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In order to minimize human impact on the environment, it is crucial to determine the best way to utilize land through assessments of its suitability. This research focuses on the Anantnag district in the Kashmir valley, exploring its potential as a suitable area for mulberry agroforestry. Consequently, the selection of suitable sites for mulberry-based agroforestry has become an essential element of sustainable land use planning and agriculture, with the aim of maintaining ecological equilibrium. In the context of a Geographic Information System (GIS), we employ a method called multi-criteria assessment to evaluate the suitability of a specific site for mulberry agroforestry in the study area. This assessment involves considering various factors such as slope, temperature, rainfall, land use and land cover (LULC), as well as the physical and chemical properties of the soil. To assign scores to these criteria, we utilized the analytic hierarchy process (AHP) technique, conducted interviews with local experts, and referred to existing literature. By applying a weighted overlay analysis, which takes into account the importance of each parameter, we generated a map depicting the suitability of the research area for mulberry agroforestry. The map for mulberry agroforestry suitability in the study area indicates that 16.59% of the land is highly suitable, 28.16% is moderately suitable, 40.29% is marginally suitable, and 14.96% is unsuitable. To ensure the accuracy of the findings, satellite images, Sentinel-2b LULC mapping, and GPS-enabled field surveys were extensively employed to verify the results. These findings can be utilized by farmers, regional developers, and the government to inform their decisions regarding potential mulberry agroforestry areas and develop sustainable agroforestry management strategies for the region. [ABSTRACT FROM AUTHOR]

This study investigates land use and land cover (LULC) changes in Samastipur District, Bihar, from 2000 to 2020 using Landsat data and GIS techniques. Our analysis reveals a significant increase in agricultural land from 64.24% to 84.80%, amounting to a rise of 59,615 ha. During the same period, natural vegetation decreased sharply from 20.76% to 3.19%, and water bodies diminished from 2.72% to 1.82%. Settlement areas expanded by 38.30%, while barren land was reduced by 44.65%. Accuracy assessments showed substantial agreement, with Kappa values improving from 0.64 in 2000 to 0.88 in 2020, and overall accuracy rising from 71.62% to 90.74%. The Productivity Rating Index (PRI) for Pusa Farm indicates high suitability for major crops, with PRI values of 82.90% for wheat, 106.57% for sugarcane, and 137.14% for paddy. These findings underscore the dynamic changes in land use and the effectiveness of remote sensing for monitoring and managing agricultural resources, providing valuable insights for sustainable land management and policy-making. [ABSTRACT FROM AUTHOR]

The Gedeo zone agroforestry systems are the main source of Ethiopia's coffee beans. However, land-use and suitability analyses are not well documented due to complex topography, heterogeneous agroforestry, and lack of information. This research aimed to map the coffee coverage and identify land suitability for coffee plantations using remote sensing, Geographic Information Systems (GIS), and the Analytical Hierarchy Process (AHP) in the Gedeo zone, Southern Ethiopia. Remote sensing classifiers often confuse agroforestry and plantations like coffee cover with forest cover because of their similar spectral signatures. Mapping shaded coffee in Gedeo agroforestry using optical or multispectral remote sensing is challenging. To address this, the study identified and mapped coffee coverage from Sentinel-1 data with a decibel (dB) value matched to actual coffee coverage. The actual field data were overlaid on Sentinel-1, which was used to extract the raster value. Pre-processing, classification, standardization, and reclassification of thematic layers were performed to find potential areas for coffee plantation. Hierarchy levels of the main criteria were formed based on climatological, edaphological, physiographic, and socioeconomic factors. These criteria were divided into 14 sub-criteria, reclassified based on their impact on coffee growing, with their relative weights derived using AHP. From the total study area of 1356.2 km2, the mapped coffee coverage is 583 km2. The outcome of the final computed factor weight indicated that average annual temperature and mean annual rainfall are the primary factors, followed by annual mean maximum temperature, elevation, annual mean minimum temperature, soil pH, Land Use/Land Cover (LULC), soil texture, Cation Exchange Capacity (CEC), slope, Soil Organic Matter (SOM), aspect, distance to roads, and distance to water, respectively. The identified coffee plantation potential land suitability reveals unsuitable (413 km2), sub-suitable (596.1 km2), and suitable (347.1 km2) areas. This study provides comprehensive spatial details for Ethiopian cultivators, government officials, and agricultural extension specialists to select optimal coffee farming locations, enhancing food security and economic prosperity. [ABSTRACT FROM AUTHOR]

Duku (Lansium domesticum) is an endemic plant in Indonesia with various benefits and distinctive tastes that many people favor. Duku originating from Kudus is known as Duku Sumber, one of the five superior duku varieties. The problem encountered today is the decreasing number of Duku Sumber plants due to land use change, and there has been no effort to increase the plant population. Information on land suitability as a basis for developing crops does not yet exist, so data about land suitability will be used as information on the wider distribution of planting areas in Kudus. This study aimed to evaluate the suitability and land use of Duku Sumber plants in the Kudus Regency. Geographic information systems and matching methods were applied to map the distribution of land suitability for Duku Sumber. The results showed that the potential and actual land suitability class for Duku Sumber are very suitable (S1) and quite suitable (S2) for the Jekulo, Hadipolo, Tenggeles, Golantepus, and Megawon areas, while the slightly suitable (S3) are Klaling, Ngembalrejo, Mejobo and Jati Wetan. The availability of nutrients (na) for nitrogen and potassium is the dominant limiting factor in this area. Nitrogen content in Jati Wetan (0.12%), Klaling (0.19%), and Hadiwarno (0.19%), while potassium content in Ngembalrejo (16.47 ppm) and Mejobo (18.57 ppm). Limitations in this area can be overcome by adding nitrogen and potassium fertilizers to become suitable land. [ABSTRACT FROM AUTHOR]

