Land Resources Research Articles

How Can Digital Economy Accessibility Accelerate Urban Land Green Transformation in China? Evidence from Threshold and Intermediary Effects

The digital economy is a new economic form that has a significant impact on urban land green use efficiency (ULGUE). With the provincial panel data between 2013 and 2021, this paper empirically tests how the digital economy development level (DEDL) promotes the improvement of ULFUE in China. The key findings include the following: (1) There were significant spatial differences for the ULGUE and DEDL of China. For China’s ULGUE, China shows an ascent after an initial decline trend from 2013 to 2017, but a decline trend after 2017. China’s DEDL took on a rising tendency during the research period. In 2021, China’s DEDL increased by 143.8% compared with that in 2013. (2) The digital economy can obviously promote the ULGUE, but the promotion effect is affected by the urbanization level; with improvements in urbanization level, the impact of that may strengthen. (3) Technological innovation demonstrates a complete intermediary effect between the digital economy and ULGUE; the mediation transmission mechanism of technological innovation is evident. These results have been verified by robustness tests, proving their stability and reliability. The research results will provide new insights into the high-quality utilization of urban land resources.

Digital rural construction, resource mismatch, and rural land use efficiency

IntroductionWith the acceleration of the allocation of agricultural resource elements in agricultural development, the relationship between digital rural construction and rural land use efficiency has become increasingly close.MethodsIn order to explore the impact and underlying mechanism of digital rural construction on rural land use efficiency, this paper constructs an evaluation system index for China's digital rural construction and uses the SBM-GML model to measure rural land use efficiency. Based on this, data from 30 provinces in China from 2010 to 2022 are used to test it using fixed effects and mediation effects models.Results(1) The construction of digital rural areas can directly promote the improvement of rural land use efficiency. This conclusion still holds true after endogeneity and robustness tests. (2) Mechanism analysis shows that digital rural construction can alleviate the mismatch of land resources, capital resources, and labor resources, thereby indirectly promoting the improvement of rural land use efficiency. (3) Heterogeneity analysis shows that the construction of digital rural areas has a more significant driving effect on the efficiency of rural land use in eastern and southern regions of China, as well as in major grain producing and selling areas.DiscussionThis article suggests continuing to promote the development strategy of digital rural construction, improving the problem of resource mismatch, and paying attention to the regional imbalance of digital rural construction. It is necessary to maintain the leading position of “first mover advantage” areas and also pay attention to filling the gaps in “later mover advantage” areas, in order to comprehensively promote the further improvement of rural land use efficiency.

Динамика земельного фонда Российской Федерации и Краснодарского края по категориям земель, составу и площади сельскохозяйственных угодий

The presented study is aimed at quantifying the dynamic characteristics of the land fund of the Russian Federation and the Krasnodar Territory in the period from 2018 to 2023. The work analyzes statistical data characterizing the distribution of land by category, changes in the composition and area of agricultural land. The methodological approach used makes it possible to identify spatial and temporal trends and differentiate them at the level of the territorial units under consideration. An analysis of official data from the State (national) Land Status and Use report revealed key trends in land transformation by category and agricultural land. At the federal level, there is a steady tendency to reduce agricultural land in parallel with an increase in the areas of specially protected natural territories and forest resources. This situation requires careful analysis from the point of view of ensuring the country's food security. In the Krasnodar Territory, known as a region with intensive agricultural production, an in-depth analysis of the dynamics of land categories revealed the main trends, taking into account possible causal factors affecting changes in the structure of land use. The results obtained made it possible to evaluate the effectiveness of existing land use strategies and identify potential ways to increase the area of agricultural land. Based on the analysis, specific recommendations are formulated to optimize spatial development both for the whole country and for the Krasnodar Territory, identifying the goal as sustainable and efficient use of land resources. Further research should focus on clarifying the contribution of individual factors and developing adaptive land-use strategies taking into account changing climatic conditions.

