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    Call number: 9783319241128 (e-books)
    Description / Table of Contents: This report examines the scientific basis for the use of remotely sensed data, particularly Normalized Difference Vegetation Index (NDVI), primarily for the assessment of land degradation at different scales and for a range of applications, including resilience of agro-ecosystems. Evidence is drawn from a wide range of investigations, primarily from the scientific peer-reviewed literature but also non-journal sources. The literature review has been corroborated by interviews with leading specialists in the field. The report reviews the use of NDVI for a range of themes related to land degradation, including land cover change, drought monitoring and early warning systems, desertification processes, greening trends, soil erosion and salinization, vegetation burning and recovery after fire, biodiversity loss, and soil carbon. This SpringerBrief also discusses the limits of the use of NDVI for land degradation assessment and potential for future directions of use. A substantial body of peer-reviewed research lends unequivocal support for the use of coarse-resolution time series of NDVI data for studying vegetation dynamics at global, continental and sub-continental levels. There is compelling evidence that these data are highly correlated with biophysically meaningful vegetation characteristics such as photosynthetic capacity and primary production that are closely related to land degradation and to agroecosystem resilience.
    Type of Medium: 12
    Pages: 1 Online-Ressource (xx, 110 Seiten) , Illustrationen
    ISBN: 9783319241128 , 978-3-319-24112-8
    ISSN: 2191-5547 , 2191-5555
    Series Statement: SpringerBriefs in environmental science
    Language: English
    Note: Contents Introduction 1.1 Introduction 1.2 Land Degradation in the UNCCD and GEF 1.3 Concepts, Processes, and Scales of Land Degradation 1.4 Assessment of Resilience of Agroecosystems 2 The Potential for Assessment of Land Degradation by Remote Sensing 2.1 Normalized Difference Vegetation Index 2.2 Remote Sensing Features That Characterize NDVI- Based Assessments of Land Degradation 2.3 Other Vegetation Indices Closely Related to NDVI 2.3.1 Indices Closely Related to NDVI 2.3.2 Comparing NDVI to EVI 3 Applications of NDVI for Land Degradation Assessment 3.1 Land-Use and Land-Cover Change 3.2 Drought and Drought Early Warning 3.3 Desertification 3.4 Soil Erosion 3.5 Soil Salinization 3.6 Vegetation Burning 3.7 Soil Organic Carbon (SOC) 3.8 Biodiversity Monitoring and Conservation 3.9 Monitoring Ecosystem Resilience 4 Limits to the Use of NDVI in Land Degradation Assessment 5 Key Issues in the Use of NDVI for Land Degradation Assessment 5.1 NDVI, NPP, and Land Degradation 5.2 NDVI, RUE, and Land Degradation 5.3 Separating the Effects of Other Causes of NDVI Changes 5.4 Abrupt Changes 6 Development of Land Degradation Assessments 7 Experts’ Opinions on the Use of NDVI for Land Degradation Assessment 7.1 NDVI: Rainfall Proportionality, an Important Consideration 7.2 Building on the GLADA Assessment 8 Main Global NDVI Datasets, Databases, and Software 8.1 Main NDVI Datasets 8.2 Quality-Related Considerations 8.3 Precipitation Datasets 8.4 NDVI Software 9 Country-Level Use of Satellite Products to Detect and Map Land Degradation Processes 10 Challenges to the Use of NDVI in Land Degradation Assessments 11 Recommendations for Future Application of NDVI 11.1 In the Convention National Reporting 11.2 In a Revised GEF Resource Allocation Methodology 12 Conclusion Appendix A Inventory of Some Global and Sub-global Remote Sensing-Based Land Degradation Assessments Appendix B Use of Remote Sensing-Derived Land Productive Capacity Dynamics for the New World Atlas of Desertification (WAD) Appendix C Developments with GLADA Appendix D China’s Experiences on the Usefulness of GLADA Appendix E Main Features of Image Products from the Different Sensors Appendix F UNCCD Core Indicators for National Reporting: ICCD/COP(11)/CST/2 Appendix G Current Cost of Selected Satellite Imagery Appendix H Software for Processing Satellite Images to Develop the NDVI References
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