Site selection analysis is a fundamental methodology for the regeneration of Xylella fastidiosa subsp. pauca (Xfp) infected areas, with the introduction of Xfp immune/resistant tree crop species. The diffusion of these species could be assessed by combining ecological optima data, climate and soil attributes of the study area, and GIS tools. The study aimed to evaluate the potential suitability of eight Xfp immune tree crops, including Neglected and Underutilized Species (NUS) drought-resistant and new species, as follows: carob, hawthorn, prickly pear, mulberry, loquat, walnut, persimmon, and avocado. The use of GIS tools allowed the integration of different layers, such as climate and soil, to contribute to the identification of suitable areas for the cultivation of these tree crops helping the policy-makers to define plans for land use at a regional scale. Following the ecological optima, which represents the ideal environmental conditions for each species, this analysis provided valuable insights into the compatibility of the selected tree crops with the prevailing environmental factors in the affected area. Carob revealed its remarkable adaptability and drought resistance, presenting the broadest suitability. Hawthorn and Loquat also exhibited high adaptability, indicating their potential contribution to agricultural diversification and ecological balance. Conversely, crops like Avocado, Prickly pear, and Walnut, despite their economic value, demonstrated limited adaptability due to their specific soil and climate requirements. These findings can potentially contribute to the development of strategies for the policymakers, aimed at diversifying and enhancing the resilience of agricultural systems, facing the problem of emerging quarantine pathogens and the incoming climate change, and highlighting the possibility of opening new cultivation scenarios in the zones affected by Xfp. [ABSTRACT FROM AUTHOR]

This paper investigates the suitability and availability of land for development in the Eastern Development Region (WP Timur) of Bogor Regency, West Java. As part of the Jakarta, Bogor, Depok, Tangerang, Bekasi, Puncak, Cianjur (Jabodetabekpunjur) National Strategic Area, WP Timur plays a crucial role in urban development, environmental conservation, and agricultural expansion. This study utilizes Geographic Information System (GIS) tools and Analytic Hierarchy Process (AHP) combined with Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis to assess land use suitability and resolve land availability issues. The research identifies that a significant portion of WP Timur's current land use comprises rainfed paddy fields, irrigated rice fields, and productive mixed gardens. These are essential for local agriculture but must align with the Regional Spatial Plan (RTRW) of Bogor Regency to support sustainable urbanization and industrial development. Analysis reveals challenges related to land conflicts and legal disputes, highlighting the need for clear land tenure and effective management strategies. By evaluating existing land use against the RTRW guidelines, the study identifies suitable and unsuitable areas for various land uses, emphasizing the importance of integrated spatial planning for balanced development. The findings provide valuable insights for policymakers and urban planners to optimize land utilization, enhance regional competitiveness, attract investments, and improve local community welfare in WP Timur. [ABSTRACT FROM AUTHOR]

Exponential population increases are threatening food security, particularly in mountainous areas. One potential solution is dual-use intercropped agroforestry systems such as olive (Olea europaea)–maize (Zea mays), which may mitigate risk by providing multiple market sources (oil and grain) for smallholder producers. Several studies have conducted integrated agroforestry land suitability analyses; however, few studies have used machine learning (ML) algorithms to evaluate multiple variables (i.e., soil physicochemical properties and climatic and topographic data) for the selection of suitable rainfed sites in mountainous terrain systems. The goal of this study is therefore to identify suitable land classes for an integrated olive–maize agroforestry system based on the Food and Agriculture Organization (FAO) land suitability assessment framework for 1757 km2 in Khyber Pakhtunkhwa province, Pakistan. Information on soil physical and chemical properties was obtained from 701 soil samples, along with climatic and topographic data. After determination of land suitability classes for an integrated olive–maize-crop agroforestry system, the region was then mapped through ML algorithms using random forest (RF) and support vector machine (SVM), as well as using traditional techniques of weighted overlay (WOL). Land suitability classes predicted by ML techniques varied greatly. For example, the S1 area (highly suitable) classified through RF was 9%↑ than that of SVM, and 8%↓ than that through WOL. The area of S2 (moderately suitable) classified through RF was 18%↑ than that of SWM and was 17%↓ than the area classified through WOL; similarly, the S3 (marginally suitable) class area via RF was 27%↓ than that of SVM, and 45%↓ than the area classified through WOL. Conversely, the area of N2 (permanently not suitable class) classified through RF and SVM was 6%↑ than the area classified through WOL. Model performance was assessed through overall accuracy and Kappa Index and indicated that RF performed better than SVM and WOL. Crop suitability limitations of the study area included high elevation, slope, pH, and large gravel content. Results can be used for sustainable intensification in mountainous rainfed regions by expanding intercrop agroforestry systems in developing nations to close yield gaps. [ABSTRACT FROM AUTHOR]

If adequately treated, sewage sludge can be a safe and sustainable source of nutrients and organic matter for soil enhancement, improving agriculture productivity. To close loops in the sewage treatment-agriculture nexus, it is crucial to compare sludge generation (quantity and location of treatment plants) and possible sites for sludge application on a regional level. This study used spatial multicriteria analysis to assess land suitability for sludge application based on several criteria related to soil, land use characteristics, and environmental legal constraints. The study area comprised two large watersheds (a total area of 52,870 km2) in Minas Gerais state, southeast Brazil. Results indicated a total sludge production of 21,778 t dry solids.year−1, which is currently mainly disposed of in landfills (76%). Even though approximately 52% of the study area presented constraints to sludge application in agricultural fields, suitable areas can receive the total amount of sludge generated. In some cases, the most suitable areas would afford for a capacity 20-fold bigger than the sludge produced. Although other factors should be addressed for effectively applying sludge to agriculture (e.g. social acceptance), this work shows the usefulness of the spatial multicriteria analysis tool to select suitable sites. [ABSTRACT FROM AUTHOR]

Land suitability (LS) classifications are essential for efficient and sustainable agricultural land use. With climate change, future LS classifications are necessary to ensure that crop growth remains sustainable and prevents land degradation. This study develops a current LS classification for rainfed corn (Zea mays) growth in the state of Georgia, USA, which is validated using historical census data on yield, acres planted, and corn crop lost. Significant (p < 0.05) differences were found between yield, acres planted, and crop loss percentage across LS classes for many years. Soil factors (Ph and soil texture) showed significant differences in fewer years compared to climate and topography factors, as soil factors can be altered by management practices such as liming and irrigation. Future LS classes determined by climate factors indicated a shift to the northwest of 150–300 km by the year 2100 based on the RCP4.5 or RCP8.5 emissions scenarios. The northwards shift in more suitable land due to rising maximum temperatures is expected to limit rainfed corn growth in Georgia in the future. As urban areas become more suitable for corn growth, farmers may need to plant crops earlier, irrigate, or switch to different crops. These results have important implications for agricultural planning and policy in the state of Georgia. [ABSTRACT FROM AUTHOR]

