Agricultural Development Planning Research Articles

Time Series Analysis of Sugarcane Plant Height and Planting Area Identification Based on DPRVI and RF Algorithm

With the modernisation of agriculture, the time series analysis of sugarcane growth and the identification of planting areas play an important role in the investigation and detection of agriculture. The study conducted a time series analysis of sugarcane plant height and identification of planting areas based on dual polarisation radar vegetation index and random forest algorithm. Firstly, dual-polarisation radar vegetation index data of sugarcane were obtained using Sentienl-1A radar remote sensing data for time-series analysis of sugarcane plant height. Then the random forest model was applied to the regression and classification of Sentinel-2A remote sensing images for sugarcane plantation area identification. According to the findings, sugarcane field 4 had an R2 value of 0.835 in the quadratic regression model inversion, and the average absolute difference between the model’s predicted plant height and the actual value was only 7.3%. It shows that the dual-polarization radar vegetation index has great reliability and is capable of accurately predicting sugarcane plant height during the pre-growth stage. The user and producer accuracies are as high as 0.911 and 0.989, respectively, and the overall accuracies and Kappa coefficients are as high as 0.976 and 0.932, respectively, indicating that the Random Forest with multi-temporal phase and multi-feature is able to effectively identify sugarcane planting areas. The accuracy under multi-temporal phase and multi-feature is better than the single-temporal phase. It offers a trustworthy way for developing contemporary agricultural policy and development planning.

Innovative trend analysis technique with fuzzy logic and K-means clustering approach for identification of homogenous rainfall region: A long-term rainfall data analysis over Bangladesh

Understanding regional climatic trends is crucial for taking appropriate actions to mitigate the impacts of climate change and managing water resources effectively. This study aims to investigate the dissimilarities and similarities among various climate stations in Bangladesh from 1981 to 2021. Fuzzy C-means (FCM) and K-means clustering techniques were employed to identify regions with comparable rainfall patterns. Moreover, the innovative trend analysis (ITA) and the Mann-Kendall (MK) test family were utilized to analyze rainfall trends. The results indicate that both K-means and FCM methods successfully detected two rainfall regions in Bangladesh with distinct patterns. The ITA curve analysis revealed that out of the 29 stations, 13 had a non-monotonic increasing trend having no monotonic increasing trend, 8 had a non-monotonic decreasing trend, and 8 exhibited a monotonic decreasing trend. Additionally, the MK tests employed in the study showed predominantly negative trends across Bangladesh. The majority of stations (65.51%) fell into Cluster 1, while the remaining 34.48% were in Cluster 2. In terms of ITA analysis, 17.24% of stations exhibited a monotonic decrease, while there were no stations with a monotonic increase. However, 37.93% of stations showed a non-monotonic increase, and 44.83% displayed a non-monotonic decrease. These identified regions can provide valuable insights for water resource management, disaster risk reduction, and agricultural planning. Moreover, detailed rainfall analysis can help policymakers and scientists develop sustainable and effective regional-scale policies for managing the country's flood and drought situations, ultimately supporting agricultural development and environmental planning.

Planowanie terenów rolniczych w Bułgarii - obecna funkcjonalność prawodawstwa i perspektywy

Development Planning for the Agricultural Territory is a problematic activity in Bulgaria in terms of the existing legal requirements. Bulgarian legislation contains certain gaps in regulating and technically ensuring the agricultural land planning. This is well settled in relation to the other types of territories like the Urban, Forest, and Protected ones, which planning rules and activities are regulated in details. The purpose of the paper is firstly to justify the necessity of improving and detailing the legal regulations for the agricultural land development planning, and secondly to suggest some expert approaches for improving and harmonization of legislation in connection with registration of the agricultural property by Agricultural Territory Development Plan (ATDP), Restored Property Map (RPM) and Cadastral Map (CM). The current legal grounds for planning development of the agricultural land in Bulgaria are presented and analysed. Lack of detailed regulations on their scope, content and operation have been found. It is also a matter of applicability of the newly created municipal CMs in settling land relations such as purchases and sales of land, inheritances, divisions, and changing the primary purpose of use of Agricultural Territory for construction. The completeness of CM with information about the quality of agricultural lands is still not regulated by Cadaster and Property Register Act. The paper contains specific proposals for amendments in Spatial Planning Act, Cadastral and Property Registry Act and Agricultural Land Ownership and Use Act.

