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L’évolution des milieux des Aires marines protégées (AMP) en Afrique de l’Ouest est appréhendée à partir de la perception des gestionnaires. Les données sont issues de l’enquête menée entre 2017 et 2018 à l’occasion de l’élaboration de l’état de référence des AMP du réseau régional des AMP en Afrique de l’Ouest (RAMPAO). Il en résulte que l’intégralité des milieux situés dans les AMP est sujette, d’après les gestionnaires, à des pertes de surface. Les milieux les plus touchés sont les zones de plage, les vasières et les chenaux estuariens. Les causes principales de ces dommages semblent être l’érosion ainsi qu’un déficit pluviométrique. L’activité humaine et les changements climatiques, en raison de leur caractère diffus, ne sont pas suffisamment quantifiés. Parmi les écosystèmes qui font l’objet d’un suivi satisfaisant, seules les forêts semblent connaître des évolutions globalement positives, en raison d’actions régulières de reboisement. En revanche, les herbiers ainsi que les fonds rocheux et coralliens ne sont que très peu connus des gestionnaires, qui ne leur accordent quasiment aucun suivi. La comparaison de la perception des gestionnaires avec les articles scientifiques utilisant l’imagerie satellite montre que leur jugement est similaire pour certains habitats (plages et forêts), bien qu’il existe des différences entre leur perception et les analyses scientifiques sur les changements des mangroves, et même entre les analyses scientifiques elles-mêmes. Par ailleurs, il y a un manque de données SIG au sein des AMP. Enfin, l’efficacité des actions des équipes de gestion est questionnée au regard de ces évolutions : il apparaît dans la littérature que les surfaces de forêts et de mangroves à proximité des AMP de la région subissent des pertes plus importantes qu’à l’intérieur des aires protégées The evolution of habitats in MPAs in West Africa is apprehended according to the perception of managers. These come from the state of reference of MPAs of the regional network of MPAs in West Africa (RAMPAO) conducted between 2017 and 2018. As a result, all environments in MPAs seem to lose surface, according to the managers. The most affected areas are the beaches, mudflats and estuarine channels. The damages appear to be mainly due to erosion as well as a rainfall deficit. Human activity and climate change are not sufficiently known for their impact to be quantified. Only forests appear to be generally positive among the ecosystems that are sufficiently monitored, due to regular reforestation activities. On the other hand, sea grasses, rocky and coral beds are only very little known by the managers, since they carry out almost no control over them. To finish, the effectiveness of the actions made by the management staffs is questioned regarding these evolutions: it appears in the scientific literature that forest and mangrove suffer greater losses outside MPAs.

Cette étude porte sur l'utilisation de l'imagerie satellite pour le suivi des cyclones et la caractérisation de leur impact. Deux événements récents sont étudiés à Madagascar : (i) Le cyclone Haruna, impactant la côte sud-ouest en février 2013, (ii) Le cyclone Enawo, touchant la côte nord-est en mars 2017. Le suivi de ces deux épisodes a montré la faisabilité de la mobilisation de l'imagerie satellitaire sur Madagascar pour une quantification des surfaces inondées associées aux cyclones. La combinaison des capteurs optiques et SAR (Synthetic Aperture Radar) à haute résolution temporelle et spatiale (HRS) abouti à : (i) un suivi en quasi temps réel d'Haruna par une surveillance des inondations pendant la crise et de la décrue en post-crise (ii) une cartographie des inondations en zone urbaine et dans les rizières de la région de Maroantsetra et Sambava, associées à Enawo, en combinant des images Sentinel-1 et 2, Pléiades et une démarche de cartographie participative.

Small reservoirs (SRs) are essential water storage infrastructures for rural populations of Sub-Saharan West Africa. In recent years, rapid population increase has resulted in unprecedented land use and land cover (LULC) changes. Our study documents the impacts of such changes on the water quality of SRs in Burkina Faso. Multi-temporal Landsat images were analyzed to determine LULC evolutions at various scales between 2002 and 2014. Population densities were calculated from downloaded 2014 population data. In situ water samples collected in 2004/5 and 2014 from selected SRs were analyzed for Suspended Particulate Matter (SPM) loads, an integrative proxy for water quality. The expansion of crop and artificial areas at the expense of natural covers controlled LULC changes over the period. We found a very significant correlation between SPM loads and population densities calculated at a watershed scale. A general increase between the two sampling dates in the inorganic component of SPM loads, concomitant with a clear expansion of cropland areas at a local scale, was evidenced. Results of the study suggest that two complementary but independent indicators (i.e., LULC changes within 5-km buffer areas around SRs and demographic changes at watershed scale), relevantly reflected the nature and intensity of overall pressures exerted by humans on their environment, and locally on aquatic ecosystems. Recommendations related to the re-greening of peripheral areas around SRs in order to protect water bodies are suggested.

[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-ATTOS; International audience; Finding suitable models of canopy reflectance in forward simulation mode is a prerequisite for their use in inverse mode to characterize canopy variables of interest, such as leaf area index (LAI) or chlorophyll content. In this study, the accuracy of the three-dimensional reflectance model DART (Discrete Anisotropic Radiative Transfer) was assessed for canopies of different genotypes of Eucalyptus, having distinct biophysical and biochemical characteristics, to improve the knowledge on how these characteristics are influencing the reflectance signal as measured by passive orbital sensors. The first step was to test the model suitability to simulate reflectance images in the visible and near infrared. We parameterized DART model using extensive measurements from Eucalyptus plantations including 16 contrasted genotypes. Forest inventories were conducted and leaf, bark, and forest floor optical properties were measured. Simulation accuracy was evaluated by comparing the mean top of canopy (TOC) bidirectional reflectance of DART with TOC reflectance extracted from a Pleiades very high resolution satellite image. Results showed a good performance of DART with mean reflectance absolute error lower than 2%. Intergenotype reflectance variability was correctly simulated, but the model did not succeed at catching the slight spatial variation for a given genotype, excepted when large gaps appeared due to tree mortality. The second step consisted of sensitivity analysis to explore which biochemical or biophysical characteristics influenced more the canopy reflectance between genotypes. Perspectives for using DART model in inversion mode in these ecosystems were discussed. [ABSTRACT FROM PUBLISHER]