Duku (Lansium domesticum) is an endemic plant in Indonesia with various benefits and distinctive tastes that many people favor. Duku originating from Kudus is known as Duku Sumber, one of the five superior duku varieties. The problem encountered today is the decreasing number of Duku Sumber plants due to land use change, and there has been no effort to increase the plant population. Information on land suitability as a basis for developing crops does not yet exist, so data about land suitability will be used as information on the wider distribution of planting areas in Kudus. This study aimed to evaluate the suitability and land use of Duku Sumber plants in the Kudus Regency. Geographic information systems and matching methods were applied to map the distribution of land suitability for Duku Sumber. The results showed that the potential and actual land suitability class for Duku Sumber are very suitable (S1) and quite suitable (S2) for the Jekulo, Hadipolo, Tenggeles, Golantepus, and Megawon areas, while the slightly suitable (S3) are Klaling, Ngembalrejo, Mejobo and Jati Wetan. The availability of nutrients (na) for nitrogen and potassium is the dominant limiting factor in this area. Nitrogen content in Jati Wetan (0.12%), Klaling (0.19%), and Hadiwarno (0.19%), while potassium content in Ngembalrejo (16.47 ppm) and Mejobo (18.57 ppm). Limitations in this area can be overcome by adding nitrogen and potassium fertilizers to become suitable land.

Since the 1980s, the Jakarta Metropolitan Area has experienced rapid urbanization, impacting the dynamics of built-up areas and agricultural land. This paper aims to understand the dynamics of rural–urban transition concerning spatial land cover in the last 20 years. The data was obtained from the Ministry of Environment and Forestry, Indonesia, and land system maps. The change in built-up land from 2000 to 2011 showed an increasing trend of converting second-class paddy fields. This situation indicates rapid urbanization is taking place. Meanwhile, the second phase (2011–2019) shows a different pattern of massive change in peri-urban areas due to rural forces and increasingly limited space in the city center, allowing only low-intensity expansion. Peri-urbanization does not necessarily involve large-scale conversion of agricultural land but a shift in regional growth that extends into what used to be rural areas. Retaining more agricultural land around Greater Jakarta provides the dual benefits of providing agricultural products for the city as well as maintaining the region’s ecosystem. [ABSTRACT FROM AUTHOR]

Exponential population increases are threatening food security, particularly in mountainous areas. One potential solution is dual-use intercropped agroforestry systems such as olive (Olea europaea)–maize (Zea mays), which may mitigate risk by providing multiple market sources (oil and grain) for smallholder producers. Several studies have conducted integrated agroforestry land suitability analyses; however, few studies have used machine learning (ML) algorithms to evaluate multiple variables (i.e., soil physicochemical properties and climatic and topographic data) for the selection of suitable rainfed sites in mountainous terrain systems. The goal of this study is therefore to identify suitable land classes for an integrated olive–maize agroforestry system based on the Food and Agriculture Organization (FAO) land suitability assessment framework for 1757 km2 in Khyber Pakhtunkhwa province, Pakistan. Information on soil physical and chemical properties was obtained from 701 soil samples, along with climatic and topographic data. After determination of land suitability classes for an integrated olive–maize-crop agroforestry system, the region was then mapped through ML algorithms using random forest (RF) and support vector machine (SVM), as well as using traditional techniques of weighted overlay (WOL). Land suitability classes predicted by ML techniques varied greatly. For example, the S1 area (highly suitable) classified through RF was 9%↑ than that of SVM, and 8%↓ than that through WOL. The area of S2 (moderately suitable) classified through RF was 18%↑ than that of SWM and was 17%↓ than the area classified through WOL; similarly, the S3 (marginally suitable) class area via RF was 27%↓ than that of SVM, and 45%↓ than the area classified through WOL. Conversely, the area of N2 (permanently not suitable class) classified through RF and SVM was 6%↑ than the area classified through WOL. Model performance was assessed through overall accuracy and Kappa Index and indicated that RF performed better than SVM and WOL. Crop suitability limitations of the study area included high elevation, slope, pH, and large gravel content. Results can be used for sustainable intensification in mountainous rainfed regions by expanding intercrop agroforestry systems in developing nations to close yield gaps.

Abstract Land use evaluation and capacity assessment for sustainable urban development in Ahvaz city has become crucial due to rapid urban expansion negatively impacting current and future development. Urban population growth and resource demands have led to a decline in environmental quality. Over the past decades, Ahvaz has identified potential areas for future expansion until 2030. This study assesses the city's physical expansion and spatial development patterns, aiming to identify optimistic future development scenarios. Emphasizing balanced and equitable development, the study focuses on suitable areas, environmental preservation, pollution reduction, and mitigating urban hazards . Various factors, including land use, soil type, vegetation density, landform, groundwater level, geology, and distances from railways, industries, roads, hinterland cities, water networks, faults, and the city itself, are considered. Three decision-making methods—logic, Analytical Hierarchy Process (AHP), and integrated Fuzzy-AHP—are applied to map urban physical development. Fuzzy logic, AHP models, Expert Choice, Arc GIS software, and a land fit zoning map are used for data analysis. The AHP assesses the factors' relative importance, followed by standardization based on fuzzy set theory. Criteria factors are then combined using AHP and fuzzy logic to generate a land suitability map. The study identifies five zones for Ahvaz's future development—very high, high, medium, low, and very low—based on their physical expansion potential. The third scenario, supported by maps, indicates favorable conditions for future development in the northwest and southwest zones, considering environmental characteristics, infrastructure, and land continuity.

Drought is a major challenge in developing the integrated farming system (IFS) in Trenggalek Regency, making it one of the factors contributing to the construction of the Tugu Dam. Additionally, in developing the IFS area, it is necessary to assess soil fertility and land suitability evaluation for food and livestock feed commodities. The research was conducted in Tugu and Karangan Sub-Districts, Trenggalek Regency by conducting spatial analysis and soil survey at locations potentially affected by dam construction and soil samples analysis at the laboratory. The results of this study found that the level of soil fertility at the research site was included in the low to very low class with characteristics of acidic pH, very low C-organic, very low total N and low base saturation. While the results of the actual land suitability evaluation of rice, maize, and elephant grass showed the land suitability class S3 with limiting factors of C-organic, pH, total N, P2O5, and base saturation.

