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Crop-Suitability Analysis Using the Analytic Hierarchy Process and Geospatial Techniques for Cereal Production in North India

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TLDR
In this paper , a study was conducted to assess cereal crops' suitability in India's Haryana state by integrating Analytic Hierarchy Process (AHP) and geographic information system (GIS) technique.
Abstract
Identification of cropland suitability is obligatory to adapting to the increased food needs driven by population expansion, environmental contamination, and climate change. Given this, the present study was conducted to assess cereal crops’ suitability in India’s Haryana state by integrating Analytic Hierarchy Process (AHP) and geographic information system (GIS) technique. Multiple factors were considered for this study, such as rainfall, temperature, soil texture, drainage density, pH, organic carbon, electrical conductivity, and slope. The AHP technique was utilized to decide the weights of each individual parameter using experts’ opinions. The crop-suitability model was developed using the model builder module in ArcGIS 10.8, and each input parameter was reclassified as per the optimum crop-growth requirement and overlaid utilizing the reclassify tool and weighted overlay analysis. The crop suitability classes were estimated as highly suitable, S1 (6%); moderately suitable, S2 (71%); and marginally suitable, S3 (23%) for the calculated arable land for the wheat crop. Similarly, the crop suitability class of rice S2 (28%); S3 (72%), for sorghum S1 (28%); S2 (71%); S3 (1%), for maize S2 (85%); S3 (15%) and for pearl millet S1 (60%); S2 (40%) were also estimated. The study has observed that, as per the soil physico-chemical characteristics and climate, the area is moderately fertile. Therefore, agricultural production can be improved by cultivating the crop in highly and moderately suitable zones. Diversification of marginally suitable regions for crops other than that for which it is not suitable can be taken up, which will also ensure the income security of marginal farmers.

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Journal ArticleDOI

GIS-Based Cropland Suitability Prediction Using Machine Learning: A Novel Approach to Sustainable Agricultural Production

Dorijan Radočaj, +1 more
- 16 Sep 2022 - 
TL;DR: A review of methods for suitability prediction according to abiotic environmental criteria is provided in this paper , where a machine learning-based approach is used to determine cropland suitability.
Journal ArticleDOI

Site suitability assessment for traditional betel vine cultivation and crop acreage expansion in Tamluk Subdivision of Eastern India using AHP-based multi-criteria decision making approach

TL;DR: In this paper , the authors employed the analytical hierarchical process-based multi-criteria decision-making approach together with geospatial inputs/methods to assess land suitability for betel leaf cultivation in Tamluk Subdivision of Purba Medinipur district in West Bengal, India.
Journal ArticleDOI

Crop suitability analysis by adopting geo-spatial algorithm: a case study of Sirajganj district (flood-prone area) in Bangladesh

TL;DR: In this paper , the authors proposed a suitable cropping pattern to mitigate the detrimental effects of flooding in Sirajganj district, a flood-prone area of Bangladesh, and conducted a crop suitability analysis of prominent Kharif (rice and maize) and Rabi (potato and wheat) crops.
Journal ArticleDOI

Environmental impact assessment of multi-source solid waste based on a life cycle assessment, principal component analysis, and random forest algorithm

TL;DR: In this article , the authors proposed a cyclic model for multi-source solid waste disposal in Dongguan in Guangdong Province, which could promote and contribute to the sustainable development of the Greater Bay Area.
Journal ArticleDOI

Construction of a water resource suitability index for agricultural production and matching analysis of cultivated land in Lhasa, Tibet

TL;DR: In this article , a water resource suitability index for agricultural production (WRSIA) was constructed for agricultural development using irrigation water supply convenience (IWSC) and precipitation conditions.
References
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Journal ArticleDOI

Decision making with the analytic hierarchy process

TL;DR: The Analytic Hierarchy Process (AHP) is a theory of measurement through pairwise comparisons and relies on the judgements of experts to derive priority scales that measure intangibles in relative terms.
Journal ArticleDOI

Spatial sensitivity analysis of multi-criteria weights in GIS-based land suitability evaluation

TL;DR: A novel approach of examining multi-criteria weight sensitivity of a GIS-based MCDM model explores the dependency of model output on the weights of input parameters, identifying criteria that are especially sensitive to weight changes and to show the impacts of changing criteria weights on the model outcomes in spatial dimension.
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Agricultural land use suitability analysis using GIS and AHP technique

TL;DR: In this paper, an analytical hierarchy process (AHP) method was used to determine suitable lands for agricultural use in the Yusufeli district of Artvin city (Turkey), where the current agricultural land in the district center and 3 villages will be completely inundated while the land in 22 villages would be partially inundated due to three large dams currently being constructed.
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Integration of MultiCriteria Decision Analysis in GIS to develop land suitability for agriculture: Application to durum wheat cultivation in the region of Mleta in Algeria

TL;DR: A spatial decision support system has been developed for establishing the land suitability map for agriculture that incorporates the multicriteria analysis method ELECTRE Tri in a GIS (ArcGIS) within the GIS program package environment and the coherence of the obtained maps confirms the system effectiveness.
Journal ArticleDOI

Multi-criteria land suitability analysis for agriculture in hilly zone

TL;DR: GIS based multi-criterion decision making approach using IRS P6 LISS-IV dataset was used to analyze land suitability for agriculture in hilly zone and experts' opinions and correlation analyses were used to decide the ranks of influencing criterion whereas pairwise comparison matrix in 'Comparison for Super Decision Software' used to determine the weights.
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