Remote Sensing of Vegetation (eBook)

Along a Latitudinal Gradient in Chile

Christian Julian Bödinger (Autor)

eBook Download: PDF

2019 | 1st ed. 2019
XXIII, 108 Seiten
Springer Fachmedien Wiesbaden (Verlag)
978-3-658-25120-8 (ISBN)

Infos

How 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.

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.

Inhalt

TanDEM-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.

Produkt-Details

• Erscheint lt. Verlag: 24.1.2019
• Reihe/Serie: BestMasters
• Zusatzinfo: XXIII, 108 p. 1 illus.
• Verlagsort: Wiesbaden
• Sprache: englisch
• Themenwelt: Naturwissenschaften ► Geowissenschaften ► Geografie / Kartografie
• Schlagworte: Chile • ecozones of Chile • Environmental Geography • Latitudinal gradient • LULC • machine learning • maps of land use and land cover • NDVI • Normalized Difference Vegetation Index • Remote Sensing • Remote Sensing/Photogrammetry • Satellite Imagery • Time Series Analysis • Vegetation monitoring
• ISBN-10: 3-658-25120-4 / 3658251204
• ISBN-13: 978-3-658-25120-8 / 9783658251208