote their assets and/or results. As an example, a total of 352 Copernicus Sentinel-1 images covering Dakar, Senegal were processed using the Parallel Small BAseline Subset (P-SBAS) on-demand processing service provided by CNR-IREA (https:// terra due. github. io/ doc-tep-geoha zards-v2/ tutor ials/ gep-sbas-s1. html). The P-SBAS algorithm is a technique for retrieving Earth surface displacement time series and mean velocity maps from a synthetic aperture radar (SAR) data set [START_REF] Casu | SBASD InSAR parallel processing for deformation time-series computation[END_REF][START_REF] Manunta | The parallel SBAS approach for sentinel-1 interferometric wide swath deformation time-series generation: algorithm description and products quality assessment[END_REF]. Details of the Copernicus Sentinel-1 SAR mission are available at Sentinel Online-ESA (https:// senti nel. esa. int/ web/ senti nel/ home).

The results in Fig. 8 highlight the status of the Greater Dakar coastal zone with respect to ongoing subsidence or uplift events. Inspection of the displacement time series provides additional information on the temporal behavior (displacement history) of each measurement point. Ground displacements measured by the interferometric synthetic aperture radar (InSAR) are measured along the satellite line of sight (LoS), expressing a combination of vertical and horizontal motion. Each measurement corresponds to the average motion in a 90 × 90 m area at the surface. The geospatial accuracy of the results is about 15 m, while the expected measurement accuracy is 1-2 mm/yr (e.g., [START_REF] Manunta | The parallel SBAS approach for sentinel-1 interferometric wide swath deformation time-series generation: algorithm description and products quality assessment[END_REF]. 1 3

Sea-Land Waters

Sea Level

Contemporary sea-level changes along the West African coast are routinely obtained from a dedicated reprocessing of satellite altimetry data as part of the ESA Climate Change Initiative sea-level project. High sampling rate (20 Hz) sea level data from the Jason-1 and Jason-2 missions over a 14-year period (July 2002 to June 2016) are considered. The data are first tracked using the adaptive leading-edge sub-probe tracker ALES [START_REF] Cazenave | The Climate Change Initiative Coastal Sea Level Team. Coastal sea level anomalies and associated trends from Jason satellite altimetry over 2002-2018[END_REF]. The X-TRACK processing system developed to optimize the completeness and accuracy of corrected sea level time series in coastal ocean areas is then applied [START_REF] Marti | Altimetry-based sea level trends along the coasts of Western Africa[END_REF].

From the 14-year sea-level time series, sea level trends along the Jason-1 & 2 tracks can be estimated, quantifying regional variations in sea level trends, with a focus on observed changes between the open ocean and the coastal zone. Compared to conventional 1-Hz sea level products dedicated to open ocean applications, the reprocessed 20-Hz measurements used in coastal studies allow the retrieval of valid sea level information much closer to the coast (within 3-4 km of the coast, depending on the satellite track; Fig. 4).

At shorter time scales of days to years, sea-level variability is characterized by poleward propagation of coastal disturbances triggered by Kelvin waves trapped on the coast. These transient sea-level changes have been observed, described [START_REF] Polo | Oceanic Kelvin waves and tropical Atlantic intraseasonal variability: I Kelvin Wave Characterization[END_REF] and their impact studied [START_REF] Abessolo | Beach adaptation to intraseasonal sea level changes[END_REF]) along the West African coast using a 1 Hz sea level product.

Coastal Flooding

A particularly important application of DEM is the investigation of coastal flood risk. Combined with hydrological data, inundation water levels can be mapped to evaluate the impact of floods. Scenario mapping allows the prediction of future inundation risk, as illustrated in Fig. 9 for Banjul area, Gambia [START_REF] Foumelis | EO4SD Disaster risk reduction terrain motion products in support of the city resilience program[END_REF]. Based on DEM information, floods can reach 1.6 m today and between 1.9 and 2.7 m in the next 100 years, depending on three IPCC scenarios considered (RCP 2.6, RCP 4.5 and RCP 8.5) (Fig. 9). The provisional result is valid for the current storm climate, taking into account only a mild evolution of the weather due to climate change, i.e., excluding unprecedented extremes; for a stable shoreline, with no erosion, i.e., the retreat of the coast that could reduce significantly the surface of the city; and for a 2100 pessimistic prediction of 2.7 m rise above the land vertical datum, combining the Intergovernmental Panel on Climate Change (IPCC) worst scenario, spring tides and the maximum-known meteorological effects (Fig. 10).

The quality of flood predictions can be improved by (a) improving the quality of tide predictions essentially by retrieving or programming extended tide observations (tide gauges whose vertical movements are monitored by GPS); (b) checking compatibility between DEM precision and water-level observations; (c) a better knowledge of extreme sea level statistics; and (d) a better knowledge of wave set-up and runoff.

Water Quality

EO4SD-Earth Observation for Sustainable Development-is an ESA initiative that aims to achieve a step increase in the uptake of satellite-based environmental information. The EO4SD portal (https:// eo4sd. eofrom. space) contains Sentinel-3 Ocean and Land Colour Instrument (OLCI) water quality data at 300 m resolution for the entire coast of Africa from both Sentinel-3A and B satellites (Fig. 11), using a polymer atmospheric correction [START_REF] Steinmetz | Atmospheric correction in presence of sun glint: application to MERIS[END_REF].