Analysis of the Spatiotemporal Evolution Patterns and Driving Factors of Various Planting Structures in Henan Province Based on Mixed-Pixel Decomposition Methods

Understanding the spatiotemporal evolution patterns and drivers of cropping structures is crucial for adjusting cropping structure policies, ensuring the sustainability of land resources, and safeguarding food security. However, existing research lacks sub-pixel scale data on planting structure, where planted area data are mainly derived from manual counting results. In this study, remote sensing technology was combined with geostatistical methods to realize the spatiotemporal evolution of crop planting structure at sub-pixel scale. Firstly, the spatial distribution of the multiple cropping structure in Henan Province was extracted based on a mixed-pixel decomposition model, and spatiotemporal evolution of the crop planting structure was analyzed using a combination of Sen’s slope estimator and Mann–Kendall trend analysis, as well as centroid migration. Then, Pearson correlation coefficients were calculated to explore the contribution of driving factors. The results indicate the following: (1) from 2001 to 2022, the cropping structure in Henan Province shows a slightly obvious increase. (2) The centroid of different cropping structures migrates to the main production areas as a whole. (3) Among the driving factors, there was a positive correlation with the labor force and a negative correlation with the urbanization rate. This study provides new insights into the evolution of large-scale crop planting structures and offers significant theoretical and practical value for sustainable agricultural development and the optimization of agricultural planting structures.

Estimation of soil erosion and risk assessment in Somalia

Soil erosion is a pressing issue that threatens environmental stability and agricultural productivity across the globe. In Somalia, where the population already contends with severe socioeconomic and environmental challenges, the effects of erosion compound problems like food insecurity and land degradation. This study investigates erosion patterns and identifies areas prone to soil loss, aiming to provide actionable insights for improving land use practices and resource management. The research employs advanced analytical tools to study how erosion factors are distributed geographically. Data such as terrain characteristics, rainfall intensity, vegetation cover, soil quality, and land usage are systematically analyzed. Cutting-edge modeling techniques, supported by historical erosion trends, help to develop accurate predictions about future soil loss, offering a robust basis for creating effective intervention strategies. The findings show that many regions in Somalia are highly susceptible to erosion, particularly where unsustainable human activities such as overgrazing, deforestation, and improper farming methods are prevalent. These insights underscore the urgent need for targeted policies to mitigate erosion and protect valuable soil resources. By forecasting potential erosion scenarios, this research equips decision-makers with the tools needed to prioritize interventions that enhance agricultural output, preserve ecosystems, and ensure long-term sustainability. This research aids policymakers, land managers, and stakeholders in formulating focused, evidence-based plans for soil conservation and sustainable land use, ultimately facilitating the preservation and enhancement of Somalia's natural resources and agricultural resilience. Int. J. Agril. Res. Innov. Tech. 14(2): 111-121, December 2024

Gender, land grabbing and agrarian livelihoods: contradictory gendered outcomes of land transactions in Ghana

ABSTRACT Based on a multi-method research design that employs a triangulation of fieldwork data, including focus group discussions (n = 35) and key informant interviews (n = 5), this paper examines the intervening role of gender in the differentiated distribution of harms and benefits from large-scale land acquisitions (LSLAs). Employing Feminist Political Ecology (FPE) as the analytical framework, this study examines how varying positionalities such as marital status, tenure systems, and local power dynamics shape women’s encounters with LSLAs. Our findings reveal that while patriarchal structures continue to restrict women’s control over land resources, the economic opportunities arising from projects in the Central and Volta regions of Ghana have enhanced some women’s financial independence and decision-making power within their households. This shift, however, has created tensions, as men perceive these changes as a challenge to traditional gender roles. By interrogating these complex gendered experiences, this study enriches the FPE framework, highlighting how intersecting positionalities influence resource access and control in agrarian communities.