Development Strategy of Leading Agricultural Commodities: Findings From LQ, GRM, and Shift-Share Analysis

This research aims to develop the potential of food crops as a first step in the development planning process. This research was conducted in Majalengka Regency and has resulted in three main studies. First, it identifies staple and non-staple food crops in the region. The data source used consists of time series data from 2018-2022, and primary data with sample determination using the Proportional Random Sampling method. The results of the analysis show that staple food crops in Kabupaten M consist of rice, corn, soybeans, peanuts and green beans, while non-staple food crops include cassava and sweet potatoes. Secondly, the study also indicated that rice is the main food crop in the region. Finally, maize and groundnuts were identified as priority crops for further development. These findings provide valuable information for agricultural development planning, focusing on the development of potential commodities.

DEVELOPMENT OF WEB GIS APPLICATIONS FOR MONITORING AGRICULTURAL ACTIVITIES IN SUNGAI KAKAP DISTRICT, KUBU RAYA REGENCY

<p>Good agricultural development planning requires an accurate and real-time database. This is very important to see the development and level of welfare of farmers as the spearhead of food security. Sungai Kakap Sub-district, Kubu Raya Regency is one of the sub-districts with the number of Gapoktan (23), Poktan (284), the number of members (6305) with Field Agricultural Extension Workers (PPL) since 2019 totalling 9 civil servants and 14 people helping themselves. The number of PPLs is not proportional to the number of farmer group members, making supervision of agricultural activities difficult. The presentation of information in the form of Web GIS is expected to be a solution so that assistance, guidance, and counselling carried out by the government through the agriculture office can be right on target. The purpose of this research is to build a Web GIS-based Agricultural Information System in Sungai Kakap District so that it can be used as a model for agricultural monitoring activities in other areas. The engineering method in this research uses Remote Sensing and Waterfall methods. Remote Sensing is a method of building spatial data using aerial photo interpretation techniques, while Waterfall is used to build a web GIS as a place to display spatial data. The result of this research is Software Engineering in the form of a Web GIS-based Agricultural Information System Application. This Web GIS application can then be used as a tool to monitor the agricultural activities of each farmer group member in each farmer group.</p>

2020–2022年三江平原主要农作物种植分布遥感监测数据集

Sanjiang Plain, renowned for its expansive and fertile black soil, serves as a crucial hub for commodity grain production in China. The per capita cultivated land area and per capita grain output in the region are five times the national average. Accurate crop acreage information is of great significance for understanding regional food security and agricultural development planning in Sanjiang Plain. In this paper, we used the Sentinel-2 satellite remote sensing data of time series and the survey data of typical ground features in Sanjiang Plain to screen the feature bands of major crops and typical ground features of surrounding areas. Using the random forest classification algorithm, we extracted the data to produce a dataset of remote sensing monitoring of planting distribution for major crops (rice, corn and soybean) in Sanjiang Plain from 2020 to 2022. Based on field survey data, it has been verified that the overall accuracy of the three crops extraction in 2020, 2021 and 2022 stands at 95.18%, 95.0% and 94.5%, and the Kappa coefficients of these three years are 0.924, 0.925 and 0.919. This dataset can not only offer basic data for the analysis of temporal and spatial changes of crop planting distribution in Sanjiang Plain, but also contribute to informed decision-making in agricultural production management for the region. Furthermore, it can support the development of agricultural informatization as well as the preservation and utilization of black soil resources.

Sustainable agricultural management: How to achieve carbon neutrality in agriculture – evidence from China agricultural sustainable development plan

AbstractAgricultural sustainable development is of significant importance for achieving food security, environmental protection, climate change adaptation, natural resource conservation, and economic development. We conducted a study using the 2015 China Agricultural Sustainable Development Plan (ASDP) as a natural experiment and employed the Difference‐in‐Differences (DID) model to estimate the impact of ASDP on agricultural carbon neutrality. Path analysis and heterogeneity analysis were also performed. The results of this study are as follows: First, ASDP promotes agricultural carbon neutrality. Second, increasing per capita agricultural machinery usage, agricultural labor efficiency, livestock manure management, wastewater and waste treatment capacity, toilet coverage rate, greening efforts, and reducing pesticide usage are potential pathways of ASDP. Third, the analysis of carbon emission types indicates that current ASDP mainly focuses on carbon emissions from traditional agricultural practices, with limited impact on carbon emissions associated with modern agricultural activities, such as diesel fuel and pesticides. Lastly, the heterogeneity analysis of agricultural regions demonstrates that ASDP has a more positive impact on grain, oil, fruit and vegetable low‐producing areas, cotton high‐producing areas, and poultry, meat, eggs and milk aquaculture high‐producing areas. This study estimates the carbon reduction effect of ASDP and provides new policy recommendations and reform directions for agricultural sustainable development in China and other developing countries.

