Arthur is one of the #DigitAg labelled PhDs
Cropping system monitoring using satellite time series and spatial modeling : study case in Madagascar Highlands
- Start Date: October 2017
- University: AgroParisTech
- PhD School: GAIA
- Field(s): Geomatics, Remote sensing, Spatial Modeling
- Doctoral Thesis Advisor: Agnès Bégué, Cirad
- Co-supervisors : Valentine Lebourgeois, Danny Lo-Seen, Mathieu Castets (Cirad TETIS)
- Funding: Cirad – CNES
- Linked Project: SAMSAM (Satellite time-series Analysus and Modeling for Small Agriculture Mapping)
- #DigitAg: Axis – Challenge
Keywords: Land use, remote sensing, spatial modeling, crop practices
In the coming decades, the combination of climate change and demographic and environmental pressures is likely to have significant impacts on livelihoods and food systems. Within developing countries, some of these impacts will be greater, especially in family farming systems where rainfed agriculture is a dominant but low-adaptive economic activity. Increasing the food security of these areas in a sustainable way requires better monitoring of cropping systems and their production.
In Madagascar, in 2010, 68% of households lived in agriculture in a context of high economic and political instability while being exposed to extreme weather events such as cyclones or droughts. Located in the center of Madagascar, in the Highlands, the Vakinankaratra region is characterized by a very high population density and by one of the most intensive agricultural production in the country. In this region, the agricultural area is defined by a very small average field size (1.05 ha for the region and between 0.10 and 0.5 ha for the Ankaratra) with a high heterogeneity within the area, strong fragmentation of the landscape, the presence of natural vegetation between fields and a synchronization of the phenologies of agro-systems and eco-systems. Mapping and characterization of this mainly family-based agriculture are therefore complex to perform using satellite data, mainly because of the size of the fields (often less than that of the pixel) and the high cloudiness during the rainy season, which corresponds to the period of growth. Recently launched, the Sentinel-2 mission has strong potential to improve the observation of this type of agricultural space thanks to the high spatial resolution of these images (10 m), and its frequency of revisit of 5 days. In order to prepare it, projects simulated these data (Sentinel2-Agriculture, TOSCA Syst-Cult Project) and used set-theoretic classification methods using machine learning. The results of these studies show good results for intensive agriculture but which are still improvable for the tropical zones of small agriculture.
This Ph.D. aims to develop an original approach coupling remote sensing and spatial dynamics modeling using the Ocelet (www.ocelet.fr) modeling language in order to improve the characterization of Malagasy small family farming areas. The approach is based on the joint use of remote sensing data with high spatial resolution (reflecting the structure of the objects composing the landscape) and temporal data (reflecting their functioning) and formalized spatio-temporal rules based on surveys of the strategies and practices of farmers in the region. This approach is therefore multidisciplinary and systemic and will make possible to associate heterogeneous data (satellite, environmental, socio-economic, etc.) and to test the complementarity between the fields of remote sensing and modeling.
Crespin-Boucaud, A.; Lebourgeois, V.; Lo Seen, D.; Castets, M.; Bégué, A. Agriculturally consistent mappingof smallholder farming systems using remote sensing and spatial modelling, ISPRS—Int. Arch. Photogramm.Remote Sens. Spat. Inf. Sci.2020,XLII-3/W11, 35–42
Bélières Jean-François (dir.), Dianah Randriamitantsoa, Harimandranto Randrianirina,Noroseheno Ralisoa, Arthur Crespin-Boucaud, 2020, Étude chaîne de valeur pomme de terre.Partie 1: Importance de la culture de la pomme de terre pour les exploitations agricoles etrentabilité de la production de plants de semence et de consommations. CASEF, MAEP
Contact: arthur.crespin-boucaud [AT] cirad.fr – +33 467558645