Schlagwort(e):
Environmental management.
;
Electronic books.
Materialart:
Online-Ressource
Seiten:
1 online resource (409 pages)
Ausgabe:
1st ed.
ISBN:
9783031140969
Serie:
Water Science and Technology Library ; v.105
URL:
https://ebookcentral.proquest.com/lib/geomar/detail.action?docID=7167853
DDC:
333.7028
Sprache:
Englisch
Anmerkung:
Intro -- Contents -- About the Editors -- 1 Applications of Geospatial and Information Technologies Toward Achieving Sustainable Development Goals -- 1.1 Introduction -- 1.2 Sustainable Development Goals -- 1.2.1 Targets -- 1.2.2 Sustainable Development Goals Index (SDGI) and Its Global Perspective -- 1.2.3 Impact of COVID-19 Pandemic on SDGs Implementation -- 1.3 Importance and Scope of Geospatial Technology on SDGs Implementation -- 1.4 Application of Geospatial Techniques Toward Achieving SDGs -- 1.5 Application of Information and Communication Technology Toward Achieving SDGs -- 1.5.1 Application of Big Data -- 1.5.2 Application of Artificial Intelligence -- 1.5.3 Application of Internet of Things -- 1.6 Integration of Geospatial Technology with ICT and Its Significance -- 1.7 Gaps or Challenges -- 1.7.1 Data-Related Challenges -- 1.7.2 Lack of Technology Infrastructure -- 1.7.3 Skilled/Trained Manpower -- 1.7.4 Lack of Awareness -- 1.7.5 Others -- 1.8 Conclusions -- References -- 2 Comparison of Maximum Likelihood, Neural Networks, and Random Forests Algorithms in Classifying Urban Landscape -- 2.1 Introduction -- 2.2 Study Area -- 2.3 Methodology -- 2.3.1 Preprocessing -- 2.3.2 Classification Algorithms -- 2.3.3 Image Classification -- 2.4 Results and Discussion -- 2.4.1 Comparison of Overall Accuracies -- 2.4.2 Comparison of Producer's and User's Accuracies -- 2.5 Conclusion -- References -- 3 Crowd-Assisted Flood Disaster Management -- 3.1 Introduction -- 3.2 Background of Crowdsourced Data (CSD) -- 3.3 Challenges and Opportunities in CSD -- 3.4 Applications of CSD -- 3.5 Quality and Performance of CSD -- 3.5.1 Credibility of Crowdsourced Data -- 3.5.2 Relevance of Crowdsourced Data -- 3.6 Case Study: Flood Disaster Management -- 3.6.1 CSD Location Availability.
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3.6.2 CSD Credibility Analysis: A Naïve Bayesian Network-Based Model for CSD Credibility Detection -- 3.7 Conclusion -- References -- 4 Geospatial Big Earth Data and Urban Data Analytics -- 4.1 Introduction -- 4.2 Big Earth Data and their Characteristics -- 4.3 Big Earth Data Sources -- 4.4 Existing Platforms for Big Earth Data Processing and Management -- 4.5 Big Earth Data Analytics -- 4.6 Big Earth Data and Urban Studies -- 4.7 Big Data Urban Analytics Toward Society 5.0 -- 4.8 Challenges and Way Forward -- References -- 5 A Comparative Analysis of Spatiotemporal Drought Events from Remote Sensing and Standardized Precipitation Indexes in Central America Dry Corridor -- 5.1 Introduction -- 5.2 Case Study -- 5.3 Methodology -- 5.3.1 Data Acquisition -- 5.3.2 Drought Calculation -- 5.3.3 Drought Vegetation Monitoring Indexes -- 5.3.4 Normalized Difference Vegetation Index NDVI -- 5.3.5 Vegetation Condition Index VCI -- 5.3.6 Climatological Drought Indexes -- 5.3.7 Spatiotemporal Monitoring -- 5.4 Results and Discussion -- 5.4.1 Climatological Drought Index -- 5.4.2 Drought Vegetation Monitoring Indexes -- 5.4.3 Spatiotemporal Approach -- 5.4.4 Drought Tracking -- 5.5 Conclusions -- 5.6 Recommendations -- References -- 6 RETRACTED CHAPTER: Application of GIS and Remote Sensing Tools in Assessment of Drought Using Satellite and Ground-Based Data -- 7 Determining the Yield of Rice Using the Leaf Area Index (LAI) in Iran -- 7.1 Rice Cultivation in Iran -- 7.2 Types of Rice Cultivation in Iran -- 7.2.1 The Method of Transplanting -- 7.2.2 Direct Seeding Method -- 7.3 Rice Yield Remote Estimation Indices -- 7.4 Leaf Area Index -- 7.5 Detection of Rice Crop by Remote Sensing Method -- 7.5.1 Unsupervised Classification -- 7.5.2 Supervised Classification -- 7.6 Determining Rice Yield -- 7.7 Results Evaluation of Rice Yield -- 7.8 Discussion and Conclusion.