La diminution du nombre de prairies, que l’on observe à l’échelle mondiale depuis plusieurs décennies, s’est accompagnée de l’évolution de leur mode de gestion dans un contexte d’intensification de l’usage des terres. Face aux enjeux que ces changements impliquent, tant sur le plan environnemental qu’économique, il est nécessaire d’identifier et de caractériser les dynamiques spatiotemporelles des prairies, afin notamment d’évaluer les impacts du changement climatique sur ces dernières et leur capacité à s’y adapter. La télédétection, qui est un outil d’observation couramment utilisé pour étudier la surface terrestre, permet de répondre aux problématiques de gestion des territoires. Cet article présente un exemple de l’utilisation de séries temporelles d’images à haute résolution spatiale pour d’une part étudier la dynamique spatiotemporelle des prairies depuis les années 50, et d’autre part les caractériser en déterminant leur mode de gestion et leur productivité. Les informations dérivées de ces séries d’images peuvent être intégrées dans des modèles agro-climatiques afin de pouvoir simuler le fonctionnement des agro-écosystèmes pour évaluer leur évolution face aux changements climatiques in fine et proposer des scénarios d’adaptation à ces changements. The decrease of grasslands, which has been observed on a global scale for several decades, occurred with changes in their management in the context of land use intensification. Faced with the environmental and economic implications of these changes, it is necessary to identify and characterize the spatial and temporal dynamics of grasslands, in particular to assess the impacts of climate change on these grasslands and their capacity to adapt. Remote sensing, which is an observation tool commonly used to study the Earth's surface, makes it possible to address territorial management issues. This article presents an example of the use of time series of high spatial resolution images to study the spatial and temporal dynamics of grasslands since the 1950s and to characterize them by determining their management and their productivity. Information derived from these images series can be integrated into agro-climatic models in order to simulate the agro-ecosystems functioning to evaluate their evolution regarding climate change and to propose adaptation scenarios. La disminución del número de praderas, observada a escala mundial desde hace varias décadas, ha ido acompañada de cambios en su modo de gestión en el contexto de una intensificación del uso de la tierra. Ante los desafíos que implican estos cambios, tanto sobre el plano ambiental como económico, resulta necesario identificar y caracterizar las dinámicas espacio temporales de las praderas, con la finalidad de evaluar los impactos en ellas producto del cambio climático y su capacidad para adaptarse a este. La teledetección, que es una herramienta de observación comúnmente utilizada para estudiar la superficie de la tierra, permite responder a los problemas de gestión de los territorios. Este artículo, presenta un ejemplo del uso de series temporales de imágenes con alta resolución espacial para estudiar la dinámica espacio temporal de los prados desde 1950, y, además, caracterizar y determinar su modo de gestión y productividad. La información derivada de esta serie de imágenes puede ser integrada en modelos agroclimáticos, con la finalidad de poder simular el funcionamiento de los agroecosistemas y evaluar así su evolución en detalle frente al cambio climático, proponiendo así escenarios para la adaptación a tales cambios.

International audience; Mapping forest composition using multiseasonal optical time series remains a challenge. Highly contrasted results are reported from one study to another suggesting that drivers of classification errors are still under-explored. We evaluated the performances of single-year Formosat-2 time series to discriminate tree species in temperate forests in France and investigated how predictions vary statistically and spatially across multiple years. Our objective was to better estimate the impact of spatial autocorrelation in the validation data on measurement accuracy and to understand which drivers in the time series are responsible for classification errors. The experiments were based on 10 Formosat-2 image time series irregularly acquired during the seasonal vegetation cycle from 2006 to 2014. Due to lot of clouds in the year 2006, an alternative 2006 time series using only cloud-free images has been added. Thirteen tree species were classified in each single-year dataset based on the Support Vector Machine (SVM) algorithm. The performances were assessed using a spatial leave-one-out cross validation (SLOO-CV) strategy, thereby guaranteeing full independence of the validation samples, and compared with standard non-spatial leave-one-out cross-validation (LOO-CV). The results show relatively close statistical performances from one year to the next despite the differences between the annual time series. Good agreements between years were observed in monospecific tree plantations of broadleaf species versus high disparity in other forests composed of different species. A strong positive bias in the accuracy assessment (up to 0.4 of Overall Accuracy (OA)) was also found when spatial dependence in the validation data was not removed. Using the SLOO-CV approach, the average OA values per year ranged from 0.48 for 2006 to 0.60 for 2013, which satisfactorily represents the spatial instability of species prediction between years.

International audience; In southern Tunisia, agricultural land has been subject to significant anthropogenic pressures since the early 20th century, which have contributed to significant changes in land use. The region's strong demographic growth has led to socio-spatial changes (sedentarisation, the descent of mountain populations down to the foothills and the Djeffara plain, the development of agriculture in the jessour (water and soil conservation works that block the gullies dug in the loess) at the expense of the rangelands. The current landscapes of southern Tunisia, from the Matmata region to the surroundings of Tataouine, now display signs of a rural exodus that is reflected in the abandonment of the jessour. This exodus has significant landscape and environmental impacts that can be measured through the use of diachronic vertical imagery (aerial photographs, satellite images). It can be observed that from the 1950s onwards, jessour developed strongly in the ravines, in line with demographics. The rural exodus that appeared in the 1970s led to the concentration of populations in the new towns, which did not prevent water and soil conservation works from continuing to be used and maintained. While some areas, particularly in the southern part of the study area, are still seeing the appearance of new jessour, most of them are abandoned and subjected to regressive erosion due to the suffocation that rapidly destroys them.; Dans le Sud Tunisien, les terres agricoles sont soumises depuis le début du XXe siècle à d’importantes pressions anthropiques qui ont contribué à modifier largement l’occupation des sols. La forte croissance démographique de la région a entraîné des mutations socio-spatiales (sédentarisation, descente des populations montagnardes vers les piémonts et la plaine de la Djeffara, développement de l’agriculture dans les jessour (ouvrages de conservation des eaux et des sols qui barrent les ravines creusées dans les lœss) au détriment des parcours). Les paysages actuels du Sud Tunisien, de la région de Matmata aux environs de Tataouine, montrent aujourd’hui les signes d’un exode rural qui se traduit notamment par l’abandon des jessour. Cet exode a des impacts paysagers et environnementaux conséquents, qu’il est possible d’appréhender et de quantifier grâce à l’utilisation de l’imagerie verticale diachronique (photographies aériennes, images satellitaires). On observe ainsi qu’à partir des années 1950, les jessour se développent fortement dans les ravines, en lien avec la démographie. L’exode rural qui apparaît dans les années 1970 se traduit par la concentration des populations vers les villes nouvelles, qui n’empêche pas que les ouvrages de conservation des eaux et des sols continuent à être utilisés et entretenus. Si de nos jours certains secteurs, en particulier au sud de la région étudiée, voient encore l’apparition de nouveaux jessour, la plupart d’entre eux sont abandonnés et soumis à une érosion régressive due à la suffosion qui les détruit rapidement.

