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E-grāmata: Geospatial Technologies for Land Degradation Assessment and Management

(Jawaharlal Nehru Technological University, Hyderabad, India)
  • Formāts: 429 pages
  • Izdošanas datums: 17-Oct-2018
  • Izdevniecība: CRC Press Inc
  • Valoda: eng
  • ISBN-13: 9781498749619
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Geospatial Technologies for Land Degradation Assessment and ManagementPalielināt
  • Formāts: 429 pages
  • Izdošanas datums: 17-Oct-2018
  • Izdevniecība: CRC Press Inc
  • Valoda: eng
  • ISBN-13: 9781498749619
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The constant growth of the worlds population and the decline of the availability of land and soil resources are global concerns for food security. Other concerns are the decrease in productivity and delivery of essential ecosystems services because of the decline of soil quality and health by a range of degradation processes. Key soil properties like soil bulk density, organic carbon concentration, plant available water capacity, infiltration rate, air porosity at field moisture capacity, and nutrient reserves, are crucial properties for soil functionality which refers to the capacity of soil to perform numerous functions. These functions are difficult to measure directly and are estimated through indices of soil quality and soil health. Soil degradation, its extent and severity, can also be estimated by assessing indices of soil quality and health.

"Geospatial Technology for Land Degradation Assessment and Management" uses satellite imagery and remote sensing technologies to measure landscape parameters and terrain attributes. Remote sensing and geospatial technologies are important tools in assessing the extent and the severity of land and soil degradation, their temporal changes, and geospatial distribution in a timely and cost-effective manner.

The knowledge presented in the book by Dr. R.S. Dwivedi shows how remote sensing data can be utilized for inventorying, assessing, and monitoring affected ecosystems and how this information can be integrated in the models of different local settings. Through many land degradations studies, land managers, researchers, and policymakers will find practical applications of geospatial technologies and future challenges. The information presented is also relevant to advancing the Sustainable Development Goals of the United Nations towards global food security.
Foreword xvii
Preface xix
Acknowledgments xxi
Author xxiii
1 An Introduction to Geospatial Technology 1(30)
1.1 Introduction
1(1)
1.1.1 Geospatial Technology
1(1)
1.2 History of Remote Sensing
2(1)
1.3 Electromagnetic Radiation
3(3)
1.3.1 Particle Model
3(1)
1.3.2 Wave Model
3(1)
1.3.3 Amplitude
4(1)
1.3.4 Phase
4(1)
1.3.5 Polarization
4(2)
1.4 Electromagnetic Spectrum
6(1)
1.4.1 The Ultraviolet Spectrum
6(1)
1.4.2 The Visible Spectrum
6(1)
