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Informed decision regarding cultivating the right crop in the right land will guarantee maximum production, which is the need of the hour to meet the world's burgeoning food demand and to ensure the sustainability of agriculture. The present study aimed to identify the land suitability for major crops in the semi-arid ecosystem of Palani block in Tamil Nadu by integrating the analytical hierarchy process (AHP) and geographic information system (GIS). Soil slope and various soil characteristics influencing crop growth such as soil depth, texture, drainage, gravelliness, pH and organic carbon were considered for assessing the land suitability. Weights and scores were assigned to the selected criteria and their respective sub-criteria based on their relative significance in influencing crop growth. It was found that soil drainage and texture were the most influencing factors for paddy cultivation, with weights of 0.49 and 0.27, respectively. For field beans, coconut, and guava, texture and depth were identified as the major influencing factors with high weightages ranging from 0.26 to 0.40. Results indicate that about 22% (8627 ha) of the study area was highly suitable for field beans, followed by paddy (18%). In contrast, paddy and coconut registered the largest land area under the marginally suitable class and were deemed unsuitable for about 19% and 21% of the land, respectively. For guava and field beans, respectively 37% and 44% of the land were found moderately suitable while 77% and 76.6% of the land were found suitable. Soil texture, soil depth, and drainage were identified as the major impediments to coconut and paddy suitability. An error matrix was generated by comparing the land suitability derived through the AHP–GIS method with the farmers' opinions on land suitability for different crops. It indicated a high agreement between the suitability classes and farmers' opinion for field beans, followed by coconut, guava and rice with kappa indices of 0.64, 0.51, 0.49 and 0.40 and overall accuracy of 75%, 65%, 62% and 60%, respectively. The present study not only helps in identifying suitable areas for crop cultivation, but also recommends land management strategies to each land parcel to improve land productivity and sustainability. [ABSTRACT FROM AUTHOR]

The modeling and assessment of land suitability is a prerequisite for land development and is one of the necessary needs to prevent land degradation. Maize is considered to be the most important crop, covering significant areas of agricultural lands in widely different regions across the world. However, not all available lands are equally suitable for maize cultivation. The main objective of this study was focused on identifying the potentials as well as the limitations of studied calcareous soils for maize cultivation in north Khuzestan province, Iran. Furthermore, some parametric models and multi-criteria land suitability evaluation methods for physical, chemical, fertility, and climatic factors (MC-LSE) were compared in estimating the maize yield. The required samples were taken from 23 land units by excavating control pedons. The necessary physicochemical parameters were then measured in the laboratory. The land indices were calculated by using different methods. The maize potential production of the investigated area was then obtained based on the climatic conditions. Finally, using land indices and the potential production, the estimated yield for each land unit was calculated and compared with the actual yield data. The obtained results indicated that the main limiting factors for maize yield in the region are high soil CaCO3 content, high salinity, high alkalinity and low organic matter. A comparison of predicted and actual yield indicated that the corrected square root method is accurate enough to assess land suitability and to estimate the maize yield with a high coefficient of determination (0.91) and a low RMSE value. [ABSTRACT FROM AUTHOR]

The crop-land suitability assessment (LSA) is important for managing land and water resources and developing sustainable agricultural systems. In the field of determining the suitability of cropland, the multi-criteria evaluation approach (MCEA) or multi-criteria decision-making (MCDM) is becoming more popular as a tool for analyzing difficult situations and obtaining logical conclusions. The 75 relevant publications from 2010 to 2023 were reviewed and summarized in this paper to precisely explain and identify MCEA application areas and decision-making problems resolved within the crop-land suitability assessment. The findings indicated that the MCDM or MCEA techniques have been applied with or without remote sensing, Agricultural Land Use Evaluation System, parametric methods, etc. for land suitability evaluation. This study also contributes to the classification of criteria used for this purpose. A total of 117 parameters from six groups: soil properties, climate, topography, hydro-geomorphology, land use compatibility, and hazard are necessary for LSA. [ABSTRACT FROM AUTHOR]

The quantitative identification of rural land functions serves as a basis for rural land planning, coordinated spatial development, and control capacity improvement and is significant for rural transformation and sustainable development. This paper constructs an analysis framework to identify and evaluate “production-living-ecological” space (PLES) in rural areas of central and western China. On the Loess Plateau, which was taken as the study area, a combination of qualitative and quantitative analysis was completed to determine framework indicators and their thresholds. Resource and environmental carrying capacity and land suitability were measured through GIS spatial analysis under different land functional orientations. This sought to recognize production space (PS), living space (LS), and ecological space (ES) in rural areas, reveal their distribution patterns on the Loess Plateau, and determine alternative areas for future land use. The results indicate that the PS and LS of the Loess Plateau rural land show a relatively low resource and environmental carrying capacity but vary significantly in different functional regions. The space distribution of PS and LS with higher carrying capacity shows obvious consistency. Although the Loess Plateau has vast sustainable land for development, the intensity of development should be carefully controlled. Additionally, significant regional differences remain in rural PLES, so reasonable future rural land planning should be formulated according to the PLES pattern. This study provides a scientific basis for promoting coordinated development of Loess Plateau rural areas and implementing a rural revitalization strategy. It is also a reference for identifying PLES and its coordinated spatial development in rural central and western China.

AbstractLand valuation is essential for developing land use planning and achieving efficient land use, food security, and poverty reduction. This study aimed to assess land suitability for cassava and bean production using the multicriteria decision analysis AHP technique and GIS. Land suitability analysis considers factors affecting crop growth and development, particularly in producing beans and cassava. The Analytical Hierarchy Process (AHP) model was used to determine the importance of main and sub-criteria parameters. ArcGIS software was used to create crop suitability distribution maps for bean and cassava production. Each parameter was subjected to pair-wise comparison by employing the Analytical Hierarchy Process (AHP). The study found that the southern region displayed a vastly suitable level of 38% and 46% for beans and cassava, respectively. Farmers can use the comprehensive data to decide whether to plant beans and cassava on their lands, increasing revenue while preserving soil quality management. The GIS-AHP integration approach was suggested to determine optimal decisions based on chosen criteria.

