Land Suitability Research Articles

Evaluating land suitability for kemiri (Aleurites moluccana) as a multi-purpose tree species in community agroforestry land within Langkat District, North Sumatra

Evaluating land suitability for Aleurites moluccana in community agroforestry land within Langkat District, North Sumatra, is crucial for promoting sustainable development, enhancing livelihoods, and preserving ecosystems while honoring local traditions and cultures. The primary objective of this research was to evaluate and map the land suitability for A. moluccana within Langkat District, located in North Sumatra, Indonesia. To gather the necessary data, this study employed a survey method, involving the collection of soil samples from ten distinct land units within the field. The assessment of land suitability was carried out using the matching method. Geographic Information System (GIS) technology was utilized to create maps illustrating the distribution of land suitability, while a Global Positioning System (GPS) was employed to accurately record the coordinates of the collected soil samples. The findings revealed that within Gunung Ambat, Simpang Kuta Buluh, Rumah Galuh, and Telagah Village, the actual land suitability classes for A. moluccana were classified as moderately suitable (S2) and marginally suitable (S3). The prevailing limiting factors in this region were temperature (tc) and the characteristics of the root zone medium (rc). Consequently, this influenced the potential land suitability classes for A. moluccana, resulting in classifications ranging from highly suitable (S1) to moderately suitable (S2) and marginally suitable (S3). By implementing land suitability evaluation for A. moluccana in community agroforestry land, promoting sustainable land use, enhancing livelihoods, and conserving natural resources.

A GIS-based land suitability assessment of wheat production in Kano using selected physical parameters

Wheat is the second largest contributor to Nigeria's food import bill and puts pressure on the foreign reserve of the nation. Land suitability assessment is a prerequisite to achieving optimum utilization of the available land resources. Lack of knowledge on best combination of factors that suit production of wheat has contributed to the low produce. The study aims to assess land suitability of wheat production in kano using selected physical materials with the objectives to map out existing locations for wheat production in kano state, determine other areas that may be suitable for wheat production. The study utilized Landsat 8; Shuttle Radar Topography Mission (SRTM) Multi-criteria Evaluator (MCE) integrated with GIS. Spatial factors for wheat cultivation such as soil texture, soil type, soil slope, rainfall range, geology map, elevation, land use land cover and their attribute were identified and were processed into spatial data. The factors were weighed according to their relevance. Land suitability model was constructed in ArcGIS software and spatial data were imported into (SRTM) and link to the land suitability model constructed. The spatial data integrated were computed and final visualization of land suitability map was produced and using ArcGIS 10.3 to identify potential areas. The result obtained showed that 16% were unsuitable, 19% were moderately suitable, 25% were highly suitably and then 40% were most suitable in the study area. Based on this finding, it is recommended that wheat cultivation should be practiced in a large scale in Kano state.

Balancing Environmental and Human Needs: Geographic Information System-Based Analytical Hierarchy Process Land Suitability Planning for Emerging Urban Areas in Bni Bouayach Amid Urban Transformation

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.

Analysis of Coconut Agribusiness Development Strategy in North Minahasa Regency

The development of coconut in North Minahasa requires an appropriate and efficient strategy. This research aims to assess and analyze the conditions in the coconut agribusiness system in North Minahasa, outline the factors of IFAS (Internal Factors Analysis Summary) and EFAS (External Factors Analysis Summary) matrices, and provide policy recommendations related to the coconut agribusiness development strategy in North Minahasa. The research was conducted over a period of 9 months, utilizing both primary and secondary data. Primary data were obtained through the distribution of questionnaires, followed by Focus Group Discussions with respondents and direct interviews with coconut farmers, collector traders, and coconut processing industries (producing copra, flour, and coconut milk) in North Minahasa Regency, as well as business entities involved in the coconut agribusiness. Secondary data were obtained from relevant institutions such as the Central Statistics Agency, the Regional Agriculture Office of North Minahasa Regency, previous research journals, and related books. The research results, analyzed through a SWOT analysis of the Coconut Agribusiness Development Strategy in North Minahasa Regency, fall into quadrant I, indicating an aggressive strategy with coordinates (0.42:0.44), aligning with strengths and opportunities. The derived strategy is S-O (Strength-Opportunity), focusing on maintaining the availability of raw materials, the market for processed coconut products, human resources, and land suitability, with support from the local government to increase community income and expand coconut processed products into the international market.

