Delineation of groundwater potential zonation using geoinformatics and AHP techniques with remote sensing data

Heliyon, Journal Year: 2024, Volume and Issue: 10(3), P. e25532 - e25532

Published: Feb. 1, 2024

Among all other valuable natural resources, groundwater is crucial for global economic growth and food security. This study aimed to delineate potential zones (GWPZ) in the Gidabo watershed of Main Ethiopian Rift. The demand supplies various applications has risen recently due rapid population upsurge. An integrated Geographical Information System, Remote Sensing, Analytical Hierarchy Process (AHP) been utilized. Eight regulating factors, including rainfall, elevation, drainage density, soil types, lineament slope, lithology, land use/land cover, have taken analysis. To assign suitable weights each factor, AHP was employed, as element contributes differently occurrence. weighted overlay analysis (WOA) technique then used ArcGIS environment integrate thematic layers generate a GWPZ map. delineated classified into five categories. poor covered 18.7 %, low 33.8 moderate 23.4 high 18.1 very 5.8 % area. Well spring data were validate model, ROC (Receiver Operating Characteristic) curve method applied. results showed good accuracy 76.8 %. result this research can be planning managing resources watershed.

Language: Английский

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Optimal Land Selection for Agricultural Purposes Using Hybrid Geographic Information System–Fuzzy Analytic Hierarchy Process–Geostatistical Approach in Attur Taluk, India: Synergies and Trade-Offs Among Sustainable Development Goals

Sustainability, Journal Year: 2025, Volume and Issue: 17(3), P. 809 - 809

Published: Jan. 21, 2025

The precise selection of agricultural land is essential for guaranteeing global food security and sustainable development. Additionally, suitability (AgLS) analysis crucial tackling issues including resource scarcity, environmental degradation, rising demands. This research examines the synergies trade-offs among development goals (SDGs) using a hybrid geographic information system (GIS)–fuzzy analytic hierarchy process (FAHP)–geostatistical framework AgLS in Attur Taluk, India. area was chosen its varied agro-climatic conditions, riverine habitats, importance. Accordingly, data from ten topographical, climatic, soil physiochemical variables, such as slope, temperature, texture, were obtained analyzed to carry out study. geostatistical demonstrated spatial variability parameters, providing insights into key factors study area. Based on receiver operating characteristic curve analysis, results showed that FAHP method (AUC = 0.71) outperformed equal-weighting scheme 0.602). Moreover, mapping designated 17.31% highly suitable (S1), 41.32% moderately (S2), 7.82% permanently unsuitable (N2). identified reinforcing conflicting correlations with SDGs, emphasizing need policies address trade-offs. findings 40% alignment climate action (SDG 13) via improved resilience, 33% clean water 6) by identifying low-salinity zones, 50% zero hunger 2) through systems. Conflicts arose SDG 13 (20%) due reliance rain-fed agriculture, 15 (11%) 2 (13%) inefficiencies low-productivity zones. A plan (SAP) can tackle these promoting drought-resistant crops, nutrient management, participatory land-use planning. provide replicable integrating agriculture sustainability objectives worldwide.

Language: Английский

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Agricultural Land Suitability Analysis for Land Use Planning: The Case of the Madrid Region

Land, Journal Year: 2025, Volume and Issue: 14(1), P. 134 - 134

Published: Jan. 10, 2025

Agricultural land is a key resource for territorial resilience. In the European context, fertile soils are under pressure not only from urbanisation processes, abandonment and establishment of non-agricultural uses but also agriculture that well adapted to resources. order inform urban planning, methodology proposed applied Madrid region analyse suitability agricultural with respect agrological quality. The majority in agroecological quality land; larger areas over-exploited located along some region’s rivers Campiña, while under-utilised mainly found south-west metropolitan comarcas. This based on official open-access information, so it can be easily replicated used planning. We propose three strategies depending use: introduction crops priority horticulture or arable crops, protection ecological regeneration areas.

Language: Английский

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Land suitability assessment for sisal production: A Machine Learning and Analytical Hierarchy Process integrated approach

Soil Advances, Journal Year: 2025, Volume and Issue: unknown, P. 100048 - 100048

Published: April 1, 2025

Language: Английский

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Flood risk susceptibility analysis in Larkana district Pakistan using multi criteria decision analysis and geospatial techniques

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 20, 2025

Flooding is one of the most devastating natural disasters in worldwide, with significant socioeconomic and environmental impacts. In such a scenario, flood susceptibility analysis essential for successful risk management disaster preparedness. The Larkana district located densely populated area Sindh province, approximately 1.8 million population 0.32 households, highly susceptible to floods due its geographical location, river systems, hot climatic patterns extremely high temperature summer mild winter. often faces risks mainly monsoon rains overflow Indus River which lead widespread flooding. research aims identify quantify key factors, including rainfall pattern, distance river, topography, land use/land cover, soil texture, vegetation index, drainage infrastructure. AHP was applied prioritize these factors based on expert opinions their relative significance contributing vulnerability. GIS employed spatial mapping zones, allowing detailed visualization high-risk areas across district. For this study, various data sources as topographic data, use landcover information, infrastructure were used develop comprehensive model. method determine weights consistency ratio (CR) techniques generate maps by considering all nine factors. Flood levels further classified into five different classes very low, moderate, high. By using AHP, each parameter calculated percentage, it determined that four out parameters had 79% impact hazard. These are ranked influential hazards study area, rainfall, slope, elevation having greatest influences, while LULC, TWI, NDVI, type, curvature 21% impacts, much less compared top parameters. After that, reclassified. superimposed weighted overlay order show 7.65% entire at risk, 63.89% 28.38% moderate 0.12% low risk. findings established complete model will facilitate policymakers authorities identifying locations prioritizing mitigation measures, ultimately reducing local communities

