Title:
Cloud computing platforms-based remote sensing big data applications

dc.contributor.authorSwati Suman
dc.contributor.authorSwati Maurya
dc.contributor.authorVarsha K. Pandey
dc.contributor.authorPrashant Kumar Srivastava
dc.contributor.authorDileep Kumar Gupta
dc.date.accessioned2026-02-19T17:23:51Z
dc.date.issued2025
dc.description.abstractGoogle Earth Engine (GEE) stands as the leading cloud-based geospatial remote sensing data processing platform. GEE repositories contain a range of satellite imageries, which can be used for various environmental applications, thanks to its easy and user-friendly application programming interface (API). One of the most compelling features of GEE includes enabling its users to explore, analyze, and visualize big geospatial data easily, all without requiring access to supercomputers or specialized coding expertise. Remarkably, even a decade after GEE's launch, its impact on remote sensing and geospatial science remains largely unnoticed. In this review, we provide a state-of-the-art report on the usage of cloud computing platforms such as GEE for processing various remote sensing data sources. We further explore the application of GEE for assessing vegetation health, agricultural monitoring, disaster management, image processing, and numerous other environmental applications using GEE. © 2025 Elsevier Ltd. All rights reserved.
dc.identifier.doi10.1016/B978-0-443-27372-8.00003-9
dc.identifier.isbn9780443273728; 9780443273735
dc.identifier.urihttps://doi.org/10.1016/B978-0-443-27372-8.00003-9
dc.identifier.urihttps://dl.bhu.ac.in/bhuir/handle/123456789/65752
dc.publisherElsevier
dc.subjectGEE
dc.subjectMachine learning
dc.subjectRemote sensing
dc.titleCloud computing platforms-based remote sensing big data applications
dc.typePublication
dspace.entity.typeBook chapter

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