Assessing the quality of land is a very important step that precedes the planning of land use and taking management decisions; for example, in the agricultural field, it can be used to evaluate the suitability of the land for planting crops, determine the suitable irrigation system type, or adjust the agricultural inputs such as fertilizers and pesticides according to the requirements of each zone in the land. The spatial–temporal dynamic nature of land characteristics entails also updated evaluation process and updated management plan. The present paper tries to exploit the advances in information and communication technologies to develop a conceptual design of a dynamic system that accommodates the spatial–temporal dynamics of the agricultural soil characteristics to realize a land suitability assessment (LSA) based on a factor analysis method. The proposed design combines IoT technologies, web development, database, and digital mapping and tries to consolidate the system with other functionalities useful for decision support and suitable for different cases. The paper conducted a survey and made comparisons to select the best technologies that fit the current use case implementation and presents its reproducible conceptual modeling by developing the static and dynamic views through schemas, diagrams, message sequence charts, IoT messaging topic tree, pseudocode, etc. The functionality of the design was validated with a simple implementation of the system model. To our knowledge, there is no previous significant contribution that has addressed a LSA IoT use case. The proposed design automates the LSA process for more accurate decision-making, saving cost, time, and effort consumed in repeated field trips. It is characterized by flexibility and centralization in its offered services of spatial analysis, detection, visualizations, and status monitoring. The design also allows for remote control of field machinery. [ABSTRACT FROM AUTHOR]

Abstract This research aimed at evaluation of a given land resource suitable for selected rain fed crops production (malt barley, wheat and teff) in Ambesh watershed. It also quantified suitable land and classified into the land mapping units (LMUs), and presents a land suitability map. Land suitability assessment (LSA) made using climatic condition, topography, soil physical and chemical properties as a major factor integrated with a multi criteria decision making (MCDM) analysis in Ambesh watershed. Fourteen composite soil samples were taken by categorizing the watershed into different land mapping units (LMUs) and analyzed in a soil laboratory. Climatic data, rainfall was obtained from two meteorological stations nearby to the study area. Temperature data derived from Landsat 8 satellite thermal bands data. Data obtained from the soil laboratory and others were finally analyzed using ArcGIS environment and priority estimation tool (PriEsT) software’s. Weighted Sum Overlay was implemented to investigate the final LSA map of the watershed. Results revealed that LMUs, VRe–LPq and LPK.Pq–FLc LMUs has higher overall suitability for all the selected rain fed crops. However, LMUs (VRe–NTu and NTu–VRe) has lower overall suitability values particularly for S1 suitability class (0.05% and 10.6%, respectively). The least suitable LMU is VRe–NTu with 0.05% S1 suitability class and above 99% of the land laid under the suitability classes of moderately suitable, marginally suitable and not suitable for the selected land utilization types. Moreover, about 219.06 ha (17.76%), 217.6 ha (17.64%), 168.9 ha (13.7%), of land are highly suitable for malt barley, teff and wheat crop production, respectively. In conclusion, during MCDM, classifying the land into closer homogeneities (LMU) an important application of LSA integrated with remote sensing and GIS for a better decision making. Meanwhile, majority (above two third’s) of the land in the watershed is under moderate and marginally suitable, it needs intensive land management activities to increase the land qualities and obtain high yields. LSA recommended before land utilization decision has to be made. It is also important to classifying the land into LMUs to make it more homogeneous for sample taking and reducing the prestigious soil laboratory analysis costs.

This research aimed at evaluation of a given land resource suitable for selected rain fed crops production (malt barley, wheat and teff) in Ambesh watershed. It also quantified suitable land and classified into the land mapping units (LMUs), and presents a land suitability map. Land suitability assessment (LSA) made using climatic condition, topography, soil physical and chemical properties as a major factor integrated with a multi criteria decision making (MCDM) analysis in Ambesh watershed. Fourteen composite soil samples were taken by categorizing the watershed into different land mapping units (LMUs) and analyzed in a soil laboratory. Climatic data, rainfall was obtained from two meteorological stations nearby to the study area. Temperature data derived from Landsat 8 satellite thermal bands data. Data obtained from the soil laboratory and others were finally analyzed using ArcGIS environment and priority estimation tool (PriEsT) software's. Weighted Sum Overlay was implemented to investigate the final LSA map of the watershed. Results revealed that LMUs, VRe–LPq and LPK.Pq–FLc LMUs has higher overall suitability for all the selected rain fed crops. However, LMUs (VRe–NTu and NTu–VRe) has lower overall suitability values particularly for S1 suitability class (0.05% and 10.6%, respectively). The least suitable LMU is VRe–NTu with 0.05% S1 suitability class and above 99% of the land laid under the suitability classes of moderately suitable, marginally suitable and not suitable for the selected land utilization types. Moreover, about 219.06 ha (17.76%), 217.6 ha (17.64%), 168.9 ha (13.7%), of land are highly suitable for malt barley, teff and wheat crop production, respectively. In conclusion, during MCDM, classifying the land into closer homogeneities (LMU) an important application of LSA integrated with remote sensing and GIS for a better decision making. Meanwhile, majority (above two third's) of the land in the watershed is under moderate and marginally suitable, it needs intensive land management activities to increase the land qualities and obtain high yields. LSA recommended before land utilization decision has to be made. It is also important to classifying the land into LMUs to make it more homogeneous for sample taking and reducing the prestigious soil laboratory analysis costs. [ABSTRACT FROM AUTHOR]

Habitat suitability analysis using species distribution models (SDMs) presents a valuable approach for determining appropriate land utilization strategies and crop planting decisions, which are vital to achieve optimal agricultural productivity and ensure environmental sustainability in the context of rapid global change. Aside abiotic conditions, pests emerge as the most important biological factor affecting crop growth. It can be an effective avenue to comprehensively assess land use suitability by building and integrating SDMs for both crops and their pests. Using the MaxEnt model and a bivariate map, we predicted and integrated the habitat suitability of tea (Camellia sinensis) and its primary insect herbivore (Empoasca onukii) in China. Our study explicitly revealed spatial heterogeneity in suitability between the two species, despite finding that they shared common environmental predictors (i.e., temperature, elevation, and soil pH). Results support South China and Southwest China as the most favorable areas for tea cultivation, while highlighting the adverse climatic challenges on tea growth in the middle and lower reaches of the Yangtze River and in the northern regions of the Yangtze River. Meanwhile, analyses emphasize the necessity of sustainable leafhopper management strategies in the middle and lower reaches of the Yangtze River and in regions along the southeast coast. These findings demonstrate the significance of comparative analysis on the habitat suitability of both crops and insect herbivores, providing valuable insights for agricultural production planning and sustainable pest management. Furthermore, the methods employed in this study hold potential for the application in diverse context, ranging from the control of invasive species to the conservation of endangered biodiversity. [ABSTRACT FROM AUTHOR]

Habitat suitability analysis using species distribution models (SDMs) presents a valuable approach for determining appropriate land utilization strategies and crop planting decisions, which are vital to achieve optimal agricultural productivity and ensure environmental sustainability in the context of rapid global change. Aside abiotic conditions, pests emerge as the most important biological factor affecting crop growth. It can be an effective avenue to comprehensively assess land use suitability by building and integrating SDMs for both crops and their pests. Using the MaxEnt model and a bivariate map, we predicted and integrated the habitat suitability of tea (Camellia sinensis) and its primary insect herbivore (Empoasca onukii) in China. Our study explicitly revealed spatial heterogeneity in suitability between the two species, despite finding that they shared common environmental predictors (i.e., temperature, elevation, and soil pH). Results support South China and Southwest China as the most favorable areas for tea cultivation, while highlighting the adverse climatic challenges on tea growth in the middle and lower reaches of the Yangtze River and in the northern regions of the Yangtze River. Meanwhile, analyses emphasize the necessity of sustainable leafhopper management strategies in the middle and lower reaches of the Yangtze River and in regions along the southeast coast. These findings demonstrate the significance of comparative analysis on the habitat suitability of both crops and insect herbivores, providing valuable insights for agricultural production planning and sustainable pest management. Furthermore, the methods employed in this study hold potential for the application in diverse context, ranging from the control of invasive species to the conservation of endangered biodiversity.