Language: Английский

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Integration Between GIS, Remote Sensing Analysis and AHP for Assessment of Cultivating Suitability in Western Desert Land of Egypt

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: April 21, 2025

The Western Desert of Egypt offers substantial potential for agricultural development to mitigate the nation’s food security issues. study uses a multi-criteria decision-making framework based on FAO land suitability classification and Analytical Hierarchy Process (AHP) determine if area is good farming. Essential factors, such as evapotranspiration (ETo), precipitation, soil types, slope, use/land cover (LULC), are classified merged into Remote Sensing (RS) GIS-based weighted overlay analysis provide detailed map. results show that we categorize 20.74% research highly suitable (S1) 41.56% moderately (S2). Furthermore, 37.36% marginally (S3), while just 0.33% labeled currently not (N1), there no regions designated permanently (N2). This suggests feasibility using whole region purposes, albeit differing degrees intervention may be necessary. lack N2 category underscores viability reclamation initiatives, contingent upon effective resource management. shows combining AHP, GIS Rs technologies can help you figure out farming, which big making smart decisions about long-term farming planning. practical recommendations policymakers improve distribution emphasize advancement in Desert, bolstering national initiatives strengthen security.

Language: Английский

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Integrating extreme temperature metrics into tea land suitability models: a GIS-based assessment in the ecological and cultural tourism circle in Western Hubei, China

Theoretical and Applied Climatology, Journal Year: 2025, Volume and Issue: 156(5)

Published: May 1, 2025

Language: Английский

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Application of geospatial technology on land suitability analysis for wheat and maize farming: In a case of Guder sub-watershed North West Oromia, Ethiopia

Heliyon, Journal Year: 2024, Volume and Issue: 10(13), P. e33557 - e33557

Published: June 27, 2024

Cereal crops like wheat and maize are crucial to providing food security in rural areas of Ethiopia. However, due population growth, agricultural practices for these cereal have been expanded vulnerable areas, increasing land degradation. Geospatial technologies essential decision-making reduce degradation ensure sustainable agriculture activities. In the Guder sub-watershed, Oromia regional state Ethiopia, where has a persistent issue, suitability study is crucial. This focused on which aimed analyze based ten controlling parameters, including elevation, slope, soil texture, depth, PH, drainage, proximity road, temperature, rainfall use/land cover, two most significant (wheat maize). All factors were weighted accordance with relative importance each component appropriateness using MCDA AHP method, recommendations numerous writers expert opinions. The findings showed that 6 %, 50.58 23.26 20.26 % total area highly, moderately, marginally not suitable cultivation, respectively, whereas 5.1 57.3 17.3 20.3 cultivating crop respectively. result support decision makers develop use planning thereby improve productivity minimize

Language: Английский

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Advancing Agricultural Land Suitability in Urbanized Semi-Arid Environments: Insights from Geospatial and Machine Learning Approaches

ISPRS International Journal of Geo-Information, Journal Year: 2024, Volume and Issue: 13(12), P. 436 - 436

Published: Dec. 3, 2024

Rising food demands are increasingly threatened by declining crop yields in urbanizing riverine regions of Southern Asia, exacerbated erratic weather patterns. Optimizing agricultural land suitability (AgLS) offers a viable solution for sustainable productivity such challenging environments. This study integrates remote sensing and field-based geospatial data with five machine learning (ML) algorithms—Naïve Bayes (NB), extra trees classifier (ETC), random forest (RF), K-nearest neighbors (KNN), support vector machines (SVM)—alongside land-use/land-cover (LULC) considerations the food-insecure Dharmapuri district, India. A grid searches optimized hyperparameters using factors as slope, rainfall, temperature, texture, pH, electrical conductivity, organic carbon, available nitrogen, phosphorus, potassium, calcium carbonate. The tuned ETC model showed lowest root mean squared error (RMSE = 0.15), outperforming RF 0.18), NB 0.20), SVM 0.22), KNN 0.23). AgLS-ETC map identified 29.09% area highly suitable (S1), 19.06% moderately (S2), 16.11% marginally (S3), 15.93% currently unsuitable (N1), 19.21% permanently (N2). By incorporating Landsat-8 derived LULC to exclude forests, water bodies, settlements, these estimates were adjusted 19.08% 14.45% 11.40% 10.48% 9.58% Focusing on model, followed land-use analysis, provides robust framework optimizing planning, ensuring protection ecological social developing countries.

Language: Английский

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Soil Characteristics, Taxonomy and land suitability of a lateritic Mantle for rain-fed maize (Zea mays) Agriculture in the Cameroon Western Highlands

African Journal of Agricultural Research, Journal Year: 2025, Volume and Issue: 21(2), P. 147 - 161

Published: Feb. 28, 2025

Language: Английский

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