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Advances in Remote Sensing for Forest Monitoring

Objektkategorie:
Elektronische Ressource
Person/Institution:
Arellano, Paul
Pandey, Prem C.
Verlag:
John Wiley & Sons, Incorporated
Veröffentlichungsort:
Newark
Entstehungszeit:
2022
Umfang, Illustration, Format:
1 online resource (400 pages)
Sprache:
Englisch
Bereitstellende Institution:
Forschungsbibliothek Gotha
GND Explorer
Abstract:
Cover -- Title Page -- Copyright Page -- Contents -- List of Contributors -- Foreword -- Preface -- List of Abbreviations -- Editors -- Section I General Introduction to Forest Monitoring -- Chapter 1 Introduction to Forest Monitoring Using Advanced Remote Sensing Technology - An Editorial Message -- 1.1 Introduction -- 1.2 Forest Monitoring: Importance and Trends -- 1.3 Advances in Remote Sensing Technology for Forest Monitoring -- 1.4 Summary -- References -- Chapter 2 Geospatial Perspectives of Sustainable Forest Management to Enhance Ecosystem Services and Livelihood Security -- 2.1 Introduction and Background -- 2.2 Major Ecological Disturbances of Forests -- 2.2.1 Livelihood Dependencies -- 2.3 Forest Fires -- 2.4 Invasive Plant Species (IPS) -- 2.5 Climate Change -- 2.6 Forest Ecosystem Services (FESs) -- 2.7 Sustainable Uses of Forests and Their Contributions to Livelihood Security -- 2.8 Landscape Based Approach (LbA) and Ecosystem-Based Approach (EbA) of Sustainable Forests Management (SFM) -- 2.9 Conclusions -- References -- Section II Forest Parameters - Biochemical and Biophysical Parameters -- Chapter 3 Distinguishing Carotene and Xanthophyll Contents in the Leaves of Riparian Forest Species by Applying Machine Learning Algorithms to Field Reflectance Data -- 3.1 Introduction -- 3.1.1 Chapter Overview -- 3.1.2 Threats to Riparian Forests -- 3.1.3 Remote Sensing of Riparian Forests -- 3.1.4 Implication of Carotenoids in Plant Stress -- 3.1.5 Advances in Carotenoid Retrieval Using Reflectance Spectroscopy -- 3.1.6 Applying Machine Learning to Reflectance Spectroscopy -- 3.2 Study Area -- 3.3 Data -- 3.3.1 Leaf Sampling and Analysis -- 3.3.2 Reflectance Measurements -- 3.4 Methodology -- 3.4.1 Preprocessing of Reflectance Data -- 3.4.2 ML Algorithms -- 3.4.3 Carotenoid Prediction -- 3.5 Results -- 3.5.1 Leaf Carotenoid Contents.
Objekttext:
Description based on publisher supplied metadata and other sources

Zugriff und Nutzungsmöglichkeiten

Universität Erfurt
Forschungsbibliothek Gotha
Schloss Friedenstein
Schlossplatz 1
99867 Gotha
+49 361 737-5540
bibliothek.gotha(at)uni-erfurt.de
Datensatz angelegt am:
2023-04-12
Zuletzt geändert am:
2023-01-30
In Portal übernommen am:
2023-04-12