A spatial analysis of the economic returns to land‐use change from agriculture to renewable energy production: Evidence from Ireland

AbstractCountries are looking to reduce their agricultural sector's carbon footprint while encouraging economic and environmental sustainability. One proposed method of making agriculture more sustainable while maintaining farm incomes is through the production of bioenergy feedstocks. We examine the spatial aspect of the production of renewable energy feedstocks in Ireland. Two feedstocks are looked at—grass silage and short‐rotation coppice (SRC) willow. Spatial microsimulation analysis is utilised to assess the spatial suitability for alternative land uses, simulating land‐use change to compare economic returns with the current agricultural use. A farm‐based carbon subsidy is modelled based on avoided agricultural emissions and carbon sequestered. We find that midlands counties, especially those in the north midlands, have the highest proportion of land where feedstocks would be more profitable than the current agricultural use. Counties on the western seaboard have the lowest proportion of land where feedstocks would give greater returns. The amount of land where feedstocks are more profitable increases as greater carbon subsidies are provided. Of the two feedstocks assessed, SRC willow cultivation is more profitable than grass silage production. The overwhelming majority of land where producing feedstocks would be more profitable has cattle farming as its current use.

Land suitability mapping for groundnut production in southern region of Borno state, Nigeria

Groundnut (Arachis hypogea) is a leguminous oilseed crop cultivated in the semi-arid and subtropical region of the world. In West Africa, groundnut plays an important role. This includes food production for household consumption, cash crops, sources of employment, and incomes for smallholders in rural households. In Nigeria, it was among the major sources of income before the oil boom. Some of the activities surrounding its production are the development of commerce, employment, and foreign exchange. This study aims to identify the most suitable sites for groundnut production in the Southern Borno Region, Nigeria with the objectives to identify areas of groundnut cultivation within the southern Borno region and to conduct a suitability analysis for groundnut production within the study area. Primary and secondary data and questionnaires were used in this study. Climatic data such as Temperature, Rainfall, Precipitation, Wind speed, Relative Humidity, Soil, and Topographic data were also used. The parameters were overlaid using the weighted overlaid operation in ArcGIS 10.3 and ranked from the most suitable to the least suitable for wheat production within the study region. The result of the study revealed that groundnut is cultivated in all parts of Southern Borno Region. It revealed that areas around Askira/Uba, Chibok and Damboa are the most suitable site for groundnut cultivation. This study demonstrates the capabilities of Remote Sensing and GIS Systems for multi-criteria analysis in Land Suitability Mapping. It is recommended that farmers around Askira/Uba, Chibok and Damboa be encouraged to cultivate more groundnuts.

China's onshore wind energy potential in the context of climate change

China has great potential for developing renewable energy to achieve its carbon neutrality goals. Orderly development of renewable energy is essential to enhance resource utilization efficiency and ensure safety during the energy system transition process. This study presents a thorough assessment of China's onshore wind power potential by considering the land suitability, the potential and temporal characteristics, and the impacts of climate change. The high-resolution maps combining wind resources with land conditions and climate scenarios are produced to provide insights into system planning, grid integration, and flexibility management. The results show that the capacity potential of onshore wind energy in China is 9.6 TW with an annual generation of 12.6 PWh, and 83 % of total capacity has a cost advantage with the levelized cost lower than the 60 $/MWh threshold. By comprehensively considering geographical, economic, and social criteria, around 8.1 % of the national territorial area is identified as the most suitable area for wind power development, primarily in Inner Mongolia and Xinjiang. The annual electricity generation from these areas can fulfill nearly 69 % of the nation's electricity demand. Future climate change projections indicate a remarkable generalized drop by 18 % in the north and a slight increase by 7 % in the south under the RCP 8.5 scenario. However, significant changes in wind resources are mostly within restricted areas, suggesting that future climate change would like to bring negative but limited impacts on wind power production in China.

