Google Earth Engine and Artificial Intelligence for Earth Observation
Language: English
Published by Elsevier Inc Jun 2025, 2025
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 219.80
Quantity: 2 available
Add to basketItem description from seller
Neuware - Google Earth Engine and Artificial Intelligence for Earth Observation: Algorithms and Sustainable Applications explores a wide range of transformative data fusion techniques of Artificial Intelligence (AI) technologies applied to Google Earth Engine (GEE) techniques. It includes a wide range of scientific domains that can utilize remote sensing and geographic information systems (GIS) through detailed case studies. This book delves into the challenges of AI-driven tools and technologies for Earth observation data analysis, offering possible solutions and directly addressing current and upcoming needs within Earth observation. Google Earth Engine and Artificial Intelligence for Earth Observation: Algorithms and Sustainable Applications is a useful reference for geospatial scientists, remote sensing experts, and environmental scientists utilizing remote sensing to apply the latest AI techniques to data obtained from GEE for their research and teaching.
Seller Inventory # 9780443273728
- Title
- Google Earth Engine and Artificial Intelligence for Earth Observation
- Author
- Vishakh Sood
- Publisher
- Elsevier Inc Jun 2025
- Publication year
- 2025
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 0443273723
- ISBN 13
- 9780443273728
- Item weight
- 765 grams
- Dimensions
- 229x152x30 mm
- Series
- Book 12 of 26: Earth Observation
- Includes utilization of AI with GEE tools for a spectrum of scientific domains in remote sensing and geographic information systems (GIS) including natural hazard assessment, aquatic and hydrological applications, and forest cover
- Highlights the challenges and possible solutions for AI-driven tools and technologies for Earth observation data analysis
- Includes detailed case studies showing specific considerations and exceptions for applications of AI in GEE for Earth observation
"Synopsis" may belong to another edition of this title.
About the Author
Dileep Kumar Gupta received his doctoral degree from the Department of Physics, Indian Institute of Technology (Banaras Hindu University), Varanasi, India. He is currently working as Assistant Professor (Grade II) at Galgotias University, Greater Noida, India. His research expertise lies in microwave active and passive remote sensing, electronics and sensor systems, GNSS-based applications, and algorithm development for soil moisture and crop parameter retrieval using ground‑based and space‑borne platforms. His work closely integrates antenna‑enabled sensing systems with data processing methodologies. He has published extensively in peer‑reviewed journals, conference proceedings, and book chapters, and has also served as an editor for academic books with international publishers. His broader research interests include multi‑sensor remote sensing, microwave system applications, geoinformatics, and the use of artificial intelligence and machine learning techniques in remote sensing data analysis.
Dr. Sartajvir Singh is currently serving as Chief Scientific Officer at the Center of Excellence in Socio-Environmental Sustainability for River Sand Mining (SENSRS) and Project Director (ICSSR Project) at Indian Institute of Technology Ropar, India. He is a digital image analyst with expertise in remote sensing and earned his PhD in Electronics & Communication Engineering (Outstanding Thesis Awardee, 2018) after completing his M. Tech (Gold Medalist) and B.Tech with Distinction. He is a Registered Indian Patent & Trademark Agent and a DGCA-approved drone operator, with 70+ innovations (35+ patents granted) and 90+ SCI/Scopus-indexed publications. He has secured over four Crore (INR) research funding, received multiple fellowships, held editorial positions, and is an IEEE Senior Member, advancing electronics, image processing, and geospatial intelligence.
Professor Pradhan is a globally recognized expert in geospatial analytics and artificial intelligence applications in Earth and environmental sciences. Currently a Distinguished Professor at the University of Technology Sydney (UTS), Australia, he also leads the Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS). With a PhD in GIS-based modeling, Prof. Pradhan has over two decades of experience in spatial data science, remote sensing, natural hazard modeling, and environmental monitoring. He has been listed among the world's top 2% scientists by Stanford University and received numerous international awards, including from IEEE and Elsevier. A Fellow of the Royal Geographical Society (FRGS), he also serves on editorial boards of several top-tier journals. His research integrates geospatial AI and deep learning for disaster risk reduction, land use planning, and sustainability.
"About the title" may belong to another edition of this title.
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