{"title":"Spatio-temporal transformation of semi-arid landscapes under declining rainfall trends: a multi-decadal LULC assessment using google earth engine","authors":"Shiphali Preeti Aind, A. R. Quaff","doi":"10.1007/s12518-026-00810-2","DOIUrl":null,"url":null,"abstract":"<div><p>Distinguishing human-driven degradation from climate variability remains a critical challenge for sustainable land management. This study introduces a Sustainability Index (SI) model using Google Earth Engine to analyze Landsat imagery and CHIRPS rainfall data (2000–2025) in Khammam, India. The findings reveal significant landscape shifts, including a 24.5% loss of water bodies and a 56.6% decline in agricultural land, both linked to localized rainfall decline rates ranging from − 3 to − 8 mm·yr⁻¹ (Sen’s slope). By mapping eco-hydrological resilience and vulnerability, the SI identified hotspots nearing irreversible degradation. This scalable framework provides a robust methodology for data-scarce, semi-arid regions, directly supporting UN Sustainable Development Goals 13 (Climate Action) and 15 (Life on Land) by identifying high-risk zones for targeted intervention.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"18 4","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2026-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Geomatics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s12518-026-00810-2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"REMOTE SENSING","Score":null,"Total":0}
引用次数: 0
Abstract
Distinguishing human-driven degradation from climate variability remains a critical challenge for sustainable land management. This study introduces a Sustainability Index (SI) model using Google Earth Engine to analyze Landsat imagery and CHIRPS rainfall data (2000–2025) in Khammam, India. The findings reveal significant landscape shifts, including a 24.5% loss of water bodies and a 56.6% decline in agricultural land, both linked to localized rainfall decline rates ranging from − 3 to − 8 mm·yr⁻¹ (Sen’s slope). By mapping eco-hydrological resilience and vulnerability, the SI identified hotspots nearing irreversible degradation. This scalable framework provides a robust methodology for data-scarce, semi-arid regions, directly supporting UN Sustainable Development Goals 13 (Climate Action) and 15 (Life on Land) by identifying high-risk zones for targeted intervention.
期刊介绍：
Applied Geomatics (AGMJ) is the official journal of SIFET the Italian Society of Photogrammetry and Topography and covers all aspects and information on scientific and technical advances in the geomatics sciences. The Journal publishes innovative contributions in geomatics applications ranging from the integration of instruments, methodologies and technologies and their use in the environmental sciences, engineering and other natural sciences.
The areas of interest include many research fields such as: remote sensing, close range and videometric photogrammetry, image analysis, digital mapping, land and geographic information systems, geographic information science, integrated geodesy, spatial data analysis, heritage recording; network adjustment and numerical processes. Furthermore, Applied Geomatics is open to articles from all areas of deformation measurements and analysis, structural engineering, mechanical engineering and all trends in earth and planetary survey science and space technology. The Journal also contains notices of conferences and international workshops, industry news, and information on new products. It provides a useful forum for professional and academic scientists involved in geomatics science and technology.
Information on Open Research Funding and Support may be found here: https://www.springernature.com/gp/open-research/institutional-agreements
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