Integrated Remote Sensing for Enhanced Drought Assessment: A Multi‐Index Approach in Rajasthan, India

AbstractThis study investigates land use, land cover (LULC) changes, vegetation health, and drought severity in Rajasthan, India, from 1985 to 2020 using remote sensing techniques. By analyzing satellite imagery with the normalized difference vegetation index (NDVI), temperature condition index (TCI), vegetation condition index (VCI), and NDVI deviation (Dev_NDVI), we assess the spatial and temporal dynamics of the region's landscape and drought conditions. Our findings indicate significant LULC changes, including a decrease in water bodies from 6412.87 to 2248.51 km2 and dense forests by 61.37%, while built‐up areas expanded by 890.50%, reflecting substantial human impact and environmental change. Drought analysis revealed that nearly 49% of the study area experienced moderate to severe drought conditions, with VCI levels below 40%, indicating widespread drought impact across different regions and time periods. The study employs weighted sum analysis of Dev_NDVI, VCI, and TCI to create a detailed drought severity map, revealing areas of severe and extreme drought that necessitate immediate action for sustainable management. The novelty of this approach lies in its integrated multi‐index method for assessing drought over a 35 year period, providing a robust framework for analyzing environmental dynamics and the resilience of ecosystems to climatic stresses. This research emphasizes the value of remote sensing for continuous environmental monitoring and highlights future implications for integrating advanced satellite technologies to enhance drought management strategies, ultimately informing policy decisions for sustainable land and water resource management in Rajasthan and similar semi‐arid regions globally.

Identification and information acquisition of high-value construction solid waste combined millimeter-wave radar and convolutional neural networks.

The accumulation of construction solid waste (CSW) leads to the waste of land resources and environmental pollution, becoming a significant social problem. Identifying the amount of high-value CSW is essential for assessing the value of accumulated CSW and formulating appropriate recycling strategies. With the development of machine learning technology, CSW recognition techniques combining image acquisition devices and convolutional neural networks have been widely applied. However, most technologies are based on 2D images, making it difficult to recognize high-value CSW in accumulated CSW. This study proposes a new method to identify high-value CSW using millimeter wave radar based on penetration properties of electromagnetic waves. First, efficient imaging of CSW was achieved by optimizing the imaging algorithm. Then, CSW were classified in combination with the selected convolutional neural network (CNN) method based on the dataset constructed in the lab. At last, high-value CSW was screened by normalizing the imaging algorithm. The findings indicate that the balance between imaging effect and efficiency is achieved when the step speed and height are 200mm/s and 4mm. The optimized imaging approach effectively captures images of CSW. Compared with SegNet and PSPNet, DeepLabv3+ can identify complete bricks and reinforcing bars precisely. The accuracy can reach 85.18%. Moreover, the millimeter-wave radar can determine the location and size of waste and can potentially acquire three-dimensional and buried information about waste.

Impact of farmland landscape characteristics on gully erosion in the black soil region of Northeast China

Gully erosion on agricultural land severely damages land resources and affects agricultural production. Topographic features, tillage methods, and roads are major elements constituting the farmland landscape, but the effect of their distribution in the farmland on the gully erosion is still unclear. This study examined the long-term impacts of changes in the farmland environment and climate change on gully erosion over a long temporal scale of nearly 60 years, the results showed that farmland reclamation over the past 60 years had led to a 2324.2 % increase in gully length density and a 3563.3 % increase in gully area density. The increase in annual rainfall amount and the frequency of extreme rainstorms had led to a rapid increase of gully erosion intensity in the last decade, with an average development rate in length density and area density of 61.5 m/km−2(−|−) and 778.7 m2/km−2(−|−), respectively. Farmlands with slope aspects between 135 and 270° were more prone to gully erosion, which was related to the redistribution of snow on hillslopes caused by prevailing wind directions. Tillage methods and roads simultaneously affect gully erosion, with newly formed gullies located in farmlands and roadsides accounting for 63.0 % and 29.8 %. Gullies in regions where the angle between furrows and unpaved roads exceeded 70° accounted for 61.1 % of the total roadside gullies. Over the last decade, the annual average increase of gully length and area was 9.8 m/yr and 246.1 m2/yr. The development rate of gully area was significantly correlated with the drainage area.