1.4.3 The Infrared Spectrum
6(1)
1.4.4 The Microwave Spectrum
7(1)
1.5 Energy-Matter Interactions in the Atmosphere
7(2)
1.5.1 Scattering
8(1)
1.5.1.1 Rayleigh Scattering
8(1)
1.5.1.2 Mie Scattering
8(1)
1.5.1.3 Nonselective Scattering
8(1)
1.5.2 Absorption
8(1)
1.5.3 Emission
9(1)
1.6 Atmospheric Windows
9(2)
1.6.1 Atmospheric Windows in Optical Region
9(1)
1.6.2 Atmospheric Windows in Microwave Region
10(1)
1.7 Energy-Matter Interactions with the Terrain
11(2)
1.7.1 Reflection Mechanism
11(1)
1.7.2 Transmission Mechanism
12(1)
1.7.3 Absorption Mechanism
12(1)
1.7.4 Emission Mechanism
13(1)
1.8 EMR Laws
13(3)
1.8.1 Planck's Law
13(1)
1.8.2 Stefan-Boltzmann Law
14(1)
1.8.3 Wein's Radiation Law
15(1)
1.8.4 Rayleigh-Jeans Law
16(1)
1.8.5 Kirchhoff's Law
16(1)
1.9 Spectral Response Pattern
16(1)
1.10 Hyperspectral Remote Sensing
17(3)
1.11 Remote Sensing Process
20(3)
1.11.1 The Source of Illumination
20(1)
1.11.2 The Sensor
20(1)
1.11.3 Platforms
20(1)
1.11.4 Data Reception
21(1)
1.11.5 Data Product Generation
21(1)
1.11.6 Data Analysis/Interpretation
22(1)
1.11.7 Data/Information Storage
22(1)
1.11.8 Archival and Distribution
22(1)
1.12 Geographical Information System
23(2)
1.12.1 Components of GIS
24(1)
1.12.1.1 Hardware
24(1)
1.12.1.2 Software
24(1)
1.12.1.3 Data
25(1)
1.13 Global Navigation Satellite Systems
25(4)
1.13.1 GPS Segments
26(1)
1.13.1.1 Space Segment
26(1)
1.13.1.2 Control Segment
26(1)
1.13.1.3 The User Segment
27(1)
1.13.2 Operating Principle of GPS
27(1)
1.13.3 Navigation
28(4)
1.13.3.1 Stand-Alone Satellite Navigation
28(1)
1.13.3.2 Differential GNSS Navigation
29(1)
1.13.3.3 Network-Assisted GNSS Navigation
29(1)
1.13.3.4 Carrier-Phase Differential (Kinematic) GPS
29(1)
1.14 Organization of This Book
29(1)
References
30(1)
2 Passive Remote Sensing 31(36)
2.1 Introduction
31(1)
2.2 Remote Sensing Platforms
32(3)
2.2.1 Airborne Platforms
32(2)
2.2.2 Spaceborne Platforms
34(1)
2.2.2.1 Geosynchronous Satellites
34(1)
2.2.2.2 Polar Orbiting Satellites
34(1)
2.3 Passive Sensors
35(5)
2.3.1 The Optics
35(2)
2.3.2 Detectors
37(3)
2.3.2.1 Quantum Detectors
38(1)
2.3.2.2 Photoemissive Detectors
38(1)
2.3.2.3 Semiconductor Detectors
38(1)
2.3.2.4 Photoconductive Detectors
38(1)
2.3.2.5 Photovoltaic Detectors
39(1)
2.3.2.6 Thermal Detectors
39(1)
2.4 Optical Sensors
40(7)
2.4.1 Conventional Photographic Cameras
40(1)
2.4.2 Digital Aerial Cameras
41(1)
2.4.3 Video Cameras
41(1)
2.4.4 Radiometers
41(6)
2.4.4.1 Radiometers Operating in Optical Region
41(2)
2.4.4.2 Radiometers Operating in Microwave Region
43(3)
2.4.4.3 Imaging Spectrometer
46(1)
2.5 Resolution of a Sensor
47(3)
2.5.1 Spatial Resolution
48(1)
2.5.2 Spectral Resolution
49(1)
2.5.3 Radiometric Resolution
49(1)
2.5.4 Temporal Resolution
50(1)
2.5.5 Angular Resolution
50(1)
2.6 Spaceborne Missions with Passive Sensors
50(14)
2.6.1 The Landsat Mission
50(1)
2.6.2 The SPOT Mission
51(1)
2.6.3 Pleiades Mission
52(1)
