A5075153591- Agriculture and Rural Development Research
- Land Use and Ecosystem Services
- Remote Sensing in Agriculture
- African Botany and Ecology Studies
- French Urban and Social Studies
- Remote Sensing and LiDAR Applications
- Soil and Land Suitability Analysis
- Remote Sensing and Land Use
- Remote-Sensing Image Classification
- Geochemistry and Geologic Mapping
- Urban Agriculture and Sustainability
- Cocoa and Sweet Potato Agronomy
- Forest ecology and management
- Island Studies and Pacific Affairs
- Geographic Information Systems Studies
- Post-Soviet Geopolitical Dynamics
- Animal Ecology and Behavior Studies
- Smart Agriculture and AI
- Russia and Soviet political economy
- Hydrocarbon exploration and reservoir analysis
- Rural Development and Agriculture
- Species Distribution and Climate Change
- Vector-borne infectious diseases
- Bat Biology and Ecology Studies
- Educational Tools and Methods
AgroParisTech
2020-2024
Université de Montpellier
2020-2024
Centre National de la Recherche Scientifique
2020-2024
Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement
2020-2024
Territoires, Environnement, Télédétection et Information Spatiale
2012-2024
Centre de Coopération Internationale en Recherche Agronomique pour le Développement
2012-2024
Territoires
2012-2024
Forests and Societies
2014-2021
Peuplements végétaux et bioagresseurs en milieu tropical
2020
Sorbonne Université
2011
Sentinel-2 images are expected to improve global crop monitoring even in challenging tropical small agricultural systems that characterized by high intra- and inter-field spatial variability where satellite observations disturbed the presence of clouds. To overcome these constraints, we analyzed optimized performance a combined Random Forest (RF) classifier/object-based approach applied it multisource data produce land use maps smallholder zone Madagascar at five different nomenclature...
Accurate cropland information is of paramount importance for crop monitoring. This study compares five existing mapping methodologies over contrasting Joint Experiment Crop Assessment and Monitoring (JECAM) sites medium to large average field size using the time series 7-day 250 m Moderate Resolution Imaging Spectroradiometer (MODIS) mean composites (red near-infrared channels). Different strategies were devised assess accuracy classification methods: confusion matrices derived indicators...
Modern Earth Observation systems provide remote sensing data at different temporal and spatial resolutions. Among all the available mission, today Sentinel-2 program supplies high (every five days) resolution (HSR) (10 m) images that can be useful to monitor land cover dynamics. On other hand, very HSR (VHSR) imagery is still essential figure out mapping characterized by fine patterns. Understanding how jointly leverage these complementary sources in an efficient way when dealing with a...
Developing better agricultural monitoring capabilities based on Earth Observation data is critical for strengthening food production information and market transparency. The Sentinel-2 mission has the optimal capacity regional to global agriculture in terms of resolution (10–20 meter), revisit frequency (five days) coverage (global). In this context, European Space Agency launched 2014 “Sentinel2 Agriculture” project, which aims prepare exploitation through development open source...
Summary While the effects of deforestation and habitat fragmentation on parasite prevalence or richness are well investigated, host–parasite networks still understudied despite their importance in understanding mechanisms these major disturbances. Because may negatively impact species occupancy, abundance co‐occurrence, we predict a link between spatiotemporal changes architecture networks. For this, used an extensive data set 16 rodent 29 helminth from seven localities South‐East Asia. We...
Summary We tested how habitat structure and fragmentation affect the spatial distribution of common murine rodents inhabiting human‐dominated landscapes in South‐East Asia. The patterns observed for each rodent species were then used to assess changes may potentially risk several major rodent‐borne diseases. For this analysis, we an extensive geo‐referenced data base containing details trapped from seven sites Thailand, Cambodia Lao PDR . also developed land‐cover layers site. Results...
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 subtropical areas due to diversity management systems seasonal cloud cover variations. This work presents supervised object-based classifications year at 2-month time-steps a heterogeneous region 12,000 km2 Sao Paulo Brazil. Different methods remote-sensing datasets were...
Predicting habitats prone to favor disease transmission is challenging due confounding information on habitats, reservoirs, and diseases. Comparative analysis, which aims at investigating ecological evolutionary patterns among species, a tool that may help. The emergence of zoonotic pathogens major health concern closely linked habitat modifications by human activities. Risk assessment requires better knowledge the interactions between hosts, parasites, landscape.We used from field spatial...
We here present a reference database and three land use maps produced in 2017 over the Reunion island using machine learning based methodology. These are result of satellite image analysis performed Moringa cover processing chain developed our laboratory. The input dataset for map production consists single very high spatial resolution Pleiades images, time series Sentinel-2 Landsat-8 Digital Terrain Model (DTM) aforementioned database. adopts an object approach: provides accuracy with...
