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A policy on agricultural land zoning, based on land suitability maps, has been introduced to optimize the use of resources for crop production in Thailand. However, the impact of activities occurring during cultivation in different land suitability classes has not been considered. A land–water–climate nexus index (LWCNI) has therefore been introduced as a holistic analysis that integrates three indicators––land-use intensity, water-use intensity, and climate change impact in terms of GHG emissions. This can guide resource allocation by highlighting areas that need improvement. We aimed to assess the land–water–climate nexus in different land-suitability classes for sugarcane and cassava in Thailand in order to compare the nexus performances and improve the planning and management of resources for sustainable production. The LWCNI was developed and assessed by combining it with geographic information system–based tools for evaluating the nexus performances of sugarcane and cassava cultivation as per the agricultural zoning policies. The scope of the work was "from cradle to farm-gate", and the final products considered were sugarcane and fresh cassava. The results revealed that sugarcane cultivation in moderate-suitability areas is the most effective, with the best LWCNI score being 0.87, suggesting efficient cultivation practices with a minimal use of land and water resources, and a minimal climate change impact. The three indicators of land-use intensity, water-use intensity, and GHG emissions for sugarcane were estimated at 0.010 ha/t, 108 m3/t, and 6.2 kg carbon dioxide equivalent (CO 2 e)/t, respectively. Cassava cultivation in the high-suitability area was the most efficient, with the best LWCNI score, at 0.95, and using less land, fewer water resources, and having less of a climate change impact. The land-use intensity, water-use intensity, and GHG emissions of cassava were estimated at 0.030 ha/t, 255 m3/t, and 35.7 kgCO 2 e/t, respectively. Growing crops in marginal and unsuitable areas presented a risk of a high climate change impact as well as competition for water resources due to limited local resources. We found that, even in the same land-suitability class, the amount of fertilizer used by the farmers varied depending on their knowledge, experience, and finances. Excessive fertilizer application increased GHG emissions, which in turn brought about a decrease in the LWCNI score, leading to a poorer nexus performance. The findings emphasize the relationship between land and water use and climate change impact across varying spatial contexts. The LWCNI approach offers valuable insights for supporting agricultural zoning policy. [Display omitted] • Cultivation in high and moderate suitability land needed for sustainable agriculture. • Farmers' practices regarding fertilizer have a major impact on GHG emissions. • Land-water-climate nexus reveals trade-offs between land, water and GHG emissions. [ABSTRACT FROM AUTHOR]

Agriculture activity contributes to greenhouse gas (GHG) emissions through its utilization of land, water, and energy for food production. Hence, the interactions between land, water, and GHG emissions in agricultural production need to be comprehensively studied. The study aimed to assess the Land-Water-GHG-Food Nexus Index (LWGFNI) of rice cultivation across various land suitability classes in Central Thailand and determining the physical, socio-economic, and policy factors that can influence farmers' decisions to choose for cultivating rice instead of shifting to other crops. The results indicated that the highest LWGFNI score was 0.69 for the rice grown in the moderate suitability land class which revealed a lower use of land and water resources as well as GHG emissions compared to other levels of land suitability. The LWGFNI scores of major rice cultivation were greater compared to the second rice in all four-land suitability. The use of fertilizers had a crucial role in enhancing productivity levels and was a significant factor in the generation of GHG emissions. Hence, improving effective production should consider the appropriate use of fertilizer. The physical, socio-economic, and policy-related aspects that significantly influenced farmers' decisions on cultivation of rice included topography, water resources, inherited professions, price guarantee, and knowledge/training factors. The methodology used and results obtained can help policy makers to plan the use of water and land resources efficiently and appropriately with local resources based on land suitability class. The assessment results revealed the GHG hotspots and the strategies to mitigate GHG emissions associated with rice cultivation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

An agricultural land suitability map was developed for rice (Oryza sativa L.) cultivation of land severely contaminated with heavy metals at Mae Tao, Thailand, as a representative area from which more than 300 soil samples and 100 rice grain samples were collected. The average concentrations for As, Cd, Pb, and Zn in the soil were 20.99, 2.66, 19.92, and 115.62 mg/kg, respectively The geo accumulation index (Igeo) values for As, Cd, Pb, and Zn indicated that this area was highly contaminated with Cd. Land suitability maps were developed for three scenarios: I—following conventional factors in the Storie index; II—adding factor D (heavy metal contamination) with the same weighting for four heavy metals; and III—with factor D focusing on As contamination. The results revealed that adding factor D in the Storie index decreased the suitable area for rice cultivation. Taking into account heavy metal contamination of the soil in land suitability mapping, it reduced the areas of highly suited, suited, and marginally suited by 15%. However, the concentration of heavy metals in rice grain in highly suited and suited land was lower than the Codex standard for food safety and quality. This was confirmed by the hazard index (HI) for rice grain planted in scenarios including factor D (HI < 1). Our research should lead to agricultural land management to protect human health from the danger of consuming rice contaminated with heavy metals. [ABSTRACT FROM AUTHOR]