International audience; In southern Tunisia, agricultural land has been subject to significant anthropogenic pressures since the early 20th century, which have contributed to significant changes in land use. The region's strong demographic growth has led to socio-spatial changes (sedentarisation, the descent of mountain populations down to the foothills and the Djeffara plain, the development of agriculture in the jessour (water and soil conservation works that block the gullies dug in the loess) at the expense of the rangelands. The current landscapes of southern Tunisia, from the Matmata region to the surroundings of Tataouine, now display signs of a rural exodus that is reflected in the abandonment of the jessour. This exodus has significant landscape and environmental impacts that can be measured through the use of diachronic vertical imagery (aerial photographs, satellite images). It can be observed that from the 1950s onwards, jessour developed strongly in the ravines, in line with demographics. The rural exodus that appeared in the 1970s led to the concentration of populations in the new towns, which did not prevent water and soil conservation works from continuing to be used and maintained. While some areas, particularly in the southern part of the study area, are still seeing the appearance of new jessour, most of them are abandoned and subjected to regressive erosion due to the suffocation that rapidly destroys them.; Dans le Sud Tunisien, les terres agricoles sont soumises depuis le début du XXe siècle à d’importantes pressions anthropiques qui ont contribué à modifier largement l’occupation des sols. La forte croissance démographique de la région a entraîné des mutations socio-spatiales (sédentarisation, descente des populations montagnardes vers les piémonts et la plaine de la Djeffara, développement de l’agriculture dans les jessour (ouvrages de conservation des eaux et des sols qui barrent les ravines creusées dans les lœss) au détriment des parcours). Les paysages actuels du Sud Tunisien, de la région de Matmata aux environs de Tataouine, montrent aujourd’hui les signes d’un exode rural qui se traduit notamment par l’abandon des jessour. Cet exode a des impacts paysagers et environnementaux conséquents, qu’il est possible d’appréhender et de quantifier grâce à l’utilisation de l’imagerie verticale diachronique (photographies aériennes, images satellitaires). On observe ainsi qu’à partir des années 1950, les jessour se développent fortement dans les ravines, en lien avec la démographie. L’exode rural qui apparaît dans les années 1970 se traduit par la concentration des populations vers les villes nouvelles, qui n’empêche pas que les ouvrages de conservation des eaux et des sols continuent à être utilisés et entretenus. Si de nos jours certains secteurs, en particulier au sud de la région étudiée, voient encore l’apparition de nouveaux jessour, la plupart d’entre eux sont abandonnés et soumis à une érosion régressive due à la suffosion qui les détruit rapidement.

International audience; Many small islands are located in the southwestern Indian Ocean. These islands have their own environmental specificities and very fragmented landscapes. Generic land use products developed from low and medium resolution satellite images are not suitable for studying these small territories. This is why we have developed a land use/land cover product, called Homisland-IO, based on remote sensing processing on high spatial resolution satellite images acquired by SPOT 5 satellite between December 2012 and July 2014. This product has been produced using an object-based classification process. The overall accuracy of the product is 86%. Homisland-IO is freely accessible through a web portal and is thus available for future use.

L'objectif de cette étude est le suivi spatio-temporel de la ligne de rivage des plages sableuses microtidales de la baie ouest du golfe de Tunis, BOGT durant le siècle dernier (1936-2016). La méthodologie adoptée s'est basée sur le traitement des photographies aériennes (1948 ; 1974 et 2000), des imageries Spot et Sentinel et des cartes topographiques (1936 et 1974) complétée par l'étude statistique Digital Shoreline Analysis System (DSAS). Les résultats sont exprimés par des taux d'évolution du rivage : 1- le NSM (Net Shoreline Mouvment) 2- l'EPR (End Point Rate) et l'indice de régression linéaire 3-LRR (Linear Regression). La ligne de rivage de la BOGT montre une morphodynamique spatio-temporelle variable. Au début du siècle (1936-1974), on observe une évolution naturelle avec des zones d'engraissement estimées à un EPR de 13 ± 0.15 m/an qui alternent avec des aires d'érosion (- 8 m ± 0.15 m/an) au niveau de la nouvelle embouchure de la Medjerda. Ce taux de recul s'avère plus accentué au cours des dernières décennies (1974-2016) relevant des zones 'hot spot' de recul estimé à un EPR de -25 m ± 0.15 m/an. Les zones les plus affectées sont localisées aux alentours du littoral de Kalâat Andalous qui a été sévèrement impacté par les activités anthropiques.

International audience; Timely and efficient land-cover mapping is of high interest, especially in agricultural landscapes. Classification based on satellite images over the season, while important for cropland monitoring, remains challenging in subtropical agricultural areas due to the high diversity of management systems and seasonal cloud cover variations. This work presents supervised object-based classifications over the year at 2-month time-steps in a heterogeneous region of 12,000 km(2) in the Sao Paulo region of Brazil. Different methods and remote-sensing datasets were tested with the random forest algorithm, including optical and radar data, time series of images, and cloud gap-filling methods. The final selected method demonstrated an overall accuracy of approximately 0.84, which was stable throughout the year, at the more detailed level of classification; confusion mainly occurred among annual crop classes and soil classes. We showed in this study that the use of time series was useful in this context, mainly by including a small number of highly discriminant images. Such important images were eventually distant in time from the prediction date, and they corresponded to a high-quality image with low cloud cover. Consequently, the final classification accuracy was not sensitive to the cloud gap-filling method, and simple median gap-filling or linear interpolations with time were sufficient. Sentinel-1 images did not improve the classification results in this context. For within-season dynamic classes, such as annual crops, which were more difficult to classify, field measurement efforts should be densified and planned during the most discriminant window, which may not occur during the crop vegetation peak.

2.1. Lugar y localización El lugar es la unidad básica de la geografía, “el átomo del espacio geográfico” (Brunet, 2001). El espacio geográfico se compone de una multitud, de una infinidad de lugares. Éstos se definen por su posición y su forma en una escala determinada. La posición es única –la latitud, la longitud y la altitud– y no se modifica por el cambio de escala. La forma se define gracias a los tres elementos básicos en geografía: el punto, la línea y la superficie (ver Capítulo 6.3....

No existen métodos de investigación específicos para el análisis del espacio o del territorio; además, muchos métodos cualitativos como cuantitativos son comunes a varias disciplinas de las ciencias sociales. Hemos citado en la Introducción los principios generales de las etapas de la investigación y aquí queremos presentar solamente una guía de preguntas necesarias para conducir esta investigación, así como algunos enfoques en los cuales hay que insistir y manejar con perfecto conocimiento p...

El territorio tiene cada día mayor importancia, tanto en su componente físico como en su dimensión sociocultural. La gestión de los recursos naturales, el problema del acceso a la tierra, la gobernabilidad, las cadenas productivas, las políticas de infraestructura, la cosmovisión campesina, la construcción de identidades y otros son temas relacionados con el espacio y el territorio. El espacio y el territorio han sido investigados desde diversas disciplinas, como la geografía, la economía y la sociología. Sin embargo, todavfa carecemos de propuestas metodológicas intégrales. Por eso, revisando los caminos transitados por la geografía moderna y centrando su preocupación en los conceptos de espacio y territorio, este libro propone una lectura multidimensional y multidisciplinaria del tema, ofreciendo un panorama de los diferentes enfoques, métodos e instrumentas para estudios empiricos, como los métodos estadísticos, cartográficos y, como dice Erwin Galoppo, "ese producto génial de la geografía francesa contemporanea: los coremas".