Satellite-derived chlorophyll concentration can be used to study seasonal and interannual phytoplankton dynamics, as well as monitor coastal water quality, eutrophication and harmful algal blooms. High Chlorophyll-a concentrations can indicate high nutrient concentrations in the surface waters and can be due to the eutrophication of coastal waters. For example, in the Gulf of Guinea off Côte d'Ivoire, research by [START_REF] Kassi | Remotely sensing the biophysical drivers of sardinella aurita variability in ivorian waters[END_REF] combines remotely sensed observations of ocean color with in situ observations of Sardinella aurita catch, temperature, and nutrient profiles, as well as reanalyses of wind and sea surface temperature, to investigate the relationships between catch and oceanic primary producers (including phytoplankton biomass and phenology). [START_REF] Kassi | Remotely sensing the biophysical drivers of sardinella aurita variability in ivorian waters[END_REF] discuss how predictive models can provide powerful tools to support the assessment and monitoring of fishing activity, which can contribute to the development of the fisheries information and management system.

Water Pollution

EO can be used to identify different types of land-based pollution (LBP) in the coastal or marine environment such as untreated sludge or sewage nearshore dredging, near-shore oil spill (this is discussed in the next section), tourism activities and illegal rubbish dumping (to be detected before being washed out). The indirect runoff of wastewater is combined with river runoff, and due to the high rates of advection and diffusion, the effluents are well-mixed in the water, and their direct detection is challenging. The direct runoff of untreated wastewater is detectable by satellite images as it has three distinctive imprint features on the surface of coastal waters: color, temperature, and surface roughness. Only the first feature, color, is detectable at a fine spatial resolution of ~ 10 m. Satellite products of sea surface temperature are merely available at coarse resolution > 500 m which is unfit for the fine-scale of land-based pollution.

Pollution methods typically use the color feature to detect and quantify the discharge of untreated sludge in coastal waters. The color of untreated sludge is commonly dark and can be detected in the visible part of the solar spectrum. In an example study from Senegal, the discharge of sewage pipelines into coastal waters of the Senegalese coastline south of Dakar is apparent (Fig. 12). This image is from the Sentinel-2 Multispectral Instrument (S2-MSI). This sensor observes the reflected sunlight in the visible part at a 10-m resolution and a 5-day revisit. This type of "visible" sensor is affected by cloud cover.

S2-MSI is used to quantify the discharge of untreated sludge along the coastline and up to 500 m offshore. The service provides probability maps [from 0 to 1] of solid waste, and dissolved waste for cloud-free observations. The probability values are estimated from water quality indicators and light penetration depth. For this purpose, the 2SeaColor model [START_REF] Salama | Two-stream remote sensing model for water quality mapping: 2SeaColor[END_REF]; https:// github. com/ suhyb salama/ 2SeaC olor) is employed. The service uses Sentinel-1A and Sentinel-1B SAR satellite images provided by the European Space Agency. SAR sensors are very sensitive to variations of sea surface roughness and can successfully detect oil slicks that effectively dampen sea waves. The slicks are visible as dark spots in the SAR images. The system uses a machine-learning approach to delineate potential oil slicks from "lookalikes" associated with variations of the wind field, currents or algal blooms.

By combining the evidence from a series of processed images with vessel-tracking data (i.e., AIS) authorities can be alerted to request Port State Inspections at the subsequent port arrival of the vessel, during which records can be checked and evidence gathered for possible breaches of international law. Such a service extension would require a regional/ international collaborative approach. The service has been successfully applied for monitoring an oil leak at Mbao in Dakar, Senegal (in the SDLAO assessment report 2020). Marine pollution was originally reported in this area by local fishermen, who observed thick oil slicks scattered in the area from Large Mbao to Small Mbao on July 16, 2020. These oil slicks are automatically detected in satellite images two days earlier, on July 14, 2020. Figure 12 shows in red the location and extent of the detected pollution areas. The largest oil slick in the image originates at the coast just opposite a refining plant.

Examples of Satellite EO Initiatives in Better Management of Coastal Zones

Recently, efforts have been made at the countries and regional levels to address some of the challenges facing the West African coast. These programs are largely based on EO.

Here, we showcase two of them: (1) the West African Coastal Areas Management Program (WACA) which was developed by the World Bank Group in partnership with the coastal countries in the region;

(2) the Space Climate Observatory (SCO), with several sites in West Africa, aims to study, monitor and adapt to the impacts of climate change, especially at local scales, using EO tools in combination with field data and models. These programs also search at developing the regionally human capacity of current managers and train future West African coastal experts and young researchers on developing the right tools and models to improve the sustainable management of the West African coastal region.

West African Coastal Areas Management Program (WACA, World Bank Group)

The program targets countries that want to improve the management of natural and manmade risks affecting coastal communities. It provides countries with access to technical expertise and financing to support sustainable development in the coastal zone, using coastal erosion and high-risk flood management as a starting point (Giardino et al. 2017b).

The World Bank and its partners are pioneering this first-of-its-kind regional approach to addressing severe coastal erosion. Other partners are expected to join this effort through the new platform launched in November 2018 in Dakar, Senegal (World Bank 2018). One of the WACA projects is the $210 million WACA Resilience Investment Project (WACA ResIP), which aims to address coastal erosion, flooding, and coastal pollution in selected target areas in six West African countries, namely Benin, Côte d'Ivoire, Mauritania, Sao Tome and Principe, Senegal, and Togo. The project was developed in collaboration with four regional institutions-the West African Economic and Monetary Union (WAEMU), the Abidjan Convention, the Ecological Monitoring Centre (EMC) based in Dakar, and the International Union for Conservation of Nature (IUCN). It is jointly funded by the Nordic Development Fund and the French Global Environment Facility (FFEM). Other partners are joining the effort through a new WACA platform that has been set up to stimulate knowledge transfer, mobilize additional funding, and foster policy dialog between countries and protect the West African coast.

