Dataset Information

Data on identification of desertified regions in Anantapur district, Southern India by NDVI approach using remote sensing and GIS.

ABSTRACT: Present dataset aims at the inventory data on preparation of Desertification Status Maps (DSM) for the first time in semi-arid region of Anantapur district in the state of Andhra Pradesh, South India by applying Normalized Difference Vegetation Index (NDVI) with acquired Remote Sensing (RS) satellite imageries and processed in ERDAS Imagine and ArcGIS software's. The NDVI has been classified into five such as water body, vegetation, fallow land, degradation land, and desertified land. Further, degradation land has been decreased to 4.87% which lead to desertification in the study region. The current research data will be resourceful to the environmental scientists and planning agencies who can utilize optimum for sustainable development and good governance in land degradation, desertification, and conserve land resources.

SUBMITTER: Kumar BP

PROVIDER: S-EPMC7186516 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Data on identification of desertified regions in Anantapur district, Southern India by NDVI approach using remote sensing and GIS.

Kumar B Pradeep BP Babu K Raghu KR Ramachandra M M Krupavathi C C Swamy B Narayana BN Sreenivasulu Y Y Rajasekhar M M

Data in brief 20200418

Present dataset aims at the inventory data on preparation of Desertification Status Maps (DSM) for the first time in semi-arid region of Anantapur district in the state of Andhra Pradesh, South India by applying Normalized Difference Vegetation Index (NDVI) with acquired Remote Sensing (RS) satellite imageries and processed in ERDAS Imagine and ArcGIS software's. The NDVI has been classified into five such as water body, vegetation, fallow land, degradation land, and desertified land. Further, d ...[more]

PMID: 32368593

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Project description:GIS and remote sensing techniques were effectively used to analyse the morphometric parameters including linear, geometric, basin texture (aerial) and relief aspects of the Halda River Basin, Bangladesh. Along with measuring the morphometric parameters using predetermined formulas, advanced geo-computing tools of spatial analysis, cartography, math, geoprocessing and geometric analysis were employed to carry out the spatial distribution of selected parameters, especially aerial parameters. The linear aspect indicates the basin is six-order and oval-shaped. The bifurcation ratio (4.03) and relevant parameters indicate the moderate effect of geology and structural control is evident. The mean stream length (1.27) and Rho value (ranges between 0.11 and 0.20) indicate high runoff in steep areas and hydrologic storage capacity in flat areas. The stream frequency (0.83), drainage density (1.22), drainage intensity (0.68), infiltration ratio (1.02), length of the overland flow (0.41), and constant of channel maintenance (0.82) indicate the presence of moderate hard rock, less structural disturbances and moderate to high surface runoff in the basin. Basin relief (489 m), relative relief (2.02), ruggedness number (400), Melton's ruggedness number (12.43), and mean slope (9.33%) indicate the potential of high erosion and material transfer. The spatial distribution of selected aerial aspects significantly correlated to elevation and slope. The hierarchical pattern and spatial distribution of the morphometric parameters indicate areas with high slopes and lower-order streams have a high potential to be affected by soil erosion, landslides and flash floods, elsewhere, the areas with low slopes are prone to short-duration riverine floods. The research findings will help policymakers for integrated river basin management, agricultural development, and water management. In addition, researchers of morphohydrological, geological and climatological research will be beneficiary.

Dataset Information

Data on identification of desertified regions in Anantapur district, Southern India by NDVI approach using remote sensing and GIS.

Publications

Data on identification of desertified regions in Anantapur district, Southern India by NDVI approach using remote sensing and GIS.

Similar Datasets

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