عنوان

Remote sensing of vegetation :

3658251204

9783658251208

3658251190

9783658251192

Remote sensing of vegetation :

[Book]

along a latitudinal gradient in Chile /

Christian Julian Bödinger.

Wiesbaden, Germany :

Springer Spektrum,

2019.

1 online resource (xxiii, 108 pages) :

illustrations

BestMasters,

2625-3577

Includes bibliographical references.

Intro; Foreword; Acknowledgements; Introduction of the Work Group; Table of Contents; List of Figures; List of Tables; Abbreviations; Abstract; Zusammenfassung; 1 Introduction; 2 State of Research; 2.1 The EarthShape Program; 2.2 Previous Work & Research Gaps; 2.3 Study Objectives; 3 Study Areas; 3.1 Pan De Azúcar; 3.2 Santa Gracia; 3.3 La Campana; 3.4 Nahuelbuta; 4 Data & Methods; 4.1 Data; 4.1.1 Sentinel Optical and Radar Data; 4.1.2 TanDEM-X DEM; 4.1.3 Training & Validation Data; 4.1.4 Landsat Surface Reflectance; 4.2 Methods; 4.2.1 Sentinel Preprocessing

4.2.2 Derivation of Terrain Variables4.2.3 GLCM; 4.2.4 Spectral Vegetation Indices; 4.2.5 Land Cover Classes; 4.2.6 Machine Learning; 4.2.7 Accuracy Assessment; 4.2.8 Time series Analysis; 5 Results; 5.1 Comparison of Topographic Corrections; 5.2 Class Separability; 5.3 Classification Accuracy; 5.3.1 Impact of the Classifier; 5.3.2 Impact of Topographic Correction and DEM; 5.4 Final LULC Maps; 5.5 Variable Importance; 5.6 Time Series Analysis; 5.6.1 Catchment-wide Analysis; 5.6.2 Height-specific Analysis; 5.6.3 Class-wise Analysis; 5.7 Summary & Interpretation of Results; 6 Discussion

6.1 Hypothesis 16.2 Hypothesis 2; 6.3 Hypothesis 3; 7 Conclusions & Outlook; References

0

8

8

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. Contents 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 Target Groups Scientists, lecturers and students in the field of geology and ecology Geoscientists and Ecologists with a focus on remote sensing 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.

Remote sensing of vegetation.

9783658251192

Geoinformatics.

Plants-- Geographic information systems-- Chile.

Geoinformatics.

Plants-- Geographic information systems.

Chile.

7

Bödinger, Christian Julian

20200823183418.0

pn

[Book]

Y