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Highlights • Our RS-based method integrates 11 dimensional features to map urban land use. • We develop multi-dimensional DPSIR-based indicators to analyze urban land expansion. • Increasing sprawl while decreasing density reduces economic-socio-ecological benefits. • Quantifying the interactions between multiple indicators can aid urban planning. • Optimizing multi-dimensional trade-offs and synergies is the key to sustainability. Abstract Rapid urban land expansion not only stimulates socioeconomic development, but can lead to negative impacts that threaten regional food security, ecological construction, and sustainable urban development, including losses of cropland and habitats, the creation of housing bubbles, and reductions in biodiversity. Because these economic-socio-ecological problems are generally more serious in ecologically fragile areas, this study focuses on trends seen in Ganzhou District, a typical oasis city within the Heihe River Basin (HRB) in an arid-to-semi-arid area of China. We apply a remote-sensing (RS)-based method that incorporates 11 dimensional features of Thematic Mapper and Enhanced Thematic Mapper Plus (TM/ETM+) images to map changes in urban land, and also develop a series of multi-dimensional indicators within a drivers, pressures, states, impacts, and responses (DPSIR) framework to quantify urban land expansion. The results of this study show that the urban land area of Ganzhou District in 2016 had expanded by 394.43% from 1987 levels, from 1979.64 ha to 9787.86 ha. These increasing pressures, jointly driven by gross domestic product (GDP), urban population, cropland area, and the industrial structure indicator (ISI), have led to the worsening economic-socio-ecological states and impacts of urban land expansion. Specifically, between 1987 and 2016, expansion intensity (EIPI) and expansion rate pressure indicators (ERPI) increased from 60.27 ha/a to 520.88 ha/a, and from 3.04%/a to 10.21%/a, respectively. Thus, the state indicators of economic development (EDSI), population carrying capacity (FDSI), food security (FSSI), and ecological construction (ECSI) decreased by 2.21 × 103 USD/ha, 17.62 population/ha, 34.20, and 10.80, respectively. Moreover, the impact indicators of economic development (EDII), population carrying capacity (FDII), and food security (FSII) decreased by 150.68 × 103 USD/ha, 62.12 population/ha, and 27.31, respectively, while the ecological construction impact indicator (ECII) increased by 29.39 between 1997 and 2007 and decreased by 13.31 between 2007 and 2016. Data also show that the area and proportion of cropland and ecological land occupied by urban land expansion increased over time. We therefore propose a series of economic-socio-ecological responses to help limit urban sprawl and foster compact green cities. Measures include planning urban growth boundaries, revitalizing urban centers and brownfields, using and re-using urban land more efficiently, strengthening land regulations, curbing excessive cropland expansion, cultivating more urban green spaces, and optimizing the trade-offs and synergies between multiple conflicting dimensions. [ABSTRACT FROM AUTHOR]

Water and land (W-L) resources become even more important in the context of urban-rural integration in China's arid northwest region in order to achieve sustainable development goals (SDGs). Our study used Gini coefficients to examine the relationship between natural resources and economic development in China's Xinjiang Uygur Autonomous Region. Cobb-Douglas (C-D) production functions were used to determine the economic impacts of W-L resources on rural-urban economic development. We also examined the spatiotemporal interaction characteristics of the growth drag effect of W-L resources. As a result of the decline in Gini coefficients between 2000 and 2020, Xinjiang experienced a decrease in water resources, land resources, and urban-rural GDP (gross domestic product). The output elasticities of urban-rural land and water resources were 0.3544 and 0.4790, respectively, whereas the output elasticities of urban-rural land resources were 0.1501 and 0.2185, respectively. As a result, water resources contribute to the growth of urban-rural GDP more than land resources, and W-L resources contribute to the economic development of rural areas more than it does to that of urban areas. Land resources were found to have a drag effect on urban and rural economies, respectively, in 7 and 56 counties, respectively, and water resources were found to have a drag effect on urban and rural economies, respectively, in 67 and 58 counties. In Xinjiang, water resources contributed more to economic growth than land resources. Even though W-L resources still have a drag effect on urban-rural economic growth, we can gain greater driving force by optimizing and improving resource use. However, this requires an optimal allocation and efficient use of water resources. • The drag model can analyze the drag effects of natural resource use on the urban-rural economy. • Water resources are more compatible with the urban-rural economy than land resources. • Water constraints affect Xinjiang's economic growth more than land constraints. • Water scarcity reduced Xinjiang's urban economic growth by 0.68%–1.57% from 2000 to 2020. [ABSTRACT FROM AUTHOR]