The WACA platform has created a coastal master plan through knowledge exchange, investment crowding-in, and policy dialog between countries (World Bank 2018). It also established the West African Regional Coastal Observatory (WARCO) to improve accurate 1 3 information on the state of the coast. WARCO is set up in collaboration with WAC countries to support, improve, and promote scientific and technical knowledge; provide tools for understanding and managing coastal phenomena; and establish sustainable and integrated coastal policy. Another program is the establishment of the African Center of Excellence for Coastal Resilience (ACECoR) hosted by the University of Cape Coast (UCC), Ghana, to support the development of technical and scientific capacity of young African professionals to develop integrated solutions to coastal degradation through short-and long-term professional and academic training programs. Finally, the "blue economy" has become a key pillar of the African Union's continent-wide Agenda 2063.

The Abidjan Convention, established in 2019, provides countries in the region with the tools and information they need to safeguard fragile coastal ecosystems and the people and biodiversity that depend on them. The 18 parties to the convention have signed four protocols designed to improve the management of their respective coastal zones. The Pointe-Noire protocol proposes sustainable approaches to integrated coastal zone management (ICZM), while the Calabar protocol provides a technical framework to ensure the sustainable management of mangroves. The Malabo protocol sets minimum standards for addressing pollution risks from oil and gas activities, and the Grand-Bassam protocol focuses on regulating land-based and air-based sources of contamination.

Space Climate Observatory (SCO, International Space Agencies)

The Space Climate Observatory (SCO), a global initiative that focuses on observing the impacts of climate change, was established in late 2017. It is made up of a group of 27 space agencies and international organizations and has an objective to provide local decision-makers with operational tools, using satellite, in situ and local socio-economic data to help them draw up climate change mitigation policies on a local scale. SCO operates through projects led by consortia bringing together the scientific community, public authorities and private sector companies. In 2020, it certified 15 projects on coastal dynamics, mangroves, floods, urban climate, agriculture, epidemiology by remote sensing, etc.

For example, a SCO demonstration project in Senegal focuses on the coastline of Saint-Louis, an area particularly vulnerable to coastal erosion and flooding [START_REF] Sadio | Shoreline changes on the wave-influenced Senegal River delta, West Africa: the roles of natural processes and human interventions[END_REF][START_REF] Almar | On the key influence of remote climate variability from Tropical Cyclones, North and South Atlantic mid-latitude storms on the Senegalese coast (West Africa)[END_REF]Bergsma et al. 2020;[START_REF] Taveneau | Observing and predicting coastal erosion at the Langue de Barbarie Sand Spit around Saint Louis (Senegal, West Africa) through Satellite-Derived Digital Elevation Model and Shoreline[END_REF]. It aims to improve our knowledge and raise awareness of stakeholders on the hazards and risks in coastal areas in the context of climate change and to propose tools and indicators of the vulnerability of populations and economic activities (e.g., [START_REF] Koroglu | Comparison of coastal vulnerability index applications for Barcelona province[END_REF]. Coastal erosion here is estimated at between 0.5 and 2 m per year, flooding due to heavy rainfall, river flooding and/or storm surges, industrial and domestic pollution, saline intrusion, and mangrove degradation. To respond to these different drivers, and to find a balance between ecosystem preservation and economic development, it is essential to carry out precise monitoring of physical, ecological and sociological key parameters.

The Saint-Louis project has four complementary objectives, (a) to improve knowledge of the multiple hazards (flooding by storm inundation and Senegal River flooding and coastline recession) and associated risks encountered in coastal areas, based on an approach combining existing in situ monitoring (e.g., water-level data, DGPS surveys), dedicated population surveys and multi-sensor satellite (including coastal altimetry) and shore-based video camera, statistical processing and cartographic simulations; (b) to define current and future hotspots at risk in relation to climate change (in relation to sea-level rise); (c) propose tools and indicators of vulnerability of populations, economic activities and infrastructures from a cross approach of satellite, in situ and socio-economic data processing and cartographic simulations; (d) to sensitize the actors toward a multi-risk vision to answer the various stakes of the coastal zones and to co-construct the coastline and the coastal cities of tomorrow.

The final product will include the identification of past major flood damage events, the definition of scenarios for the mapping simulation of floods, quantification of sea-level rise as it approaches the coast based on existing elevation data, map simulation of flooding with several sea-level rise scenarios, reference DEM of shallow water bathymetry and intertidal topography, automatic coastline detection algorithm, a geospatial database of risk areas and risk features, including mapping of current and future hot spot areas.

