Remote Sensing of Vegetation

Along a Latitudinal Gradient in Chile
1. Auflage 2019
ISBN: 978-3-658-25119-2
Verlag: Springer

Buch, Englisch, 108 Seiten, Format (B × H): 148 mm x 210 mm, Gewicht: 183 g

Reihe: BestMasters

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.

Zielgruppe

Research

Autoren/Hrsg.

Bödinger, Christian Julian

Fachgebiete

• Geowissenschaften Geographie | Raumplanung Physische Geographie und Topographie
• Geowissenschaften Geographie | Raumplanung Geographie: Allgemeines, Karten & Atlanten
• Geowissenschaften Geologie Geodäsie, Kartographie, Fernerkundung
• Geowissenschaften Geologie GIS, Geoinformatik
• Geowissenschaften Geographie | Raumplanung Geodäsie, Kartographie, GIS, Fernerkundung

Inhaltsverzeichnis

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.

Über Autor(innen)

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.