The characteristics and quality of soil can affect the suitability of a land for a certain type of land use. The quality of the soil itself has a close relationship with the characteristics of the land because it has a score weight that affects the suitability of the land. Land characteristics such as slope and land cover affect soil quality such as nutrient content. Erosion calculations using the USLE method show that slope and land cover affect the rate of erosion, where erosion can leach nutrients that result in decreased soil quality. This study aims to determine the suitability of land for carrot plants in Sirampog District. Sirampog District has suitable marginal to suitable temperature, suitable humidity and rainfall, suitable soil texture (loam, sandy loam, and silty loam) relatively low cation exchange capacity (CEC) with very high base saturation, acidic soil pH, medium C-organic, medium N-total, very low P2O5 and very low K2O. This study provided an evaluation of land suitability so that farmers use effective and efficient techniques in cultivating carrot plants, so that carrot crop productivity can be optimal.

The plantation sector, especially tobacco plants, is the biggest contributor to the country's foreign exchange value non-mining through tobacco excise and export. With the increasing number of active smokers in Indonesia, the need for tobacco continues to increase, emphasizing the role of this crop in the economy and providing large profits for farmers. However, along with the growing issue of land use change, recently many tobacco plants have been planted on unsuitable land. The research was conducted on all rice fields in Bondowoso Regency from October 2022 to March 2023. The land suitability evaluation method was used to assess land characteristics that affect tobacco plant growth. The parameters used were soil pH, soil texture, C-organic, electrical conductivity, cations bases (K, Ca, Na, Mg), cation exchange capacity (CEC), base saturation, total N, available and exchangeable K, slope, temperature, and rainfall. Data analysis was carried out by matching techniques, namely matching land characteristics with the growing conditions of tobacco plants to get some suitable land suitability classes for tobacco plants. The results of the analysis showed that the area of ​​land currently planted with tobacco reaches about 12,155.06 hectares, with a suitable class (S2) reaching 897.82 hectares, marginal (S3) reaching 1,614.44 hectares, and not suitable (N) reaching 9,642.79 hectares. Land that has the potential to grow tobacco is S2 (quite suitable) and S3 (marginal).

Abstract Grasslands are crucial ecosystems that provide numerous ecological services and support biodiversity conservation. Grasslands undergo significant threats from both anthropogenic and natural sources, compromising their ability to maintain biodiversity, ecosystem services, and human well-being. However, grasslands are frequently ignored in sustainable development objectives. Adequate knowledge of how grassland degradation affects ecosystem services is essential for sustainable management and grassland ecological restoration. The Kachchh region in western India harbours a unique grassland ecosystem known as the Banni grassland, which once became the finest grassland in Asia. However, undesirable anthropogenic interventions have accelerated its degradation. This research paper aims to assess the suitability of different land areas in Banni for sustainable grassland restoration, considering ecological value as a primary criterion. In the present research, land suitability for grassland management was assessed using a geographical information system (GIS)-based multi criteria evolution (MCE) method with satellite data and the analytic hierarchy process (AHP). The ground truthing of the soil samples was carried out alongside. Slope, rainfall, infiltration rate, LULC, geomorphology, soil texture, soil organic carbon, water holding capacity, SAR, CEC, pH, EC, and soil nutrients were among the criteria used. The weights for each criterion were calculated using a pairwise comparison matrix, and the scores were allocated to sub criteria based on field work, expert opinions, and a literature review. The proposed method can be very useful for evaluating the state of the land and can help with the best possible planning for grassland development and conservation. Banni grassland has the potential to be developed into a critical zone observatory (CZO) in the future, and the present study, with further inputs, holds promise for furthering the cause of its sustainable management. Overall, this study underscores the importance of assessing land suitability for sustainable grassland management and highlights the potential for maximising the ecological value of grasslands in western India and beyond.

Suitability evaluation of soils of Hyuku in Wukari Local Government Area of Taraba State, Nigeria was carried out with the view to characterize and evaluate the soils for its suitability for maize production. Two soil units were identified based on their physical, chemical and morphological features using grid method of soil survey. Two profile pits were sunk in each unit, making a total of four pits in all. The soils were deep (80 to 115 cm), well drained with sandy loam surface textures and sandy loam to clay loam subsurface textured. The soil reaction was moderately acidic (5.65 to 6.75) with high base saturation (95.07 to 96.40 %), low organic carbon (0.13 to 0.34 %), low nitrogen (0.17 to 0.67 %), and moderate to low available phosphorus (2.77 to 5.52 ppm). The soil characteristics were matched with the requirement of maize and the overall suitability rating of the soils were obtained using limitation method. Units I and II soils were rated as moderately suitable (S2) for maize production.

Land use conflicts (LUCs) have become a significant global issue. Accurately identifying potential LUCs is crucial for mediating these conflicts, optimizing land use structure, and enhancing land use function. The necessary conditions of LUCs are land use multi-suitability (LUMS), land resource scarcity (LRS), and diversity of demands (DD). However, few studies have approached LUC identification from these three dimensions simultaneously. In addition, when assessing the diversity of demand, only human needs are considered and wildlife needs are ignored. In order to address this gap in the research, this paper constructs a novel framework for LUC identification and proposes an induction-oriented governance path. LUMS was evaluated from three aspects: construction suitability, cultivation suitability, and ecological suitability. LRS is measured from three dimensions: construction land, cultivated land, and ecological land scarcity. The DD is expanded into human and wildlife demand diversity. By analyzing the combination of LUMS, LRS, and DD, LUCs are classified using the potential LUC identification Rubik's cube model, and corresponding governance paths are suggested. In Shandong Province, potential LUCs are relatively high, with strong, medium, and weak conflicts accounting for 27.39%, 57.10%, and 13.06%, respectively. Potential strong conflicts are mainly distributed in the metropolitan suburbs and in the western plain of Shandong Province. Cultivated land is the main potential land use conflict space. The new framework of LUC identification proposed in this paper can effectively identify potential LUCs. Our research provides scientific reference for sustainable land use. [ABSTRACT FROM AUTHOR]

Land suitability assessment is integral to the advancement of precision agriculture. This inquiry is focused on identifying optimal regions for cultivating Alphonso mango in the coastal belt of Maharashtra, spanning across Palghar, Raigad, Thane, Ratnagiri, and Sindhudurg districts. Employing a GIS-based Analytic Hierarchy Process (AHP) methodology, 10 crucial parameters have been considered, encompassing climatic, physical, and chemical soil characteristics: cation exchange capacity, organic carbon, slope, rainfall, soil pH, soil texture, mean annual soil temperature, base saturation, soil drainage, and soil depth. Weights are assigned to these parameters based on expert opinions and existing literature to determine their significance in developing a soil suitability map. The study reveals distinct land suitability zones for Alphonso mango cultivation. The land suitability map designates 25.78% of the study area as highly suitable, while 9.18% is considered unsuitable for Alphonso mango cultivation. To validate the study, the Receiver Operating Characteristic (ROC) curve has been employed, indicating an 83% approval rate for the reliability and performance of the soil suitability. The results categorise soil suitability classes, providing valuable insights for farmers and agricultural planners to make informed decisions regarding Alphonso mango cultivation in similar geoenvironmental regions. [ABSTRACT FROM AUTHOR]