Land suitability assessment for mango production in Kitui County, Kenya

Land suitability assessment for mango production in Kitui County, Kenya

Land-use suitability assessment for urban development using Multi-Criteria Decision-Making Analysis in the Himalayan districts of Shimla, Nainital, and Darjeeling, India

After India gained independence in 1947, notable advancements in healthcare and socio-economic sectors resulted in a remarkable population surge, consequently driving substantial expansion in built-up areas throughout the country. The consequences of the rapid and unplanned expansion are adverse in the Himalayas where earthquake, landslides, flash floods are frequent. The already established hill stations saw a rapid surge in tourism and subsequent urbanization. This study delves into assessing the urban suitability of such hill stations namely Nainital, Shimla, and Darjeeling. The surge in tourism led to alarming population growth with haphazard urbanization which is often severely affected by growing natural hazards. The aim of this study is to assess the urbanization suitability of the regions based on multiple factors that affects the choice of suitable place for urban growth. We employed the GIS based Multi-Criteria Decision-Making Approach (MCDMA) considering geological, socio-economical, ecological, and prohibitive factors using the Analytical Hierarchy Process (AHP) method. The obtained land-use suitability maps for urbanization show that in Nainital the most suitable area for urbanization is the foothills of the Himalayas whereas in Shimla it is around the central and southern part. The northern part and the eastern boundary of Darjeeling are the most suitable area for urbanization. Upon comparing the already existing built-up areas with the AHP derived site suitability results we found that the Darjeeling district is most vulnerable as almost half of the built-up area (49%) lies within a very low to moderate suitable zone. Our findings show that Darjeeling has the highest amount of suitable land for urbanization as the bare ground in the region is not suitable for agriculture. Interestingly, the farmlands in Nainital show highest suitability when urbanization is considered. This brings out a serious problem in urbanization trend and it is observed throughout the world. Thus, more careful research is needed ensuring proper land use and food security for the growing population. This study lays a foundational understanding of challenges associated to urbanization in a tectonically active mountain range.

Analisis Daya Dukung Lahan untuk Permukiman di Kota Bukittinggi

Bukittinggi City, with the land conversion to built-up land continues to increase and the availability of land that does not increase, faces difficulties in utilizing land for settlements along with increasing population growth. The purpose of this study is to analyze the suitability of land for settlements and the carrying capacity of Bukittinggi City's residential land for the next 30 years. The quantitative descriptive research method with data presented through tables and maps, calculations refer to the Ministry of Environment's 2014 carrying capacity guidelines and RP3KP. The results of the study indicate that the area of land suitable for settlements is Suitable (S2) covering 710 ha, less suitable (S3) covering 1,147 ha, and not suitable covering 430 ha. For the carrying capacity of Bukittinggi City settlements, in Guguk Panjang District it is in the deficit class, with a DDPm value of 0.24, while 2 other districts are in the surplus class, with Mandiangin Koto Selayan District valued at 2.42, and Aur Birugo Tigobaleh District of 4.09. And for a period of 30 years, 2032, 2042, and 2052, Mandiangin Koto Selayan sub-district and Aur Birugo Tigobaleh sub district still have a surplus while Guguk Panjang sub-district is still in deficit.

Enhancing agricultural sustainability through CNN-LSTM based land suitability assessment for improved production

Agricultural sustainability is an important concern facing global population expansion and environmental challenges. Accurate land suitability evaluation is critical for ensuring efficient and effective land usage. The aim of this research is to assess the following framework that the Food and Agriculture Organization (FAO) developed, if the land in India is suitable for two key crops, namely maize and barley. Soil specimens and physical-chemical properties from 105 genetic soil profile layers are collected. Weather and landscape data were gathered. Deep learning (DL) techniques were used to map the two crops' land suitability classifications after computation. This study suggests a unique method for assessing land potential for increased agricultural output by Convolution Neural Networks-Long Short-Term Memory (CNN-LSTM) networks. The maps generated by the two ways showed significant disparities. Studies on rain-fed corn, for example, showed that DL-based land suitability maps were more accurate than those created using the traditional method. The outcomes demonstrated that when contrasting the CNN-LSTM method with the conventional methodology, the areas with classes C2 were higher and the areas with categories C1 were less projected. Rainfall during the flowering period, steep slopes, poor soil depth, high pH and a high gravel component were the research area's main drawbacks. Land development activities are recommended to boost productivity and build a sustainable agricultural system. This research contributes to balance farm expansion and environmental protection, supporting a sustainable and resilient agricultural system to fulfill the requirements of the world's rising population.

