Seo, B; Bogner, C; Koellner, T; Reineking, B: Mapping Fractional Land Use and Land Cover in a Monsoon Region: The Effects of Data Processing Options, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(9), 3941-3956 (2016), doi:10.1109/JSTARS.2016.2544802 | |
Abstract: Existing global land use/land cover (LULC) raster maps have limited spatial and thematic resolution relative to the strong heterogeneity of agricultural landscapes. One promising approach to derive more informative maps is using fractional cover instead of hard classification. Here, we evaluate the effect of three key data processing options on the performance of random forest (RF) fractional cover models for moderate resolution imaging spectroradiometer (MODIS) data in a heterogeneous agricultural landscape in a monsoon region: 1) selection of spectral predictor sets [normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), surface reflectance (SR), and all combined (Full)]; 2) time interval (8-day vs. 16-day); and 3) smoothing (no smoothing versus Savitzky–Golay (SG) filter). Model performance was assessed with spatially stratified root-mean-square error (RMSE), Spearman’s rank correlation, and |