Urbanization in Bni Bouayach, Morocco, threatens vital irrigated areas and agricultural land, raising concerns about environmental sustainability. This study employs a GIS-based Analytical Hierarchy Process (GIS-AHP) framework to assess land suitability for sustainable development. It addresses knowledge gaps in urban planning as follows: (i) Evaluating land suitability for sustainable development: this analysis identifies areas appropriate for urban expansion while minimizing environmental impact. (ii) Balancing environmental and human needs: the framework integrates ten criteria encompassing accessibility, economic, social, geomorphological, and environmental factors. This comprehensive approach results in a Land Suitability Map with five categories: prohibited/unfit, extremely unsuitable, moderately unsuitable, adequately suitable, and highly suitable. Notably, 39.5% of the area falls within the adequately suitable or highly suitable categories, primarily consisting of accessible bare lands and pastures. These findings provide valuable insights for policymakers to guide Bni Bouayach towards sustainable urban development, ensuring balanced growth that respects both environmental preservation and resident needs. [ABSTRACT FROM AUTHOR]

Land use evaluation and capacity assessment for sustainable urban development in Ahvaz city has become crucial due to rapid urban expansion negatively impacting current and future development. Urban population growth and resource demands have led to a decline in environmental quality. Over the past decades, Ahvaz has identified potential areas for future expansion until 2030. This study assesses the city's physical expansion and spatial development patterns, aiming to identify optimistic future development scenarios. Emphasizing balanced and equitable development, the study focuses on suitable areas, environmental preservation, pollution reduction, and mitigating urban hazards. Various factors, including land use, soil type, vegetation density, landform, groundwater level, geology, and distances from railways, industries, roads, hinterland cities, water networks, faults, and the city itself, are considered. Three decision-making methods—logic, Analytical Hierarchy Process (AHP), and integrated Fuzzy-AHP—are applied to map urban physical development. Fuzzy logic, AHP models, Expert Choice, Arc GIS software, and a land fit zoning map are used for data analysis. The AHP assesses the factors' relative importance, followed by standardization based on fuzzy set theory. Criteria factors are then combined using AHP and fuzzy logic to generate a land suitability map. The study identifies five zones for Ahvaz's future development—very high, high, medium, low, and very low—based on their physical expansion potential. The third scenario, supported by maps, indicates favorable conditions for future development in the northwest and southwest zones, considering environmental characteristics, infrastructure, and land continuity. [ABSTRACT FROM AUTHOR]

Regional development is one of the efforts to improve socioeconomic development, reduce regional disparities and preserve the environment. The Gross Regional Domestic Product (GRDP) of Banyumas Regency has increased over the past 5 years, with the largest contributor to the Gross Value Added category being the Agriculture and Forestry sector. Arabica coffee varieties are one of the mainstay commodities in the region and a source of income for the people of Kabupaten Banyumas. Arabica coffee is a plantation commodity that has been determined to be developed in Kabupaten Banyumas in accordance with the plantation commodity development plan in the RTRW Kabupaten Banyumas 2012-2032. The main objective of this research is to develop a strategy in planning the development of arabica coffee plantation area in Kabupaten Banyumas. The research area covers all 29 subdistricts starting from January to April 2024. In looking at the actual distribution of arabica coffee plantations, overlay analysis techniques were used using data from land use maps, elevation maps. Land availability was analyzed through overlay and matching techniques with ArcGIS software and direct measurement. Arabica coffee agribusiness system was analyzed through R/C ratio descriptively. The development strategy of Arabica coffee plantation area in Banyumas Regency was conducted using AWOT analysis. The results showed that the actual distribution of arabica coffee plantations in the cultivation area in Banyumas Regency covers several sub-districts and the area reaches 1,214 ha. Available and suitable land for the development of arabica coffee plantation in the cultivation area is indicated to reach an area of 20,471 ha, of which the largest area is located in Lumbir Sub-district with an area of 3,726 ha or 18.09% of the total available land area. [ABSTRACT FROM AUTHOR]

Greece committed to the European Green Deal plans to complete mining operations by the end of 2028 and to transition from coal-based electricity to renewable energy sources (RES). The mine closure under the principles of effective strategic planning of the post-mining land uses constitutes an integral part of this transition. This research aims to simulate land use changes in the Ptolemais lignite mining area from 2023 to 2030 using a cellular automata-based (CA) calibrated model. The model analyzed three distinct scenarios with directions of agriculture development, industrial growth, and nature and biodiversity conservation. Five areas' topographic-morphologic characteristics (slope, distance from roads, predetermined RES, future lakes, and cities) were assessed through the Analytic Hierarchy Process (AHP) to calibrate the model for each scenario. A fuzzification algorithm was developed in a Geographical Information System (GIS) environment to generate a land use suitability map for each scenario. The generated suitability maps were imported into the simulation model, serving as transition rules for each scenario. The study's findings revealed that each scenario diachronically derives different land use types of distribution. The scenario-based approach has proven to be a valuable tool for simulating the dynamic transitions of post-mining land uses, offering significant assistance to decision-makers in planning new land use. [ABSTRACT FROM AUTHOR]