Dental microwear of extant Lutrinae

Abstract Few living mammals are as exemplary of a semiaquatic lifestyle as otters, exhibiting a diverse array of ways that an animal can use water and land resources similar to the way other clades, such as cetaceans or pinnipeds, may have used their habitats during the transition from terrestrial to aquatic life. Otters (subfamily Lutrinae of the Mustelidae) are known to differ greatly in their diets between species and even within individuals depending on seasons, often differing largely in proportions of fishes versus crabs and echinoderms. Such diets including or excluding hard objects like these should result in differences in tooth wear, including dental microwear. In this study, 46 specimens of eight species of extant otters were sampled for dental microwear with the aim of developing an understanding of how their dental microwear reflects these dietary differences. Dental microwear surfaces were obtained using an optical scanner, resulting in the collection of 13 scale-sensitive fractal analysis parameters, as well as 61 ISO-25718-2 areal roughness parameters for each tooth. Among these, the greatest numbers of significant variables were found between dietary categories, particularly when Pteroneura brasiliensis and Hydrictis macullicolis were classified as durophages. When compared independently as species, Enhydra lutris is found to have the greatest numbers of variables significantly different from other species.

A Coupling Coordination Assessment of the Land–Water–Food Nexus in China

The synergistic relation among land resources, water resources, and food production plays a crucial role in sustainable agricultural development. This research constructs a coupling coordination assessment system of the land–water–food (LWF) nexus from 2005 to 2020 for 31 provinces (municipal cities, autonomous regions) in China, and explores the current development status of land, water, and food systems at multiple scales as well as the coupling coordination characteristics of the LWF nexus. The exploring spatial data analysis and spatial Tobit model are used to explain the spatial correlations and influencing factors of coupling coordination development on the LWF nexus. On that basis, the gray GM (1,1) model is used to forecast the future development of the LWF nexus in China. The results show that the comprehensive development indexes of the land system, water system, food system, and LWF nexus are on the rise, but the land system lags behind the water system and food system. The coupling coordination degree of the LWF nexus in different regions ranges from 0.538 to 0.754, and the coupling coordination development of the LWF nexus in China has reached the preliminary coupled coordination type, with an evolutionary process similar to that of its comprehensive development level. Further empirical research shows that there is a significant positive spatial correlation between coupling coordination development levels for the LWF nexus in China. The level of urbanization and agricultural industry agglomeration have negative effects, while economic development, ecological environment, and scientific and technological progress have positive effects. The prediction results indicate that the coupling coordination degree of the LWF nexus in China will show a stable upward trend from 2024 to 2025, and most provinces will reach the intermediate coupled coordination type in 2025. This study can inform decision-making for policy-makers and practitioners and enrich the knowledge hierarchy of the LWF nexus’ sustainable development on the national and regional scales.

Automating band selection for hyperspectral indices: bridging AVIRIS-NG and Sentinel-2 satellite data for earth science applications

Hyperspectral data from the Airborne Visible and Infra-Red Imaging Spectrometer – Next-Generation (AVIRIS-NG) offers transformative potential for Earth science research, enabling detailed analysis of land surface processes, resource monitoring, and environmental dynamics. This study presents an automated methodology to optimize the selection of AVIRIS spectral bands, improving the computation of indices critical to Earth science applications. By leveraging multiple hyperspectral bands, the approach enhances the accuracy of indices used to monitor water resources, vegetation health, urban expansion, and built-up areas. The methodology involves calculating indices from all possible AVIRIS band combinations, evaluating their root mean squared error (RMSE) against Sentinel-2 indices, reducing RMSE skewness, and selecting bands with minimal deviation for specific Land Use Land Cover (LULC) categories. The process is automated and employs parallel processing with Python, significantly reducing execution time and enabling scalability for large geospatial datasets. Key indices, including the Normalized Difference Water Index (NDWI), Normalized Difference Red Edge (NDRE), and Normalized Difference Built-up Index (NDBI), Green Normalized Difference Vegetation Index (GNDVI) were validated using the proposed methodology. Results demonstrate the potential of hyperspectral data to outperform traditional single-band approaches, providing more precise and reliable assessments.