AbstractIn Tanzania, land degradation has been ranked as the top environmental problem for more than 62 years after independence. Land degradation is a catalyst for poverty increment in rural people’s livelihoods by contributing up to a 48% increase in poverty of this population. This paper highlights land degradation as a key constraint to sunflower production while looking at the potential role of Geographic Information System (GIS) in revitalizing the sector. The review focuses on Tanzania, where sunflower production is done mainly by smallholder farmers as a cash crop and a source of vegetable oil. Sunflower production is threatened by land degradation in the form of nutrient mining that decreases the fertility of the soil, hence lowering its potential. Such degradation is mainly contributed to by continuous crop cultivation without replenishment of the soil fertility, crop removal after harvesting, and low fertilizer input. This calls for the adoption of modern systems of utilizing GIS, in assessing the suitability potential of the land giving the best decision in managing and adopting the right soil management practices for increasing and sustaining the productivity of the farmland concerning sunflower production in Tanzania.

Site selection for pistachio orchards is an important issue for sustainable agricultural policies, crop productivity, agricultural planning, and communities. This study aims to investigate suitable places for pistachio in the Mardin Province (SE Turkey) by considering several variables, such as meteorological data, topographic conditions, economic factors, and soil characteristics, using Geographic Information System (GIS) and Multi-Criteria Decision Analysis. Pistachio farmers, expert opinions, and literature data were used to determine the requirements for pistachio cultivation. Four main assessment criteria (thirteen sub-criteria), sixty value ranges, and fourteen exclusion criteria were determined for the pistachio land suitability assessment. The weighting of the evaluation criteria was calculated using the Analytical Hierarchy Process (AHP). Farmers and experts have stated that meteorological factors are more important than soil, topography, and economic factors. All data were transferred to the GIS environment, and a land suitability map was created using the weighted linear combination method. The results show that Mardin province has very suitable lands for pistachio cultivation. The resulting map determined that the 228,891.59 ha area in Mardin province is very suitable for pistachio. To evaluate the accuracy of the land suitability map generated for pistachio, the Receiver Operating Characteristic (ROC) curve was used. The value of the area under the curve (AUC) was calculated to be 0.806, which indicates that the study is consistent. The created suitability map will be an essential data source for developing sustainable agricultural strategies in the Southeastern Anatolia region. [ABSTRACT FROM AUTHOR]

Parametric land suitability assessment (LSA) sometimes does not correspond to the reality of the region due to low index values. Thus, new multi-criteria decision-analysis approaches (MCDA) that consider the mutual effects of criteria, such as the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method, can be utilized. This study aimed to compare the efficiency of the TOPSIS approach and parametric methods in assessing land suitability for sugarcane cultivation in southwest Iran. Hence, 45 sugarcane fields were selected in sugarcane cultivation and industrial areas in the south of Khuzestan province. In each farm, one pedon was studied in detail. Soil samples were collected from different horizons and taken to the laboratory for the designated physicochemical analyses. Sugarcane yields over the past three years were also gathered for each farm in the study. Then, the land suitability index values were compared with the sugarcane yield in the studied units using Storie, square root, and TOPSIS methods. The results revealed that soil salinity (EC) exhibited the highest specific weight value for sugarcane farming followed by soil pH, calcium carbonate equivalent (CCE), and soil depth. Furthermore, the preferred value with the TOPSIS method for sugarcane cultivation ranged from 0.42 to 0.92. The explanation coefficient (R2) obtained by comparing the order of priority of 45 options with their observed performance using the Storie, square root, and TOPSIS methods was 0.62, 0.64, and 0.76, respectively. Our results revealed that TOPSIS outperformed the other two methods to determine land suitability for growing sugarcane. The multi-criteria method improved the land suitability class and resulted in a higher land suitability class than the traditional method, which is more consistent with the reality in the region. In conclusion, the results of this study demonstrated the high efficiency and potential of TOPSIS compared to other commonly used models. Overall, it can be concluded that agricultural land use can be better planned and managed with the TOPSIS method. [ABSTRACT FROM AUTHOR]

Land suitability assessment matches crop requirements with available resources to promote sustainable production. Scaling out of sustainable agricultural intensification practices to suitable biophysical and socio-economic conditions reduces the risk of failure and increases their adoption rate. This study applies a geospatial framework to identify potentially suitable sites for extrapolating two improved vegetable cultivars grown under integrated management practices (IMP's) in Babati District of Tanzania. On-farm trial data on the yield and income of two cultivars were used as a reference. Extrapolation was based on the gridded biophysical and socio-economic layers that limit the production of the two improved vegetable cultivars'. The extrapolation suitability index (ESI) showed the areas where cultivation of the two improved vegetable cultivars under IMP's can be scaled-out with a potentially low risk of failure. We generate maps of the most important limiting factor for each cultivar in every pixel to guide the spatial targeting of appropriate remedial measures. Application of these maps will promote evidence-based scaling out of improved vegetable technologies by the extension and development agencies.