4.1. La evolución de las metodologías de investigación Como la mayoría de las ciencias, la geografía fue atravesada por los grandes debates de la epistemología y se dividió en varias corrientes y escuelas que tuvieron un impacto importante en la historia de la humanidad. No es el objetivo de este libro presentar estas escuelas ni estos debates, el lector puede referirse a los clásicos como Claval, 1987; Johnston, 1983 o los artículos de Capel en la revista Geocrítica (Capel, 1983; 1987; 1989)...

Antes de los años 70, en las ciencias sociales, el concepto de territorio no existía afuera de la concepción jurídica del término: un área de control territorial con fronteras y sistema de dominación. Este concepto fue introducido por los etólogos, como sistema de defensa de los miembros de una misma especie animal. La etología, estudiando los animales en su entorno, desarrolló el concepto de territorialidad, basado en un sistema de comportamiento individual y colectivo, concepto que fue tran...

La cartografía es la herramienta más usual de representación de un espacio o de un territorio por medio de un enfoque cognoscitivo: “la representación es una creación de esquemas pertinentes de lo real que nos ayudan, en el análisis espacial, a estructurar mentalmente el espacio y a practicarlo en función de nuestras posibilidades y de nuestros valores” (Bailly, 1994). Todo el conocimiento espacial está basado en representaciones (científicas o no, concretas o virtuales, conscientes o inconsc...

El lector ha podido darse cuenta de la diversidad y de la riqueza de los enfoques relacionados con el estudio del espacio y del territorio. Por naturaleza, estos dos conceptos traspasan las disciplinas. “La Historia no se escribe fuera del espacio y no hay sociedad aespacial. El espacio, en sí mismo, es social” decía Milton Santos (1996). Esto significa que el espacio y el territorio constituyen conceptos trans-disciplinarios muy fuertes, capaces de integrar múltiples visiones de la construcc...

El territorio tiene cada día mayor importancia, tanto en su componente físico como en su dimensión sociocultural. La gestión de los recursos naturales, el problema del acceso a la tierra, la gobernabilidad, la demanda identitaria, las cadenas productivas, las políticas de infraestructura, el imaginario campesino, la reciprocidad y otros son temas relacionados con el espacio y el territorio. Los dos términos, hoy en día, son de uso común, incluso en la comunidad científica. Sin embargo, los co...

En los últimos años algunos ecólogos del paisaje han señalado que la frontera final de la ecología es en realidad el espacio geográfico, remarcando que gran parte de la historia de esa ciencia se desarrolló en un ambiente no espacial, asumiendo por ejemplo a las presas perfectamente mezcladas con sus depredadores o considerando a los ecosistemas como depósitos homogéneos de carbono o de nutrientes, etc. Esos mismos ecólogos señalan que, puesto que la ecología se define como el estudio de las ...

[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-ATTOS [TR2_IRSTEA]SYNERGIE [ADD1_IRSTEA]Équiper l'agriculture [ADD2_IRSTEA]Dynamiques spatiales d'anthropisation; International audience; The recently launched Sentinel-1 satellite with a Synthetic Aperture Radar (SAR) sensor onboard offers a powerful tool for irrigation monitoring under various weather conditions, with high spatial and temporal resolution. This research discusses the potential of different metrics calculated from the Sentinel-1 time series for mapping irrigated fields. A methodology for irrigation mapping using SAR data is proposed. The study is performed using VV (vertical-vertical) and VH (vertical-horizontal) polarizations over an agricultural site in Urgell, Catalunya (Spain). With field segmentation information from SIGPAC (the Geographic Information System for Agricultural Parcels), the backscatter intensities are averaged within each field. From the Sentinel-1 time series for each field, the statistics and metrics, including the mean value, the variance of the signal, the correlation length, and the fractal dimension, are analyzed. With the Support Vector Machine (SVM), the classification of irrigated crops, irrigated trees, and non-irrigated fields is performed with the metrics vector. The results derived from the SVM are validated with ground truthing from SIGPAC over the whole study area, with a good overall accuracy of 81.08%. Random Forest (RF) machine classification is also tested in this study, which gives an accuracy of around 82.2% when setting the tree depth at three. The methodology is based only on SAR data, which makes it applicable to all areas, even with frequent cloud cover, but this method may be less robust when irrigation is less dominated to soil moisture change.

L’urbanisme et la mobilité contraignent fortement les conditions environnementales présentes et futures des grands centres urbains. L’extension désorganisée des villes algériennes engendre aujourd’hui de multiples risques liés au secteur des transports. La pollution de l’air représente l’un de ces risques.L’objectif de cette étude est de développer une méthodologie permettant d’évaluer les émissions de polluants atmosphériques dues au trafic routier. La méthodologie est basée sur un couplage entre SIG et modélisation déterministe pour mieux représenter la répartition spatio-temporelle des émissions.Elle est appliquée à la ville d’Oran en Algérie, dont on montre que la croissance du tissu urbain, et plus particulièrement son étalement en périphérie, sur la période 1966-2015 a induit un transfert des populations du centre-ville vers les pôles périphériques de Bir El Djir, Es Sénia et Sidi Chahmi. Cet étalement est confirmé par l’étude d’une série chronologique d’images satellitaires. Cette évolution de la forme urbaine génère un besoin en mobilité accru et aggrave les problèmes de circulation et de congestion de véhicules fonctionnant à l’énergie fossile qui est la source d’émissions polluantes significatives dont l’impact négatif sur la santé et l’environnement n’est plus à démontrer.La réalisation d’un cadastre des émissions polluantes est une étape essentielle afin d’évaluer la qualité de l’air sur la région d’Oran. Ces émissions sont ici quantifiées dans le temps et dans l’espace grâce à l’application du modèle EMISENS, à partir de comptages de véhicules. Compte tenu de l’évolution du tissu urbain et du transport, ces émissions devraient continuer à augmenter en raison des besoins en mobilité induits par l’étalement ininterrompue de la ville et par la forte attractivité que le centre de la ville exerce sur les citoyens de l’agglomération d’Oran. Urbanism and mobility strongly constrain present and future environmental conditions in large urban centers. The disorganized expansion of Algerian cities now creates multiple risks related to the transport sector. Air pollution is one of those risks.The objective of this study is to develop a methodology for assessing air pollutant emissions from road traffic. The methodology is based on a coupling between GIS and deterministic modeling to better represent the spatio-temporal distribution of emissions.It is applied to the city of Oran in Algeria, which shows that the growth of the urban fabric, and in particular its peripheral spreading over the period 1966-2015, has led to a transfer of population from the city center to the peripheral poles of Bir El Djir, Es Sénia and Sidi Chahmi. This spread is confirmed by the study of a chronological series of satellite images. This evolution of the urban form generates a greater need for mobility and aggravates the circulation and congestion problems of fossil-fueled vehicles that are sources of significant polluting emissions whose negative impact on health and environment is no longer to prove.The implementation of a pollutant emissions cadastre is an essential step in order to evaluate the air quality in the Oran region. These emissions are here quantified in time and space thanks to the application of the EMISENS model, based on vehicle counts. Given the evolution of the urban fabric and transport, these emissions should continue to increase because of the mobility needs induced by the uninterrupted spread of the city and by the high attractiveness of the city center to the Oran agglomeration citizens. 城市化与交通极大地限制了大都市当今与未来的环境状况。阿尔及利亚城市的无序扩张造成了与交通相关的许多风险。其中空气污染是较为突出的一个。此项研究的目的是建立一套评估交通污染的方法 。为更好地呈现污染排放的时空分布，该方法结合地理信息系统（GIS）与确定性建模（deterministic modeling）。 本文将该方法运用于阿尔及利亚奥兰地区，结果显示奥兰地区城市增长，尤其是1966年至2015年间城市边际的扩张已经使城市人口逐渐从中心城区转移至城市边缘的Bir El Djir, Es Sénia 和 Sidi Chahmi。通过对一系列不同时序的卫星图片的研究进一步证实了这一人口转移。 城市形态的转变带来了对交通的需求，也恶化了机动车的拥堵问题。而这些使用化石燃料的机动车是空气污染物的主要来源，它们所造成的空气污染对人体和环境的危害无需赘述。 污染排放物地籍的实施是评估奥兰地区空气质量的重要的举措。基于机动车数据的EMISENS模型从时间有空间两个角度量化了污染排放。 基于城市结构与交通状况的转变，一方面持续扩张的城市带来新的交通需求，另一方面奥兰的中心城区保持其对居民的吸引力，由此可见奥兰地区的污染排放将持续上升。

