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OverviewHow is the vegetation distribution influencing the erosion and surface formation in the different eco 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 Bödinger utilizes satellite imagery in combination with machine learning to derive maps of land use and land cover (LULC) in four study sites along a climatic gradient and to monitor vegetation using monthly Normalized Difference Vegetation Index (NDVI) time series. The findings contribute to a better understanding of climate impacts on Chilean vegetation and serve as a basis of landscape evolution models. About the Author: Christian Bödinger holds a M.Sc. in Physical Geography from the University of Tübingen, Germany. His focus in research lies on remote sensing and image analysis for environmental applications. He is currently working for a company focusing on aquatic remote sensing. Full Product DetailsAuthor: Christian Julian BödingerPublisher: Springer Fachmedien Wiesbaden Imprint: Springer Spektrum Edition: 1st ed. 2019 Weight: 0.454kg ISBN: 9783658251192ISBN 10: 3658251190 Pages: 108 Publication Date: 05 February 2019 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand We will order this item for you from a manufactured on demand supplier. Table of ContentsTanDEM-X DEM, Sentinel Optical and Radar Data, Landsat Surface Reflectance.- Machine Learning Using SVMs and Random Forest.- Statistical Time-Series Evaluation.- Maps of Land Use and Cover (LULC).- Time-Series Showing the Impact of ENSO.ReviewsAuthor InformationChristian Bödinger holds a M.Sc. in Physical Geography from the University of Tübingen, Germany. His focus in research lies on remote sensing and image analysis for environmental applications. He is currently working for a company focusing on aquatic remote sensing. Tab Content 6Author Website:Countries AvailableAll regions |