Given the beneficial effects of cover crops, their planting is a good way to improve soil fertility, reduce soil erosion, effectively control weeds, etc. some ecological variables were selected for sunflower and berseem clover land suitability assessment, and thematic maps were developed for each of the parameters in Geographic Information System (GIS). Finally, highly suitable, suitable, moderately suitable and unsuitable areas were detected by analytic hierarchy process (AHP). The findings indicated that the ordinary kriging interpolation model was the best model to evaluate the agricultural land suitability assessment for sunflower and berseem clover production in the region. Also, the climatic variables had a major role in the development of sunflower and berseem cultivation, and soil and topography variables ranked next. The final land suitability map revealed that the most highly suitable areas (3358.4 ha) were located in the north of the region, and the rest was suitable (15257 ha) areas for growing sunflower. Also, northwest and very limited areas from the northeast and southeast of the region showed highly suitable conditions (3534.4 ha), and other areas had suitable (15081 ha) condition in cultivation of berseem clover. Therefore, almost areas were suitable for it. [ABSTRACT FROM AUTHOR]

The quantitative identification of rural land functions serves as a basis for rural land planning, coordinated spatial development, and control capacity improvement and is significant for rural transformation and sustainable development. This paper constructs an analysis framework to identify and evaluate "production-living-ecological" space (PLES) in rural areas of central and western China. On the Loess Plateau, which was taken as the study area, a combination of qualitative and quantitative analysis was completed to determine framework indicators and their thresholds. Resource and environmental carrying capacity and land suitability were measured through GIS spatial analysis under different land functional orientations. This sought to recognize production space (PS), living space (LS), and ecological space (ES) in rural areas, reveal their distribution patterns on the Loess Plateau, and determine alternative areas for future land use. The results indicate that the PS and LS of the Loess Plateau rural land show a relatively low resource and environmental carrying capacity but vary significantly in different functional regions. The space distribution of PS and LS with higher carrying capacity shows obvious consistency. Although the Loess Plateau has vast sustainable land for development, the intensity of development should be carefully controlled. Additionally, significant regional differences remain in rural PLES, so reasonable future rural land planning should be formulated according to the PLES pattern. This study provides a scientific basis for promoting coordinated development of Loess Plateau rural areas and implementing a rural revitalization strategy. It is also a reference for identifying PLES and its coordinated spatial development in rural central and western China. [ABSTRACT FROM AUTHOR]

For assisting in the effective utilization of land resources at the regional level, Land Suitability (LS) evaluation can be employed. If proper gauges and implementations are made, then the LS assessment can well be attained, which is useful for credible development. In the Land-Use (LU) analysis, a powerful means for taking care of spatial data is the Geographical Information Systems (GIS). Whilst attempting to assign comparative significance to the numerous criteria pondered in a suitability evaluation, this tool's application can't singly trounce the scarcity of the opinions’ constancy offered by experts. The aim of the presented research study is the assessment of LS for Sustainable Development (SD) of Peri-Urban (PU) areas of Coimbatore city, in Tamil Nadu, India. For resolving the issue of individually using the GIS tool, this analysis uses the combination of GIS, Multi-Criteria Decision Making (MCDM), along with Analytical Hierarchy Process (AHP). Here, the mandatory aspects function as a key for a long SD, and the requirement for ecological planning was highlighted. Additionally, to envisage the LS of the Coimbatore PU area for SD utilizing weighted overlay analysis by means of integrating ‘7’ thematic layers, geo-visualization technology was implemented. The presented study’s result implies that only 49.80% and 31.86% of the area are highly suitable for Urban Development (UD) in the future. [ABSTRACT FROM AUTHOR]

The present study illustrates the Spatial-temporal dynamics of Land use/Land cover (LULC), and locate land suitability for agricultural use. Landsat satellite images of three different years 1990, 2000 and 2018 over 28 years were acquired from Global Land Cover Facility Site (GLCF) and earth explorer. Land suitability for agriculture use was assessed on five criteria; rainfall, temperature, slope percentage, soil types and water Wells distribution. The different geospatial layers were transferred using suitability coding system to produce the suitability maps for rainfed and irrigated areas using weighted overlay method. Ma’an Governorate covers approximately 37% of the total area of Jordan, and consists mostly of uncultivated land 33304.66 km2 (99.49%). Three main LULC classes were identified of the three years; 1990, 2000 and 2018; forest and irrigated areas have been fluctuated between 86.00 km2 (0.26%), 108.06 km2 (0.32) and 102.68 km2 (0.31%), built-up area increased by 24.00 km2, (0.07%), 41.88 km2 (0.13%) and 68.66 km2 (0.21%), while the bare land has been decreased from 33366 km2 (99.67%),33476 km2 (99.55%) and 33304.66 km2 (99.49%) during 1990, 2000 and 2018 respectively. land suitability for the agricultural use (rainfed areas and irrigated crops); Data from the five parameters (mentioned above) are used for spatial analysis applying weighted overlay method. The results showed that only about (0.2%) from the total area of Ma’an is highly suitable for agriculture dependent on rainfall. While about (1.4%) is high suitable for the irrigation crops. The main reason of the low levels of land suitability for agriculture is very low soil fertility, and the water scarcity.

With the goal of evaluating biomass resource availability in certain regions in the United States, the Department of Energy, Department of Agriculture, Environmental Protection Agency, national laboratories, and Forest Service research laboratories, together with academic and industry collaborators, performed a resource analysis study, 2016 Billion-Ton Report: Advancing Domestic Resources for a Thriving Bioeconomy, Volume 1: Economic Availability of Feedstocks, using POLYSYS model to estimate biomass potential. The study provided county- and state-level biomass potential projections, with biomass feedstock production estimates and suitability assessment of lands acreage likely to transition to energy crops. For this analysis, we estimate biomass supply by year 2028, more specifically, lands acreage transition to switchgrass in the Midwest of the United States, across 50 counties in 3 states (Nebraska, Kansas, and Colorado). We propose a multi-criteria site suitability framework, to determine the potential acreage and production for switchgrass, at the field level. Site selection criteria span agronomic and ecosystem services such as previous land cover, crop rotation, soil water holding capacity, crop productivity, field efficiency, topography, soil organic matter, soil leaching propensity, distance to surface water bodies, and soil erosivity. Efficient agricultural field selection for dedicated energy crops field allocation is critical to evaluate biomass resource availability, and it is our position that estimation at the field level would provide a more accurate and useful estimation to support an emerging bioeconomy. Using field suitability scores and county-level assessments, we model land allocation decision for energy crop in the future, estimating the spatial distribution of dynamics of energy crop adoption with priority to fields scoring the highest. Compared with POLYSYS results from the report mentioned above, our method shows good performance overall, with about 2% and 1.2% of difference in switchgrass acreage allocation and crop production, respectively.

An evidence base was developed to facilitate adoption of hemp (Cannabis sativa L.) in tropical environments (Wimalasiri et al. (2021)). Agro-ecological requirements data of hemp were acquired from international databases and was contrasted against local climate and soil conditions using an augmented species ecological niche modeling. The outputs were then used to map the suitability for all locations for 12 possible calendar-year seasons within peninsular Malaysia. The most probable seasonal map was then used to generate a land suitability map for agricultural areas across 5 standard land suitability categories. Having developed the general suitability maps of hemp in Malaysia, detailed crop growth data were collected from literature and was then used to simulate an ideotype crop model (for both seed and fiber) for selected locations across Malaysia, where detailed daily climate data and soil information were available. Following the development of a downscaled future climate dataset, a simulated dataset of yield for the future conditions were also developed. Next, the simulated seed and fiber yield data were used to create yield maps for hemp across peninsular Malaysia. An economic value and cost-benefit analyses were also carried out using data that were collected from literature and local sources to simulate the true cost and benefit of growing hemp both for now and future conditions. This data provides the first ever evidence base for an underutilized crop in Southeast Asia. All data that was generated using the proposed published framework for the adoption of hemp in the future are stored in their original format in an online repository and is described in this article. The data can be used to map the suitability at finer scales, analyze and re-calibrate a yield model using any climate scenario and evaluate the economics of production using the standard methodology described in the above-mentioned publication.