2.6.4 The Indian Earth Observation Mission
53(1)
2.6.4.1 Resourcesat-1
53(1)
2.6.4.2 Resourcesat-2
53(1)
2.6.4.3 Resourcesat-2A
53(1)
2.6.5 The Earth Observing System Mission
54(2)
2.6.5.1 Terra (EO-AM)
54(1)
2.6.5.2 Aqua (EOS PM-1)
54(2)
2.6.6 Earth Observing-1 Mission (EO-1)
56(1)
2.6.7 RapidEye
56(1)
2.6.8 Hyperspatial Resolution Earth Missions
57(3)
2.6.8.1 WorldView Mission
57(1)
2.6.8.2 Cartosat Mission
58(1)
2.6.8.3 GeoEye-1
59(1)
2.6.9 Passive Microwave Missions
60(7)
2.6.9.1 National Oceanic and Atmospheric Administration AMSU-A
60(1)
2.6.9.2 Defense Meteorological Satellite Program
60(1)
2.6.9.3 Aqua (EO: PM-1)
61(1)
2.6.9.4 Soil Moisture and Ocean Salinity Mission
61(2)
2.6.9.5 Soil Moisture Active Passive Mission
63(1)
2.7 Conclusion
64(1)
References
64(3)
3 Active Remote Sensing 67(30)
3.1 Introduction
67(1)
3.2 Active Microwave Sensors
67(13)
3.2.1 Imaging Sensors
67(8)
3.2.1.1 Real Aperture Radar
68(3)
3.2.1.2 Synthetic Aperture Radar
71(2)
3.2.1.3 The Operating Modes of SAR
73(2)
3.2.2 Non-imaging Microwave Sensors
75(5)
3.2.2.1 Scatterometers
76(2)
3.2.2.2 Radar Altimeter
78(2)
3.3 Spaceborne Radars Systems
80(9)
3.3.1 RISAT Mission
80(1)
3.3.1.1 RISAT-1
80(1)
3.3.1.2 RISAT-2
80(1)
3.3.2 Sentinel Mission
81(1)
3.3.2.1 Sentinel-1
81(1)
3.3.2.2 Sentinel-2
81(1)
3.3.2.3 Sentinel-3
81(1)
3.3.2.4 Sentinel-4
81(1)
3.3.2.5 Sentinel-5
82(1)
3.3.2.6 Sentinel-5P
82(1)
3.3.3 CryoSat
82(1)
3.3.4 Soil Moisture and Ocean Salinity Mission
82(1)
3.3.4.1 Measurement Principle
83(1)
3.3.5 Soil Moisture Active Passive
83(2)
3.3.6 RADARSAT Mission
85(1)
3.3.6.1 RADARSAT Constellation
85(1)
3.3.7 The Advanced Land Observing Satellite-2
86(1)
3.3.8 TerraSAR-X and TanDEM-X
87(2)
3.4 Light Detection And Ranging
89(6)
3.4.1 Discrete Return LiDAR
89(2)
3.4.2 Waveform LiDAR
91(1)
3.4.3 Scanning Mechanism
91(8)
3.4.3.1 Oscillating Mirror Scanning Mechanism
91(2)
3.4.3.2 Rotating Polygon Scanning Mechanism
93(1)
3.4.3.3 Nutating Mirror Scanning System
93(1)
3.4.3.4 Fiber Pointing System
93(1)
3.4.3.5 Spaceborne LiDAR Mission
94(1)
3.4.3.6 Cloud Profiling Radar (CPR)
95(1)
3.5 Conclusion
95(1)
References
96(1)
4 Digital Image Processing 97(52)
4.1 Introduction
97(2)
4.2 Data Storage Media
99(1)
4.2.1 Compact Disc
99(1)
4.2.2 Digital Versatile Disk
99(1)
4.2.3 Memory Sticks
99(1)
4.3 Digital Data Format
100(1)
4.3.1 Generic Binary
100(1)
4.3.2 Graphic Interchange Format
100(1)
4.3.3 JPEG
100(1)
4.3.4 TIFF and GeoTIFF
101(1)
4.3.5 Portable Network Graphics
101(1)
4.4 Image Preprocessing
101(10)
4.4.1 Radiometric Correction
101(4)
4.4.1.1 Atmospheric Effects
101(1)
4.4.1.2 Absolute Atmospheric Correction
102(2)
4.4.1.3 Relative Atmospheric Correction
104(1)
4.4.1.4 Instrumental Errors
104(1)
4.4.2 Corrections for Solar Illumination Variation
105(1)
4.4.3 Noise Removal
105(2)
4.4.4 Geometric Image Correction
107(3)
4.4.4.1 Correction for Systemic Distortions
108(1)
4.4.4.2 Correction of Nonsystemic Errors
109(1)
