Changes occurring because of human activity in protected natural places require constant monitoring of land use (LU) structures. Therefore, Korgalzhyn District, which occupies part of the Korgalzhyn State Natural Reserve territory, is of considerable interest. The aim of these studies was to analyze changes in the composition of the land use/land cover (LULC) of Korgalzhyn District from 2010 to 2021 and predict LU transformation by 2030 and 2050. Landsat image classification was performed using Random Forest on the Google Earth Engine. The combined CA-ANN model was used to predict LULC changes by 2030 and 2050, and studies were carried out using the MOLUSCE plugin. The results of these studies showed that from 2010 to 2021, there was a steady increase in the share of ploughable land and an adequate reduction in grassland. It is established that, in 2030 and 2050, this trend will continue. At the same time, there will be no drastic changes in the composition of other land classes. The obtained results can be helpful for the development of land management plans and development policies for the Korgalzhyn District.

Long-term spatiotemporal Land Use and Land Cover (LULC) analysis is an objective tool for assessing patterns of sustainable development (SD). The basic purpose of this research is to define the Driving Mechanisms (DM) and assess the trend of SD in the Burabay district (Kazakhstan), which includes a city, an agro-industrial complex, and a national natural park, based on the integrated use of spatiotemporal data (STD), economic, environmental, and social (EES) indicators. The research was performed on the GEE platform using Landsat and Random Forest. The DM were studied by Multiple Linear Regression and Principal Component Analysis. SD trend was assessed through sequential transformations, aggregations, and integrations of 36 original STD and EES indicators. The overall classification accuracy was 0.85–0.97. Over the past 23 years, pasture area has changed the most (−16.69%), followed by arable land (+14.72%), forest area increased slightly (+1.81%), and built-up land—only +0.16%. The DM of development of the AOI are mainly economic components. There has been a noticeable drop in the development growth of the study area in 2021, which is apparently a consequence of the COVID-19. The upshots of the research can serve as a foundation for evaluating SD and LULC policy.

An ecosystem health assessment (EHA) is essential for comprehensively improving the ecological environment and socio-economic conditions, thereby promoting the sustainable development of a specific area. Most previous EHA studies have focused on urbanized regions, paying insufficient attention to rural areas with urban enclaves and national natural parks. This study employed the Basic Pressure–State–Response methodological approach. The composition of indicators (35) encompassed both spatiotemporal data and socio-economic information. The random forest algorithm was used on the Google Earth Engine platform to classify and evaluate changes in land use and land cover (LULC). In addition, weighting coefficients were calculated, and driving factors were subsequently identified. The analysis revealed that the rural administrative divisions in the central part of Zerendy district, where the city of Kokshetau is situated, exhibited a relatively low level of ecosystem health (EH). The southwestern rural administrative divisions of the studied district, where the national nature park and the reserve territories are located, exhibited a higher level of EH. Other rural administrative divisions located in the eastern parts of the district generally exhibited a moderate level of EH. Interested managers can use the results of our assessment to implement adequate measures aimed at improving the health of the Zerendy district ecosystem.

The purpose of the scientific article is the implementation of an important part of the agricultural spatial data infrastructure, planning of the domestic economy using geographic information systems (GIS). Taking this direction into account, the work examines the following main elements of designing the domestic economy: location of settlements and economic centers; design of internal roads; placement of external engineering networks; use of types of land reclamation for agricultural purposes; allocation of land for the construction of roads of various categories of local importance; placement of agricultural machinery in land use; conduct a technical and economic analysis of the effective use of road junctions and reclamation works as an engineering structure, as well as systematize the engineering and geodetic process necessary to implement these studies based on GIS technologies. With the help of geographic information systems technologies, it will be necessary to determine the following directions of engineering and geodetic equipment of the territory: Information about road transport and roads, Roads in plan, longitudinal and horizontal profiles, Driving through bodies of water and bodies of water on the road, Road surfaces, Road surveys and design of agricultural roads, The basic principle of organizing the construction, maintenance and repair of agricultural roads.