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Multicriteria Spatial Decision Support System for Soil Fertility Assessment in Agriculture
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 174 - Number 10 |
| Year of Publication: 2021 |
| Authors: Neelam Agrawal, Kesari Verma, Tarun Kumar |
10.5120/ijca2021920975
|
Neelam Agrawal, Kesari Verma, Tarun Kumar . Multicriteria Spatial Decision Support System for Soil Fertility Assessment in Agriculture. International Journal of Computer Applications. 174, 10 ( Jan 2021), 29-34. DOI=10.5120/ijca2021920975
Abstract
The main goal of smart agriculture is balanced fertilization that is guided by the conflicting objectives of sustainability and productivity. The Geographical information system (GIS) is an effective way to manage, store, analyze, retrieve, modify, and display spatial information. However, it lacks in supporting spatial decisions through analytical approaches. The integrated approach of GIS and Multi-Criteria Decision Analysis (MCDA) models allow us to overcome such tradeoffs. This study aims to develop a web-GIS-based, Multi-Criteria Spatial Decision Support System (MCSDSS) to support fertility assessment of the farmland. The proposed framework is useful in identifying the farmland's optimum fertilizer requirements, which will ultimately increase farm profitability, productivity, and sustainability with reduced environmental pollution. To achieve the objective multiple soil attributes with varying significance and nature are evaluated using the MCDA models of Weighted Sum Model (WSM), Weighted Product Model (WPM), and Weighted Aggregated Sum Product Assessment (WASPAS). The proposed multi-criteria spatial decision support system suggests soil's fertilizer requirement into the categories of low, moderate, and high levels. The results reveal that the WPM MCDA model outperformed among all with an accuracy of 82.9%.
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