MODIS based continuous fields of tree cover using generalized linear models

Knowledge about the land cover over huge area is important for monitoring and modeling of ecological and environmental processes. Considerable efforts have recently resulted in the development of global continuous fields for different land cover types at small spatial scales based on NOAA-AVHRR and TERRA-MODIS data. Researchers have applied a range of techniques to depict the sub-pixel fraction of land cover types from remotely sensed data. As a result, such products have a high potential to accurately monitor land cover change overtime. In this study, a methodology is described for deriving and optimizing continuous fields of tree cover for complex topography at the regional scale of the European Alps using generalized linear models (GLM) which are commonly used in ecological research. The presented study is carried out in Switzerland a central part of the European Alps with a complex topography and a highly fragmented landscape. MODIS data (MOD09) at a spatial resolution of 500 m are used as explanatory variables and Landsat TM based data of fractional tree-cover are used as target variable to calibrate the GLM. For purpose of evaluation we calculated different accuracy measures of the resulting continuous fields of tree cover, and we compared the model output with two available global data sets: (1) TERRA-MODIS Vegetation Continuous Fields product (MOD44), and (2) the NOAA-AVHRR vegetation continuous fields. Our regionally optimized GLM model produces higher accuracies compared to MOD44- and AVHRR-products. The GLM model achieve an average mean absolute error (MAE) of 0.093, while the average MAE of the MOD44 and the AVHRR products are 0.205 and 0.200, respectively. We conclude that GLM's are appropriate for deriving fractional tree cover for complex topography at the scale of the European Alps. Regional calibrations of vegetation continuous fields may offer significantly improved predictions compared to globally calibrated models. Such regionally calibrated and optimized models may serve as valuable tools for regional monitoring of land cover pattern and its temporal change.