4.4.5 Image Processing Levels
110(1)
4.5 Image Enhancement
111(15)
4.5.1 Contrast Modification
111(7)
4.5.1.1 Density Slicing
112(1)
4.5.1.2 Contrast Enhancement
112(5)
4.5.1.3 Edge Enhancement and Detection
117(1)
4.5.2 Multiple Image Manipulation
118(8)
4.5.2.1 Band Ratioing
118(1)
4.5.2.2 Vegetation Indices
118(1)
4.5.2.3 Image Transformation
119(7)
4.6 Image Classification
126(8)
4.6.1 Unsupervised Classification
126(1)
4.6.1.1 Unsupervised Classification using the Chain Method
126(1)
4.6.1.2 Unsupervised Classification using the ISODATA Method
126(1)
4.6.1.3 K-Means Clustering Algorithm
127(1)
4.6.2 Supervised Classification
127(7)
4.6.2.1 Parallelepiped Classification
127(1)
4.6.2.2 Minimum Distance Classification
128(1)
4.6.2.3 Maximum Likelihood Classification
128(1)
4.6.2.4 k-Nearest Neighbors
128(1)
4.6.2.5 Mahalanobis Spectral Distance
129(1)
4.6.2.6 Artificial Neural Networks
130(1)
4.6.2.7 Object-Oriented Classification
130(1)
4.6.2.8 Spectral Angular Mapper Algorithm
131(1)
4.6.2.9 Spectral Correlation Classifier
132(1)
4.6.2.10 Support Vector Machines Classifier
133(1)
4.7 Digital Change Detection
134(3)
4.7.1 Image Enhancement Techniques
135(2)
4.7.1.1 Univariate Image Differencing
135(1)
4.7.1.2 Image Regression
135(1)
4.7.1.3 Image Ratioing
135(1)
4.7.1.4 Principal Component Analysis
136(1)
4.7.1.5 Multivariate Alteration Detection
136(1)
4.7.1.6 Post-Classification Comparison
136(1)
4.7.1.7 Artificial Neural Network-Based Change Detection
137(1)
4.8 Accuracy Assessment
137(6)
4.8.1 Uni-Temporal Thematic Maps
138(2)
4.8.1.1 Sampling Scheme
138(1)
4.8.1.2 Accuracy Assessment
138(1)
4.8.1.3 Kappa Coefficient (K)
139(1)
4.8.2 Multi-Temporal Thematic Maps
140(3)
4.9 Conclusions
143(1)
References
144(5)
5 An Introduction to Land Degradation 149(22)
5.1 Introduction
149(11)
5.1.1 Components of Land Degradation
150(12)
5.1.1.1 Soil Degradation
151(8)
5.1.1.2 Vegetation Degradation
159(1)
5.1.1.3 Water Degradation
159(1)
5.1.1.4 Climate Deterioration
159(1)
5.1.1.5 Losses to Urban/Industrial Development
160(1)
5.2 Extent and Spatial Distribution
160(2)
5.3 Land Degradation Assessment
162(4)
5.3.1 Expert opinion/GLASOD Approach
162(1)
5.3.2 Remote Sensing-Based Approach
163(2)
5.3.2.1 Computation of NDVI Indicators
164(1)
5.3.2.2 NDVI-to-NPP Conversion
164(1)
5.3.2.3 Identification of the Areas Experiencing Land Degradation
164(1)
5.3.3 Biophysical Models
165(1)
5.3.4 Abandonment of Agricultural Lands
165(1)
5.3.5 The Land Degradation Impact Index
166(1)
5.4 Conclusions
166(1)
References
167(4)
6 Water Erosion 171(26)
6.1 Introduction
171(1)
6.2 Factors of Water Erosion
171(3)
6.2.1 Climatic Factors
172(1)
6.2.2 Land Factors
172(2)
6.2.2.1 Soil Texture and Clay Mineralogy
172(1)
6.2.2.2 Organic Matter
172(1)
6.2.2.3 Sodium and Other Cations
173(1)
6.2.2.4 Iron and Aluminum Oxides
173(1)
6.2.2.5 Antecedent Soil Moisture
173(1)
6.2.2.6 Soil Crusting
173(1)
6.2.2.7 Topography
