Retrieving crop specific green area index from remote sensing data when the spatial resolution is close to the target field size
(2010) RAQRS’III — Location: Universitat de Valencia, Torrent, Spain (27.September.2010)
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- Abstract
- Remote sensing observations can be used to estimate biophysical variables, such as the Green Area Index (GAI), which is a key variable in the photosynthetic processes of the canopy. For crop growth monitoring, high observation frequency is mandatory, especially when anomalies due to climatic variability must be detected. Wide geographic coverage is a further requisite to monitor specific crops at regional/continental scales. Nowadays, the instruments satisfying these requirements have coarse spatial resolutions for which crop specific GAI retrieval approaches have proven difficult to apply due to the fragmented land cover of many parts of the world. This paper demonstrates how it is possible to characterize the regional crop specific GAI dynamics using MODIS imagery by controlling the degree at which the observation footprints of the coarse pixels fall within the crop-specific mask delineating the target. This control is done by filtering out less reliable GAI estimations in both the spatial and temporal dimensions using thresholds on 3 proxy variables: pixel purity, observation coverage and view zenith angle. The discrepancies in results between using MODIS or SPOT/HRV 20m imagery to estimate the median GAI of winter wheat all along growing over a 40 by 40 km study region can be reduced to an RMSE of 0.055 by choosing adequate thresholds.
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Duveiller Bogdan, G., Weiss, M., Baret, F., de Wit, A., & Defourny, P. (2010). Retrieving crop specific green area index from remote sensing data when the spatial resolution is close to the target field size. RAQRS’III, Universitat de Valencia, Torrent, Spain. https://hdl.handle.net/2078.5/200205