• Land suitability evaluation assessed the suitability of land for urban development. • Intensive development of 3 urban growth boundary scenarios were simulated for 2040. • Landscape pattern of three urban growth scenarios were generated. • Intensive scenario is an ideal development mode. In designing national parks, it is important to balance land use with ecological protection and local socio-economic development. In the past decades, the national park has undergone landscape fragmentation and degradation of ecological functions due to climate change and land use change, especially in national parks with urban areas. Therefore, ecological environmental protection projects should include the assessment of land use when planning urban area development in the national park region. Consequently, we used the Land Suitability Evaluation (LSE) method, with 13 indicators for natural, social and ecological variables, to assess the suitability of the newly created national park for urban land use on the Tibetan Plateau. Combining results of the suitability assessment and the Cellular Automata (CA) method, three urban intensification scenarios were simulated for 2040: (1) unplanned, (2) intensified, and (3) strictly regulated urban growth boundaries (UGBs). The impact of land use on the normalized difference vegetation index (NDVI) was analyzed by remote sensing and GIS tools, and the landscape patterns of the three urban growth scenarios were calculated. Close to 87 % of the area was basically suitable, nearly 13 % was unsuitable, and only 0.06 % (43.4 km2–also included in the basically suitable) was suitable for urban land use. In 2040, the built-up areas are predicted to be 3.38, 2.71 and 2.32 times greater than in 2020 under the unplanned (without considering ecological restrictions), the intensive development (emphasizing the driving force of transportation and tourism on the expansion of built-up areas) and the strict control (maximizing ecological restrictions) scenarios, respectively. An ideal development model was used to balance ecological protection and population growth and economic development. The NDVI analysis revealed that the impact of land use on vegetation cover in the intensive development scenario was ranked as winter pastures > tourist development zones > summer pastures. It is concluded that the intensification scenario, with transport and tourism as the main spatial drivers, is the most desirable for the future coordination of ecological conservation and socio-economic development in the national park. This scenario may alleviate the current environmental pressure of livestock grazing on winter pastures in the national park on the Tibetan Plateau. However, realizing this model requires appropriate engineering design for town development. Future research should assess the impacts of urban growth on the ecological environment, with the aim to achieve sustainable urban development tailored to the various geographic regions. [ABSTRACT FROM AUTHOR]

The present study illustrates the Spatial-temporal dynamics of Land use/Land cover (LULC), and locate land suitability for agricultural use. Landsat satellite images of three different years 1990, 2000 and 2018 over 28 years were acquired from Global Land Cover Facility Site (GLCF) and earth explorer. Land suitability for agriculture use was assessed on five criteria; rainfall, temperature, slope percentage, soil types and water Wells distribution. The different geospatial layers were transferred using suitability coding system to produce the suitability maps for rainfed and irrigated areas using weighted overlay method. Ma'an Governorate covers approximately 37% of the total area of Jordan, and consists mostly of uncultivated land 33304.66 km2 (99.49%). Three main LULC classes were identified of the three years; 1990, 2000 and 2018; forest and irrigated areas have been fluctuated between 86.00 km2 (0.26%), 108.06 km2 (0.32) and 102.68 km2 (0.31%), built-up area increased by 24.00 km2, (0.07%), 41.88 km2 (0.13%) and 68.66 km2 (0.21%), while the bare land has been decreased from 33366 km2 (99.67%),33476 km2 (99.55%) and 33304.66 km2 (99.49%) during 1990, 2000 and 2018 respectively. land suitability for the agricultural use (rainfed areas and irrigated crops); Data from the five parameters (mentioned above) are used for spatial analysis applying weighted overlay method. The results showed that only about (0.2%) from the total area of Ma'an is highly suitable for agriculture dependent on rainfall. While about (1.4%) is high suitable for the irrigation crops. The main reason of the low levels of land suitability for agriculture is very low soil fertility, and the water scarcity. [ABSTRACT FROM AUTHOR]

Among oilseeds, rapeseed is the third most important source of oil production in the world after soybean and palm oil. Mazandaran province produces about 19% of the country's oilseeds with thermal and precipitation potential. Therefore, the main purpose of this study is to assess the land suitability of Mazandaran province for rapeseed cultivation based on multi-criteria decision making in GIS.To achieve the land suitability assessment of the study area, climatological and Synoptic data at the provincial level since its establishment in 2011 were established for each of the phenological stages of rapeseed such as temperature, precipitation, daylight-hours, degree of day lgrowth. Sunny hours, number of frost days and relative humidity as well as environmental capability data, including soil type, land use, soil depth, elevation and slope were used. Depending on the purpose and nature of the research, the type of research is applied and the method of research is descriptive-analytical. collecting descriptive information was done by the library linguistic documentation method using library method and then in order to prioritize and evaluate the criteria related to rapeseed cultivation ، based on multi-criteria decision analysis method (MCDM ) based on Hierarchical Analysis Process AHP ) was used. Finally ، by ​​weighting the prepared layers according to the criteria and model ، the layers were combined and overlapped in GIS environment and the final land suitability assessment layer was prepared for rapeseed cultivation. The results of the discussions showed that the lands of the study area were 15.3% unlimited, 28.2% limited, 48.2% moderate and 8.3% unlimited.

Land suitability assessment is an essential step for land use planning and development. Over the last decade, many researchers, organizations, research institutes and governments have tried to provide a comprehensive procedure for the optimal use of agricultural land, but have failed to balance competing issues in a systematic way. Matter element is a multiple criteria decision analysis (MCDA) technique which has shown high potential for solving complicated issues. The use of MCDA techniques such as matter element and analytic hierarchy process (AHP) based on remote sensing (RS) and GIS is a flexible and effective framework to assess and map several different criteria for the strategic placement of cropping. We used data from 167 soil profiles covering 12,000 ha of land located in Ardabil province, northwest of Iran to assess criteria using MCDA techniques that may limit barley production under irrigation. After soil sampling and analysis, 24 soil series (all Aridisols) and 66 land units were identified and separated in the study area. Several criteria were limiting, but the most limiting criteria included: soil depth, slope, climate characteristics, pH, electrical conductivity, exchangeable sodium percentage, calcium carbonate equivalent and gypsum content. Combining and analyzing criteria in an AHP-matter element model generated a land suitability map for barley production. The coefficient of determination (R2) between land suitability index and observed barley yield was 0.947 for AHP-matter element hybrid model. Modeled estimates were compared and showed that the hybrid approach of AHP and matter element techniques was more accurate than the storie and square root methods in selecting the most suitable areas for barley production. The AHP-matter element hybrid method can therefore improve planning and decision making regarding land which is suitable for barley cultivation. This approach may also be suitable other crops. • Matter element, AHP and GIS were used to assess land suitability for barley production. • AHP-matter element model had higher accuracy than conventional methods. • The proposed model was found reasonably useful for land suitability assessment. • The hybrid model of this research is an effective and powerful system for land assessment. • The findings facilitate the land allocation and management for barley production. [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.)