The Strategy for Developing an Arabica Coffee Plantation-Based Area in Banyumas Regency

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. 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 sub-districts 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.

Spatial distribution and habitat suitability of seaweed on West Simeulue Island, Aceh Province, Indonesia

Seaweed is an important biological resource for human life, serving essential ecological functions, including providing shelter and feeding grounds for marine biota. Seaweed can be found in several Indonesian waters, growing naturally or through cultivation, including in the waters around Simeulue Island. This study aimed to assess the distribution of seaweed in relation to land suitability, using oceanographic parameters in Simeulue Island waters. The research was conducted at five stations within the West Teupah District, South Teupah District, and Alafan District. In situ measurements were taken to evaluate land suitability for seaweed growth based on oceanographic parameters such as current speed, depth, substrate type, salinity, temperature, pH, and dissolved oxygen. Results indicated that seaweed in Simeulue Island waters is distributed along the coastline and attached to coral reefs and rocks at depths of 2-5 meters. The total area of seaweed distribution is approximately 351.83 hectares along a coastline of 206.12 km. The measured parameters of seaweed habitats include a pH of 7.7 to 7.9, salinity of 31-35.3 ppt, temperature of 20-30 °C, dissolved oxygen levels of 3-4.8 mg/L, depth of 2-5 meters, current speed of 0.10 to 0.60 m/s, and a sandy coral substrate. Based on these water quality and substrate parameters, the seaweed habitats in Simeulue Island are classified as highly suitable, with suitability values ranging from 64 to 82. The recorded environmental conditions collectively support optimal seaweed growth.

Evaluation and Promotion of Alluvial Fan Land Suitability for Agriculture in the Lhasa River Basin, Qinghai–Tibet Plateau

Alluvial fans have been proven to have great utilisation potential in QTP, but to what extent they are suitable for agricultural development is unknown. Therefore, using the alluvial fan in the Lhasa River Basin (LRB) as a case study, this paper established an evaluation system of land suitability for agriculture (LSA). Principal component analysis (PCA) and the exhaustive method (EM) were used to define the minimum dataset (MDS) and then the LSA of the alluvial fan in the LRB was evaluated using a comprehensive index of LSA. Two scientific approaches were implemented to improve the LSA using a scenario simulation. The results showed that the MDS assessed by the EA was more representative compared to the PCA. Alluvial fans with suitable grades are mainly distributed in the Lhasa River’s middle and lower reaches. Developing facility agriculture and repairing roads accessing the alluvial fans are effective approaches to improve the LSA, which can increase the suitable-grade area from 58.62% to 97.82% and 63.85%, respectively. Therefore, most alluvial fans in the LRB are suitable for developing agriculture, and under the influence of human activities, there will be more alluvial fans suitable for developing agriculture. Our research provides scientific methods for the sustainable development of land in alpine regions.

Nonbreeding distributions of four declining Nearctic–Neotropical migrants are predicted to contract under future climate and socioeconomic scenarios

