Environmental Monitoring with Integrated Earth Observation Data and Machine Learning

Erscheinungsjahr 2026
ISBN: 978-3-032-19934-8
Verlag: Springer

Buch, Englisch, 84 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 334 g

Reihe: Studies in Computational Intelligence

This book offers practical insights for researchers and policymakers to demonstrate how EO and ML can strengthen environmental monitoring to support informed decision-making, and advance sustainable development. The Earth faces rising challenges like climate instability, land degradation, water scarcity, rapid urban expansion, etc., making reliable environmental monitoring imperative. Traditional methods lack the precision and scale required for global environmental monitoring. However, advances in Earth Observation (EO) and Machine Learning (ML) enable accurate, large-scale environmental monitoring through accessible open-source datasets. Further ML integration with these datasets supports predictive analysis and detailed environmental assessments. Thus, this book outlines the principles of EO, data management, ML integration, and applies them through a case study of the Narmada River Basin, India to examine land use, pollution, and the overall environmental conditions.

Zielgruppe

Research

Autoren/Hrsg.

Roy, Srija

Goyal, Manish Kumar

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Geowissenschaften Geologie Geologie
• Geowissenschaften Umweltwissenschaften Umweltüberwachung, Umweltanalytik, Umweltinformatik

Inhaltsverzeichnis

Environmental Monitoring with Integrated Earth Observation Data and Machine Learning.- Earth Observation Data Management and Analytical Tools. - Machine Learning for Earth Observation. - Case Study of the Narmada River Basin. - Challenges and Future Directions.

Über Autor(innen)

Dr. Srija Roy is a research associate in the Department of Civil Engineering at IIT Indore, working on the Condition Assessment and Monitoring of the Narmada River Basin Project funded by the Ministry of Jal Shakti. Her research focuses on Remote Sensing, GIS, and Water Resources Engineering, with a strong emphasis on applying Machine Learning and AI in Earth Science studies. She holds a B.Tech. in Civil Engineering from MAKAUT, a M.Tech. in Environmental and Water Resources Engineering from NIT Manipur, and a Ph.D. from NIT Jamshedpur. Dr. Roy has published in reputable international journals and presented her work at prestigious platforms like AGU, EGU, HYDRO, etc. She also serves as a peer reviewer for journals like  . Passionate about environmental conservation, she advocates for integrating social sciences with engineering to develop sustainable, interdisciplinary solutions to pressing environmental challenges.

Prof. Manish Kumar Goyal is a professor in the Department of Civil Engineering at IIT Indore and holds the prestigious Chair Professorship for BIS Standardization. His research encompasses water resources engineering, GIS, remote sensing, and climate change. He earned his B.Tech from NIT Warangal and M.Tech and Ph.D. from IIT Roorkee, with collaborative research at the University of Waterloo, Canada. He pursued postdoctoral fellowships at NTU Singapore and McGill University, Canada. With over 300 publications and 6,702 citations, he has an h-index of 54 and i-index of 141. He serves as an associate editor for the Nature Scientific Reports, ASCE  . His edited book   (Wiley) received global acclaim.