Bu çalışmada, Türkiye’nin önemli çeltik ekim alanlarının bulunduğu Trakya Yarımadasında yer alan Hayrabolu Deresi Havzası’nda çeltik tarımı için Coğrafi Bilgi Sistemleri CBS destekli arazi uygunluk değerlendirmesinin yapılması amaçlanmıştır. Havza alanı Tekirdağ ilinde çeltik tarımının yapıldığı en önemli sahadır. Bu bakımdan Tekirdağ ilinin Türkiye çeltik üretimine olan katkısını değerlendirmek ve gelecekte yapılacak tarımsal amaçlı planlamalara destek olması açısından çalışmanın önemli olduğu düşünülmektedir. Çalışma amacı kapsamında Dengiz 2013 tarafından kullanılan yöntem içeriğinden yararlanılmıştır. Bu amaçla Ekinci 1990 tarafından bildirilen yöre topraklarının fiziksel ve kimyasal özellikleri kullanılmıştır. Çalışma sonunda Hayrabolu Deresi Havzası’nın % 74.1 oranla çeltik tarımına uygun arazilerden oluştuğu tespit edilmiştir. Türkiye’deki çeltik ihtiyacındaki artışa bağlı olarak yakın gelecekte havzada yeni sahalarında bu tahılın yetiştirilmesi için kullanılacağı anlaşılmaktadır. Bu bakımdan çeltik tarımına açılacak yeni sahaların bu veya buna benzer farklı çalışmalarla tespit edilip, araştırılması doğal kaynakların kullanımının sürdürülebilir olması bakımından oldukça mühim bir husustur. Sonuç olarak CBS teknikleri kullanılarak gerçekleştirilen bu çalışmanın sonuçları, benzer sahalar için aynı yöntemin rahatlıkla kullanılabileceğini göstermiştir

Copyright of Journal of Soil Science & Plant Nutrition / Toprak Bilimi ve Bitki Besleme Dergisi is the property of Soil Science Society of Turkey 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.)

The majority of the research on the uncertainties of spatial data and spatial analysis focuses on some specific data feature or analysis tool. Few have accomplished the uncertainties of the whole process of an application like planning, making the research of uncertainties detached from practical applications. The paper discusses the uncertainties of the geographical information systems (GIS) based land suitability assessment in planning on the basis of literature review. The uncertainties considered range from index system establishment to the classification of the final result. Methods to reduce the uncertainties arise from the discretization of continuous raster data and the index weight determination are summarized. The paper analyzes the merits and demerits of the "Nature Breaks" method which is broadly used by planners. It also explores the other factors which impact the accuracy of the final classification like the selection of class numbers, intervals and the autocorrelation of the spatial data. In the conclusion part, the paper indicates that the adoption of machine learning methods should be modified to integrate the complexity of land suitability assessment. The work contributes to the application of spatial data and spatial analysis uncertainty research on land suitability assessment, and promotes the scientific level of the later planning and decision-making. [ABSTRACT FROM AUTHOR]

Land suitability assessment is a fundamental process in various types of space control planning and land development, due to its effects on proper land use and reasonable urban layout. However, this form of assessment has also received much criticism for its theoretical and empirical deficiencies. This study aims to review Chinese land suitability assessment from the perspective of rainfall-waterlogging focusing on the Su Yu Yuan area in Changsha. It finds that more than half of the land in the Su Yu Yuan area that is assessed as (very) suitable for urban development has high risk of rainfall-waterlogging. The prevailing Chinese land suitability assessment method is therefore deficient as it cannot accurately reflect the rainfall-waterlogging risk of land use. To refine the land suitability assessment, it is suggested that either (1) the indictor “inundation degree of flood” is replaced with “rainfall-waterlogging risk” or (2) rainfall-waterlogging risk assessment results are superimposed onto land suitability assessment results for regions with plentiful rainfall and low-lying terrain. [ABSTRACT FROM AUTHOR]

Bioenergy is currently regarded as a renewable energy source with a high growth potential. Forest-based biodiesel, with the significant advantage of not competing with grain production on cultivated land, has been considered as a promising substitute for diesel fuel by many countries, including China. Consequently, extracting biodiesel from Jatropha curcas has become a growing industry. However, many key issues related to the development of this industry are still not fully resolved and the prospects for this industry are complicated. The aim of this paper is to evaluate the net energy, CO2 emission, and cost efficiency of Jatropha biodiesel as a substitute fuel in China to help resolve some of the key issues by studying data from this region of China that is well suited to growing Jatropha. Our results show that: (1) Jatropha biodiesel is preferable for global warming mitigation over diesel fuel in terms of the carbon sink during Jatropha tree growth. (2) The net energy yield of Jatropha biodiesel is much lower than that of fossil fuel, induced by the high energy consumption during Jatropha plantation establishment and the conversion from seed oil to diesel fuel step. Therefore, the energy efficiencies of the production of Jatropha and its conversion to biodiesel need to be improved. (3) Due to current low profit and high risk in the study area, farmers have little incentive to continue or increase Jatropha production. (4) It is necessary to provide more subsidies and preferential policies for Jatropha plantations if this industry is to grow. It is also necessary for local government to set realistic objectives and make rational plans to choose proper sites for Jatropha biodiesel development and the work reported here should assist that effort. Future research focused on breading high-yield varieties, development of efficient field management systems, and detailed studies lifecycle environmental impacts analysis is required to promote biologically and economically sustainable development of Jatropha biodiesel and to assist government agencies in setting realistic objectives and appropriate and advantageous policies for the regions and the country.