The system of criteria and indicators for assessing the efficiency of large-scale agricultural production placement (national and regional levels)

One of the reasons for the low efficiency of large-scale agroindustrial enterprise development is the imperfection of the system of land use and location of agricultural organizations. In modern socio-economic conditions, excessive concentration of land resources at some enterprises that do not have sufficient production potential for their use, and lack of land at others that lack their own fodder land, leads to significant losses for the national economy, deterioration of financial performance of large-commodity agroindustrial enterprises. This study presents a balanced system of criteria and indicators for assessing the efficiency of large-scale agricultural production location (national and regional levels). Four zones of production efficiency are singled out, the optimal sizes of large-scale crop production are established, and a mechanism for identifying inefficiently used land plots of insolvent large agricultural enterprises is proposed. The relevance and novelty of this system lies in the development of tools to assess the efficiency of large-scale agroindustrial enterprise location within the framework of multi-structure agricultural production, taking into account the current organizational and economic conditions.

LANDSCAPE FACTORS FORMING THE STEPPE ZONE OF THE ZHAYIK RIVER BASIN OF THE WEST KAZAKHSTAN REGION

This article examines the influence of various natural factors on the formation of landscape and soil complexes in the Zhaiyk River basin. The key components considered in the study include soil types, topography, and natural landscapes. The analysis reveals that the soils of the region range from chestnut and chernozem to sod-podzolic and solonetz soils, which determine the characteristics of vegetation and agricultural potential. Soil complexes are largely shaped by topography, water regime, and climatic conditions. Based on cartographic data obtained from satellite imagery and digital terrain models, an analysis was conducted to assess the distribution of soils and their relationship with vegetation types, water bodies, and other natural features. The results of the study reveal important patterns in the distribution of soil types and assess their role in the region’s ecosystems, providing practical insights for land resource management, agriculture, and environmental conservation in the Zhaiyk River basin. Topography, in turn, affects water exchange and erosion processes, which significantly influence soil types and their distribution. Special attention is given to identifying the interrelationships between soils, topography, and vegetation, as well as the role of these factors in the formation of sustainable ecosystems. The findings confirm that the complex interaction of topographical and soil features influences the distribution of landscape zones, which is crucial for planning agricultural activities and nature conservation.

Understanding the Rise and Fall of Rural Specialty Agriculture from Social–Ecological Land System Perspective: A Longitudinal Case Study in China

Specialty agriculture, promoted in China to enhance rural revitalization and farmers’ wellbeing, depends heavily on local social–ecological conditions and land transformations. However, existing studies often emphasize socio-institutional successes while oversimplifying ecological complexity and neglecting failures. This study examines the rise and fall of rural specialty agriculture through a social–ecological land system perspective, using the cherry tomato industry in C Town, China, as a case study. Drawing on qualitative data from field investigations and interviews, we adapt an extended Social–Ecological Systems Framework (SESF) to analyze interactions among governance subsystems, land resources, and external shocks, and their role in social–ecological transitions. Our findings show that the shift from farmer-led self-organization to government-driven and enterprise-dominated governance significantly undermined system resilience and adaptability. Although external interventions initially spurred industrialization and scaling, they marginalized farmers, leading to the system’s collapse under stressors like market fluctuations and environmental challenges. Our findings highlight the importance of inclusive governance for sustaining land-based agricultural systems, and point to the need of prioritizing farmer autonomy, sustainable land use planning, and adaptive governance to ensure the resilience and long-term sustainability of specialty agriculture systems.