A Probe into Shifts in Cropping Pattern in Telangana State, India: A Markov Chain Approach

Assessing variations in cropping patterns across various locations is crucial for a better understanding of the agricultural development plan. The goal of the current study was to look at Telangana state's changing cropping patterns. Data spanning the years 2000-01 to 2020-21 were gathered from the Directorate of Economics and Statistics, Government of Telangana and they were then evaluated using the Markov chain method. The research's key findings showed that none of the crops in Telangana kept their acreage; instead, the area devoted to each crop changed continually during the course of the study, from one crop to another. The area under crops other than cereals, major oil seeds, pulses has more retention while it lost area to rice, cotton, black gram, chillies, cow gram, ground nut, jowar and mesta. This indicated that there was greater shift in cropping pattern in Telangana State. The selection of crops holds immense potential to elevate agriculture to the forefront of property growth, and it should be a focal point in research and extension programmes.

EFFECTIVENESS EVALUATION OF THE WATER USE PLAN IN THE BA RIVER BASIN

The Ba River basin has abundant water resources for agriculture and power generation. To respond to the socio-economic development of the basin, the water work system has been planning to improve the efficiency of water resource allocation, serving sustainable development. This study was designed to evaluate the effectiveness of water work plans built on the Ba River basin by assessing their ability to supply water for agriculture, domestic, industries and services. Water balance calculations show that water demand in irrigation areas in the Ba River basin increases significantly corresponding to basin development, especially in the Krong Pa and Nam Bac An Khe regions. With the application of irrigation planning, agricultural development plans and changes in land use structure, water resource allocation in the Ba River basin has been improved in the future. The effectiveness of the planning is obviously shown in the Upper Ayun, Ayun Pa, Upper and Lower Dong Cam where water demand increases sharply and water shortages are controlled, ensuring water supply requirements for irrigation and other sectors of over 85% and over 90%, respectively.

Assessment and projection of the groundwater drought vulnerability under different climate scenarios and land use changes in the Sanjiang Plain, China

Study RegionA district of the Sanjiang Plain, China. Study focusAiming at assessing the likelihood of groundwater exposure to drought in the present and future, a comprehensive evaluation framework based on the groundwater drought vulnerability index (GDVI) is proposed. Firstly, nine influencing factors are selected in terms of groundwater dependence, hydrogeology, and meteorology, and the current drought vulnerability is assessed by combining the analytic hierarchy process (AHP) and random forest (RF) models. Afterwards, by projecting land use and future climate under the shared socioeconomic pathways of SSP1–2.6, SSP2–4.5, and SSP5–8.5, the GDVI is calculated for three future periods, i.e., 2015–2039, 2040–2064, and 2065–2089. New hydrological insights for the regionMore than 30% of the groundwater experiences high and very high vulnerability during the baseline period, concentrated in areas with arable land and a thick clay cover. With rising temperatures and the rapid expansion of paddy fields, areas of high-vulnerability will continue to expand and will exceed 50% by the middle of the 21st century. If the groundwater irrigation and the agricultural land development are not restricted, the groundwater drought will be exacerbated. The proposed evaluation framework can be used in other areas with high groundwater use or where groundwater resources are at risk of depletion, and the findings provide guidance for agricultural development planning and joint surface water-groundwater scheduling.

Optimal feature selection and crop extraction using random forest based on GF-6 WFV data

