Untangling the Integral Impact of Land Use Change, Economic, Ecological and Social Factors on the Development of Burabay District (Kazakhstan) during the Period 1999–2021

Onggarbek Alipbeki, Gauhar Mussaif (), Chaimgul Alipbekova, Aizada Kapassova, Pavel Grossul, Meirzhan Aliyev and Nursultan Mineyev
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Onggarbek Alipbeki: Department Geodesy and Cartography, S. Seifullin Kazakh Agrotechnical Research University, Astana 01011, Kazakhstan
Gauhar Mussaif: Department Geodesy and Cartography, S. Seifullin Kazakh Agrotechnical Research University, Astana 01011, Kazakhstan
Chaimgul Alipbekova: Department Biology, Plant Protection and Quarantine, S. Seifullin Kazakh Agrotechnical Research University, Astana 01011, Kazakhstan
Aizada Kapassova: Department Geodesy and Cartography, S. Seifullin Kazakh Agrotechnical Research University, Astana 01011, Kazakhstan
Pavel Grossul: Department Geodesy and Cartography, S. Seifullin Kazakh Agrotechnical Research University, Astana 01011, Kazakhstan
Meirzhan Aliyev: Department Geodesy and Cartography, S. Seifullin Kazakh Agrotechnical Research University, Astana 01011, Kazakhstan
Nursultan Mineyev: Department Geodesy and Cartography, S. Seifullin Kazakh Agrotechnical Research University, Astana 01011, Kazakhstan

Sustainability, 2023, vol. 15, issue 9, 1-36

Abstract: 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.

Keywords: sustainable development; remote sensing; land use; agriculture; city; national natural park; driving mechanisms; assessing development (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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