173(1)
6.2.2.8 Vegetation
174(1)
6.3 Water Erosion Models
174(2)
6.3.1 Empirical Models
174(1)
6.3.2 Physically Based Models
175(1)
6.3.2.1 Water Erosion Prediction Project Model
175(1)
6.3.3 Mixed Models
175(1)
6.3.3.1 Creams
175(1)
6.3.3.2 Answers
176(1)
6.4 Role of Remote Sensing
176(13)
6.4.1 Spectral Response Pattern of Eroded Soils
176(1)
6.4.2 Airborne Sensor Data
177(1)
6.4.3 Spaceborne Multispectral Data
178(19)
6.4.3.1 Detection of Erosion Features and Eroded Areas
178(6)
6.4.3.2 Monitoring Eroded Lands
184(1)
6.4.3.3 Detection of Erosion Consequences
185(1)
6.4.3.4 Erosion Controlling Factors
186(1)
6.4.3.5 Soil Erosion Risk
186(2)
6.4.3.6 Assimilation of Remote Sensing Data into Runoff and Erosion Models
188(1)
6.5 Conclusion
189(1)
References
190(7)
7 Wind Erosion 197(32)
7.1 Introduction
197(1)
7.2 Background
197(4)
7.2.1 Wind Erosion Processes
198(1)
7.2.2 Causative Factors
198(4)
7.2.2.1 Soil Erodibility
199(1)
7.2.2.2 Soil Surface Conditions
199(1)
7.2.2.3 Soil Texture
200(1)
7.2.2.4 Climate
200(1)
7.2.2.5 Vegetation
200(1)
7.2.2.6 Soil Moisture
201(1)
7.3 Global Scenario
201(1)
7.4 Role of Remote Sensing
202(12)
7.4.1 Airborne Sensors Data
202(1)
7.4.2 Orbital Sensor Data
203(11)
7.4.2.1 Detection of Wind Erosion Features and Eroded Areas
204(2)
7.4.2.2 Characterization of Dune Activity
206(1)
7.4.2.3 Measuring Sand Availability
206(2)
7.4.2.4 Erosion Control Measures and Impact Assessment
208(6)
7.5 Modeling Wind Erosion
214(6)
7.5.1 Field Scale Wind Erosion Models
214(2)
7.5.1.1 Wind Erosion Equation
214(1)
7.5.1.2 Revised Wind Erosion Equation
214(1)
7.5.1.3 Wind Erosion Prediction System
215(1)
7.5.1.4 Texas Erosion Analysis Model
215(1)
7.5.1.5 Wind Erosion Stochastic Simulator
215(1)
7.5.2 Regional Scale Models
216(1)
7.5.2.1 Wind Erosion on European Light Soils
216(1)
7.5.2.2 Wind Erosion Assessment Model
217(1)
7.5.2.3 Integrated Wind Erosion Modeling System
217(1)
7.5.3 Global Scale Models
217(2)
7.5.3.1 Dust Production Model
218(1)
7.5.3.2 Dust Entrainment and Deposition Model
219(1)
7.5.4 Other Global Dust Models
219(1)
7.6 Conclusion
220(4)
References
224(5)
8 Soil Salinization and Alkalinization 229(34)
Jamshid Fareftih
8.1 Introduction
229(1)
8.2 Origin of Salts
230(1)
8.3 Nature of Salt-Affected Soils
231(1)
8.4 Extent and Spatial Distribution
232(1)
8.5 Soil Salinity. Symptoms
233(2)
8.5.1 Surface Manifestation
233(1)
8.5.2 The Presence of Halophytic Plants
234(1)
8.5.3 Crop Performance
235(1)
8.6 Proximal Sensing
235(4)
8.6.1 Spectral Measurements in Laboratory
235(2)
8.6.2 In situ Spectral Measurements
237(1)
8.6.3 Frequency-Domain Electromagnetic Techniques
238(1)
8.6.4 Ground Penetrating Radar Measurements
239(1)
8.7 Inventory and Monitoring of Salt-Affected Soils
239(15)
8.7.1 Airborne Sensors Data
240(1)
8.7.1.1 Aerial Photographs, Videography, and Digital Multispectral Camera Images
240(1)
8.7.2 Orbital Sensor Data
241(6)