ABSTRACT For precision agriculture, agricultural development planning, and regional food security, accurate crop mapping is essential. The GF-6 satellite offers novel approaches for crop identification. As Jinzhou, Hebei province, China, comprises a mix of grain and fruit trees, this research has selected the area for a case study. First, spectral, index, and texture features are combined in various classification feature schemes. Second, the random forest algorithm is employed to ascertain the significance of these features. Optimal features are then chosen to accurately identify winter wheat, summer maize, and pear orchards. Concurrently, land cover for wheat and maize seasons is mapped. The results demonstrate that: (1) multisource features considerably enhanced the accuracy of crop classification based on GF-6 WFV data. Among these, index features have the greatest contribution, followed by spectral features, while the contribution of texture features, is almost negligible. (2) The classification effect utilizing random forest feature optimization is superior, with an overall accuracy of 94% and a kappa coefficient of 0.91. The extracted land area for each scheme exhibits an accuracy of over 70% when compared to the statistical area. (3) The critical time phases for extracting winter wheat, summer maize, and pear orchards are identified as, in sequence, the leaf-out and jointing stage, the tasselling stage, the leaf-fall stage, fruit development, and the first flowering/full flowering stages. Based on GF-6 WFV data, these research findings will offer a technical reference for the identification of grain crops and the extraction of pear orchards.

Modern issues of the organizational and legal basis improving of land reclamation

The article deals with topical issues of the development of the organizational and legal framework for water use in land reclamation. Land reclamation based on a developed reclamation and water management complex largely determines the increase in the efficiency of agriculture, ensuring the country's food security, meeting the needs of the rural population and the agro-industrial complex in water resources. At present, the provision of water resources is complicated by modern climate changes, which cause an increase in the aridity of the climate in the south of the European part of Russia. The performed zoning of the territory confirmed insignificant renewable water resources and high anthropogenic pressure on water bodies of the Stavropol and Krasnodar Territories, the Republic of Kalmykia and the Rostov Region, which affects not only the volume of water resources available for irrigation, but also the quality. Significant physical deterioration of the structures of the reclamation and water management complex, reaching 80% or more, low values of the efficiency of reclamation systems determine significant unproductive water losses during irrigation. To normalize agricultural water use, ensure accident-free and uninterrupted supply of water of the required quantity and quality to the population and agricultural producers, develop and improve the efficiency of irrigated agriculture, it is important to improve the organizational and legal framework for water use in land reclamation. The principal directions of legal regulation of the development of land reclamation and water management of the country and regions are determined by the need to legally consolidate the transition to integrated water resources management in agriculture, improve existing legislative acts, standardize the rights and obligations of water users, determine the role of the state in the implementation of measures to modernize the water management complex. For the transition to a new technological level of management of the reclamation and water management complex of the agro-industrial complex, the introduction of water accounting systems and control over the use of water resources, the improvement of organizational principles for managing the operation mode of reservoirs to take into account the requirements of agriculture in the zone of insufficient moisture, audit of reclamation systems to assess their effectiveness and long-term planning of agricultural development based on land reclamation and other activities.

Dynamics of photosynthetic solar active radiation in Ukraine over 1986 - 2015

Photosynthetically active solar radiation (PSR) – solar radiation within the wavelength range of 380 ¼710 nm – forms a basis of plants' life that determines their photosynthesis. No measurements of photosynthetically active solar radiation (PSR) take place in Ukraine due to the lack of standard devices. Direct, scattered and total PSR is calculated via transition measurements and coefficients, whereas total PSR is measured via sunshine duration – using the indirect method. The purpose of the research is to determine PSR and its dynamics during specific months and the warm period of the year (April-October). The components of the radiation regime within the network of actinometric and meteorological observations in Ukraine for 1986 - 2015, 1986 - 1995, 1996 - 2005, 2006 - 2015 were obtained using mathematical statistics and climatological methods. In the course of the research changes in the PSR during specific months and the warm period over specific decades were determined. During the months of the warm period over 1986 -2015, direct, diffused, total PSR and total PSR calculated via sunshine duration tend to increase from the west, northwest or Ukrainian Carpathians to the southern steppe zone and Crimea. During the warm period over 1986 - 1995, the amount of direct PSR varies within 472 ¼ 891 MJ/m², diffused radiation – 887 ¼ 1156 MJ/m², total radiation – 1457 … 1917 MJ/m², total PSR calculated based on sunshine duration – 1621 … 2056 MJ/m²; over 1996 - 2005 the amount of direct PSR varies within – 469 … 1030 MJ/m², diffused – 802 … 1004 MJ / m², total – 1305 … 1973 MJ/m², total PSR calculated based on sunshine duration – 1654 … 2192 MJ/m²; over 2006 - 2015 the amount of direct PSR varies within 485 ¼ 1065 MJ/m², diffused radiation – 737 ¼ 951 MJ / m², total PSR – 1270 … 1977 MJ / m², total PSR calculated based on sunshine duration – 1649 … 2233 MJ / m². The increase in integrated direct solar radiation over 1996 - 2005 compared to 1986 - 1995, as well as over 2006 - 2015 compared to 1996 - 2005, led to an increase in direct PSR; the decrease in diffused solar radiation led to a decrease in diffused PSR; and ambiguous changes in the components of total solar radiation led to fluctuations in total PSR; increase in sunshine duration is accompanied by an increase in total PSR calculated based on sunshine duration. The research is relevant due to the factor of modern climate variability at the global and regional levels. The study of PSR changes is an urgent task of modern agrometeorology. It enables long-term effective planning of agricultural development.