Copyright of Irrigation & Drainage is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Irrigation & Drainage is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Irrigation & Drainage is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Jurnal Tanah dan Sumberdaya Lahan is the property of Brawijaya University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Jurnal Tanah dan Sumberdaya Lahan is the property of Brawijaya University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Jurnal Tanah dan Sumberdaya Lahan is the property of Brawijaya University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Grasslands are crucial ecosystems that provide numerous ecological services and support biodiversity conservation. Grasslands undergo significant threats from both anthropogenic and natural sources, compromising their ability to maintain biodiversity, ecosystem services, and human well-being. However, grasslands are frequently ignored in sustainable development objectives. Adequate knowledge of how grassland degradation affects ecosystem services is essential for sustainable management and grassland ecological restoration. The Kachchh region in western India harbours a unique grassland ecosystem known as the Banni grassland, which once became the finest grassland in Asia. However, undesirable anthropogenic interventions have accelerated its degradation. This research paper aims to assess the suitability of different land areas in Banni for sustainable grassland restoration, considering ecological value as a primary criterion. In the present research, land suitability for grassland management was assessed using a geographical information system (GIS)-based multi criteria evolution (MCE) method with satellite data and the analytic hierarchy process (AHP). The ground truthing of the soil samples was carried out alongside. Slope, rainfall, infiltration rate, LULC, geomorphology, soil texture, soil organic carbon, water holding capacity, SAR, CEC, pH, EC, and soil nutrients were among the criteria used. The weights for each criterion were calculated using a pairwise comparison matrix, and the scores were allocated to sub criteria based on field work, expert opinions, and a literature review. The proposed method can be very useful for evaluating the state of the land and can help with the best possible planning for grassland development and conservation. Banni grassland has the potential to be developed into a critical zone observatory (CZO) in the future, and the present study, with further inputs, holds promise for furthering the cause of its sustainable management. Overall, this study underscores the importance of assessing land suitability for sustainable grassland management and highlights the potential for maximising the ecological value of grasslands in western India and beyond. [ABSTRACT FROM AUTHOR]

Prediction and monitoring of urban sprawl is a significant urban issue for planners, decision makers, and local authorities in terms of spatial data, strategies, and prediction models. Egyptian cities have expanded rapidly in the last 40 years. This uncontrolled urban growth requires a review of Egyptian urban policies and regulations. The Greater Cairo Region (GCR) is Egypt's economic capital and a significant industrial and commercial city. This study uses spatio-temporal data to suggest an approach based on integrating cellular automata (CA) and multicriteria evaluation (MCE) like analytical hierarchy process (AHP) and running it within the geographical information system (GIS) for monitoring, analyzing, and allocating informal growth in the context of unplanned regions like the GCR. At first, the weights of influencing growth factors were determined and calculated using AHP. Next, the probability map was created according to AHP weights. The historical probability map was then generated based on the historical development. Then a standalone CA macro was developed based on AHP weights to calculate the proximity index for existing urban and transportation features using Moore's extended neighborhood matrix. Finally, the general suitability map was created to identify the most sensitive areas for growth over the next two decades. The prediction process was performed based on the 2012 urban boundary. Then, the prediction accuracy was verified using the Kappa coefficient based on actual urban extents in 2017. The results showed that 676 km2 (35%) of the study area was not sensitive, 386.5 km2 (20%) was slightly sensitive, 522 km2 (27%) was almost sensitive, and 348 km2 (18%) was extremely sensitive to urban sprawl. Finally, we predicted the urban growth for the period from 2022 to 2052 for every 5 years. The outcomes showed a linear scattered sprawl pattern along transportation features and an annular pattern around existing urban spaces. Therefore, fertile farming land and natural resources in the GCR are set to become almost extinct over the next two decades, threatening food production and security. These results indicate the necessity to modify the region's urban policies to protect the agricultural areas and control the unplanned urban sprawl. [ABSTRACT FROM AUTHOR]

Choosing appropriate locations for built-up growth while maintaining natural balance has become necessary for sustainable urban planning. To this end, two multi-criteria decision-making (MCDM) approaches--the multi-influencing factor (MIF) and the analytical hierarchy process (AHP)--have been applied in this work. The MIF model results show that 23.546% of the study region was very highly suitable for newly built-up areas, and 18.786% was restricted for urban settlement, whereas, in the AHP model, 28.907% of the area was highly suitable, 17.619% was restricted for urban settlement. Finally, the dependability and efficiency of the two models used for the study area were assessed through the receiver operating curve (ROC) and area under curve (AUC) analysis. The comparative analysis demonstrates that the MIF approach (AUC 0.817) is more suitable and reliable than the AHP (AUC 0.783). The present work provides new insights to integrate GIS tools with MCDM for practical urban land suitability assessment. [ABSTRACT FROM AUTHOR]

Knowledge-based evidence about potential and existing rainfed cropping is crucial for decision-making for sustainable land use and food security. Using multi-criteria spatial analysis techniques, this study assessed the current status of cropland availability and projected impacts on future crop production in Ethiopia. The study primarily defined the extent of the Rainfed Cropping Area (RCA) and assessed the performances of different cropping practices. After precisely mapping cultivated area, cropping intensification potentials were estimated. Subsequently, disregarding the existing cultivated area, completely unsuitable areas, and protected and intact forest areas, the potentially available arable land using suitability analysis techniques was determined. In addition, the performance of existing crop production systems was evaluated against the natural potential. The findings reveal that RCA covers ~60% of the country’s landmass, of which cropping is practiced in only 33%. The coverage of Potentially Available Cropland (yet uncultivated) accounts for 16% of the country’s RCA. This is dominantly located in sparsely populated western and southwestern parts of the country. This study confirms that Horizontal Cropping Intensification (HCI) in the RCA of Ethiopia reaches only 33%. On the other hand, Vertical Cropping Intensification (VCI) practices cover only 10%, while about 1/3 of the RCA is suitable for VCI strategies at various levels of suitability. The performance of existing VCI-oriented cropping (which covers only 10% of the RCA) is very poor. Challenges to the use of the available cropland and ways of addressing land shortage for needy farmers are highlighted to inform efforts to readdress landlessness and food insecurity in Ethiopia.

The decline in corn production is influenced by several factors, one of which is the suitability of land characteristics. This research analyses land characteristics' suitability and GDD for West Sumatra Province corn crops. The suitability of land characteristics is studied by combining the suitability of land characteristics with the GDD value in the area. The suitability of land characteristics is determined by matching plant growth requirements and land characteristics. The parameters used to determine the suitability of land characteristics are land use, slope, soil pH, soil texture and rainfall. GDD suitability by matching the accumulated daily temperature data during one growing season to the optimal GDD value for corn plant growth. This research created 12 planting time scenarios, and the analysis was carried out based on Regency/city administrative areas in the West Sumatra region. The analysis results obtained a suitable land area based on land characteristics and GDD values, namely an area of 1,206,079.48 ha with a planting season of December-March. Areas in West Sumatra Province with great potential for corn crop development are Lima Puluh Kota Regency, Pasaman Regency, Sijunjung Regency, South Solok Regency, and Tanah Datar Regency.

