Note: Förderkennzeichen BMBF 031B0516F , Verbundnummer 01184804 , Literaturverzeichnis: Seite 9-10 , Unterschiede zwischen dem gedruckten Dokument und der elektronischen Ressource können nicht ausgeschlossen werden

Note: Description based upon print version of record , Tentative with international authorship from DFD, IMF, ESA, NASA, USGS etcSnow dynamics in Europe over the past 30 years -- Dynamic of net primary productivity in Europe -- Biomass development in Kasachsthan -- Land degradation in South Africa -- Land cover and land use change in central Asia -- Vegetation dynamics in western Africa -- Dynamics of soil moisture in the Mekong Basin -- Temperature trends in the Mekong Basin -- Landcover dynamics during the past decade in the Mekong Basin -- Coastal zone dynamics of the yellow river delta -- Landcover change in the yellow river delta -- Flood dynamics in the Mekong delta.

Note: Förderkennzeichen BMBF 033L040AN. - Verbund-Nummer 01051714 , Laufzeit des Vorhabens: 01.10.2010-30.09.2013, kostenneutral verlängert bis 28.02.2014 , Enthält die Teilvorhaben: "Arbeitspaket 1000: Project management, Projektmanagement", "Teilvorhaben Arbeitspaket 3000: Information System Design, Design des Informationssystems", "Unterauftrag der UNU-EHS: Pesticide modelling and monitoring, Pestizidmodellierung und -monitoring, vulnerability assessment, Verwundbarkeitsforschung" und "Unterauftrag der TU Wien: Remote sensing of soil moisture, Fernerkundung zur Ermittlung von Bodenfeuchteparametern" , Unterschiede zwischen dem gedruckten Dokument und der elektronischen Ressource können nicht ausgeschlossen werden , Text deutsch und englisch

Note: Förderkennzeichen BMBF 0330777A. - Verbund-Nr. 01051714 , Unterschiede zwischen dem gedruckten Dokument und der elektronischen Ressource können nicht ausgeschlossen werden , Auch als gedr. Ausg. vorhanden , Systemvoraussetzungen: Acrobat reader. , Text teilw. dt., teilw. engl.

Note: Förderkennzeichen BMBF 0330490B. - Verbund-Nr. 01023038 , Unterschiede zwischen der elektronischen Ressource und dem gedruckten Dokument können nicht ausgeschlossen werden , Auch als gedr. Ausg. vorhanden , Systemvoraussetzungen: Acrobat reader.