Simulations are used to generate plausible realisations of soil and climatic variables for input into an enterprise land suitability assessment (LSA). Subsequently we present a case study demonstrating a LSA (for hazelnuts) which takes into account the quantified uncertainties of the biophysical model input variables. This study is carried out in the Meander Valley Irrigation District, Tasmania, Australia. It is found that when comparing to a LSA that assumes inputs to be error free, there is a significant difference in the assessment of suitability. Using an approach that assumes inputs to be error free, 56% of the study area was predicted to be suitable for hazelnuts. Using the simulation approach it is revealed that there is considerable uncertainty about the ‘error free’ assessment, where a prediction of ‘unsuitable’ was made 66% of the time (on average) at each grid cell of the study area. The cause of this difference is that digital soil mapping of both soil pH and conductivity have a high quantified uncertainty in this study area. Despite differences between the comparative methods, taking account of the prediction uncertainties provide a realistic appraisal of enterprise suitability. It is advantageous also because suitability assessments are provided as continuous variables as opposed to discrete classifications. We would recommend for other studies that consider similar FAO (Food and Agriculture Organisation of the United Nations) land evaluation framework type suitability assessments, that parameter membership functions (as opposed to discrete threshold cutoffs) together with the simulation approach are used in concert.

This study aims to generate a Geographic Information Systems (GIS) based land suitability assessment for rice cultivation in the Hayrabolu Stream Basin located in the Thrace Peninsula where important rice cultivation areas of Turkey situated. The basin area is most important rice cultivation site in Tekirdağ province. In this regard, the study was considered significant attributes for evaluating current contribution of Tekirdağ province to the rice cultivation in Turkey and supporting the future agricultural plans in the region. The method employed by Dengiz (2013) was used in the present study. In addition, the physical and chemical properties of the soils reported by Ekinci (1990) were utilized in the study. It was determined that 74.1% of the Hayrabolu Stream Basin consisted of typical rice cultivation lands. New sites in the basin may be used for the cultivation of this grain in near future due to increasing rice demand in Turkey. Therefore, determination and characterization of possible new rice sites by means of GIS technologies is quite important for sustainable utilization of natural resources. Consequently results of this study indicated that GIS based techniques could be used for similar sites. [ABSTRACT FROM AUTHOR]

The petrochemical industry makes environmental impact and land suitability assessment is important for the petrochemical industry. The objective of this research is to develop a model to analyze the land suitability and site selection for petrochemical industry through a spatial-geographical study and environmental planning and management approach. To this purpose, the land suitability and site selection were performed using the PROMETHEE II and ELECTERE III methods in combination with GIS. These methods were used to undertake the study objective in three stages. Firstly, a review of the literature led to the formulation of analytic land suitability importance for site selection of petrochemical industry. Secondly, the major factors influencing the identification of suitable locations for petrochemical industry were identified using experts. The outranking methods were used to determine final zoning map. The final zoning map shows about 16% (45.207 Km2 ) by PROMETHEE II and 10% (29.207 Km2 ) by ELECTERE III is suitable for development of petrochemical industry. Sensitivity analysis shows suitable area is consistent with each of input factors in the model. So, this model is suitable to analyze land suitability and site selection for petrochemical industry. [ABSTRACT FROM AUTHOR]

The main objective of this study is to investigate the potential of artificial neural network (ANN) for integration with geographical information system (GIS) to assess the suitability of land to cultivate a selected crop. For this purpose, requirements of a system for intelligent assessment of land suitably were determined and the architecture of the integrated system was designed according to capabilities of ANN and GIS. For evaluation of the integrated system performance, a case study was carried out in the Mazandaran Province, located in the northern part of Iran. In the system implemented for the case study, four effective parameters in crop cultivation were utilized in the multilayer feed-forward back-propagation neural network analysis. The activation function of the hidden layer was set to log-sigmoid function. Designed ANN was trained using the samples extracted from GIS database, and 4-6-1 (4 input parameters as input layer, 6 neurons in hidden layer and 1 target value representing suitability level) structure shows the best result. Evaluation of the system shows that 83.43 % of ANN's results are acceptable and consistent with the real world. [ABSTRACT FROM AUTHOR]

Land suitability analysis is a prerequisite to achieving optimum utilization of the available land resources. Lack of knowledge on best combination of factors that suit production of rice has contributed to the low production. The aim of this study were to determine the most suitable areas for rice crop ( Oryza sativa) based on some physic-chemical properties of various alluvial soils in the Gokirmak catchment located on the Sinop-Boyabat district in the Central Black Sea Region of Turkey. To overcome the management and analysis of large volumes of spatial data for land suitability in this study, the geographic information system, geostatistic techniques and multi-criteria assessment using analytical hierarchy approach approaches were used to solve complex geographical problems and to reach reliable results for rice cultivation. According to results, 65.1 % of the study area has highly (S1) and moderately (S2) suitable whereas, 34.9 % of the study area has marginally suitable coded as S3 for rice cultivation. [ABSTRACT FROM AUTHOR]

• Approach using a linear fuzzy-logic model and a site suitability scoring method is presented. • First-of-its-kind LSA to estimate land allocation for energy crops at the field level. • By 2028, switchgrass acreage allocation and production can reach 806,582 acres and 3,174,146 dt, respectively. With the goal of evaluating biomass resource availability in certain regions in the United States, the Department of Energy, Department of Agriculture, Environmental Protection Agency, national laboratories, and Forest Service research laboratories, together with academic and industry collaborators, performed a resource analysis study, 2016 Billion-Ton Report: Advancing Domestic Resources for a Thriving Bioeconomy, Volume 1: Economic Availability of Feedstocks, using POLYSYS model to estimate biomass potential. The study provided county- and state-level biomass potential projections, with biomass feedstock production estimates and suitability assessment of lands acreage likely to transition to energy crops. For this analysis, we estimate biomass supply by year 2028, more specifically, lands acreage transition to switchgrass in the Midwest of the United States, across 50 counties in 3 states (Nebraska, Kansas, and Colorado). We propose a multi-criteria site suitability framework, to determine the potential acreage and production for switchgrass, at the field level. Site selection criteria span agronomic and ecosystem services such as previous land cover, crop rotation, soil water holding capacity, crop productivity, field efficiency, topography, soil organic matter, soil leaching propensity, distance to surface water bodies, and soil erosivity. Efficient agricultural field selection for dedicated energy crops field allocation is critical to evaluate biomass resource availability, and it is our position that estimation at the field level would provide a more accurate and useful estimation to support an emerging bioeconomy. Using field suitability scores and county-level assessments, we model land allocation decision for energy crop in the future, estimating the spatial distribution of dynamics of energy crop adoption with priority to fields scoring the highest. Compared with POLYSYS results from the report mentioned above, our method shows good performance overall, with about 2% and 1.2% of difference in switchgrass acreage allocation and crop production, respectively. [ABSTRACT FROM AUTHOR]

The main objective of this study was to develop a spatial model for land suitability assessment for rice (Oryza sativa L.) cultivation using geographic information system (GIS) techniques. The land mapping units, resulting from the overlay of the selected theme layers, have unique land quality information, on which land suitability is based. Results showed that 55.5% of the study area is highly or moderately suitable for rice cultivation, whereas 34% of that area is unsuitable for rice cultivation due to soil and topographic conditions. The model was also validated with field studies. According to the statistical analysis, there was a significant, positive relationship between land suitability classes and grain yields. Grain yield was significantly affected by land suitability class at the level of P < 0.001. The highest grain yield was obtained from rice plots in the S1 class (7287 kg ha-1), followed by S2 (6872 kg ha-1) and S3 (3928 kg ha-1) classes. [ABSTRACT FROM AUTHOR]