As planícies de inundação amazônicas são áreas de grande importância econômica, social e ecológica. A ocupação desses ambientes complexos e frágeis traz variados impactos. Esse estudo pretende analisar dinâmicas de alteração de uso e cobertura da terra em uma região de planície de inundação, próximo a cidade de Santarém (PA), sendo a bacia hidrográfica do Lago Grande do Curuai o foco da pesquisa. Para isso foram utilizadas geotecnologias associadas à métricas de paisagens, e uma análise a partir de dois recortes geográficos distintos na mesma área de estudo. O primeiro recorte geográfico é equivalente a toda a bacia hidrográfica, tendo foco na análise da cobertura vegetal natural, correspondente as florestas de terra firme e de várzea; o segundo recorte diz respeito a divisão da área de estudo em seis zonas de paisagem, sendo que essa divisão levou em conta os sistemas produtivos e as características de uso da região em sua delimitação. Foram classificadas imagens dos satélites Landsat 5 e 7, dos anos de 1985, 1997 e 2014. As métricas de paisagem permitiram estabelecer padrões da paisagem, facilitando a comparação entre os momentos distintos. No primeiro recorte, as métricas apontam para uma dinâmica moderada no período; embora haja uma diminuição das áreas de floresta de terra firme, a classe em que há maior aumento é a de vegetação secundária/capoeira. Ocorrem aumentos das áreas de pastagem, entretanto as áreas de cultivo de roça mantêm-se estáveis. As áreas de pasto e roça ocorrem de forma dispersa no território e em pequenas parcelas; essa dinâmica apontada pela classificação é um indicativo de que as áreas de cultivo ocorrem de forma rotacionada, com a ocupação de áreas diferentes que vão se recuperando com o passar do tempo. No segundo recorte, dentre as seis zonas da paisagem, duas são concentradoras de grande parte dos processos de substituição da cobertura vegetal natural por atividades antrópicas, sendo as zonas 3 e 4 as que tem mais alteração da paisagem. A análise em recortes geográficos distintos permitiu identificar que a área de estudo possui padrões heterogêneos de ocupação no tempo e no espaço. Floodplains in the Amazon are areas of great economic, social and ecological importance. Occupation in these areas brings various impacts due to its complexity and fragility. This paper aims to analyze dynamics of change in land use and land cover in the floodplain of Lago Grande do Curuai, near Santarém city, in the state of Pará. To that end, geotechnologies associated with landscape metrics and an analysis of two different geographic clippings of the region were used. The first geographic clipping covers the entire hydrographic basin, focusing on the analysis of the natural vegetation cover (dryland and lowlands); the second geographic clipping shows the area divided in six landscape zones, whose criteria are the productive systems and the characteristics of use of the region. We classified images from satellites Landsat 5 and 7 from the years 1985, 1997 and 2014. Landscape metrics established patterns that facilitated the comparison between different times. In the first geographic clipping, metrics show a moderate dynamic in the period. Although there is a decrease in dry land forest areas, the class in which there is greater increase is the secondary/"capoeira" vegetation. There are increases in the pasture areas, the farmlands, however, remain stable; pasture and farming areas occur in a dispersed way in the territory and in small allotments; this dynamic revealed by classification indicates that cultivation areas are occupied by rotation, being occupied and abandoned over time. In the second geographic clipping, zones 3 and 4 concentrate most of the processes of replacing the natural vegetation cover by anthropic activities. The analysis in different geographic clippings shows the researched area has heterogeneous patterns of occupation in time and space. Les bassins d’inondation amazoniens sont de grande valeur économique, sociale et écologique. Ces espaces complexes et fragiles sont confrontés à une grande diversité d’usage. Cette recherche analyse la dynamique de changement de l’occupation du sol dans le bassin d’inondation du Lac Grand do Curuai, à proximité de Santarém (État du Pará). Pour cela, des métriques paysagères ont été calculées dans deux zonages préalablement sélectionnés afin d’affiner l’analyse des changements spatio-temporels. D’une part les traitements ont porté sur l’ensemble du bassin versant afin d’appréhender les différents types de végétation naturelle (forêt de varzea et forêt de terre ferme). D’autre part, il s’est agit d’effectuer les calculs dans un zonage paysager qui exprime la diversité des systèmes agricoles associés aux caractéristiques environnementales de la région. Les images de satellites utilisées (Landsat 5 et Landsat 7) permettent de conduire l’analyse sur 3 périodes : 1985, 1997 et 2014. Les métriques paysagères ont aidé à établir un modèle paysager qui a pour fonction la comparaison dans le temps et dans l’espace. Les calculs effectués dans le premier zonage expriment une dynamique d’évolution modérée. Si la classe de « forêt de terre ferme » diminue, celles de « végétation secondaire» et de « pâturage » augmentent en superficie. En revanche, la classe « parcelle de manioc » reste stable. Ces classes dispersées dans la zone d’étude, sont de petite taille et changent d’emplacement d’une période sur l’autre. Cette répartition et ces changements sont le signe d’un usage rotationnel des terres. Le deuxième niveau de zonage montre que ces évolutions rotationnels ont essentiellement lieu dans deux des paysages les plus anthropisés. Les dynamiques des autres paysages augurent des modifications d’usage des milieux. L'analyse basée sur ces deux types de zonages permet de mieux affiner les hétérogénéités spatiales dans le temps et dans l'espace.