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References -- 8 Soil Erosion Modeling Using Remote Sensing and GIS -- 8.1 Introduction -- 8.2 Study Area -- 8.3 Methodology -- 8.3.1 Erosion Modeling Using RUSLE -- 8.3.2 Erosion Modeling Using MMF Model -- 8.3.3 Sediment Delivery Ratio (SDR) -- 8.3.4 Model Validation -- 8.4 Results and Discussion -- 8.4.1 Soil Loss by RUSLE Model -- 8.4.2 Soil Loss by MMF Model -- 8.5 Conclusions -- References -- 9 The Mapping of the Intensity of Degradation According to the Different Land Use in Arid Regions: The Case of the Bouhamed Watershed, Southern Tunisia -- 9.1 Introduction -- 9.2 Study Area Exposed to Desertification Problems -- 9.2.1 Arid Climate and Fragile Biophysical Context -- 9.2.2 Ancient and Changing Human Occupation -- 9.3 Methodological Approach to Mapping Land Degradation Based on Remote Sensing and GIS -- 9.3.1 Data and Tools -- 9.3.2 Soil Degradation Mapping Method -- 9.4 Study and Assessment of Degradation Intensity in the Bouhamed Watershed -- 9.4.1 Mapping of the Surface State by the Spectral Indices Approach -- 9.4.2 Mapping Human Occupation Patterns -- 9.4.3 Determination of the Intensity of Degradation -- 9.4.4 Assessment of the State of Desertification by Specification of the Sensitivity Level: Summary Map -- 9.5 Discussion -- 9.6 Conclusion -- 9.7 Recommendation -- References -- 10 Applicability of the Global Land Evaporation Amsterdam Model Data for Basin-Scale Spatiotemporal Drought Assessment -- 10.1 Introduction -- 10.2 Materials and Methods -- 10.2.1 Case Study -- 10.2.2 WEAP Model -- 10.2.3 GLEAM Data -- 10.2.4 The Wet-Environment Evapotranspiration and Precipitation Standardized Index (WEPSI) -- 10.2.5 Experimental Setup -- 10.3 Results and Discussion -- 10.3.1 WEPSI Calculation and Performance Evaluation -- 10.3.2 Eligibility of a Global ET Dataset for Local WEPSI Applications -- 10.4 Conclusions -- References.