8.7.2.1 Multispectral Visible, NIR, and Thermal IR Sensor Data
242(4)
8.7.2.2 Computer-Assisted Digital Analysis
246(1)
8.7.3 State-of-the-Art
247(18)
8.7.3.1 Temporal Behavior of Salt-Affected Soils
248(4)
8.7.3.2 Spaceborne Microwave Sensor Data
252(1)
8.7.3.3 Spaceborne Hyperspectral Sensor Data
253(1)
8.8 Solute Transport Modeling
254(1)
8.9 Conclusion
254(1)
References
255(8)
9 Soil Acidification 263(22)
9.1 Introduction
263(1)
9.2 Background
263(1)
9.3 Global Scenario
264(1)
9.4 Development of Soil Acidity
265(4)
9.4.1 Causative Factors of Soil Acidification
265(2)
9.4.1.1 Acidic Precipitation
265(1)
9.4.1.2 Acidifying Gases and Particles
266(1)
9.4.1.3 Acidifying Fertilizers and Legumes
266(1)
9.4.1.4 Nutrient Uptake by Crops and Root Exudates
267(1)
9.4.1.5 Mineralization
267(1)
9.4.2 The Impact of Soil Acidification
267(1)
9.4.3 Soil Acidity and Base Saturation and Buffering Capacity
268(1)
9.4.4 Soil Acidity and Crop Responses
268(1)
9.5 Delineation and Mapping of Acid, Soils
269(12)
9.5.1 Aerial Photographs
269(2)
9.5.1.1 Aspect/Elemental Analysis
270(1)
9.5.1.2 Physiographic Analysis
270(1)
9.5.1.3 Morphogenetic Analysis
270(1)
9.5.2 Spaceborne Multispectral Measurements
271(8)
9.5.2.1 Visual Interpretation
271(5)
9.5.2.2 Computer-Assisted Digital Analysis
276(3)
9.5.3 Mapping Vegetation-Covered Soils
279(1)
9.5.4 Digital Soil Mapping
279(2)
9.6 Conclusion
281(1)
References
281(4)
10 Waterlogging 285(18)
10.1 Introduction
285(1)
10.2 The Effects of Waterlogging
286(2)
10.2.1 The Effects on Soils
286(1)
10.2.2 Plant Responses to Waterlogging
286(2)
10.3 Norms for Categorization
288(1)
10.4 Role of Remote Sensing
288(9)
10.4.1 In situ Spectral Reflectance Studies
289(1)
10.4.2 Aerial Photographs and Airborne Spectral Measurements
290(1)
10.4.3 Spaceborne Multispectral Measurements
290(5)
10.4.3.1 Optical Sensor Data
290(4)
10.4.3.2 Thermal Sensor Data
294(1)
10.4.4 Geophysical Techniques
295(10)
10.4.4.1 Ground-Penetrating Radar (GPR)
295(1)
10.4.4.2 Electromagnetic Induction (EMI) Sensors
296(1)
10.5 Using Models to Simulate Plant Responses to Waterlogging
297(1)
10.6 Conclusions
298(1)
References
298(5)
11 Land Degradation due to Mining, Aquaculture, and Shifting Cultivation 303(18)
11.1 Introduction
303(1)
11.2 Global Distribution
304(1)
11.3 Role of Remote Sensing
305(12)
11.3.1 Aerial Photographs
305(1)
11.3.1.1 Mining
305(1)
11.3.1.2 Aquaculture
305(1)
11.3.1.3 Shifting Cultivation
306(1)
11.3.2 Sapaceborne Multispectral Measurements
306(15)
11.3.2.1 Mining
306(4)
11.3.2.2 Aquaculture
310(5)
11.3.2.3 Shifting Cultivation
315(2)
11.4 Conclusions
317(1)
References
317(4)
12 Drought 321(34)
12.1 Introduction
321(1)
12.2 Background
321(3)
12.2.1 Drought Indicators
323(1)
12.3 Global Scenario
324(1)
12.4 Drought Assessment and Monitoring
325(14)
12.4.1 Meteorological Indicators
326(3)
12.4.1.1 Deciles
326(1)
12.4.1.2 Percent of Normal Precipitation
326(1)
12.4.1.3 Palmer Drought Severity Index