International audience; Soil erosion processes which contribute to desertification and land degradation, constitute major environmental and social issues for the coming decades. This is particularly true in arid areas where rural populations mostly depend on soil ability to support crop production. Assessment of soil erosion across large and quite diverse areas is very difficult but crucial for planning and management of the natural resources. The purpose of this paper is to investigate a prediction model for soil vulnerability to erosion based on the use of the information contained in satellite images. Based on neural networks models, the used approach in this paper aims at checking a correlation between the digital content of satellite images and soil vulnerability factors: erosivity (R), the soil erodibility (K), and the slope length and steepness (LS); vulnerability (V) as described in the RUSLE model. Significant results have been obtained for R and K factors. This promising pilot study was conducted in South Ferlo, Senegal, a region with Sahelian environmental characteristics.

International audience; When the Amazonian rain forest is cut to create pasture, some of the original vegetal species survive clearing, even expressing their ability to invade agro-systems. It is true of the babassu palm, which can be considered, paradoxically, a natural resource by the "Interstate Movement of Babassu Fruit Breaker Women" or as native weed by land owners-farmers. To manage potential conflict of land uses, we study here the current density of this palm tree in different habitats, based on a combination of field data and remote sensing data. Firstly, we checked that the field survey methodology (i.e., counting free-trunk palm trees over 20 cm in circumference) provides density values compatible with those stemming from satellite images interpretation. We can see then that, a PA-Benfica Brazilian territory revealed an average density of the babassu lower in pastures (2.86 ind/ha) than in the dense forest (4.72 ind/ha) from which they originate and than in fallow land (4.31 ind/ ha). We analyze in detail density data repartition in three habitats and we discuss results from the literature on the density of this palm tree versus its resilience at different developmental stages after forest clearing, depending on anthropogenic -or not- factors, including solar radiation, fire, weeding, clear cutting, burying fruit, and competition with forage grass. All these results can be exploited for the design of future management plans for the babassu palm and we think that the linked methodology and interdisciplinary approach can be extended to others palms and trees species in similar problematic issues.

The research and improvement of methods to be used for crop monitoring are currently major challenges, especially for radar images due to their speckle noise nature. The European Space Agency’s (ESA) Sentinel-1 constellation provides synthetic aperture radar (SAR) images coverage with a 6-day revisit period at a high spatial resolution of pixel spacing of 20 m. Sentinel-1 data are considerably useful, as they provide valuable information of the vegetation cover. The objective of this work is to study the capabilities of multitemporal radar images for rice height and dry biomass retrievals using Sentinel-1 data. To do this, we train Sentinel-1 data against ground measurements with classical machine learning techniques (Multiple Linear Regression (MLR), Support Vector Regression (SVR) and Random Forest (RF)) to estimate rice height and dry biomass. The study is carried out on a multitemporal Sentinel-1 dataset acquired from May 2017 to September 2017 over the Camargue region, southern France. The ground in-situ measurements were made in the same period to collect rice height and dry biomass over 11 rice fields. The images were processed in order to produce a radar stack in C-band including dual-polarization VV (Vertical receive and Vertical transmit) and VH (Vertical receive and Horizontal transmit) data. We found that non-parametric methods (SVR and RF) had a better performance over the parametric MLR method for rice biophysical parameter retrievals. The accuracy of rice height estimation showed that rice height retrieval was strongly correlated to the in-situ rice height from dual-polarization, in which Random Forest yielded the best performance with correlation coefficient R 2 = 0.92 and the root mean square error (RMSE) 16% (7.9 cm). In addition, we demonstrated that the correlation of Sentinel-1 signal to the biomass was also very high in VH polarization with R 2 = 0.9 and RMSE = 18% (162 g·m − 2 ) (with Random Forest method). Such results indicate that the highly qualified Sentinel-1 radar data could be well exploited for rice biomass and height retrieval and they could be used for operational tasks.

En Côte d’Ivoire, la densité de population est passée de 8 hab./km² en 1950 à 71 hab./km² en 2014. Cette augmentation a impulsé de fortes dynamiques de peuplements et a généré l’augmentation des superficies cultivées. Pour visualiser ces dynamiques dans la région de Méagui, une étude diachronique du peuplement et de l’emprise rurale a été effectuée sur un transect qui allait de la ville de Méagui (Est) jusqu’au Parc National de Taï (Ouest), sur une superficie de 233km². Le croisement entre les informations récoltées sur le terrain et l’analyse d’images satellitaires Landsat prises à différentes dates (1986, 2002 et 2014) a permis de faire une discrimination des dynamiques de peuplement et des types d’occupation du sol. De 6 unités de peuplement, identifiées à l’Est de la zone au début des années 1975, on est passé à 489 en 2016. Parallèlement, la forêt qui occupait 40% de l’espace étudié en 1986, avait presque disparue en 2014, au profit des cultures pérennes (plus de 90%). En 2016, la densité de population globale était de 416 hab./km², soit près de 6 fois supérieure à la densité de population nationale. Ces résultats montrent l’importance de la problématique population/ressource en Côte d’Ivoire., Anthropogenic Pressure and Landscape Dynamics in the Ivoirian Forest Area in the Meagui Region.In Ivory Coast, population density increased from 8 inhabitants/km² in 1950 to 71 inhabitants/km² in 2014. The population growth impulse strong dynamics of settlement and generated an increase of the cultivated surfaces. To visualize these dynamics in the area of Meagui, a diachronic study was realized on settlement and landscape on a transect from Meagui town (East) to National Park of Taï (West), covering a surface of 233 km². The combination of field information and analysis of LANDSAT satellite imagery taken at different dates (1986, 2002 and 2014) allowed to discriminate settlement dynamics and land-use patterns. From 6 units of settlements, identified in the eastern part of the zone in the early 1975s, the number was increased to 489 in 2016. In the same time, the forest, which occupied 40% of the area studied in 1986, had almost disappeared in 2014, in favor of perennial crops (more than 90%). The total population density is estimated at 416 inhabitants/km², i.e 6 times most important than the national density. These results show how important the population/resource problem is in Ivory Coast.