ABSTRACT Climate and land use/land cover change are expected to influence the stationary nonbreeding distributions of 4 Nearctic–Neotropical migrant bird species experiencing population declines: Cardellina canadensis (Canada Warbler), Setophaga cerulea (Cerulean Warbler), Vermivora chrysoptera (Golden-winged Warbler), and Hylocichla mustelina (Wood Thrush). Understanding how and where these species’ distributions shift in response to environmental drivers is critical to inform conservation planning in the Neotropics. For each species, we quantified current (2012 to 2021) and projected future (2050) suitable climatic and land use/land cover conditions as components of stationary nonbreeding distributions. Multi-source occurrence data were used in an ensemble modeling approach with covariates from 3 global coupled climate models (CMCC-ESM2, FIO-ESM-2-0, MIROC-ES2L) and 2 shared socioeconomic pathways (SSP2-RCP4.5, SSP5-RCP8.5) to predict distributions in response to varying climatic and land use/land cover conditions. Our findings suggest that distribution contraction, upslope elevational shifts in suitable conditions, and limited shifts in latitude and longitude will occur in 3 of 4 species. Cardellina canadensis and S. cerulea are expected to experience a moderate distribution contraction (7% to 29% and 19% to 43%, respectively), primarily in response to expected temperature changes. The V. chrysoptera distribution was modeled by sex, and females and males were projected to experience a major distribution contraction (56% to 79% loss in suitable conditions for females, 46% to 65% for males), accompanied by shifts in peak densities to higher elevations with minimal changes in the upper elevation limit. Expected changes in precipitation had the greatest effect on V. chrysoptera. Hylocichla mustelina experienced the smallest distribution change, consistent with the species’ flexibility in habitat selection and broader elevational range. We recommend defining priority areas for conservation as those where suitable conditions are expected to remain or arise in the next 25 years. For V. chrysoptera in particular, it is urgent to ensure that mid-elevation forests in Costa Rica and Honduras are adequately managed and protected.

Optimizing land use for climate mitigation using nature based solution (NBS) strategy: a study on afforestation potential and carbon sequestration in Rajasthan, India

Rajasthan faces significant environmental challenges, including the pressing need for effective climate change mitigation strategies. Recognizing afforestation as a vital tool in this endeavor, this study leverages the latest in remote sensing and geospatial analysis to map out the state's afforestation potential. The goal is to assess land suitability across Rajasthan for afforestation projects and evaluate the potential carbon sequestration capabilities of different tree species. This aims to inform sustainable land management strategies that can contribute to climate change mitigation. By integrating satellite imagery, land cover data, terrain analysis, and vegetation indices, the study evaluates environmental factors such as slope, soil moisture, and vegetation health to identify areas optimal for tree planting. A carbon sequestration model was also developed to estimate sequestration rates based on species-specific growth patterns. Findings indicate that approximately 40% of Rajasthan is suitable for afforestation, with potential carbon sequestration rates ranging from 2 to 8 tons per hectare per year. Species such as Azadirachta indica (Neem) and Prosopis cineraria (Khejri) are identified as particularly effective for short-term sequestration, while Phyllanthus emblica (Amla) and Ziziphus mauritiana (Ber) are better suited for long-term carbon capture. This research highlights the importance of targeted afforestation using suitable tree species as a nature-based solution (NBS) for climate change mitigation in Rajasthan. The study offers a data-driven approach to enhancing ecosystem resilience and supports decision-making for climate adaptation in arid regions, highlighting the significant potential of Rajasthan's land for carbon sequestration through afforestation.

Arahan Sistem Pertanian Ideal Berbasis Potensi Sumberdaya Lahan: Komponen Dasar Cukilan Smart Village

In recent years, the concept of smart villages has gained increasing prominence as a means of encouraging sustainable development in rural areas. This is particularly relevant in the agricultural sector, where the potential of land resources is crucial. Cukilan Village, located in Suruh District, Semarang Regency, Central Java, is primarily an agricultural area, with over 80% of its land designated for agricultural purposes. The village government has expressed a desire to develop Cukilan as a smart village through an FGD process. Based on this background, a community service program was implemented with the aim of designing Cukilan Village as a smart village in stages, to enhance economic growth and prosperity by leveraging the potential of agricultural resources and human resources, as well as accelerating the village development process. The method for implementing this PKM (Community Service) program utilized the Assets-Based Community Development (ABCD) approach, which involved outreach, discussion, mapping of agroecological zones, as well as land suitability and evaluation. As a result of this initiative, the Cukilan Village government received guidance for an ideal agricultural system based on land resource potential, which serves as a basic component towards the realization of Cukilan Smart Village.