Note: Intro -- Foreword -- Acknowledgements -- Contents -- Contributors -- Abbreviations -- Chapter 1: Remote Sensing Time Series Revealing Land Surface Dynamics: Status Quo and the Pathway Ahead -- 1.1 Introduction -- 1.2 Earth Observation Sensors for Time Series Analysis -- 1.3 Remote Sensing Time Series Variables -- 1.4 Remote Sensing Time Series Components and Features -- 1.5 Example Applications -- 1.6 Challenges for Remote Sensing Based Time Series Analysis -- 1.7 Current Developments and Upcoming Opportunities -- References -- Chapter 2: Time Series Analyses in a New Era of Optical Satellite Data -- 2.1 Introduction -- 2.2 Process Dynamics and Time Series Analysis Requirements -- 2.2.1 Variables Used in Time Series Analysis -- 2.2.2 Implementing Time Series Analyses -- 2.3 Time Series Analysis Examples -- 2.3.1 Monitoring Tropical Deforestation -- 2.3.2 Mapping Pan-Carpathian Agricultural Land Use Change -- 2.4 Challenges and Opportunities -- References -- Chapter 3: Calibration and Pre-processing of a Multi-decadal AVHRR Time Series -- 3.1 Introduction -- 3.2 The Advanced Very High Resolution Radiometer (AVHRR) Instrument Series -- 3.2.1 Overview of the NOAA AVHRR Series -- 3.2.2 Calibration and System Correction Procedures -- 3.2.2.1 Calibration and System Correction of the Reflective Channels -- 3.2.2.2 Calibration and System Correction of the Thermal Channels -- 3.2.2.3 Corrections of Satellite Orbit Changes and Related Effects -- 3.3 DLR´s AVHRR Pre-processing Chain -- 3.4 Influence of Calibration and Re-calibration -- 3.4.1 Calibration Over Time -- 3.4.2 Impact on Generated L1b Products -- 3.5 Towards Data Harmonization and Consensus Calibration -- 3.6 Conclusions -- References -- Chapter 4: Analysis of Snow Cover Time Series - Opportunities and Techniques -- 4.1 Introduction -- 4.2 Remote Sensing of Snow. , 4.2.1 Snow Cover Mapping from Space - Physical Background and Limitations -- 4.2.2 Processing of Snow Cover Time Series -- 4.2.2.1 Estimation of Snow Cover Status Below Clouds -- 4.2.2.2 Generation of Snow Cover Parameters From Cloud-Cleared Snow Cover Time Series -- 4.3 Analysis of Snow Cover Time Series -- 4.4 Summary and Conclusions -- References -- Chapter 5: Global WaterPack: Intra-annual Assessment of Spatio-Temporal Variability of Inland Water Bodies -- 5.1 Introduction -- 5.2 Study Area and Materials -- 5.2.1 Study Area -- 5.2.2 Data -- 5.2.2.1 Data for Water Detection -- 5.2.2.2 Ancillary Data -- 5.3 Methodology -- 5.3.1 Pre-processing -- 5.3.2 Water Classification Based on Dynamic Thresholding -- 5.3.3 Accuracy Assessment -- 5.4 Results -- 5.4.1 Temporal Development of Water Bodies -- 5.4.2 Evaluation of Accuracy -- 5.5 Time-Series of Water Bodies -- 5.6 Conclusion -- References -- Chapter 6: Analysing a 13 Years MODIS Land Surface Temperature Time Series in the Mekong Basin -- 6.1 Introduction -- 6.2 Study Region -- 6.3 Data and Methodology -- 6.4 Quantitative Analysis of the LST_8day Dataset -- 6.4.1 Analysis of LST_8day Time Series -- 6.4.2 Analysis of Deviations from the 13-Year Mean -- 6.4.3 Analysis of the Variability -- 6.5 Influencing Factors -- 6.6 Discussion and Summary -- 6.7 Conclusions -- References -- Chapter 7: TIMESAT: A Software Package for Time-Series Processing and Assessment of Vegetation Dynamics -- 7.1 Introduction -- 7.2 Handling Remotely Sensed Time-Series Data - Assumptions and Some General Problems -- 7.3 Processing Considerations and Common Methods -- 7.4 The TIMESAT Approach -- 7.4.1 Processing Principles -- 7.4.2 Applications of TIMESAT -- 7.5 Future Perspectives -- References -- Chapter 8: Assessment of Vegetation Trends in Drylands from Time Series of Earth Observation Data -- 8.1 Introduction. , 8.2 Detection of Dryland Vegetation Change from Space -- 8.2.1 Towards EO-Based Monitoring of Vegetation Productivity -- 8.2.2 Building Consistent Long-Term Time Series -- 8.3 Greening or Browning of Global Drylands -- 8.3.1 Trend Estimation -- 8.3.2 Global Trends in Vegetation Greenness -- 8.3.3 Refining Vegetation Metrics for Long-Term Trends -- 8.4 Assessing Abrupt Changes in Vegetation Cover and Productivity: Beyond Linear Trends Analysis -- 8.5 The Importance of Spatial Resolution for Vegetation Trend Analysis -- 8.5.1 Downscaling Vegetation Dynamics by Fusing Multi-temporal MODIS and Landsat Data -- 8.6 Summary -- References -- Chapter 9: Assessing Drivers of Vegetation Changes in Drylands from Time Series of Earth Observation Data -- 9.1 Introduction -- 9.2 Inferring Causes for Observed Changes -- 9.2.1 Precipitation Controlling Observed Vegetation Changes in the Sahel -- 9.2.2 Assessing Drivers of Observed Changes Based on Rain-Use Efficiency -- 9.2.3 Assessing Drivers of Observed Changes Using the Residual Trends Productivity Approach -- 9.2.4 Limitations/Challenges for RUE and