Roadmap on How Satellite Imagery Can Support Sustainable Coastal Zone Management in West Africa

A major challenge in the coming decades will be to predict how coasts (land, sea, and ecosystems) will evolve under the effects of global change, especially in low-lying and urbanized West Africa, which exposes it disproportionately [START_REF] Oppenheimer | Sea level rise and implications for low lying islands, coasts and communities[END_REF]Almar et al. 2021a;[START_REF] Vousdoukas | African heritage sites threatened as sea-level rise accelerates[END_REF]. Descriptive and predictive models typically rely on numerous historical observations, making their application difficult in regions such as West Africa due to the lack of detailed information. With recent advances in satellite remote sensing techniques, it is now possible to obtain rich data sets, often also retrospectively if satellite data are available for earlier periods. These data can provide a solid foundation for the development of data-driven models and management strategies [START_REF] Ranasinghe | On the need for a new generation of coastal change models for the 21st century[END_REF]. EO has already begun to better assess climate impacts and provide valuable information to coastal communities that lack historical data sets, such as in West Africa and the tropical Atlantic. Of primary importance for adapting coastal development or even natural resource exploitation includes sand mining and renewable ocean energy harvesting. The use of EO for monitoring is still rare along the West African coast for metocean conditions, coastal hydro-geo-morphological parameters and hazards, although data availability has increased considerably with the growing number of satellites. Today, Copernicus is the largest producer of freely available EO data (Sentinels) in the world [START_REF] Traon | From observation to information and users : the Copernicus Marine Service Perspective[END_REF]. Currently, EO data acquisition alone is not sufficient to address dynamic, short-scale coastal ocean and hazard monitoring. Coastal processes and hazards can be highly localized in space and time, for example, flash floods with a typical duration of a few hours cannot be observed with a typical satellite revisit time of several days. These hydrodynamic/oceanic variables can be monitored by satellites (SST, SSH, wind, currents, waves, ocean color, etc.-see e.g. [START_REF] Ardhuin | Observing Sea States[END_REF][START_REF] Gommenginger | SEASTAR: a mission to study ocean submesoscale dynamics and small-scale atmosphere-ocean processes in coastal, shelf and polar seas[END_REF][START_REF] Rodriguez | The winds and currents mission concept[END_REF]Villas Bôas et al. 2019), as well as coastal hazards (e.g., floating debris and pollutant pathways, larval dispersal, marine navigation safety, etc.). Coastal geomorphic processes and features (e.g., land subsidence, topography) are generally characterized by low temporal variability but significant spatial heterogeneity. These specificities of the coastal zone pave the way for future missions, revisit and resolution requirements for new observing strategies [START_REF] Turner | Satellite optical imagery in coastal engineering[END_REF]Bergsma and Almar 2020;Bersgma et al. 2022).

3

In order to provide relevant information for coastal zone management, there is a need for cross sectional, coherent, synoptic spatio-temporal monitoring of the coastal ocean, where EO is assimilated jointly with in situ or other remotely sensed observations into operational numerical models. Such integrated systems form the backbone of geo-environmental forecasting, which, by itself or through back-to-back forecasting or early warning systems, is critical to reducing exposure to coastal hazards and related risks. Coastal forecasting skills have been shown to increase when near real-time EO is assimilated. They would further benefit from (a) joint observations of different variables, especially in the development of more integrated and coupled operational numerical monitoring and forecasting systems, (b) better exploitation of EO by using more types of observations and more efficient and potentially coupled data assimilation techniques for model development and validation.

These satellite data are now mostly good alternative to traditional surveys in certain for developing countries, which lack historical data, making it difficult to implement numerical models and science-based policies. Using these new observations will make it possible to determine whether rising seas are the primary threat to the West African coast and whether the assumption of resilience in the face of anthropogenic and climatic pressure is likely [START_REF] Dada | Towards West African coastal social-ecosystems sustainability: interdisciplinary approaches[END_REF]Hzami et al. 2021). The influences of important processes such as changes in river flow driven by changes in precipitation and land uses such deforestation and urbanization are particularly important in developing countries, with possible mitigation strategies such as dikes, nature-based solutions, and set back [START_REF] Lincke | Economically robust protection against 21st century sea-level rise[END_REF][START_REF] Morris | Climate-resilient coasts require diverse defence solutions[END_REF][START_REF] Tiggeloven | Global-scale benefit-cost analysis of coastal flood adaptation to different flood risk drivers using structural measures[END_REF].

Overall, the West African coastal system can be better managed through EO:

• Strengthen monitoring by Earth observation, in a holistic and uniform manner across West Africa. Quantify what is happening on the coast, what protections and actions are needed and also monitor the effectiveness of applied solutions and identify potential socio-environmental bottlenecks: satellite data provide such variable multi-geo-environmental solutions, • Promote the observation network and generalize data centralization and open data sharing (Find, Access, Interoperate, Reuse) such as COPERNICUS platform and common tools such as those developed by ESA (SNAP) or free-to-use chains (e.g., for stereotopography CARS-CNES, AMS-ASP-NASA, etc.) developed by spatial agencies and laboratories (S2Shores, by LEGOS-CNES), • Establishment of a roadmap/strategy for future EO missions to support coastal zone management in West Africa, including appropriate revisit, resolution and priority variables monitored, • Strengthen capacity development and networking of coastal EO skills: The creation of networks of scientists and engineers and companies. Strengthen the existing education system (e.g., masters, PhDs, thematic workshops on concrete problems and solutions), • Establishment of a common policy for all West African countries, based on decisionmaking adapted to regional hazards.

Conclusions

The evolution of the West African coast is little known up to now, and the processes driving these dynamics are poorly described (e.g., climate change is still seen as the main driver of coastal change, which is incorrect, as human pressure and local infrastructure often dominate). The low-lying and urbanized West African coast is one of the most vulnerable regions in the world to hazards due to socio-economic development and climate changes.

As compared with other observation means, most of the satellite-derived data are a free source and can be used to monitor an increasing number of variables, at an increasing frequency and resolution. They face, however, a double bottleneck of the lack of ground truth and a certain level of the technical complexity of use for regional implementation. Better use of EO data in West Africa for improving sustainable coastal zone management requires investing in developing these multiple EO-derived techniques, designing future missions, promoting these EO data and techniques available and reinforcing capacity building for the practitioners and young scientists of the region.

