International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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Volume 8 Issue 3
May-June 2026
Indexing Partners
Technology-Enabled Livelihood Transformation in Korwa Tribal Regions of Chhattisgarh: Geospatial and Data-Driven Perspectives Study
| Author(s) | Ms. Priyanka Bhagat, Dr. Anupam Tiwari |
|---|---|
| Country | India |
| Abstract | Tribal regions in India suffer from chronic vulnerabilities of livelihood, which is explained by geographical isolation, ecological sensitivity and limited access of services to both infrastructure and institutional structures. Among these, Korwa tribal areas of the State of Chhattisgarh are one of the most under studied and developmentally marginalised places, amidst sustained policy focus. In recent years, technological improvements in geographical information systems (GIS), remote sensing and data driven analytics have certainly shown great potential in creating and improving livelihood assessment, planning & governance in rural and tribal landscapes. This paper presents a comprehensive review of the available literature on Technology enabled livelihood transformation with a specific contextualization to Korwa tribal areas of Chhattisgarh. The review integrates studies related to sustainable livelihood frameworks, geospatial applications, satellite based environmental monitoring and new machine learning approaches of tribal and rural development research. Key research gaps, method limitations and future opportunities are critically identified. Grounded in the synthesized evidences, a conceptual review framework is proposed taking both livelihood assets, spatial indicators, and data driven decision support for sustainable tribal development. The present review, therefore, is dedicated to sustainable development discourse in terms of offering a systematic and technology-centric approach geared towards inclusive livelihood transformation in the ecologically sensitive and socially vulnerable tribal areas. |
| Keywords | Korwa Tribe, Tribal Livelihoods, Sustainable Development, GIS, Remote Sensing, Data-Driven Planning. |
| Field | Biology > Agriculture / Botany |
| Published In | Volume 8, Issue 1, January-February 2026 |
| Published On | 2026-01-19 |
| DOI | https://doi.org/10.36948/ijfmr.2026.v08i01.66868 |
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