The low Prachinburi watershed is a gateway to other regions of the country. Due to a rapid increase in population there, there is also an increase in agricultural production area. This study aims to assess the appropriateness of land use by using an analytical hierarchy process (AHP) for land use planning. The results of the study revealed that there is a moderate level of the appropriateness in land use development. The most appropriate area (S1) accounts for 22.07%; the moderately appropriate area (S2) accounts for 54.15%; the lowly appropriate area (S3) accounts for 10.25%; and the inappropriate area accounts 13.52% of the area. Regarding a guideline for agricultural area management, it is found to be most appropriate, particularly on field crop growing such as cassava, sugar cane, and maize growing and followed by rice growing and or charding (58.51%, 25.17%, and 6.04%, respectively). Only 10.25% of the total area is inappropriate for farming. [ABSTRACT FROM AUTHOR]

• GIS and AHP were integrated to analyse the land suitability for urban development. • Policies and flood have a key role in assessing urban development areas in Nong Khai. • 24.73 % of the total area are high suitability for urban development. • Very highly suitable areas show high values in hazard, accessibility, and policy. • A planning case in the small city coping with urbanisation due to BRI are provided. The Belt and Road Initiative is a megaproject expected to accelerate urban growth. However, the accompanying urban development process can endanger the environment. Thus, land suitability assessment for urban development is crucial to cope with the urban expansion, especially in the anticipated rapid urbanisation areas. This study aims to assess the land suitability for urban development in Nong Khai City, Thailand. Eighteen criteria were selected to indicate suitability by integrating the analytical hierarchy process with the geographical information system. The results showed that the policy to conserve the cultural assets, flood, and the policy to conserve the natural assets have the biggest influence on the decision-making for urban development areas. Precisely 24.73% of the areas were very highly suitable for urban development, most of which are flood-free with high accessibility and high suitability regarding policy. Precisely 12.10% of the areas were very lowly suitable for urban development, most of which are prone to flooding, have low accessibility, and are distributed in the zones under the policy to conserve natural assets. The results highlighted how the suitability map for urban development is utilized in urban planning and provided evidence to support urban planning in the context of small cities. [ABSTRACT FROM AUTHOR]

Understanding the pattern–process relations of land use and land cover change is an important area of research that provides key insights into human–environment interactions. The suitability or likelihood of occurrence of land use such as agricultural crop types across a human-managed landscape is a central consideration. Recent advances in niche-based geographic species distribution models (SDMs) offer a novel approach to understanding land suitability and land use decisions. SDMs link species presence and location data with geospatial information and use machine learning algorithms to develop nonlinear and discontinuous species–environment relationships. Here, we apply the maximum entropy (MaxEnt) model for land suitability modeling by adapting niche theory to a human-managed landscape. In this article, we use data from an agricultural district in northeastern Thailand as a case study for examining the relationships among the natural, built, and social environments and the likelihood of crop choice for the commonly grown crops that occur in the Nang Rong District—cassava, heavy rice, and jasmine rice, as well as an emerging crop, fruit trees. Our results indicate that although the natural environment (e.g., elevation and soils) is often the dominant factor in crop likelihood, the likelihood is also influenced by household characteristics, such as household assets and conditions of the neighborhood or built environment. Furthermore, the shape of the land use–environment curves illustrates the noncontinuous and nonlinear nature of these relationships. This approach demonstrates a novel method of understanding nonlinear relationships between land and people. The article concludes with a proposed method for integrating the niche-based rules of land use allocation into a dynamic land use model that can address both allocation and quantity of agricultural crops. [ABSTRACT FROM AUTHOR]

Abstract: Recent advances in ecological modeling have focused on novel methods for characterizing the environment that use presence-only data and machine-learning algorithms to predict the likelihood of species occurrence. These novel methods may have great potential for land suitability applications in the developing world where detailed land cover information is often unavailable or incomplete. This paper assesses the adaptation and application of the presence-only geographic species distribution model, MaxEnt, for agricultural crop suitability mapping in a rural Thailand where lowland paddy rice and upland field crops predominant. To assess this modeling approach, three independent crop presence datasets were used including a social-demographic survey of farm households, a remote sensing classification of land use/land cover, and ground control points, used for geodetic and thematic reference that vary in their geographic distribution and sample size. Disparate environmental data were integrated to characterize environmental settings across Nang Rong District, a region of approximately 1300sq. km in size. Results indicate that the MaxEnt model is capable of modeling crop suitability for upland and lowland crops, including rice varieties, although model results varied between datasets due to the high sensitivity of the model to the distribution of observed crop locations in geographic and environmental space. Accuracy assessments indicate that model outcomes were influenced by the sample size and the distribution of sample points in geographic and environmental space. The need for further research into accuracy assessments of presence-only models lacking true absence data is discussed. We conclude that the MaxEnt model can provide good estimates of crop suitability, but many areas need to be carefully scrutinized including geographic distribution of input data and assessment methods to ensure realistic modeling results. [Copyright &y& Elsevier]