Intervensi Pemerintah Desa dalam Program Pembangunan Pertanian: Suatu Pendekatan Ekonomi Politik di Konteks UU Desa 2014

In the context of the 2014 Village Law, village government intervention in agricultural development is very important in improving the welfare of village communities. This study aims to determine the intervention of the village government on agricultural development programs and to find out the opportunities and limitations of the village government in agricultural development in the village. This research uses a qualitative method with a literature study approach. This study uses Henry Bernstein's theory of agrarian political economy. Data collection was carried out through secondary data sourced from books, journals, the internet, official documents related to village government and agricultural development. Data analysis used the interactive model Miles, Huberman and Saldana. The scope of this research is limited to village government intervention in the planning and implementation of agricultural development. The findings in this study are that the change in the system from centralization to decentralization has also changed the planning of agricultural development programs in villages that are more decentralized, participatory between the community and the village government. The recommendations/implications of these findings are expected to be able to contribute findings/ideas to studies of rural development in Indonesia, particularly the role of village governments in agricultural development and a political economy perspective in agricultural development to alleviate poverty, food security, and increase the income of people in rural areas. In addition, recommendations for village government intervention in development that are more pro-poor in rural areas.

Strategic Planning of Agricultural Entrepreneurship Development in Kerman Province (Application of Fuzzy Hierarchical Analysis and SWOT)

Strategic Planning of Agricultural Entrepreneurship Development in Kerman Province (Application of Fuzzy Hierarchical Analysis and SWOT)

The Potency of the Tumih Village Farmer Community's Participation in the Agricultural Development Planning Strategy

In Tumih Village, Wanaraya District, Barito Kuala Regency, South Kalimantan Province, this study attempts to assess the strategy and growth of the agricultural sector as well as the level of community engagement in relation to agriculture. The settlement of Tumih itself has excellent potential for agriculture, particularly rice production. The analytical technique used employs the Strength Field Analysis approach to identify development plans and Participation Strength Analysis to identify the level of community involvement in agriculture in Tumih Village while determining the agricultural sector's strategy. The analysis' findings indicate that the key influencing elements for agricultural development plans in Tumih Village are the availability of human resources in the agricultural sector, particularly in the case of rice, and the farmers' receptivity to new technology. A hindrance in Tumih Village is the absence of irrigation and agricultural technologies. With only 36.5 percent, the assessment of the level of community involvement in planning for agricultural growth is still insufficient.

Spatial correlations and driving mechanisms of low-carbon agricultural development in china

Low-carbon agricultural development in China is a prerequisite for rural revitalization and a key to achieving socio-economic green transformation. This paper used agricultural data from 30 Chinese provinces from 2001 to 2020, considering both carbon emissions from farming and livestock, agricultural low-carbon total factor productivity (ALTFP) was measured using the RSBM-GML index. Based on this, the network characteristics and driving mechanisms of low-carbon synergistic development in agriculture were explored with the help of an improved gravity model and social network analysis, and the dominant provinces in low-carbon synergistic development in agriculture are identified. The study revealed that the spatially linked network of ALTFP in China exhibits multi-threaded characteristics of spillover to non-adjacent provinces, and the whole network has a sparse structure and hierarchy. The eastern regions such as Beijing, Tianjin, Shanghai, Jiangsu, and Zhejiang are at the core of the network, with closer ties to other regions and a stronger role in allocating resources. While the western regions such as Xinjiang, Qinghai, and Gansu are located at the periphery of the network, with weaker access to the resources. Meanwhile, the spatial proximity of provinces, the widening of differences in urbanization levels and differences in financial support for agriculture, and the narrowing of differences in the educational attainment of rural labor have significantly contributed to the formation of provincial spatial linkages. This study reveals that China’s government needs to give full play to the role of core regions as “leaders”, and promote the balanced and coordinated regional development of low-carbon agriculture in China. In addition, policy makers should further optimize the spatial allocation of agricultural resource elements between provinces. The findings of the study provide reference suggestions for the development of regionally differentiated agricultural low-carbon development plans.