326(1)
12.4.1.4 Standardized Precipitation Index
327(1)
12.4.1.5 Crop Moisture Index
327(1)
12.4.1.6 Standardized Precipitation Evapotranspiration Index
328(1)
12.4.1.7 Soil Moisture Deficit Index
328(1)
12.4.1.8 Surface Water Supply Index
329(1)
12.4.2 Remote Sensing-Based Methods
329(8)
12.4.2.1 Estimation of Meteorological Parameters
330(2)
12.4.2.2 Drought Impacts
332(5)
12.4.3 Process-Based Indicators
337(1)
12.4.4 Water Balance Approach
338(1)
12.5 Drought Forecasting
339(2)
12.5.1 Regression Analysis
339(1)
12.5.2 Time Series Analysis
339(1)
12.5.3 Probability Models
340(1)
12.5.4 ANN Model
340(1)
12.5.5 Hybrid Models
341(1)
12.6 Long-Lead Drought Forecasting
341(1)
12.7 Drought Monitoring Systems: Global Scenario
341(5)
12.7.1 Global Integrated Drought Monitoring and Prediction System
342(1)
12.7.1.1 Approach
342(1)
12.7.2 European Drought Monitoring System
343(1)
12.7.3 Drought Monitoring System for South Asia
344(1)
12.7.4 Indian National Agricultural Drought Assessment and Monitoring System
344(2)
12.8 Conclusion
346(1)
References
347(8)
13 Land Degradation Information Systems 355(24)
13.1 Introduction
355(1)
13.2 Background
356(2)
13.2.1 Components of an IS
356(2)
13.3 Database
358(3)
13.3.1 Database Model
358(3)
13.3.1.1 Hierarchical Model
358(1)
13.3.1.2 Network Model
358(1)
13.3.1.3 Relational Model
359(1)
13.3.1.4 Object-Oriented Model
360(1)
13.4 Land Degradation ISs
361(8)
13.4.1 Soil Database
362(7)
13.4.1.1 Data Acquisition
362(1)
13.4.1.2 Geo-referencing and Creation of Digital Data
362(1)
13.4.1.3 Data Verification and Editing
363(1)
13.4.1.4 Data Updation
363(1)
13.4.1.5 Soil Degradation Data
363(1)
13.4.1.6 Soil ISs
363(6)
13.5 Gladis/GIS System
369(6)
13.5.1 Panning Method
374(1)
13.5.1.1 Metadata, Formats and Resolution Information, Layers
374(1)
13.6 Conclusion
375(1)
References
376(3)
Index 379
Dr Ravi Shankar Dwivedi is a consultant and guest faculty at Jawaharlal Nehru Technological University Hyderabad, India. He is an expert Land resources management: Soil resources inventory, mapping and monitoring land degradation/ desertification, wastelands and land use/ land cover using a variety of remote sensing data. He has a long experience also in Watershed management- Generation of inputs especially soil resources, land capability and land irrigability maps, surface water bodies maps and drainage maps ; integration of these maps with hydrogeoplogical maps and development of action plan, monitoring and impact assessment using multi-temporal satellite and ancillary data.He holds Awards from Indian Society of Remote Sensing for outstanding contribution in the field of remote sensing and Doreen Mashler Team Award for outstanding contribution to integrated watershed management for sustainable development (as a member of ICRISAT team).
Biežāk uzdotie jautājumi par e-grāmatām Biežāk uzdotie jautājumi par e-grāmatām
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