The article considers the sphere of land management in the Republic of Kazakhstan. The purpose of the study is to determine problems of land management system in the republic and the tasks of its improvement in the future. The research methodology included a desk method for collecting and analyzing data on the activities of land administration authorities. The problems were identified in the following three areas: legislative regulation of land use, management and control of state ownership of land, the process of digitalization of land management. As a result, it was found that the national land administration system does not fully meet the needs of the modern economy. In order to improve the land management system, it is proposed to solve the following tasks: to improve the quality of legal regulation; carry out a complete digitization of land; form an integrated electronic land management system; develop and implement the state program “Digital Land Management” until 2025. The results of the study contribute to the development of a new land management model in Kazakhstan, aimed at encouraging the national government to develop a new land management strategy, increasing the transparency of the management system as well as simplifying the process of administration in this area.

In the context of the digitalization of the agricultural sector, the implementation of Geographic Information Systems (GIS) in the processes of monitoring and managing agricultural land is of particular importance. The purpose of this study is to evaluate the effectiveness of GIS tools for solving tasks related to the updating of land use contours, the analysis of agricultural land conditions, and the support of decision-making processes. A comparative analysis of several functional modules and analytical instruments implemented in ArcGIS was carried out. The research employed remote sensing data, vector layers of agricultural land, and cadastral information. The results demonstrated that the use of GIS technologies significantly improves the accuracy of cartographic materials, the efficiency of data updating, and the quality of spatial analysis, which in turn contributes to more effective land resource management. The paper provides recommendations for integrating the most productive tools into land management and cadastral monitoring practices.

The current system of state land cadastral valuation relies predominantly on economic indicators, overlooking natural and environmental hazards in its calculations. Ignoring these local risks severely distorts the objective value of land parcels in complex territo-ries such as the Bostandyk District of Almaty. Determining fair property values re-quires implementing a methodology capable of mathematically accounting for tectonic faults, zones of 9- and 10-point seismic intensity, and environmental discomfort indi-cators. A GIS-based spatial analysis of 62 cadastral blocks, utilizing up-to-date seismic microzoning maps, enabled the calculation of an integrated risk coefficient for each specific location. Mathematical modeling demonstrated the impact of negative exter-nalities on land pricing. Accounting for geological hazards results in a proportional 20–45% reduction in the unit cadastral value for the most vulnerable areas. This new valu-ation paradigm shifts the focus toward urban environmental safety and restores the so-cial equity of the cadastre. Establishing objective, discounted prices creates a natural economic barrier against urban densification in hazardous zones. The developed ana-lytical algorithm is universal and can be scaled to other seismically active regions in Central Asia.

Sustainable development of the agro-industrial complex (AIC) requires an integrated assessment of investment activity, production performance, financial returns, and resource provision at the district level. This study evaluates the production and economic performance of 13 districts of the North Kazakhstan Region using a composite scoring approach based on seven groups of indicators: investment activity, gross agricultural output, crop yields, livestock productivity, crop-production profitability, livestock-production profitability, and capital intensity. The information base includes official district-level statistics, materials of the regional agricultural authorities, data on fixed production assets for 2021–2023, and national land-use reporting. The results reveal substantial territorial differentiation. Kyzylzhar and Taiynsha districts form the high-performance group, Esil District is classified above average, whereas Ualikhanov District occupies the lowest position in the aggregate ranking. The analysis also identifies a scale-efficiency mismatch: large agricultural territories do not necessarily demonstrate high profitability or productivity, while several medium-sized districts achieve stronger returns on land and production resources. The findings provide a comparative basis for territorially differentiated agricultural policy, targeted investment support, technological modernization, and the development of processing infrastructure in the North Kazakhstan Region.

The study aims to improve the procedures of state cadastral valuation of agricultural lands by incorporating spatial information on geo-ecological threats. Mudflow-prone plots of the Talgar District in the Almaty Region are examined as a test site. The methodological framework relies on a GIS-overlay that integrates land-use vector boundaries with the Ile-Alatau Mudflow Hazard Typization Map. The transformation of physical disaster characteristics into an economic indicator is carried out through the mathematical toolkit of value functions v(x). The final stage involves calculating the mudflow hazard discounting coefficient (Kc). An analysis of the current regulatory framework (Art. 11 of the Land Code of the RK) revealed a significant methodological gap: the dynamics of exogenous processes are entirely omitted from calculation algorithms. Testing the updated approach on data from nine land parcels demonstrates the necessity of revising base rates. The application of the Kc parameter results in a 49–80% drop in normative value for transit zones, while foothill risk lands receive a fixed price reduction of 30%. The proposed computational model helps mitigate overestimated cadastral values and land lease fees for agricultural enterprises, synchronizing land prices with their actual productivity. The resulting financial discount takes the form of indirect preventive insurance. Responsibility for potential damage is appropriately distributed between the budget and the tenant. Such a practice can protect the budget from unforeseen compensation costs after mudflow events, while simultaneously motivating farmers to invest in the construction of local mudflow protection barriers.