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11 Remote Sensing-Based Estimation of Shallow Inland Lake Morphometry: A Case Study of Sambhar Salt Lake, Ramsar Site-464, India -- 11.1 Introduction and Background -- 11.1.1 Why Lake Morphometry? -- 11.2 Significant Literature Inferences About Importance of Lake Morphometry -- 11.3 Material and Methods -- 11.3.1 Study Area-General Description -- 11.3.2 Image Preprocessing -- 11.3.3 Extraction of Water Surface -- 11.3.4 Calculation of the Lake Morphometric Parameters -- 11.4 Results and Discussion -- 11.4.1 Lake Water Surface Area (A) or (a) -- 11.4.2 Maximum Length (Lmax) -- 11.4.3 Maximum Width (Bmax) and Mean Width (overlineB) -- 11.4.4 Lake Water Depth (Maximum Depth Dmax) and (Mean Depth overlineD) -- 11.4.5 Lake Volume (V) and Form Factor (Vd) -- 11.4.6 Dynamic Ratio (DR), Erosion-Transportation (ET) Areas, and Accumulation Areas (Ao) -- 11.5 Conclusion -- References -- 12 Remote Sensing and GIS in Spatial Monitoring of the Wetlands: A Case Study of Loktak Lake Catchment, India -- 12.1 Introduction -- 12.2 Wetlands Classifications and Distributions -- 12.2.1 Ramsar Classification -- 12.2.2 Wetlands Classifications in India -- 12.2.3 Distributions of Wetlands in India -- 12.3 Drivers for Change in Wetland Conditions -- 12.4 Land Use Land Cover Change (LULCC) Modeling Techniques -- 12.4.1 Vector-Based CA (VEC-GCA) -- 12.4.2 CA-Support Vector Machine (SVM) (CA-SVM) -- 12.4.3 CA-MCE -- 12.5 Case Study of Herbaceous Wetlands (Phumdis) and Wetlands in Loktak Lake Catchment, Manipur, India -- 12.6 Results -- 12.7 Discussions -- 12.8 Conclusion and Recommendation -- References -- 13 Delineation of Groundwater Potential Zones in a Tropical River Basin Using Geospatial Techniques and Analytical Hierarchy Process -- 13.1 Introduction -- 13.2 Study Area -- 13.3 Data and Methodology -- 13.4 Results and Discussion -- 13.4.1 Lithology.
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13.4.2 Geomorphological Features -- 13.4.3 Land Use/Land Cover (LU/LC) -- 13.4.4 Soil Texture -- 13.4.5 Lineament Density -- 13.4.6 Slope Angle -- 13.4.7 Drainage Density -- 13.4.8 Topographic Wetness Index (TWI) -- 13.4.9 Rainfall -- 13.4.10 Relative Importance of the Factors -- 13.4.11 Groundwater Potential Zones (GWPZs) -- 13.4.12 Discussions -- 13.5 Summary and Conclusions -- References -- 14 Management of Environmentally Stressed Areas in Watershed Using Multi-criteria Decision Tool in GIS: A Noble Technique to Conserve Soil for Agriculture -- 14.1 Introduction -- 14.1.1 Rain Splash Erosion -- 14.1.2 Sheet Erosion -- 14.1.3 Rill Erosion -- 14.1.4 Gully Erosion -- 14.1.5 Bank Erosion -- 14.2 Soil Erosion in India -- 14.3 Assessment of Soil Erosion -- 14.4 Watershed Prioritization and Design of SWC Measures -- 14.5 Application of GIS -- 14.6 Case Study -- 14.6.1 Module-I: Prioritization -- 14.6.2 Module-II: Development of CAT Plan for SWC Measures -- 14.7 Study Area and Data Used -- 14.8 Results and Discussion -- 14.8.1 Module-I: Prioritization of Sub-watersheds -- 14.8.2 Module-II CAT Plan for Soil Water Conservation Measures -- 14.9 Conclusions -- References -- 15 Geospatial Technology for Estimating the Physical Vulnerability of Building Structures to Natural Hazards -- 15.1 Introduction -- 15.2 The Study Area -- 15.3 Methodology -- 15.3.1 Identification and Grading of Relevant Hazards -- 15.3.2 Determination of Physical Vulnerability of Building Structures to Floods -- 15.3.3 Calculation of the Vulnerability Index (VI) -- 15.4 Risk Assessment for Physical Vulnerability of Building Structures to Floods -- 15.4.1 The Results of Hazard Assessment -- 15.4.2 Results of the Vulnerability Assessment -- 15.5 Conclusion -- 15.6 Future Directions -- References.
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16 Cooling Potential Simulation of Urban Green Space Using Remote Sensing and Web-Based GIS Integration in Panat Nikom Municipality, Thailand.
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