The main objective of this research is to develop GIS-based modeling of land allocation for industrial-agricultural land-use planning. To achieve the ultimate goal, 2 main processes were integrated as a chain. They were (1) land suitability assessments and (2) the land allocation process. Phra Nakhon Si Ayutthaya Province in Thailand was selected to be the study area because of the presence of conflicts among various high potential types of development within it. The results of the land suitability assessment showed that almost 80% of the study area was suitable for agriculture whereas about 70% of the area was suitable for industry. Unavoidably, there was considerable spatial overlap within the study area. Therefore, the land allocation process was able to designate which should be the agricultural or industrial areas. The results were collated to the study area for 4 different land-use scenarios under different policies, which were the promotions of agriculture, industries, and their combinations with an orientation towards either one. These scenarios were scenario I: maximizing the agricultural area; scenario II: maximizing the industrial area; scenario III: optimizing the industrial-agriculture (I-A) area with an agricultural orientation; and scenario IV: optimizing the I-A area with an industrial orientation. These results were shown in 4 maps of the scenarios. [ABSTRACT FROM AUTHOR]

Bioenergy is currently regarded as a renewable energy source with a high growth potential. Forest-based biodiesel, with the significant advantage of not competing with grain production on cultivated land, has been considered as a promising substitute for diesel fuel by many countries, including China. Consequently, extracting biodiesel from Jatropha curcas has become a growing industry. However, many key issues related to the development of this industry are still not fully resolved and the prospects for this industry are complicated. The aim of this paper is to evaluate the net energy, CO2 emission, and cost efficiency of Jatropha biodiesel as a substitute fuel in China to help resolve some of the key issues by studying data from this region of China that is well suited to growing Jatropha. Our results show that: (1) Jatropha biodiesel is preferable for global warming mitigation over diesel fuel in terms of the carbon sink during Jatropha tree growth. (2) The net energy yield of Jatropha biodiesel is much lower than that of fossil fuel, induced by the high energy consumption during Jatropha plantation establishment and the conversion from seed oil to diesel fuel step. Therefore, the energy efficiencies of the production of Jatropha and its conversion to biodiesel need to be improved. (3) Due to current low profit and high risk in the study area, farmers have little incentive to continue or increase Jatropha production. (4) It is necessary to provide more subsidies and preferential policies for Jatropha plantations if this industry is to grow. It is also necessary for local government to set realistic objectives and make rational plans to choose proper sites for Jatropha biodiesel development and the work reported here should assist that effort. Future research focused on breading high-yield varieties, development of efficient field management systems, and detailed studies lifecycle environmental impacts analysis is required to promote biologically and economically sustainable development of Jatropha biodiesel and to assist government agencies in setting realistic objectives and appropriate and advantageous policies for the regions and the country. [ABSTRACT FROM AUTHOR]

Abstract: Representing voices from communities of different identities and intents has been an integral part of land suitability assessment. Typically, voices of multiple communities are first synthesized and transformed into a set of coherent voices, often in the form of shared goals, objectives, criteria, or thresholds. These synchronized voices are then incorporated into an assessment model to appraise which level of suitability best characterizes each parcel of land for a specific use. The ensuing maps, as such, are a manifestation of the synthesized voices. The study reported in this article represents a different yet complementary approach to multiple voice representation, one that aims at preserving and manifesting the differences among the voices. The rendering of non-synthesized voices on the resulting maps depicts the range of valued differences. With this piece of knowledge as a reference point, planners can more effectively work with difference and make plans and facilitate consent for specific concerted actions. As a primitive experiment, the study highlights several key issues in the future development of a formal approach to multi-voice representation. [Copyright &y& Elsevier]

Nature reserves can be considered a land-use category that competes with other land-uses for territory. Therefore, one fundamental goal in conservation planning is to arrive at nature reserve designs that protect the most valuable lands for conservation, and avoid the inclusion of tracts of land valuable for other stakeholders. However, the complexity of conservation issues, the urgency for protecting critical biodiversity components and the lack of data have forced planners to rely on expert knowledge and public participation for designing nature reserves. Handling expert and public knowledge is challenging because it can be subjective, biased, value laden, context specific, and ambiguous. Here, we present a land suitability assessment (LSA) approach for designing the Sierra San Pedro Ma´rtir National Park, Baja California, Mexico. The LSA allowed us the optimal configuration SSPM in terms of delimitation (inclusion of the most valuable biological resources) and zoning (segregation of incompatible land-uses). [Copyright &y& Elsevier]

A total of 17404 soil samples (2003rd-2009th year) were analysed in the eastern Croatia. The largest number of soil samples belongs to the Osijek-Baranya county, which together with both Eastern sugar beet Factories (Osijek and Županja), conduct the soil fertility control (~4200 samples/yr.). Computer model suitability assessment for crops, supported by GIS, proved to be fast, efficient enough reliable in terms of the number of analyzed soil samples. It allows the visualization of the agricultural area and prediction of its production properties for the purposes of analysis, planning and rationalization of agricultural production. With more precise data about the soil (soil, climate and reliable Digital Soil Map of Croatia), the model could be an acceptable, not only to evaluate the suitability for growing different crops but also their need for fertilizer, necessary machinery, repairs (liming, and other measures of organic matter input). The abovementioned aims to eliminate or reduce effects of limiting factors in primary agricultural production. Assessment of the relative benefits of soil presented by computer model for the crops production and geostatistical method kriging in the Osijek-Baranya county showed: 1) Average soil suitability being 60.06 percent. 2) Kriging predicted that 51751 ha (17.16%) are of limited resources (N1) for growing crops whereas a) 86142 ha (28.57%) of land is limited suitably (S3), b) 132789 ha (44.04%) are moderately suitable (S2) and c) 30772 ha (10.28%) are of excellent fertility (S1). A large number of eastern Croatian land data showed that the computer-geostatistical model for determination of soil benefits for growing crops was automated, fast and simple to use and suitable for the implementation of GIS and automatically downloading the necessary benefit indicators from the input base (land, analytical and climate) as well as data from the digital soil maps able to: a) visualize the suitability for soil tillage, b) predict the benefits of growing crops using kriging method and c) conduct analysis for production area, planning and/or rationalization with more efficient and economical investment in primary agricultural production. Application of computer model is accurate for fertilizer crops recommendations, but caution should be taken until the model is calibrated allowing prediction within acceptable error/risk, because of relatively small number of samples and insufficient reliability of pedoclimatic data.