Shortly after strong rains or tropical storms, chlorophyll-a concentration (Chla), turbidity, and colored dissolved organic matter (CDOM) in the lagoon of New Caledonia may be tripled. This effect is visible as far as 50 km offshore. The Eastern Coast of New Caledonia is more impacted than the Western Coast because of its geomorphological structure. Higher frequency and intensity of the rains, and the dominance of highly erosive lateritic formations resulted from deep weathering of ultramafic rocks. At the deeper parts of the lagoon (> 20 m), increases of Chla, turbidity, and CDOM absorption can be detected by satellite imagery with their plumes extending off shore as a result of wind-driven circulation in the lagoon. Such increases agree with the oceanographic measurements of Chla, absorption, backscattering, turbidity and CDOM during extensive cruises. Satellite and in situ measurements allow tracing of particulates and dissolved matter in lagoon waters and up to the coral barrier reefs. The largest particles settle at a short distance from the coast influencing the sediments not far from the river outflows. Fine particles (< 10 µm), colloids and/or CDOM are exported to reefs where they can be beneficial through protection from high UV illumination (colloids) and feeding of the corals (CDOM). Phytoplankton and associated detritus, when not dominated by toxic filamentous cyanobacteria, can also feed coral reefs. Finally, the export of fine particles associated with colloids and/or CDOM can also contribute to the distribution of trace metals to the barrier reefs of the East Coast and offshore. The question whether this input of trace metals has an overall positive or negative effect on the coral reefs is still under debate.

When the Amazonian rain forest is cut to create pasture, some of the original vegetal species survive clearing, even expressing their ability to invade agro-systems. It is true of the babassu palm, which can be considered, paradoxically, a natural resource by the "Interstate Movement of Babassu Fruit Breaker Women" or as native weed by land owners-farmers. To manage potential conflict of land uses, we study here the current density of this palm tree in different habitats, based on a combination of field data and remote sensing data. Firstly, we checked that the field survey methodology (i.e., counting free-trunk palm trees over 20 cm in circumference) provides density values compatible with those stemming from satellite images interpretation. We can see then that, a PA-Benfica Brazilian territory revealed an average density of the babassu lower in pastures (2.86 ind/ha) than in the dense forest (4.72 ind/ha) from which they originate and than in fallow land (4.31 ind/ ha). We analyze in detail density data repartition in three habitats and we discuss results from the literature on the density of this palm tree versus its resilience at different developmental stages after forest clearing, depending on anthropogenic -or not- factors, including solar radiation, fire, weeding, clear cutting, burying fruit, and competition with forage grass. All these results can be exploited for the design of future management plans for the babassu palm and we think that the linked methodology and interdisciplinary approach can be extended to others palms and trees species in similar problematic issues.

Global wheat production reached 754.8 million tons in 2017, according to the FAO database. While wheat is considered as a staple food for many populations across the globe, mapping wheat could be an effective tool to achieve the SDG2 sustainable development goal&mdash, End Hunger and Secure Food Security. In Lebanon, this crop is supported financially, and sometimes technically, by the Lebanese government. However, there is a lack of statistical databases, at both national and regional scales, as well as critical information much needed in the subsidy and compensation system. In this context, this study proposes an innovative approach, named Simple and Effective Wheat Mapping Approach (SEWMA), to map the winter wheat areas grown in the Bekaa plain, the primary wheat production area in Lebanon, in the years of 2016 and 2017. The proposed methodology is a tree-like approach relying on the Normalized Difference Vegetation Index (NDVI) values of four-month period that coincides with several phenological stages of wheat (i.e., tillering, stem extension, heading, flowering and ripening). The usage of the freely available Sentinel-2 imageries, with a high spatial (10 m) and temporal (5 days) resolutions, was necessary, particularly due to the small sized and overlapped plots encountered in the study area. Concerning the wheat areas, results show that there was a decrease from 11,063 &plusmn, 1309 ha in 2016 to 7605 &plusmn, 1184 in 2017. When SEWMA was applied using 2016 ground truth data, the overall accuracy reached 87.0% on 2017 data, whereas, when implemented using 2017 ground truth data, the overall accuracy was 82.6% on 2016 data. The novelty resides in executing early classification output (up to six weeks before harvest) as well as distinguishing wheat from other winter cereal crops with similar NDVI yearly profiles (i.e., barley and triticale). SEWMA offers a simple, yet effective and budget-saving approach providing early-season classification information, very crucial to decision support systems and the Lebanese government concerning, but not limited to, food production, trade, management and agricultural financial support.

[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-ATTOS [ADD1_IRSTEA]Dynamiques spatiales d'anthropisation; International audience; The objective of this paper is to evaluate the potential of Sentinel-1 Synthetic Aperture Radar "SAR" data (C-band) for monitoring agricultural frozen soils. First, investigations were conducted from simulated radar signal data using a SAR backscattering model combined with a dielectric mixing model. Then, Sentinel-1 images acquired at a study site near Paris, France were analyzed using temperature data to investigate the potential of the new Sentinel-1 SAR sensor for frozen soil mapping. The results show that the SAR backscattering coefficient decreases when the soil temperature drops below 0 °C. This decrease in signal is the most important for temperatures that ranges between 0 and -5 °C. A difference of at least 2 dB is observed between unfrozen soils and frozen soils. This difference increases under freezing condition when the temperature at the image acquisition date decreases. In addition, results show that the potential of the C-band radar signal for the discrimination of frozen soils slightly decreases when the soil moisture decreases (simulated data were used with soil moisture contents of 20 and 30 vol%). The difference between the backscattering coefficient of unfrozen soil and the backscattering coefficient of frozen soil decreases by approximately 1 dB when the soil moisture decreases from 30 to 20 vol%). Finally, the results show that both VV and VH allow a good detection of frozen soils but the sensitivity of VH is higher by approximately 1.5 dB. In conclusion, this study shows that the difference between a reference image acquired without freezing and an image acquired under freezing conditions is a good tool for detecting frozen soils.

[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-ATTOS [ADD1_IRSTEA]Équiper l'agriculture; International audience; This study evaluates the accuracy of several recent remote sensing Surface Soil Moisture (SSM) products at sites in southwestern France. The products used are Soil Moisture Active Passive "SMAP" (level 3: 36 km x 36 km, level 3 enhanced: 9 km x 9 km, and Level 2 SMAP/Sentinel-1: 1 km x 1km), Advanced Scatterometer "ASCAT" (level 2 with three spatial resolution 25 km x 25 km, 12.5 km x 12.5 km, and 1 km x 1 km), Soil Moisture and Ocean Salinity "SMOS" (SMOS INRA-CESBIO "SMOS-IC", SMOS Near-Real-Time "SMOS-NRT", SMOS Centre Aval de Traitement des Données SMOS level 3 "SMOS-CATDS", 25 km x 25 km) and Sentinel-1(S1) (25 km x 25 km, 9 km x 9 km, and 1 km x 1 km). The accuracy of SSM products was computed using in situ measurements of SSM observed at a depth of 5 cm. In situ measurements were obtained from the SMOSMANIA ThetaProbe (Time Domaine reflectometry) network (7 stations between 1 January 2016 and 30 June 2017) and additional field campaigns (near Montpellier city in France, between 1 January 2017 and 31 May 2017) in southwestern France. For our study sites, results showed that (i) the accuracy of the Level 2 SMAP/Sentinel-1 was lower than that of SMAP-36 km and SMAP-9 km; (ii) the SMAP-36 km and SMAP-9 km products provide more precise SSM estimates than SMOS products (SMOS-IC, SMOS-NRT, and SMOS-CATDS), mainly due to higher sensitivity of SMOS to RFI (Radio Frequency Interference) noise; and (iii) the accuracy of SMAP-36 km and SMAP-9 km products was similar to that of ASCAT (ASCAT-25 km, ASCAT-12.5 km and ASCAT-1 km) and S1 (S1-25 km, S1-9 km, and S1-1 km) products. The accuracy of SMAP, Sentinel-1 and ASCAT SSM products calculated using the average of statistics obtained on each site is defined by a bias of about -3.2 vol. %, RMSD (Root Mean Square Difference) about 7.6 vol. %, ubRMSD (unbiased Root Mean Square Difference) about 5.6 vol. %, and R coefficient about 0.57. For SMOS products, the station average bias, RMSD, ubRMSD, and R coefficient were about -10.6 vol. %, 12.7 vol. %, 5.9 vol. %, and 0.49, respectively.