Abstract. The availability of crop type reference datasets for satellite image classification is very limited complex agricultural systems as observed in developing and emerging countries. Indeed, land use dynamic, censuses are often poorly georeferenced types difficult to interpret directly from imagery. In this paper, we present a database made 24 collected standardized manner over nine sites within the framework international JECAM (Joint Experiment Crop Assessment Monitoring) initiative;...
Canopy height is a fundamental parameter for describing forest ecosystems. GEDI spaceborne LiDAR system that was designed to measure vegetation's vertical structure at global scale. This study evaluates the accuracy of GEDI-derived canopy estimates over complex tropical forests in Mayotte Island (Overseas France) characterized by moderate and biomass levels as well relatively steep terrain. The influence signal environmental parameters (canopy height, beam sensitivity slope) on assessed....
Extensive research studies have been conductedin recent years to exploit the complementarity among multi-sensor (or multi-modal) remote sensing data for prominentapplications such as land cover mapping. In order make a step further with respect previous which investigate multi-temporal SAR and optical or multi-temporal/multi-scale combinations, here we propose deep learning framework that simultaneously combine all these input sources, specifically SAR/optical fine scale information. Our...
In France, in the peri-urban context, urban sprawl dynamics are particularly strong with huge population growth as well a land crisis. The increase and spreading of built-up areas from city centre towards periphery takes place to detriment natural agricultural spaces. conversion potential is all more worrying it usually irreversible. French Ministry Agriculture therefore needs reliable repeatable spatial-temporal methods locate quantify loss at both local national scales. main objective this...
High urbanization rates in cities lead to rapid changes land uses, particularly southern where population growth is fast. Urban and peri-urban agricultural often seen as available space for the city expand, but at same time, provides many benefits pertaining food, employment, eco-services. In this context, there an urgent need provide spatial information support planning complex urban systems. The challenge integrate analysis of agriculture land-cover classes, their functional patterns. This...
Land Use and Cover (LULC) maps are important tools for environmental planning social-ecological modeling, as they provide critical information evaluating risks, managing natural resources, facilitating effective decision-making. This study aimed to generate a very high spatial resolution (0.5 m) detailed (21 classes) LULC map the greater Mariño watershed (Peru) in 2019, using MORINGA processing chain. new method mapping consisted supervised object-based classification, random forest...
Accurate mapping of land-cover diversity within riparian areas at a regional scale is major challenge for better understanding the influence landscapes and related natural anthropogenic pressures on river ecological status. As structure (composition spatial organization) area land cover (RALC) generally not accessible using moderate-scale satellite imagery, finer resolution imagery specific techniques are needed. For this purpose, we developed classification procedure based multiscale...
Dans de nombreuses agglomérations du Sud, l’étalement urbain se poursuit au détriment des terres agricoles. Cependant, peu travaux qualifient et quantifient les recompositions paysagères qu’engendrent la croissance urbaine sur espaces bâtis L’agglomération d’Antananarivo, capitale Madagascar, est encore fortement agricole, mais connait une urbanisation plus en forte. ce contexte, cet article vise à qualifier, quantifier spatialiser dynamiques d’urbanisation agricoles l’échelle cette...
Modern Earth Observation systems provide sensing data at different temporal and spatial resolutions. Among optical sensors, today the Sentinel-2 program supplies high-resolution (every 5 days) high resolution (10m) images that can be useful to monitor land cover dynamics. On other hand, Very High Spatial Resolution (VHSR) are still an essential tool figure out mapping characterized by fine patterns. Understand how efficiently leverage these complementary sources of information together deal...
We describe a reference spatial database and four land use maps of Antananarivo city produced over 2017 year using methodology combining machine learning object based image analysis (OBIA). These are by processing satellite images the Moringa cover chain developed in our laboratory. single very high resolution (VHSR) Pleiades image, time series Sentinel-2 Landsat-8 images, Digital Terrain Model (DTM) aforementioned database. According to workflow, is used generate suitable layer at VHSR...
Abstract. The availability of crop type reference datasets for satellite image classification is very limited complex agricultural systems as observed in developing and emerging countries. Indeed, land use dynamic, census are often poorly georeferenced, types difficult to photo-interpret directly from imagery. In this paper, we present nine collected a standardized manner between 2013 2020 seven tropical subtropical countries within the framework international JECAM (Joint Experiment Crop...
Alors que l’économie circulaire (EC) comme nouveau paradigme économique et sociétal émerge, la place du secteur agricole dans les initiatives d’accroissement de circularité territoires est questionnée. Ce questionnement d’autant plus pertinent un contexte insulaire celui La Réunion, où enjeux d’autonomie alimentaire énergétique sont majeurs. De 2017 à 2020, projet Recherche Développement intitulé GABiR (Gestion Agricole des Biomasses sur l’île Réunion) a mobilisé acteurs issus Développement,...