Abstract
The study of land suitability (LS) for agriculture is one of the most competent mechanisms that show concern for cultivable land and forecasts the supply of sustainable production in semi-arid areas. In view of this, the purpose of the present study is to suggest a conceptual framework for the analysis of LS that would greatly enhance green cover to tackle environmental challenges caused by groundwater recharge (water resources). In semi-arid areas, physiographic components play a fundamental role in agriculture. LULC, NDVI, TGSI, soil, geology, geomorphology, slope, DD, LD, and availability of nutrients affect agricultural production. Analysis of LS may lead to formulating strategies for improving agricultural productivity. A multi-criterion decision-making methodology focused on GIS using the Landsat 8 (OLI) dataset was used to evaluate LS maps in semi-arid regions for agriculture. For LS analysis, the structure and recommendations of the Food and Agriculture Organization were followed and it was found that 23.79% of the land is “highly suitable”, 20.17% of the land is “moderately suitable”, while approximately 28.28% of the total area is calculated to be “marginally suitable” for forestation, approximately 23.20% is “not suitable” for forestation, and water resources or water bodies are 4.53%. The study's methods, techniques, and conclusions can be useful in determining the LS for agriculture in semi-arid regions. The multi-criterion decision-making tool AHP incorporated with GIS introduces a new approach and the findings of the study may be useful for the identification of suitable agricultural land in any part of the world.
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The raw data is obtained from NRSC Bhuvan and USGS website (https://bhuvan.nrsc.gov.in/ and https://earthexplorer.usgs.gov/) which is available free of cost and the findings of this study are available from the corresponding author, upon reasonable request.
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The authors wish to thank all who assisted in conducting this work.
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The first author B. Pradeep Kumar, greatly thankful to Department of Science and Technology (DST), Government of India, for financial support through Inspire programme (Sanction order No. DST/INSPIRE Fellowship/2017/IF170114). Also thankful to USGS for remote sensing data utilization, and Department of Geology, Yogi Vemana University for providing laboratories to carrying out my research work.
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BPK manuscript preparation, Methodology creation, Sample Collection and sample analysis. Remote Sensing and GIS mapping work. KRB methodology and manuscript corrections, corresponding author, English expert. MR Water resource estimation, motivator for the manuscript. MR GIS maps preparation.
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Badapalli, P.K., Kottala, R.B., Madiga, R. et al. Land suitability analysis and water resources for agriculture in semi-arid regions of Andhra Pradesh, South India using remote sensing and GIS techniques. Int J Energ Water Res 7, 205–220 (2023). https://doi.org/10.1007/s42108-021-00151-3
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DOI: https://doi.org/10.1007/s42108-021-00151-3