RESTREND Approaches -- 9.3 Assessment of the Roles of Climate on Anomalies of Dryland Vegetation Productivity -- 9.3.1 Combining Dynamic Global Vegetation Models and EO Data -- 9.3.2 Sea Surface Temperature and Vegetation Productivity Teleconnections -- 9.4 Summary -- References -- Chapter 10: Land Surface Phenology in a West African Savanna: Impact of Land Use, Land Cover and Fire -- 10.1 Introduction -- 10.2 Study Region -- 10.3 Material and Methods -- 10.3.1 Time Series of Land Surface Phenology -- 10.3.2 Land Cover and Land Use Changes -- 10.3.3 Time Series of Burned Areas -- 10.4 Results -- 10.4.1 Land Cover Types and Land Use History -- 10.4.2 Spatio-Temporal Patterns of Fires -- 10.5 Spatio-Temporal Patterns of Phenology. , 10.5.1 Multi-annual Average Patterns of Phenology -- 10.5.2 Effects of Fire Frequency on Phenological Characteristics -- 10.5.3 Effects of Fire Events on Phenological Characteristics -- 10.6 Discussion and Conclusions -- References -- Chapter 11: Assessing Rainfall-EVI Relationships in the Okavango Catchment Employing MODIS Time Series Data and Distributed La... -- 11.1 Introduction -- 11.2 Material and Methods -- 11.2.1 Study Area -- 11.2.2 Data -- 11.2.2.1 Enhanced Vegetation Index (EVI) -- 11.2.2.2 Precipitation and Actual Evaporation -- 11.2.3 Methods -- 11.2.3.1 Data Pre-processing -- 11.2.3.2 Distributed Lag Models (DLM) -- 11.3 Results and Discussion -- 11.3.1 The General Significant Rainfall-ANPP Relationship in the Okavango Catchment -- 11.3.2 Temporal Rainfall-ANPP Relationships at Specific Lags -- 11.4 Conclusion -- References -- Chapter 12: Land Degradation in South Africa - A Degradation Index Derived from 10 Years of Net Primary Production Data -- 12.1 Introduction -- 12.2 The Study Area of Southern Africa -- 12.3 Method -- 12.3.1 NPP Time-Series from the Vegetation Model BETHY/DLR -- 12.3.2 NPP Variations from Annual Sums -- 12.3.3 Anomalies in Climatic Time-Series -- 12.3.4 The Degradation Index -- 12.4 Results -- 12.5 Discussion -- 12.5.1 Namibia -- 12.5.2 Botswana -- 12.5.3 Zimbabwe -- 12.6 Conclusion -- References -- Chapter 13: Investigating Fourteen Years of Net Primary Productivity Based on Remote Sensing Data for China -- 13.1 Introduction -- 13.2 Data and Methods -- 13.2.1 Study Area -- 13.2.2 The Model BETHY/DLR -- 13.3 Results and Discussion of NPP for China -- 13.3.1 Spatial NPP Distribution -- 13.3.2 Monthly NPP Patterns -- 13.3.3 Interannual NPP Variability -- 13.3.4 Impact of Urban Sprawl Around Shanghai -- 13.3.5 Monitoring Forest Disturbance in North China -- 13.4 Conclusions -- References. , Chapter 14: The Utility of Landsat Data for Global Long Term Terrestrial Monitoring -- 14.1 Introduction -- 14.2 Web Enabled Landsat Data (WELD) Products -- 14.2.1 Current WELD Products -- 14.2.2 Planned Global WELD Products -- 14.3 Landsat Time Series Applications and Research That Are Developing Rapidly in Response to the Opening of the Landsat Archi... -- 14.3.1 Phenology Monitoring -- 14.3.2 Land Cover Change Monitoring -- 14.4 Prospectives for Landsat Time Series Monitoring -- 14.5 Summary -- References -- Chapter 15: Forest Cover Dynamics During Massive Ownership Changes - Annual Disturbance Mapping Using Annual Landsat Time-Seri... -- 15.1 Introduction -- 15.2 Data and Methods -- 15.2.1 Study Region -- 15.2.2 Landsat Imagery -- 15.2.3 Preprocessing -- 15.2.4 Time Series Segmentation and Fitting -- 15.2.5 Disturbance, Recovery and Growth Mapping -- 15.2.6 Validation -- 15.3 Results -- 15.4 Discussion and Conclusion -- References -- Chapter 16: Radar Time Series for Land Cover and Forest Mapping -- 16.1 Introduction -- 16.2 Radar Time Series as a Tool for Land Monitoring -- 16.2.1 Time Series for Information Retrieval About Land Cover State -- 16.2.2 Time Series as Source for Statistical Land Surface Indicators -- 16.2.3 Time Series for Choosing the Right Scene(s) -- 16.3 Case Studies -- 16.3.1 Land Cover Classification Using Multi-temporal C-Band Data -- 16.3.2 Forest Mapping Using Radar Time Series -- 16.3.2.1 DRAGON-1 Case Study -- 16.3.2.2 BIOMASAR Case Study -- 16.3.3 Forest Cover Change with Radar Time Series -- 16.3.3.1 DRAGON-2 Case Study: Merging Space and Time -- 16.3.3.2 ZAPÁS Case Study - Operational Radar-Optical Synergy -- 16.3.4 Special Seasonal Case: Savanna Systems -- 16.4 Perspectives -- References -- Chapter 17: Investigating Radar Time Series for Hydrological Characterisation in the Lower Mekong Basin -- 17.1 Introduction. , 17.1.1 Hydrological Information.

Note: Intro -- The Mekong Delta System -- Foreword -- Acknowledgements -- Contents -- Contributors -- Part I: Deltas Under Change -- Part II: Water and Development in the Mekong Delta -- Part III: Water Resources and Related Risks -- Part IV: Water and Environment -- Part V: Water Knowledge and Information -- Index.