Data Analytics and Artificial Intelligence for Earth Resource Management offers a detailed look at the different ways data analytics and artificial intelligence can help organizations make better-informed decisions, improve operations, and minimize the negative impacts of resource extraction on the environment. The book explains several different ways data analytics and artificial intelligence can improve and support earth resource management. Predictive modeling can help organizations understand the impacts of different management decisions on earth resources, such as water availability, land use, and biodiversity.Resource monitoring tracks the state of earth resources in real-time, identifying issues and opportunities for improvement. Providing managers with real-time data and analytics allows them to make more informed choices. Optimizing resource management decisions help to identify the most efficient and effective ways to allocate resources. Predictive maintenance allows organizations to anticipate when equipment might fail and take action to prevent it, reducing downtime and maintenance costs. Remote sensing with image processing and analysis can be used to extract information from satellite images and other remote sensing data, providing valuable information on land use, water resources, and other earth resources.

This book provides compelling new insights into how cities are attempting to address sustainability challenges via major applications of geospatial technology in an urban area. It elucidates the role of geospatial techniques such as GIS and GNSS, including remote sensing in urban management, and covers the theory and practice of urban sustainability transitions. It provides case studies and contextualised tools for the governance of urban transitions to present various applications of geospatial techniques in an urban environment.

Features:

This book is aimed at graduate students, researchers, and professionals in GIS, urban sciences, and geography.

This book provides compelling new insights into how cities are attempting to address sustainability challenges via major applications of geospatial technology in an urban area. It elucidates the role of geospatial techniques such as GIS and GNSS, including remote sensing in urban management, and covers the theory and practice of urban sustainability transitions. It provides case studies and contextualised tools for the governance of urban transitions to present various applications of geospatial techniques in an urban environment.

Features:

This book is aimed at graduate students, researchers, and professionals in GIS, urban sciences, and geography.

This book is an earnest effort in understanding the slums and their needs by taking a case study of Kalaburagi, India. This study aims to contribute sustainable methodologies to advance the living conditions of slum dwellers and for better execution of slum policies. The core objectives are: 1) mapping the existing slums of Kalaburagi (formerly Gulbarga) city using slum ontology from very high-resolution data and validating the slum map through ground survey and using reliable data; 2) developing a model to understand the factors which are responsible for the present growth as well as to predict the future growth of slums; 3) estimating the housing demand of urban poor and suggesting a suitable site for the rehabilitation program; and 4) suggestions for the better intervention of government policies with special reference to in-situ program.

Urban is the future, and slums are its reality. Sustainable development goals are directly and indirectly concerned about theincreasing urbanization and the slums. Housing the urban poor and affordable housing to all are the national missions. Practically making these plans successful depends on a deep understanding of urban issues and proper methodology and technology to handle it. The participatory slum mapping, cellular automata slum model, housing demand analysis, and the spatial decision support system demonstrated in the book help in monitoring and managing the slums and thus lead towards a slum-free India.

Data Analytics and Artificial Intelligence for Earth Resource Management offers a detailed look at the different ways data analytics and artificial intelligence can help organizations make better-informed decisions, improve operations, and minimize the negative impacts of resource extraction on the environment. The book explains several different ways data analytics and artificial intelligence can improve and support earth resource management. Predictive modeling can help organizations understand the impacts of different management decisions on earth resources, such as water availability, land use, and biodiversity.Resource monitoring tracks the state of earth resources in real-time, identifying issues and opportunities for improvement. Providing managers with real-time data and analytics allows them to make more informed choices. Optimizing resource management decisions help to identify the most efficient and effective ways to allocate resources. Predictive maintenance allows organizations to anticipate when equipment might fail and take action to prevent it, reducing downtime and maintenance costs. Remote sensing with image processing and analysis can be used to extract information from satellite images and other remote sensing data, providing valuable information on land use, water resources, and other earth resources.

This book provides compelling new insights into how cities are attempting to address sustainability challenges via major applications of geospatial technology in an urban area. It elucidates the role of geospatial techniques such as GIS and GNSS, including remote sensing in urban management, and covers the theory and practice of urban sustainability transitions. It provides case studies and contextualised tools for the governance of urban transitions to present various applications of geospatial techniques in an urban environment.

Features:

This book is aimed at graduate students, researchers, and professionals in GIS, urban sciences, and geography.

This book provides compelling new insights into how cities are attempting to address sustainability challenges via major applications of geospatial technology in an urban area. It elucidates the role of geospatial techniques such as GIS and GNSS, including remote sensing in urban management, and covers the theory and practice of urban sustainability transitions. It provides case studies and contextualised tools for the governance of urban transitions to present various applications of geospatial techniques in an urban environment.

Features:

This book is aimed at graduate students, researchers, and professionals in GIS, urban sciences, and geography.

This book is an earnest effort in understanding the slums and their needs by taking a case study of Kalaburagi, India. This study aims to contribute sustainable methodologies to advance the living conditions of slum dwellers and for better execution of slum policies. The core objectives are: 1) mapping the existing slums of Kalaburagi (formerly Gulbarga) city using slum ontology from very high-resolution data and validating the slum map through ground survey and using reliable data; 2) developing a model to understand the factors which are responsible for the present growth as well as to predict the future growth of slums; 3) estimating the housing demand of urban poor and suggesting a suitable site for the rehabilitation program; and 4) suggestions for the better intervention of government policies with special reference to in-situ program.

Urban is the future, and slums are its reality. Sustainable development goals are directly and indirectly concerned about theincreasing urbanization and the slums. Housing the urban poor and affordable housing to all are the national missions. Practically making these plans successful depends on a deep understanding of urban issues and proper methodology and technology to handle it. The participatory slum mapping, cellular automata slum model, housing demand analysis, and the spatial decision support system demonstrated in the book help in monitoring and managing the slums and thus lead towards a slum-free India.