Titlebook: Remote Sensing of Vegetation; Along a Latitudinal Christian Julian B?dinger Book 2019 The Editor(s) (if applicable) and The Author(s), und

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Introduction,imate of the Patagonian steppe in the south. Along with this climatic gradient goes a spectacular gradient of vegetation including such disparate communities like the coastal Lomas formation of low growing shrubs and cacti on the border of the Atacama and the Valdivian temperate rainforests in south

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Conclusions & Outlook,. This was accomplished by producing extensive LULC maps using machine learning algorithms (RF & SVM) and calculating NDVI time series for a 4- year period between 2013 and 2017. The BFAST algorithm (Verbesselt et al., 2010) was applied to statistically analyze the time series catchment-wide, vegeta

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Results,e final maps are presented (chapters 5.3, 0 and 5.5). Chapter 5.6 deals with the three kinds of NDVI time series calculated as part of this study, followed by a final summarizing interpretation of the most important results.

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2625-3577 co zones of Chile? To answer this question, it is mandatory to possess fundamental knowledge about plant species habitats, occurrence and their dynamics. In his study Christian B?dinger utilizes satellite imagery in combination with machine learning to derive maps of land use and land cover (LULC) i

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Conclusions & Outlook,tion category specific and inside altitude belts to investigate the impact of climatic forcing. Furthermore, the performance of the recently released 12 m resolution TanDEM-X DEM in topographic correction and as an input in the classification variable framework was tested and compared to a Lidar DEM and the established SRTM DEM.