Characteristics of Soil Microbial Community Structure in Different Land Use Types of the Huanghe Alluvial Plain

The Huanghe alluvial plain plays a crucial role in biodiversity conservation. However, its ecosystem has become sensitive and fragile due to long-term human disturbances. Enhancing the resilience of this ecosystem and promoting the sustainable use of land resources are key to addressing its ecological challenges. Soil microbial communities are vital to ecosystem functioning, and land use is a major human factor influencing their structure and diversity. Existing research on the Huanghe alluvial plain primarily focuses on soil physicochemical properties and moisture content, with relatively limited attention given to soil microorganisms. Therefore, this study, using the Wudi Tanyang Forest Farm in the Huanghe alluvial plain as a case study, employs high-throughput metagenomic sequencing to analyze the composition and diversity of soil bacteria, eukaryota, archaea, and virus communities in five different land use types (Tamarix chinensis forest, Fraxinus chinensis forest, farmland, wetland, and grassland). The results indicate that: (1) At the phylum level, the top three bacteria communities were Pseudomonadota, Acidobacteriota, and Actinomycetota; the top three in the eukaryota communities were Ascomycota, Mucoromycota, and Basidiomycotina; the top three in the archaea communities were Nitrososphaerota, Euryarchaeota, and Candidatus Thermoplasmatota; and the virus communities were dominated by Uroviricota; (2) The microbial community structure of the Tamarix chinensis forest and the Fraxinus chinensis forest was similar, and was significantly different from the other three land use types; (3) The land use type had a significant effect on the diversity of the soil microbial communities, with a higher diversity in the wetland and grassland soils; (4) The dominant species of the soil microbial communities under different land use types showed significant differences. This study provides theoretical support for land use optimization and sustainable soil management in the Huanghe alluvial plain region.

Interaction of population density and slope will exacerbate spatiotemporal changes in land use and landscape patterns in mountain city

The complex topography of the mountain cities leads to uneven distribution of land resources. Currently, available studies mainly focuse on land use and landscape patterns (LU and LP) in plains or plateaus. Thus, it is necessary to carry out an analysis of the drivers of changes in LU and LP in mountain cities. As the typical mountain city in China, Chongqing has changed significantly of land use in recent years. Here, we identified LU and LP changes from 2000 to 2020, and explored their drivers using GeoDetector in Yubei District, Chongqing. The following are the outcomes: (1) From 2000 to 2020, construction land, wetland and cropland had the greatest change in area, with 876.03%, -70.72% and -24.53%, respectively. The area of cropland transferred out was larger than the area transferred into it, while cropland still the largest among all land use types. (2) At the landscape level,construction landscape was at a low level. Grassland had the greatest degree of fragmentation, but showed a decreasing trend. The landscape’s complexity resulted from the conversion of various land uses. (3) The results of GeoDetector indicated that the interaction of population density and slope was the primary LU and LP changing factor. The results of the study provided a rational basis for the development of land use and landscape plans in the mountain cities.

Monitoring of Soil Salinity in the Weiku Oasis Based on Feature Space Models with Typical Parameters Derived from Sentinel-2 MSI Images