Fig. 2

 2 Fig. 2 Coastal vulnerabilities in West Africa: Illustration of coastal erosion and flooding, destruction of the mangrove for smoked fish and shrimps, water contamination and eutrophication, and Sargassum landing in Ghana (from Marsh et al. 2021)

Fig. 3

 3 Fig. 3 Coastal Land Cover Map of Benin showing urban, vegetated and water surfaces (from SDLAO/ UEMOA/WAEMU 2020 report on West Africa Coast)

Fig. 4 A

 4 Fig. 4 A built up-area in 2016 and evolution between 2016 and 2019 generated with Copernicus Sentinel-2 imagery in the EO4SD DRR project. B Example of the product accuracy with built-up area superimposed over Copernicus Sentinel-2 imagery (B) and over a very high-resolution imagery (A) (SDLAO assessment report 2020)

Fig. 5

 5 Fig. 5 Shoreline change rates at Port de Cotonou, Benin (SDLAO/UEMOA/WAEMU 2020 West Africa Coastal Areas assessment report)

Fig. 6

 6 Fig. 6 (left) Saint Louis city (Senegal) location with the insert illustrating a Pleiades satellite acquisition showing an overview of the Langue de Barbarie. (right) Sand spit topography derived from Pleiades-03/2019. DEMs difference (03/20-03/19). Sand spit topography derived from Pleiades-03/2020 (from Taveneau et al. 2021)

Fig. 7

 7 Fig. 7 West African bathymetry from Sentinel-2: inset shows the estimate and GEBCO product (from Daly et al. 2021)

Fig. 8

 8 Fig. 8 Line-of-sight ground motion velocity in mm per year-1 for the entire 1993-2010 period (ERS1, ERS2, and Envisat). Negative values indicate subsidence (Le Cozannet et al. 2015)

Fig. 10 Fig. 9

 109 Fig. 10 Sea-level rise at the coast from the C3S gridded product from July 2002 to June 2016 in West Africa. Jason satellite tracks (identified by numbers) are overlaid (from Marti et al. 2016)

Fig. 11

 11 Fig. 11 View of the EO4SD Marine Portal satellite-derived chlorophyll concentration off the west coast of Africa on May 16, 2020. In this area, upwelling of nutrient-rich deep water occurs and leads to high productivity (accessed on https:// eo4sd-marine. eu, SDLAO assessment report, 2020)

Fig. 12

 12 Fig. 12 Color composite (red, green, blue) from Sentinel-2 MSI image acquired on April 24, 2020 (using 2SeaColor model of Salama and Verhoef 2015) (SDLAO assessment report, 2020)

Table 1

 1 Examples (non-exhaustive) of monitored variables from EO and their level of maturity and implementation in WA. Cell color indicates the maturity/level of implementation (green: operationally used by practitioners, yellow: first showcases and pilot use, orange: pioneer studies at the research level)

	Status of implementation in West Africa	Operational -used for indicators in the West African	Coastal Observatory	Used as pre-operational state-showcase	Research level	Used as pre-operational state -showcase at urban	areas and deltas	Operational (from altimetry) but of low frequency and	distance from the coast. Models are effective	Operational but not used in West Africa (SAR-Senti-	nel-1)-of low frequency and distance from the coast.	Models are effective	Largest rivers/estuaries only can be monitored through	altimetry and too low frequency of revisit (10 days)	Research level	Operational -used for indicators in the West African	Coastal Observatory
	Vulnerability/resources	Erosion		Protection to flooding	Sediment scarcity, erosion, aqua life nesting	Subsidence and flooding		Flooding		Flooding and erosion, risk for offshore infrastruc-	tures, blue economy and power		Flooding at estuaries and delta-compound effect	with ocean drivers	Pollution and contamination	Deforestation, flooding, illegal or uncontrolled urban	extension, algae and Sargassum landing, sustain-	able management
	Type Geo-environment variables	Geomorphology Shoreline		Topography	Bathymetry	Land motion		Sea-land waters Sea level		Waves			Rivers		Water color	Land cover/land use Classes of water, mangroves, forests,	beaches, urban areas and infrastruc-	tures, etc

Acknowledgments

The authors are grateful to the conveners of the International Space Science Institute (ISSI) workshop on "Global Change in Africa," held from January 11 to 15, 2021, in Bern, Switzerland. The authors particularly thank Anny Cazenave for the early stage contributions and orientations of this contribution. R.A and D.A received funding from JEAI IRD COASTS-UNDER-CONTROL.

Author Contributions RA and TS designed and drafted the manuscript. KAA, KB, GAO, EWJB, FB, OD, DA and OA contributed the different sections of the manuscript, review of coastal environments and the implementation of the satellite techniques in West Africa.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.

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Authors and Affiliations


Aliyah Morgenstern

Martine Sekali

WHAT CAN CHILD LANGUAGE TELL US ABOUT PREPOSITIONS?

. The factors determining the acquisition of prepositions would be linguistic rather than cognitive, and linked to language use and frequency of input (Rice, 1999). In order to tackle these questions, we conduct a contrastive corpus-based study of French/English acquisition of prepositions. Our findings support the claim that some aspects of children's discourse are influenced by the particular structure of the language the child is acquiring (Talmy, 2003, Hickman & Robert, 2006), together with other parameters such as discursive organization and context. Ultimately, "grammatical words" can express and organize social interaction, and are acquired by children thanks to the mediation of adults.