LAND REFORM AND SUSTAINABLE DEVELOPMENT - A MARRIAGE OF NECESSITY

In order for land reform to be successful in the agricultural arena, the end-result must promote sustainable development. The question is whether legislation and policy initiatives have been conducive in furthering the partnership between land reform and sustainable development. Although the link between the two seems apparent, after a brief analysis of existing land reform legislation it is clear that legislation generally does not reflect this. Many actors have an impact on the harmonization of land reform and sustainable development, inter alia (a) problems resulting from the former racially-based land control approach and (b) geographical and climatic factors. The problems experienced in the rural areas in especially the former national states and self-governing territories are discussed in more detail. In order to place the current situation in perspective, recent developments that impact on land reform and development are then discussed, namely the Land Redistribution for Agricultural Development Plan and the Strategic Plan for SA Agriculture. In light of these developments various shortcomings are further identified that still hamper the closer working partnership between land reform and sustainable development. The conclusion is reached that the mere transfer of land is no guarantee for a successful land reform programme. What is needed, is a balanced approach towards addressing the demand for land on the one hand and maintaining agricultural production on the other.

Analysis of Change in Maize Plantation Distribution and Its Driving Factors in Heilongjiang Province, China

Accurate identification of maize plantation distribution and timely examination of key spatial-temporal drivers is a practice that can support agricultural production estimates and development decisions. Previous studies have rarely used efficient cloud processing methods to extract crop distribution, and meteorological and socioeconomic factors were often considered independently in driving force analysis. In this paper, we extract the spatial distribution of maize using classification and regression tree (CART) and random forest (RF) algorithms based on the Google Earth Engine (GEE) platform. Combining remote sensing, meteorological and statistical data, the spatio-temporal variation characteristics of maize plantation proportion (MPP) at the county scale were analyzed using trend analysis, kernel density estimation, and standard deviation ellipse analysis, and the driving forces of MPP spatio-temporal variation were explored using partial correlation analysis and geodetectors. Our empirical results in Heilongjiang province, China showed that (1) the CART algorithm achieved higher classification accuracy than the RF algorithm; (2) MPP showed an upward trend in more than 75% of counties, especially in high-latitude regions; (3) the main climatic factor affecting the inter-annual fluctuation of MPP was relative humidity; (4) the impact of socioeconomic factors on MPP spatial distribution was significantly larger than meteorological factors, the temperature was the most important meteorological factor, and the number of rural households was the most important socioeconomic factor affecting MPP spatial distribution. The interaction between different factors was greater than a single factor alone; (5) the correlation between meteorological factors and MPP differed across different latitudinal regions and landforms. This research provides a key reference for the optimal adjustment of crop cultivation distribution and agricultural development planning and policy.

Cropland suitability assessment using multi criteria evaluation techniques and geo-spatial technology: A review

Cropland suitability assessment is an essential technique for agricultural development and future planning. It is an evaluation to determine how suitable the land is for growing a specific crop in a particular region based on multiple parameters like soil, climate, topography, socio-economic condition, infrastructure, irrigation, existing land use/land cover and environmental aspects. The paper presents different multi-criteria evaluation (MCE) techniques such as Analytical Hierarchy Process (AHP), Fuzzy Analytical Hierarchy Process (FAHP), Analytic Network Process (ANP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and ELimination Et Choice Translating REality (ELECTRE) approaches integrated with geospatial technology, namely remote sensing and Geographical Information System for cropland suitability assessment. Review findings indicate that the AHP technique was used by53% of the researchers, followed by FAHP (16%); ANP (6%); TOPSIS (6%); ELECTRE (3%) and other techniques (16%) with or without geospatial technology. The integrated approach of MCE with geospatial was used by 69%, among which AHP technique of MCE was used by 72%; whereas, 22% used geospatial and 9% used MCE techniques alone. The results from the selected research articles also indicated that the most important input parameters were soil, topography and climate used by 97%, 88% and 74% of the researchers, respectively. The review can be helpful for researchers and decision-makers to select the most robust methods and standard parameters required for cropland suitability assessment to achieve higher agricultural production on a sustained basis.