[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [ADD1_IRSTEA]Dynamiques spatiales d'anthropisation [ADD2_IRSTEA]Adaptation des territoires au changement global; International audience; The aim of this study is to analyze the sensitivity of airborne Global Navigation Satellite System Reflectometry (GNSS-R) on soil surface and vegetation cover characteristics in agricultural areas. Airborne polarimetric GNSS-R data were acquired in the context of the GLORI'2015 campaign over two study sites in Southwest France in June and July of 2015. Ground measurements of soil surface parameters (moisture content) and vegetation characteristics (leaf area index (LAI), and vegetation height) were recorded for different types of crops (corn, sunflower, wheat, soybean, vegetable) simultaneously with the airborne GNSS-R measurements. Three GNSS-R observables (apparent reflectivity, the reflected signal-to-noise-ratio (SNR), and the polarimetric ratio (PR)) were found to be well correlated with soil moisture and a major vegetation characteristic (LAI). A tau-omega model was used to explain the dependence of the GNSS-R reflectivity on both the soil moisture and vegetation parameters. This article belongs to the Special Issue Environmental Research with Global Navigation Satellite System (GNSS).

En Côte d’Ivoire, la densité de population est passée de 8,3 hab./km² en 1950 à 71,4 hab./km² en 2015. Cette augmentation de densité de population, surtout en zone forestière, a provoqué un phénomène de saturation foncière qui a orienté les derniers fronts pionniers de café-cacao vers les espaces protégés, comme c’est le cas pour le Parc National de la Marahoué (PNM). Dans ce Parc, une enquête par questionnaire et une cartographie du territoire visant à dénombrer la population, à localiser les peuplements et à tracer les pistes à l’aide du « Global Positioning System » ont été réalisées. Parallèlement, une analyse spatio-temporelle de l’occupation du sol à l’intérieur du PNM a été effectuée. Les résultats révèlent que la dynamique de peuplement dans le PNM était depuis1955 caractérisé par une installation progressive mais lente des localités, qui s’est brusquement accélérée à partir de 2000. Ce parc est, en 2015, habité par une population de 53651 habitants (soit 52,15 hab./km²), distribuées dans 174 unités d’habitat. Avec la pression de cette population sur l’espace naturel, la forêt a laissé la place aux cultures. Leur superficie est passée de 82281 hectares en 1974 à 00 hectares en 2015., Dynamics of Settlement and Landscaped Modification in the National Park of Marahoue (Côte d\'Ivoire).In Ivory Coast, the population grew from 8.3 inh;/km² in 1950 to 71.4 inh;/km² in 2015. This increase of density of population, especially in forest area, caused land saturation that has oriented the last pioneering fronts of coffee-cocoa to the protected areas, as is the case of the National Park of Marahoué (NPM). In this park, an questionnaire survey and a mapping of the territory with the Global Positioning System were realized in order to count the population, to locate the settlements and to trace tracks. At the same time, a diachronic analysis of the land use inside the NPM was made. The results show that the dynamics of populating in the NPM was characterized since 1955 by a progressive but slow settlement of localities, which abruptly accelerated from 2000 onwards. In 2015, 53651 persons (52,15 inh./km ²) lived in this park, dispatched in 174 localities. Due to this pressure of population on the natural space, the forest disappeared for the benefit of cultures. Their area increased from 82281 hectares in 1974 to 00 hectares in 2015.

International audience; The development and improvement of methods to map agricultural land cover are currently major challenges, especially for radar images. This is due to the speckle noise nature of radar, leading to a less intensive use of radar rather than optical images. The European Space Agency Sentinel-1 constellation, which recently became operational, is a satellite system providing global coverage of Synthetic Aperture Radar (SAR) with a 6-days revisit period at a high spatial resolution of about 20 m. These data are valuable, as they provide spatial information on agricultural crops. The aim of this paper is to provide a better understanding of the capabilities of Sentinel-1 radar images for agricultural land cover mapping through the use of deep learning techniques. The analysis is carried out on multitemporal Sentinel-1 data over an area in Camargue, France. The data set was processed in order to produce an intensity radar data stack from May 2017 to September 2017. We improved this radar time series dataset by exploiting temporal filtering to reduce noise, while retaining as much as possible the fine structures present in the images. We revealed that even with classical machine learning approaches (K nearest neighbors, random forest, and support vector machines), good performance classification could be achieved with F-measure/Accuracy greater than 86% and Kappa coefficient better than 0.82. We found that the results of the two deep recurrent neural network (RNN)-based classifiers clearly outperformed the classical approaches. Finally, our analyses of the Camargue area results show that the same performance was obtained with two different RNN-based classifiers on the Rice class, which is the most dominant crop of this region, with a F-measure metric of 96%. These results thus highlight that in the near future these RNN-based techniques will play an important role in the analysis of remote sensing time series.This article belongs to the Special Issue High Resolution Image Time Series for Novel Agricultural Applications

International audience

Among the striking features specific to drylands is the discontinuous vegetation cover, discontinuous in space (e.g. steppes) and/or in time (e.g. dry savannas). Soils are more exposed than in any other environment, as a result they are prone to erosion, particularly by wind. A second consequence is soils are an important component of the land surface viewed by satellite sensors, more and more dominant the dryer the climate. Whereas optical properties of vegetation are well studied and widely used in satellite monitoring of the biosphere (i.e. vegetation indices), soil surface features are less known and rarely monitored. In an attempt to fill this gap, this short review allows to distinguish biological and mineralogical characteristics. Soil color appears to be a major parameter of the drylands soils optical properties, as illustrated by examples in the Sahara. Previously explored causes of "soil noise" in vegetation indices are confirmed as well as the way to correct it. Strategies for optimal use of optical remote sensing of drylands taking into account the soil surface are discussed in conclusion.