Introduction

Prepositions represent a problematic category for theories of syntax. Recent syntactic theory suggests a classification of prepositions according to either lexical or functional features: lexical prepositions contribute semantic content while functional prepositions merely assign case.

Yet the same preposition can exhibit both features, and its classification will therefore depend on its use (the same preposition to in English can thus be used as a lexical spatial preposition: I'm going to London, or as a functional preposition assigning dative case: Give it to him!).

Language acquisition, which is necessarily studied in spontaneous dialogical contexts, may give new insight on prepositions as a grammatical category. Which prepositions are used by children first? How are they used? In what order do they appear and why? Do French and English children use the same first sets of prepositions? In order to tackle these questions, we analyse the emergence of prepositions in spontaneous verbal interactions between children age 1;08 to 2;04 and their parents, and try to determine the function of their first uses in context.

We can observe that prepositions are used by children as soon as they elaborate two word utterances, at the end of the second year. The literature on the acquisition of English insists on the fact that prepositions appear quite early in children's language: they are part of the first twenty items learnt by English speaking children according to [START_REF] Brown | A first language[END_REF], and are primarily spatial localizers.

These results have enabled researchers to compare the evolution of language in acquisition and the history of languages (Traugot 1992, Lakoff 1987[START_REF] Ziegeler | Retention in ontogenetic and diachronic grammaticalization[END_REF], since prepositions in the diachrony of the English language were spatial before being functional, which fits perfectly into the grammaticalization process underlined by cognitive linguists.

But if this order of emergence in acquisition is true of English, we may wonder whether this is a general process, which is not language dependent. First prepositions in English are semantically rich (they are called coloured prepositions), but are these features specific to English, in which so-called prepositions can be used as adverbials in isolation as in down or up? Is it the case in French? We were interested in testing these claims and comparing first uses in English to first uses in French. We first conducted a quantitative analysis of the emergence of prepositions on two English and two French-speaking children, based on the syntactic opposition between lexical and functional features. We then focus on two French children for a qualitative analysis of their use of prepositions in context.

Quantitative analyses

In order to check the claims found in the literature on English data, we ran a morpho-syntactic analyser through Peter's data (taken from the CHILDES database collected by Lois Bloom). It must be said that the analyser extracts morphemes according to their form and not their function, which, unfortunately, amalgamates prepositions and particles. The results for Peter can be viewed in table 1 showing the percentages of Peter's first prepositions according to his age. We notice that the morphemes related to spatial orentation up, on and in in particular are quite frequent. The detail of the distribution of Peter's prepositions according to functional and spatial uses can be observed on the following graph, showing a vast majority of prepositions related to space. The same analyses conducted on another child, Will, recorded by Katherine Demuth's team at Brown University, yield similar results, the proportion of « spatial » prepositions being significant as opposed to the proportion of « functional » prepositions. Leonard's data yield significantly different results, with a greater number of functional rather than spatial prepositions. In addition to that, the 'spatial' prepositions found mostly correspond to Leonard's use of dans/('in') in set expressions such as "dans le bain" ('in the bath') and in some utterances where the form dans stands for the adverb dedans, which shows us that quantitative analysis on forms counted as prepositions by the morpho-syntactic analyser have their limits.

The same analysis was made on Madeleine's data, which is part of the new French data we are currently recording and transcribing in a large research program financed by the French National Research Agency (Projet Léonard, 2005-2008). Madeleine was filmed by the second author, and we found her to be quite a precocious little girl, her linguistic development being very quick. At 2;02, she already had a large variety of prepositions in her repertoire. The distribution of functional and spatial prepositions in Madeleine's data is quite similar to Léonard's, but Madeleine has more types and more tokens at a younger age.

The results for the four children are quite interesting to compare: the English children confirm previous researches and show a predominantly spatial use of first prepositions. But the French children tend to use mostly functional prepositions in their first usage of the category. These findings support the idea that what was presented as a general trend in child language might in fact be specific to English and should be reconsidered as far as other languages are concerned. Furthermore, a finer analysis of the data leads us to add several remarks.

-The English-speaking children use prepositions such as in, on, or up very early, but in a 'verb-like' manner and often in isolation. Interestingly enough, where the English-speaking children say 'up!' or 'down!' the French-speaking children use verbs such as "monter!" ('go up') or "descendre!" ('go down').

-The French-speaking children first use prepositions such as pour, à and de around 1;10 only (François 1977 ;[START_REF] Morgenstern | L'acquisition des premières prépositions chez un enfant francophone, Faits de langues -La préposition : une catégorie accessoire[END_REF]. These mostly correspond to the possessive case in English. Where the French child says "les jambes de maman", or "à moi la poupée!" the English-speaking child will say 'Mummy's legs' and 'My doll!' Yet Peter's data shows the presence of possessive adjectives from the very first recordings ('my turn') and the genitive morpheme appears as soon as the age of 1;10 ('Patsy's pencil'). This remark tends to argue against the temptation to transfer observations made on English data on the acquisition of French.

-Around the age of 2;04, the four children use a larger variety of prepositions, semantically charged as well as more functional ones. We find pour, à, de, dans, sur, avec, en in French. In English at the same age, the variety of prepositions used is even more important, with at, by, for, from, in, of, off, on, out, over, to, under, up, and with. The quantitative analysis of prepositions in our data thus shows significant differences between English and French. Yet it is not sufficient to reveal the type of function that the children assign to this emergent category. Investigating early functions of morphemes can only be done through a qualitative analysis of utterances in context.

