Environmental evaluation of MODIS-derived land units | Évaluation environnementale des unités terrestres dérivées de MODIS
2017
Bisquert, Mar | Bégué, Agnès | Deshayes, Michel | Ducrot, Danielle | Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS) | Centre d'études spatiales de la biosphère (CESBIO) ; Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3) ; Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-ATTOS
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Show more [+] Less [-]English. A land stratification of the French territory had been previously performed based on time series of vegetation and texture indices. This stratification led to 300 radiometrically homogenous regions that were considered as land units (LUs). In this paper, we present a quantitative analysis of the LUs, with the aim of testing if these LUs are linked to landscape. In this sense, an evaluation of their thematic meaning in terms of environmental variables and land cover was performed. In order to achieve this, we first conducted a statistical analysis at national scale using a set of environmental variables and land cover by means of Moran's autocorrelation index and Spearman rank correlation index. Second, to analyze the quality of the boundaries between neighboring LUs, we developed a method based on the Spearman rank correlation index calculated on test areas across the boundaries. The first analyses showed that the most explanatory variables of the LUs were land cover, topography and parent material. The boundaries analysis was applied at a regional scale (Pyrenean region), and showed that 89% of the boundaries were well explained by the land cover compositions. The results obtained support the hypothesis that time series of broad resolution remote-sensing images can capture landscape identities and produce LUs maps that have an environmental and land occupation sense.
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