Pertanian berkelanjutan merupakan strategi esensial dalam menjaga keseimbangan ekosistem dan keamanan pangan. Penelitian ini mengkaji integrasi antara penggunaan lahan pertanian dan pemeliharaan ternak dalam rangka pengembangan energi terbarukan melalui teknologi biodigester. Potensi produksi biogas dari limbah kotoran ternak dinilai sangat tinggi. Dengan lahan seluas 7.11 hektar yang terbagi menjadi 2.27 hektar untuk ditanami rumput gajah dan 4.48 hektar untuk ditanami jagung mampu mendukung kebutuhan pakan bagi 11 ekor sapi. Dari limbah kotoran yang dihasilkan diperoleh potensi produksi biogas harian sebesar 2.2 m3. Proses digestifikasi anaerob menggunakan biodigester berkapasitas minimal 4.4 m3 berhasil menghasilkan gas metana murni sebanyak 1.45 m3 per hari. Hasil ini menunjukkan bahwa kesesuaian lahan dan jumlah ternak memiliki peranan signifikan dalam mendukung efektivias biodigester untuk menghasilkan energi terbarukan. Hasil pengujian biogas pada efisiensi kompor menunjukkan nilai efisiensi sebesar 0.8% lebih besar dari pada biogas tanpa dilakukan pemurnian. Penggunaan biodigester juga memberikan kontribusi pada pengurangan emisi gas rumah kaca dan pemberdayaan masyarakat pedesaan melalui teknologi ramah lingkungan.

Urban growth has accelerated significantly in recent decades, categorized into two spatial patterns: adjacent and outlying growth. Traditional Cellular Automata (CA)-based models excel at simulating adjacent growth but exhibit limitations in modeling outlying growth, which can be summarized into two issues: 1) the overestimation of neighborhood effects caused by models’ excessive dependence on neighboring cell states; and 2) the ignorance of spatial heterogeneity in the relative importance of land suitability and neighborhood effects on urban growth. To address these problems, a novel CA model with Separate Extraction and Adaptive Fusion of land suitability and neighborhood effects (SEAF-CA) is proposed. In this model, a dual-path convolution structure is employed to extract spatial features from driving factors and cell states; geographical coordinates of each cell then input into a multilayer perceptron to derive spatially varying weights for feature fusion. Finally, the derived conversion probability is integrated with CA to simulate urban growth. Land use data collected from 2000 to 2020 in Wuhan are selected to evaluate the proposed model. Experimental results illustrate that SEAF-CA outperforms three typical CA models, achieving the closest outlying growth proportion to reality and the highest simulation accuracy. In addition, the source code of SEAF-CA is now available at GitHub (https://github.com/ohXu/SEAF-CA).

The cropped area of Krishnagiri district is about 37 % of the total geographical area, and due to the utilization of non-agricultural purposes (8.2% of agricultural land) it is mandatory to increase the agricultural production to feed the people. So, this study has been planned to find the agricultural suitability and crop suitability of the Krishnagiri district using AHP-TOPSIS and GIS techniques. In this study, three main limiting factors, such as climate, soil, and topographical parameters (Annual average rainfall, Annual average temperature, slope, pH, Electrical conductivity (EC), Soil organic carbon (SOC), available NPK, and soil texture), were used as criteria for the suitability of crops. All criteria maps were generated using Arc info 10.4 software. The AHP used to estimate the weight and TOPSIS (Technique for Order of Preference by Similarity to an Ideal Solution) approach was assign the rank of each criterion for the suitability analysis. Based on the relative closeness to the ideal solution(pi), the generated crop suitability maps were categorized into five classes, namely “highly suitable (S1), moderately suitable (S2), marginally suitable (S3), and not suitable (N)”. The results revealed that, crop suitability maps finds that that maize, field bean, cluster bean, groundnut, pomegranate, lemon, and lemongrass were highly suitable for the Krishnagiri district. Rice, cotton, sugarcane, sunflower, and cashewnut were moderately suitable, and vanilla was unsuitable. This study will guide farm managers and land policymakers in making decisions and assist farmers in selecting crops that are highly suitable for achieving potential yield and profit.

AbstractLand potential assessment has enormous use for smallholder farmers for the sustainable utilization of scarce physical land resources. The study area is faced with a significant lack of available studies on irrigation land suitability due to limited information regarding soil and land resources. This scarcity of data poses a significant challenge in effectively assessing the suitability of land for irrigation purposes. The study aimed to assess the land suitability for irrigation in the case of the Zenti River Catchment, Ethiopia. To achieve the objectives, soil properties, land use/cover, slope, and proximity to a perennial river were used. This was accomplished by using the analytical hierarchical process (AHP) and GIS-based tools. Soil samples were collected and used as criteria for irrigation suitability analysis: soil salinity, soil reaction (pH), soil organic matter, soil cation exchange capacity, and soil moisture content. To evaluate the land suitability for irrigation potential, the weighted linear combination analysis of AHP and reclassified thematic layers were overlaid in the Arc GIS tool. The result showed that soil suitability and land slope factors shared higher weights of 40% and 30%, respectively. A large portion of the study area falls in a high (19%) to moderate (37%) irrigation potential zone. Decision-makers can utilize this information to plan and allocate resources for irrigation projects in the most suitable locations. Moreover, smallholder farmers can benefit from understanding, which areas are suitable for irrigation, allowing them to make informed decisions when selecting land for cultivation and adopting proper management.

AbstractThis study aimed to analyze the appropriateness of land in Tungi Farm based in Morogoro District, Tanzania for sunflower production using a Geographic Information System (GIS). To determine appropriate areas for sunflower production, three criteria: soil properties (pH, organic carbon, total nitrogen, cation exchange capacity, available phosphorus, potassium, and soil texture), topography (slope and altitude), and climate (temperature and rainfall) were selected from the literature and employed in suitability analysis. The Analytic Hierarchy Process (AHP) method of the Multi-Criteria Evaluation was used to assign a weight to each criterion as per Saaty’s Table. Cumulative weights for each criterion were used in coming up with output maps using ArcGIS 10.8. Each criterion was reclassified and assigned a weighted value. Organic carbon, total nitrogen, cation exchange capacity, and potassium were found to be adequate. Topography and climate were suitable for the sunflower production. The results from land suitability gave S1 (vastly suitable), S2 (relatively suitable), and S3 (minimally suitable) of about 51% (1022 ha), 34% (671 ha), and 15% (307 ha), respectively. The suitability map in this study could be vital and helpful in management decision options. However, the criteria considered for land suitability evaluation were mainly based on the biophysical environment, and, hence, further studies can be carried out by integrating socioeconomic parameters to improve the suitability results of the study area.