The qualitative analysis of the French children's first uses of the 'functional' preposition pour in context will now show interesting recurrent patterns, suggesting that the acquisition of grammatical paradigms could be made through a series of transitory subsystems.

Qualitative analyses

The in-depth examination of Léonard and Madeleine's data required considering parallel and interacting linguistic processes in their development. In order to study the emergence of prepositions in the framework of the child's development, we established an overview of salient features, first syntactic features, first grammatical markers in parallel with the use of prepositions for each month from 1;08 to 2;04. This overview shows that, at 1;08, Leonard starts using two-word utterances and has his first tries at nominal determination. Pour is the first preposition used by Leonard in our data. It is first associated with a nominal element ("pour papa" / 'for daddy', "pour moi" / 'for me') and is then very quickly used with a verbal element ("pour sauter" / 'to jump', "pour dessiner" / 'to draw').

The syntactic level of analysis proves insufficient to understand the emergence of prepositions at this age; interpersonal relations as well as pragmatic speech-acts must be taken into account in the analysis of spontaneous children's discourse (as opposed to electronic data). The pragmatic explanatory function of pour in situations of conflict or misunderstanding, is confirmed in Madeleine's data.

At the age of 1;11, Madeleine uses the preposition pour several times during the same film session but in an unconventional way. While she is reading a book with her mother, she is moved by the story of a mother crying because her children have nothing to eat, and wants to give the mother her bunny to console her. Picking up her bunny, she says:

(5)

Le doudou pour Madeleine 'The bunny for Madeleine'

Our first reaction to Madeleine's use of the preposition pour here is that she's using it in the wrong way, or making a mistake, since her use of it seems to be the exact opposite of the function an adult would give to the preposition pour. In adult speech, pour before a noun indicates the destination, or target of an object, in a similar way to the English preposition for. "Le doudou pour Madeleine" would then mean 'the bunny for Madeleine.'

Yet in the context of use, it is absolutely obvious that she doesn't mean that the bunny is 'for' her, but that she wants to give her bunny to the mother in the story so as to comfort her. Rather than considering the child's use of the preposition as a mistake, especially since this particular use is recurrent, it is more interesting to find out what function she ascribes to it, in what must be seen as an 'emergent category' [START_REF] Clark | Emergent categories in first language acquisition[END_REF] in her language. Quite striking too is the fact that that particular film session (1;11) showed a new surge of possessive determiners: mon/ma, son, sa ('my', 'her'/his') so that she had the linguistic ability to use the possessive form "mon doudou" if she had wanted to point at herself as the possessor of the bunny (and she does use it later on in the situation):

(6)

Ne veux mon doudou. I want my bunny'

In fact, it seems that Madeleine's use of the preposition pour is meant not to designate herself as the recipient or the possessor of the bunny, but rather to point to herself (in the 3rd person) as the agent of an intended action to console the mother, so that her utterance could be paraphrased as: 'the bunny for Madeleine to console the mother. ' The preposition pour is given a particular function by Madeleine when she first uses it: the category of prepositions as it emerges in her speech is used not so much to assign case, but to assign argument structure to an implicit verb, and to explain and justify her intentions. The category thus emerges with a pragmatic and argumentative function in the dialogue with her mother: the preposition pour directs the addressee to the agent rather than to the destination of her actions, so as to justify them. The destination of the bunny is then made obvious by a gesture: she puts the bunny on the picture of the mother and says "Tiens!"('Here!').

The same use of the preposition pour occurs a second time in the same session, when Madeleine is eating her lunch. Martine had just been telling her how to use her fork to pick the ham and put it in her mouth, and she suddenly points to the inside of her mouth and says: (7) La bouche pour Madeleine' 'The mouth for Madeleine'

In the context, Madeleine does not mean that the mouth is 'for' her: she does not consider her mouth as a separate object given to her, nor does she indicate herself as the possessor of the mouth. The preposition pour here again associates the mouth with its use, so that Madeleine's utterance can be interpreted as 'the mouth for Madeleine to eat.' This recurrent function, which Madeleine, at this age (1.11), assigns to this emergent prepositional marker used before a noun is thus quite close to Léonard's use of pour before an infinitive verb, except that Madeleine emphasizes herself as the agent of the process.

Conclusions

On the syntactic level of analysis, prepositions are classified as being either semantically coloured with a primary lexical and spatial value, or semantically weak and marking syntactic function within the prepositional phrase. In this opposition, quantitative observations of emerging prepositions show that French and English children do not behave in the same way, with a clear priority of spatial first prepositions for the English children while the French children use mainly functional ones first.

But a qualitative corpus-based analysis of the actual use of these emerging prepositions in context shows that this purely syntactic opposition is not entirely adequate and that another level of analysis would be more appropriate. In our corpus of French children, the category of prepositions emerges with a pragmatic rather than syntactic function: first prepositions are used to mark a relation between speakers, objects and the situation of utterance and not just to link parts of speech or phrases within the utterances.

In the acquisition of French, this particular grammatical category is first organised as a pragmatic paradigm, with prepositions used as tools for speech acts performed to justify action, disambiguate intentions or interpersonal positioning.

