Interdisciplinary Approaches To Spatial Optimization Issues
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Interdisciplinary Approaches to Spatial Optimization Issues
As metropolises continue to see a growth in population, planners are continually searching for trending methods for utilizing space and seeking the best geographical arrangements for these cities. Professionals have continually used geographic information systems (GIS) to solve these issues; however, limitations in this technology remain prevalent. Integrating multiple-criteria decision analysis and evolutionary computing tools with GIS has created an array of robust solutions for spatial optimization problems in densely populated areas. Interdisciplinary Approaches to Spatial Optimization Issues is a pivotal reference source that provides vital research on advancements within the field of GIS and evolutionary solutions for spatial optimization issues. While highlighting topics such as computing machinery, vehicular routing, and operational research, this publication is ideally designed for practitioners, technicians, developers, academicians, students, government officials, planners, and researchers seeking current research on applications and improvements within spatial optimization and GIS.
Addressing Environmental Challenges Through Spatial Planning
Urbanization is giving rise to environmental concerns including urban flooding, which generally occurs due to the construction of houses in the low-lying areas; loss of green cover leading to a disturbance in the ecological cycle; water scarcity due to growing needs; and deforestation leading to habitat fragmentation, wildlife corridors disturbance, forest fires, and climate change. In order to correct these issues, a consolidated balance between human, nature, and spatial aspects must be resolved and spatial solutions integrated on a common platform. Addressing Environmental Challenges Through Spatial Planning is devoted to addressing environmental concerns and technology innovations in domains such as pollution, water insecurity, and resources management. This text works to bridge the gap between engineering considerations and spatial aspects of planning. Covering topics such as sustainable housing, environmental restoration, and air emissions, this text is essential for environmental engineers, planning researchers, faculty, environmental and civil administrators, architects, consultants, environmental activists, town and country planning organizations, and professionals in all industries who aspire to have an environmentally friendly atmosphere and to provide a sustainable way of dealing with the environment in their respective domains for process efficiency and cost optimization.
Emerging Trends, Techniques, and Applications in Geospatial Data Science
With the emergence of smart technology and automated systems in today’s world, big data is being incorporated into many applications. Trends in data can be detected and objects can be tracked based on the real-time data that is utilized in everyday life. These connected sensor devices and objects will provide a large amount of data that is to be analyzed quickly, as it can accelerate the transformation of smart technology. The accuracy of prediction of artificial intelligence (AI) systems is drastically increasing by using machine learning and other probability and statistical approaches. Big data and geospatial data help to solve complex issues and play a vital role in future applications. Emerging Trends, Techniques, and Applications in Geospatial Data Science provides an overview of the basic concepts of data science, related tools and technologies, and algorithms for managing the relevant challenges in real-time application domains. The book covers a detailed description for readers with practical ideas using AI, the internet of things (IoT), and machine learning to deal with the analysis, modeling, and predictions from big data. Covering topics such as field spectra, high-resolution sensing imagery, and spatiotemporal data engineering, this premier reference source is an excellent resource for data scientists, computer and IT professionals, managers, mathematicians and statisticians, health professionals, technology developers, students and educators of higher education, librarians, researchers, and academicians.