GIS for Rural Infrastructure Mapping: Aurangpur Case Study
| International Journal of Civil Engineering |
| © 2026 by SSRG - IJCE Journal |
| Volume 13 Issue 2 |
| Year of Publication : 2026 |
| Authors : Ramesh Babu C, Arvind Kumar |
10.14445/23488352/IJCE-V13I2P121
How to Cite?
Ramesh Babu C, Arvind Kumar, "GIS for Rural Infrastructure Mapping: Aurangpur Case Study," SSRG International Journal of Civil Engineering, vol. 13, no. 2, pp. 311-324, 2026. Crossref, https://doi.org/10.14445/23488352/IJCE-V13I2P121
Abstract:
The integration of geospatial technologies into rural planning is a transformative approach to achieving the Sustainable Development Goals. Uttar Pradesh in India devised a plan of urbanization in 29 villages of the Yamuna Expressway Industrial Development Authority (YEIDA) region. The plan was drafted in 2012. This was inspired by the PURA (Providing Urban Amenities in Rural Areas) of Dr.A.P.J. Abdul Kalam. This research investigates the Aurangpur of the YEIDA region and explores the efficacy of Geographical Information Systems (GIS) in conducting a micro-level mapping and analysis of socio-economic and infrastructural facilities in a rural context. A comprehensive household survey was conducted in 121 families, capturing data on demographics, caste, income, livestock, and housing, complemented by precise GPS coordinates. The collected data were integrated with the GIS environment for spatial analysis, employing thematic mapping and Kernel Density Estimation (KDE). The results revealed significant spatial clustering, with 28% of Below Poverty Line (BPL) families concentrated in the southern sector of the Aurangpur village. A strong and positive correlation was observed between livestock density hotspots and higher family income. The findings underscored the substantial role of geospatial technology in uncovering intra-village disparities, thereby facilitating targeted, data–driven interventions in infrastructure planning. This methodology provided a replicable model for equitable development in rapidly urbanizing regions. The investigation revealed recommendations to the policy makers and YEIDA authorities based on the Earth Observation (EO) data, geospatial data, and digital mapping developed.
Keywords:
Geospatial Information System, Rural Infrastructure, Spatial Analysis, Kernel Density Function, Poverty Mapping, YEIDA.
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