A closer look at English corpora shows that this spatial predominance should perhaps also be reconsidered. It appears that in quantitative morpho-syntactic analysis, the items that are gathered around the term 'preposition' are free preposition-like morphemes that do not always have a prepositional syntactic function in child speech. The first items appearing in English: up and down, which [START_REF] Tomasello | Learning to use prepositions: a case study[END_REF] considers as 'verb like', could well belong to the category of verbal particles and correspond to truncated phrasal verbs ('pick me up', 'put me down') used as requests for the addressee's actions in context. Those particles do not so much mark a spatial relation between objects or people but rather a request for action. In that case, particles would appear before prepositions (and not the opposite).

There again, it is interesting to note that syntactically, all these free preposition-like morphemes form a kind of morphological 'supercategory' when they emerge, and that the items within this category will be subcategorized as particles and prepositions according to a functional and pragmatic discriminating feature.

First uses by children are therefore interesting to analyse, and show that parallels between language acquisition and language histories may not be so accurate either. A better parallel to draw would perhaps be the one between first uses in language acquisition and the core, basic or schematic operations to be found behind those grammatical markers.

Figure 1 .

 1 Figure 1. Peter's functional and spatial prepositions

Figure 2 .

 2 Figure 2. Will's functional and spatial prepositions These results confirm previous research on English data. In order to compare these results to French data, we conducted the same analyses on Léonard and Madeleine, two French children living in Paris. Léonard's data was collected by the first author before the beginning of the current research and is complete 1 . The transcription is aligned with the video thanks to CLAN provided by the CHILDES project supervised by Brian McWhinney (1995).

Figure 3 .

 3 Figure 3. Leonard's functional and spatial prepositions

Figure 4 .

 4 Figure 4. Madeleine's functional and spatial prepositions

Table 1 .

 1 Percentage of prepositions per age

Léonard's data is a longitudinal follow-up from 1;08 to 3;03. For the purpose of this study, we analyzed his use of prepositions up to

2;04.

The following example illustrates how Leonard uses the preposition pour in order to disambiguate a previous utterance.

(1)

Father: Les belles saucisses! 'What beautiful sausages!' Léonard: Donne! 'Give!' Mother: J'te l'ai donnée! 'I gave it to you' Léonard: Pour papa. 'For Daddy.'

In the situation, Leonard's parents do not understand who is to be the 'recipient' of the sausage; thanks to the use of pour in "pour papa", Léonard clarifies the target and thereby makes the argument of the verb give ("donne") explicit. The preposition is thus used in the context of a misunderstanding with an argumentative value.

The same argumentative feature appears in Léonard's use of pour with infinitives. At the age of 2;02, Léonard is naked on his bed:

(2) Léonard: Maman, où est le petit lit? 'Mummy, where's the little bed?' : Le petit lit? 'The little bed?' Léonard: Pour sauter. 'To jump' ( = 'For jumping')

In this exchange, the preposition pour helps Léonard add an argument in order to elaborate his request of a bed. Here again, he is giving his reason for that request when faced to his mother's incomprehension, explaining that he wants the bed because he wants to jump (on it and use it as a trampoline).

Strikingly enough, during this period, whenever Léonard uses [pour+ verb], he is adding arguments in order to justify, explain, clarify the intentions he has previously expressed, but which his co-speaker did not understand: he wants his towel TO hide himself ("pour cacher"), he used chalks in school TO draw ("pour dessiner"). This argumentative function of the preposition pour goes along with its appearance as an emergent category. The French preposition à also figures among Léonard's early prepositions, but is used with another function, as exemplified below.

Léonard (2;02) is in his bath. Arianne, a friend of his parents comes into the bathroom to say goodbye. As soon as he sees her, he splashes and screams:

( 'Yes the bottom is yours, and the beauty mark is yours, and girls are going to love that, really love it.'

In this dialogue Léonard reacts to Ariane's intrusions as if she were taking away a beloved possession: not the objects themselves (the bath, the beauty mark), but his freedom to use them as he wishes. The bath is his kingdom, he asserts his freedom to refuse Ariane's admission to it; he also forbids Ariane to make comments on HIS birth mark and sees her remarks as a violation of his privacy. In the utterances with "à moi", the preposition à acts as a polemic re-enforcement of the property of objects described as being in the child's possession. In all the examples we find in our data, Léonard uses à to assert himself as a sort of stage director, an orchestra conductor. The same uses can be found with "à toi" meaning 'your' or 'your turn' according to the context.

In fact, the data shows that Léonard uses à and pour in complementary distribution. The following exchange is particularly interesting as to the alternating uses of à and pour: Léonard (2;01) has given Aliyah an imaginary piece of candy. His mother offers him a real piece candy, and a situation of conflict ensues as to who is to be its recipient.

( In this dialogue, the mother intends to give the candy to Léonard ('it's FOR you'), but Aliyah wants it too ('the candy is for me'). Léonard makes an attempt at solving the conflict by alternating the use of pour and à in his discourse. He first uses à ("à moi"), thus redefining the candy as being his own (this property has been assigned to the candy by his mother and is set as inalienable). The functional preposition à here links the candy to its TRUE possessor, Léonard. However, pour is also used immediately afterwards ("pour moi"), this time in order to solve the conflict raised by Aliyah over the recipient of the candy. The preposition pour is used with an argumentative value so as to redefine the target. After Aliyah's incredulous reaction: "you're sure?" Léonard is forced to reassert his own identity ('Léonard') in order to reassess the property of the candy (of it being HIS) in order for this legitimate recipient of the candy to be reestablished.

The two prepositions therefore have different bearings: à puts the focus on the object, with a polemic redefinition of one of its inherent properties, while pour focuses on the recipient of the object.