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6 October 2011 Interception modeling with vegetation time series derived from Landsat TM data
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Abstract
Rainfall interception by the vegetation may constitute a significant fraction in the water budget at local and watershed scales, especially in Mediterranean areas. Different approaches can be found to model locally the interception fraction, but a distributed analysis requires time series of vegetation along the watershed for the study period, which includes both type of vegetation and ground cover fraction. In heterogeneous watersheds, remote sensing is usually the only viable alternative to characterize medium to large size areas, but the high number of scenes necessary to capture the temporal variability during long periods, together with the sometimes extreme scarcity of data during the wet season, make it necessary to deal with a limited number of images and interpolate vegetation maps between consecutive dates. This work presents an interception model for heterogeneous watersheds which combines an interception continuous simulation derived from Gash model and their derivations, and a time series of vegetation cover fraction and type from Landsat TM data and vegetation inventories. A mountainous watershed in Southern Spain where a physical hydrological modelling had been previously calibrated was selected for this study. The dominant species distribution and their relevant characteristics regarding the interception process were analyzed from literature and digital cartography; the evolution of the vegetation cover fraction along the watershed during the study period (2002-2005) was produced by the application of a NDVI analysis on the available scenes of Landsat TM images. This model was further calibrated by field data collected in selected areas in the watershed.
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M. J. Polo, A. Díaz-Gutiérrez, and M. P. González-Dugo "Interception modeling with vegetation time series derived from Landsat TM data", Proc. SPIE 8174, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII, 81740B (6 October 2011); https://doi.org/10.1117/12.898144
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