Remote sensing and GIS-based land assessment in Zhanaarka region of Ulytau oblast, Kazakhstan

Dana Shokparova ^1* Mukhabat Sirazhitdinova ² Sanim Bissenbayeva ² Nilanchal Patel ³

• ¹ Department of Geography, Land Management and Cadastre, China-Kazakhstan Joint Laboratory for Remote Sensing Technology and Application, Al-Farabi Kazakh National University, Al-Farabi Kazakh National University, Almaty, Kazakhstan
• ² Department of Geography, Land Management and Cadastre, Al-Farabi Kazakh National University, Almaty, Kazakhstan
• ³ Department of Remote Sensing, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India

The agricultural practices in Kazakhstan are causing considerable pressure on the landscape, resulting in adverse environmental impacts, changes in landscape morphology, degradation and fragmentation of pasturelands, and threats to biodiversity. It is an essential component of economic development; therefore, special attention is paid to the quality of land resources, their use, and the preservation of natural conditions. Agricultural land use data from for 2009, 2013, and 2018 were derived from satellites Landsat 5 and 8 to examine the state of the land, its valuation, and its characteristics in the Zhanaarka region. By employing remote sensing data, we gain an in-depth understanding of the intricate interplay between land use practices, environmental parameters, and climate dynamics. The objectivess of this study was to assess the condition of pastures in the Zhanaarka region of the Ulytau oblast, Kazakhstan, considering climatic changes and anthropogenic impacts. Remote sensing data, including NDVI, climate factor analysis (temperature and precipitation), and mapping methods, were utilized. The analysis covered changes in vegetation cover and land boundaries for the years 2009, 2013, and 2018, allowing for the identification of key drivers of land degradation. Pearson's Correlation was applied to determine between the main factors influencing the state of the land, i.e., temperature and precipitation. These climatic variables, intrinsic to the arid landscape, are critical in deciphering the region's agricultural potential and vulnerabilities. No climatic variable was identified as the limiting factor for Normalized difference vegetation index (NDVI) changes in the multivariate correlation analysis. Moreover, we extend our focus to the profound impact of human activities on land resources, acknowledging the role of land development, irrigation practices, and land degradation. Through this integrated analysis, we aim to contribute to the informed and sustainable management of land resources, thus supporting both economic growth and ecological preservation in the region. The findings formed the basis for recommendations to prevent pasture degradation and ensure sustainable land resource management in the region. These recommendations are designed to mitigate the effects of climate change and human activities on the landscape, promoting resilience and sustainability in agricultural practices.