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Hardcover. Zustand: Brand New. 424 pages. 10.00x7.00x10.00 inches. In Stock.

Hardcover. Zustand: new. Hardcover. This book focuses on geospatial techniques, climate science, and predicting risk applications and challenges. It bridges the gap between the principles of geographic information science (GIS), remote sensing technology, global positioning system (GPS), and machine learning. It emphasizes the application and significance of remotely sensed data and GIS technologies in different aspects of climate science data. It considers the use of geospatial and AI in resource studies, primarily focusing on water, air, soil, urban, climate, and environmental aspects supported by case studies. Features: Includes geographic technologies application with an emphasis on its modeling of climate change and meteorological elements. Merges geospatial technologies and AI methodologies. Provides canvas for social impact and community involvement in the application of geospatial technology across several industries. Examines heatwaves, cold waves, and dust storm models using satellite data and GIS. Case studies highlight the use and applicability of drones with geospatial technology. This book is aimed at researchers and graduate students in geospatial sciences and environmental engineering. This book focusses on geospatial techniques, climate science, and predicting risk applications and challenges. It bridges the gap between the principles of geographic information science (GIS), remote sensing technology, global positioning system (GPS), and machine learning. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardcover. Zustand: new. Hardcover. This book focuses on geospatial techniques, climate science, and predicting risk applications and challenges. It bridges the gap between the principles of geographic information science (GIS), remote sensing technology, global positioning system (GPS), and machine learning. It emphasizes the application and significance of remotely sensed data and GIS technologies in different aspects of climate science data. It considers the use of geospatial and AI in resource studies, primarily focusing on water, air, soil, urban, climate, and environmental aspects supported by case studies. Features: Includes geographic technologies application with an emphasis on its modeling of climate change and meteorological elements. Merges geospatial technologies and AI methodologies. Provides canvas for social impact and community involvement in the application of geospatial technology across several industries. Examines heatwaves, cold waves, and dust storm models using satellite data and GIS. Case studies highlight the use and applicability of drones with geospatial technology. This book is aimed at researchers and graduate students in geospatial sciences and environmental engineering. This book focusses on geospatial techniques, climate science, and predicting risk applications and challenges. It bridges the gap between the principles of geographic information science (GIS), remote sensing technology, global positioning system (GPS), and machine learning. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

HRD. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Zustand: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Pradeep Kumar is a senior Assistant Professor in the Department of Physics, Manipal University Jaipur, India. He received his doctorate degree from the Department of Physics, Indian Institute of Technology (BHU), Varanasi, India. He has made signi.

Hardcover. Zustand: new. Hardcover. This book focuses on geospatial techniques, climate science, and predicting risk applications and challenges. It bridges the gap between the principles of geographic information science (GIS), remote sensing technology, global positioning system (GPS), and machine learning. It emphasizes the application and significance of remotely sensed data and GIS technologies in different aspects of climate science data. It considers the use of geospatial and AI in resource studies, primarily focusing on water, air, soil, urban, climate, and environmental aspects supported by case studies. Features: Includes geographic technologies application with an emphasis on its modeling of climate change and meteorological elements. Merges geospatial technologies and AI methodologies. Provides canvas for social impact and community involvement in the application of geospatial technology across several industries. Examines heatwaves, cold waves, and dust storm models using satellite data and GIS. Case studies highlight the use and applicability of drones with geospatial technology. This book is aimed at researchers and graduate students in geospatial sciences and environmental engineering. This book focusses on geospatial techniques, climate science, and predicting risk applications and challenges. It bridges the gap between the principles of geographic information science (GIS), remote sensing technology, global positioning system (GPS), and machine learning. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Buch. Zustand: Neu. Geospatial Technologies | Environmental and Climate Science Applications and Challenges | Pradeep Kumar (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2026 | CRC Press | EAN 9781032901282 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Buch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book focusses on geospatial techniques, climate science, and predicting risk applications and challenges. It bridges the gap between the principles of geographic information science (GIS), remote sensing technology, global positioning system (GPS), and machine learning.