Soil salinization, as one of the types of land degradation, is a global threat. It not only poses serious ecological problems, but also poses great challenges for the sustainable utilization of land resources, especially in arid and semi-arid areas. The Weiku Oasis is undoubtedly one of the typical areas under severe salinization. The wide spread of saline soil brings numerous negative impacts to the local region. To prevent the escalation of soil salinization, timely monitoring of soil salinization is urgently needed for informed decision-making. Remote sensing technology can obtain large-scale datasets in a short period, allowing researchers to carry out the rapid and accurate investigation of soil salinization. Sentinel-2 images have a relatively high spatial resolution and provide red-edge bands data, referring to bands 5, 6, and 7, and the use of red-edge bands is a new approach to estimate soil salinization in the Weiku Oasis. In this study, we selected five typical indices (NDre1, RNDSI, MSAVI, NDWI, SI3, with the first two being red-edge indices) from twenty potential indices to construct multiple two-dimensional feature space models. Consequently, an optimal and novel monitoring index for soil salinization in the Weiku Oasis was developed. The result showed that: (1) The monitoring index MSAVI-RNDSI, which includes red-edge indices, had the highest inversion accuracy of R2 = 0.7998 and MAE = 3.3444; (2) The red-edge salinity indices effectively captured the conditions of salinization, with the feature space model composed of red-edge indices achieving an average inversion accuracy of R2 = 0.7902; (3) Land-use type was identified as the primary factor affecting the degree of soil salinization in the study area. The proposed approach provides a highly accurate and high-resolution soil salinity mapping strategy.

Analysis of Land Use in the Seaside Regions of Ukraine in 2017—2022 Based on Satellite Information

Introduction. Land is recognized as a primary national asset under the special protection of the state, as mandated by Ukrainian law. It serves as the foremost natural resource, a vital foundation for human life and activity, and underpins the establishment and development of all sectors of the national economy. Therefore, an eff ectively organized, sustainable economy is unattainable without the rational utilization and protection of land resources.Problem Statement. Research on land use in Ukraine’s coastal regions has become especially relevant. Since parts of these areas have been under occupation since 2014, understanding the spatial-temporal variability of land use in these regions presents significant challenges for Ukraine.Purpose. To analyze land use in the coastal regions of Ukraine using satellite data to assess spatio-temporal changes.Materials and Methods. This research utilized land use/land cover (LULC) mapping based on satellite data from Sentinel-2, analyzed through deep learning models using artificial neural networks.Results. The spatial distribution of land use in Ukraine’s coastal regions in 2022 was thoroughly analyzed. Additionally, the spatio-temporal variability of land use from 2017 to 2022 was assessed, revealing distinctive patterns in the spatial distribution of various land cover classes. The findings show that the innovative approaches to LULC mapping and the resulting data can be effectively applied to land resource management in Ukraine.Conclusions. The LULC mapping approach demonstrates significant potential for interdisciplinary research and applied work in natural resource management and territorial planning at both the national and regional levels. Moreover, these innovative LULC mapping methods present a robust tool for identifying and understanding the scale of natural, anthropogenic, and military-induced emergencies.

Assessment of Economic Management of Land Resources to Enhance Food Security

To achieve the goals of balanced development of the agricultural sector to ensure food security, there is a need to improve management processes in the sphere of agricultural land use. The aim of the article is to provide a rationale for the ecological-economic management of land resources based on agricultural zoning to improve the efficiency of agricultural enterprises. Research gaps include the need for detailed studies on localized ecological impacts and long-term outcomes of AZ-based land redistribution on soil health and agricultural productivity. Based on the analysis of documents (sources) and an expert survey, this study proposes a framework for ecological-economic management of agricultural land resources in Kazakhstan through agricultural zoning (AZ), aiming to optimize the allocation of grasslands, pastures, arable land, and water resources. Based on document analysis and expert surveys, an optimal land ratio of approximately 30% meadows/pastures, 20% arable land, and 20% water is recommended, aligned with practices in Western Europe and North America. The study suggests measures for sustainable land use, including transferring degraded lands to pasture, preferential taxation for ecologically clean production, and financial incentives for restoring and conserving land. These strategies aim to increase agricultural productivity, meet international quality standards, and support sustainable food security through enhanced land use planning and policy. Scientific novelty of the obtained results relates to the improvement of ecological-economic management of land resources at agricultural enterprises in the conditions of zoning, considering the potential of the agricultural zones of Kazakhstan.