AbstractAgricultural Land Suitability Analysis plays a pivotal role in sustainable land use planning, aiding decision-makers in identifying areas most conducive to agriculture. This study employs a systematic approach integrating Analytical Hierarchy Process and Multi-Criteria Decision Analysis techniques to assess and prioritize the suitability of agricultural land in in Southern Punjab (Multan region). The methodology involves defining clear objectives, identifying relevant criteria and sub-criteria, establishing a hierarchical structure and conducting pairwise comparisons to determine the relative importance of each factor. Our outcomes indicated that almost 43% area was highly suitable for agriculture, 27% moderately suitable, 16% marginally suitable, 8% less suitable and 6% not suitable for agriculture in study area. All the suitable lands had silty clay or clay type soil, which had sandy loam type soil in Multan region. The output is a comprehensive suitability map that identifies the most suitable areas for agriculture in Multan region. Sensitivity analysis and validation are incorporated to enhance the robustness and reliability of the results. This methodology provides a valuable tool for land use planners and policymakers to make informed decisions regarding agricultural land allocation, contributing to sustainable agricultural practices and resource management.

Projection of land use and land-cover change is highly uncertain yet drives critical estimates of carbon emissions, climate change, and food and bioenergy production. We use new, spatially explicit land availability data in conjunction with a model sensitivity analysis to estimate the effects of additional land protection on land use and land cover. The land availability data include protected land and agricultural suitability and is incorporated into the Moirai land data system for initializing the Global Change Analysis Model. Overall, decreasing land availability is relatively inefficient at preserving undeveloped land while having considerable regional land-use impacts. Current amounts of protected area have little effect on land and crop production estimates, but including the spatial distribution of unsuitable (i.e., unavailable) land dramatically shifts bioenergy production from high northern latitudes to the rest of the world, compared with uniform availability. This highlights the importance of spatial heterogeneity in understanding and managing land change. Approximately doubling the current protected area to emulate a 30% protected area target may avoid land conversion by 2050 of less than half the newly protected extent while reducing bioenergy feedstock land by 10.4% and cropland and grazed pasture by over 3%. Regional bioenergy land may be reduced (increased) by up to 46% (36%), cropland reduced by up to 61%, pasture reduced by up to 100%, and harvested forest reduced by up to 35%. Only a few regions show notable gains in some undeveloped land types of up to 36%. Half of the regions can reach the target using only unsuitable land, which would minimize impacts on agriculture but may not meet conservation goals. Rather than focusing on an area target, a more robust approach may be to carefully select newly protected land to meet well-defined conservation goals while minimizing impacts to agriculture.

Global forests are increasingly crucial for achieving net-zero carbon emissions, with a quarter of the mitigation efforts under the Paris Climate Agreement directed towards forests. In China, forests currently contribute to 13% of the global land's carbon sink, but their stability and persistence remain uncertain. We examined and identified that published studies suffered from oversimplifications of ecosystem succession and tree demographic dynamics, as well as poor constraints on land quality. Consequently, substantial estimations might have been suffered from underrepresented or ignored crucial factors, including tree demographic dynamics, and disturbances and habitat shifts caused by global climate change. We argue that these essential factors should be considered to enhance the reliability and accuracy of assessments of the potential for forest carbon sinks. [ABSTRACT FROM AUTHOR]

Sorghum is an alternative food ingredient that contains high levels of carbohydrates and calories so it can be a solution to food security problems. This research aims to evaluate the suitability of land for sorghum (Sorghum bicolor L.) in Tolitoli Regency, Indonesia. This research was conducted in Lampasio District, Tolitoli Regency using purposive sampling and survey methods on five land map units (SPL). The results of the research show that the area is classified as quite suitable land class (S2) with limiting factors for drainage and nutrient retention (oa, nr) with a land area of 3,652.7 ha spread over 5 SPL, namely SPL 1,2,3 and 5 while class The land (S3) is SPL 4. However, this can be overcome by adding fertilizer and adding organic material. So that it can improve the status of each land to be very suitable (S1) and quite suitable (S2). [ABSTRACT FROM AUTHOR]

Yam (Dioscorea spp.) is a key tuber crop in sub-Saharan Africa (SSA) with huge potential for poverty alleviation, food sovereignty, and nutrition security. Exploiting its full potential requires that factors holding it down are understood and mitigated. This study, conducted between May and July 2022 and 2023, assessed yam farming practices, varietal preferences, and land suitability in the Eastern Democratic Republic of Congo (DRC). We interviewed 765 smallholder farmers within four agro-ecological zones (AEZ) to assess the sociocultural, agronomic, varietal, and biophysical factors affecting yam production. Land suitability analyses were conducted using the Analytic Hierarchy Process (AHP) to identify areas suitable to extensive yam production and to cluster environments that could optimize yam varietal selection and testing. Results showed that yam is mainly cultivated by women in eastern DRC (70%). The seed delivery system is informal, relying primarily on farmer-saved seeds and farmer-seed exchanges (74.9%). Soil depletion (68.3%), limited access to high-quality seeds (54.5%), youth disengagement in yam value chain (50.3%), insect pests (17.9%), and short tuber shelf-life (65.8%) were, respectively, the main ecological, agronomic, sociocultural, biological, and tuber quality factors hindering yam production in eastern DRC. However, the perceived importance of most factors significantly varied with farmer gender and age categories. A multitude of varietal traits was used to assess yam varieties in eastern DRC, of which the tuber taste (59%) was the most valued trait regardless of gender and age categories, though it had highest scores among middle-aged adult women. Land suitability analyses discriminated five clusters; the most significant part of the region falling under suitable (27%), highly suitable (24%), and very highly suitable classes (37%). We further discussed how breeding initiatives for delivering yam varieties, suiting local producers' and end-users' needs, could unlock the crop's potential for enhancing food security and wealth creation in eastern DRC. The land suitability map from this study is a valuable decision-making tool in defining priority areas for extensive yam production and varietal selection and testing. This study provided valuable insights on factors affecting yam production and suggested yam breeding as a backbone of a holistic approach seeking to address challenges faced in unlocking the potential for yam production in eastern DRC. [ABSTRACT FROM AUTHOR]