Unravelling the complexities of wetland agriculture, climate change, and coping mechanisms: an integrative review using economics and satellite approaches

AbstractThe flash flood-affected wetland region of Bangladesh contributes around 20–25% of the annual Boro rice production, which is vital for local, regional, and national food security. Considering the crucial significance of Boro rice and the growing susceptibility of wetland regions to flash floods and climate change, it is imperative to investigate viable approaches and adaptation methods to reduce the adverse effects on agricultural output. This review study investigated the relationships between wetlands, climate change, and coping mechanisms while incorporating economic and advanced satellite remote sensing approaches. Through a comprehensive analysis of flash flood impacts on Boro rice yield using satellite remote sensing technique, the findings revealed significant adverse effects on the vegetative reproduction of Boro rice in the study areas. Notably, flash floods in 2017 exhibited more pronounced impacts than other years (2018 and 2019), underscoring the urgency for effective and integrated coping strategies to ensure sustainable agricultural production. Consequently, the study identified and discussed probable coping strategies, including changes in cropping patterns through land suitability assessment, evaluating vulnerable areas through vulnerability mapping, analyzing yield forecasting models, and introducing a damage-based crop insurance approach to mitigate farmers’ losses. These probable adaptation strategies will offer viable solutions to address the recurrent issue of flash floods and safeguard sustainable agricultural production in the wetland areas of Bangladesh. Considering the current situation, climate change issues and probable alternative coping strategies are crucial for developing a resilient agricultural system in light of flash floods, ensuring the long-term viability of wetland agriculture. The study outcomes provide valuable insights for policymakers, researchers, and stakeholders in wetland agricultural planning and management to develop proper and long-term sustainable adaptation and mitigation strategies.

A fusion approach using GIS, green area detection, weather API and GPT for satellite image based fertile land discovery and crop suitability

Proper utilization of agricultural land is a big challenge as they often laid over as waste lands. Farming is a significant occupation in any country and improving it further by promoting more farming opportunities will take the country towards making a huge leap forward. The issue in achieving this would be the lack of knowledge of cultivable land for food crops. The objective of this work is to utilize modern computer vision technology to identify and map cultivable land for agricultural needs. With increasing population and demand for food, improving the farming sector is crucial. However, the challenge lies in the lack of suitable land for food crops cultivation. To tackle this issue, we propose to use sophisticated image processing techniques on satellite images of the land to determine the regions that are capable of growing food crops. The solution architecture includes enhancement of satellite imagery using sophisticated pan sharpening techniques, notably the Brovey transformation, aiming to transform dull satellite images into sharper versions, thereby improving the overall quality and interpretability of the visual data. Making use of the weather data on the location observed and taking into factors like the soil moisture, weather, humidity, wind, sunlight times and so on, this data is fed into a generative pre-trained transformer model which makes use of it and gives a set of crops that are suitable to be grown on this piece of land under the said conditions. The results obtained by the proposed fusion approach is compared with the dataset provided by the government for different states in India and the performance was measured. We achieved an accuracy of 80% considering the crop suggested by our model and the predominant crop of the region. Also, the classification report detailing the performance of the proposed model is presented.

Case study on climate change effects and food security in Southeast Asia

Agriculture, a cornerstone of human civilization, faces rising challenges from climate change, resource limitations, and stagnating yields. Precise crop production forecasts are crucial for shaping trade policies, development strategies, and humanitarian initiatives. This study introduces a comprehensive machine learning framework designed to predict crop production. We leverage CMIP5 climate projections under a moderate carbon emission scenario to evaluate the future suitability of agricultural lands and incorporate climatic data, historical agricultural trends, and fertilizer usage to project yield changes. Our integrated approach forecasts significant regional variations in crop production across Southeast Asia by 2028, identifying potential cropland utilization. Specifically, the cropland area in Indonesia, Malaysia, Philippines, and Viet Nam is projected to decline by more than 10% if no action is taken, and there is potential to mitigate that loss. Moreover, rice production is projected to decline by 19% in Viet Nam and 7% in Thailand, while the Philippines may see a 5% increase compared to 2021 levels. Our findings underscore the critical impacts of climate change and human activities on agricultural productivity, offering essential insights for policy-making and fostering international cooperation.