Spatiotemporal analysis and identifying the driving forces of land use change in the Abay district (Karagandy Region, Kazakhstan)

Onggarbek Alipbeki, Pavel Grossul, Daniyar Rakhimov, Erassyl Aliken, Kairat Augambayev, Chaimgul Alipbekova, Maira Begaliyeva, Ravshanov Alisher Saydullaevich

E3S Web of Conferences, 2024

Full text Open access: Gold Metadata (CSL-JSON)

DOI 10.1051/e3sconf/202459004007

Data confidence 85 high

How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

Land use and cover change (LUCC) affects the nature of human activities in a particular area. Therefore, the manifestation of the driving forces of these changes plays a decisive role. This paper analyses the LULC dynamics of the Abay district of Karagandy oblast from 2016 to 2023. The study’s main objective is to find the driving forces of land use based on the integrated assessment of spatio-temporal data (STD) and socio-economic, climatic and environmental indicators (SECEI). Classification of Sentinel- 2 images into LULC classes is carried out using the Random Forest (RF) algorithm on the Google Earth Engine (GEE) platform. The driving factors were assessed using principal component analysis (PCA) and linear regression (LR). The results obtained can be used to guide the development planning of the territory.