How does urbanization evolve heterogeneously in urbanized, urbanizing, and rural areas of China? Insights from ecosystem service value
Yikun Zhang , Yongsheng Wang
Geography and Sustainability ›› 2025, Vol. 6 ›› Issue (3) : 100254
How does urbanization evolve heterogeneously in urbanized, urbanizing, and rural areas of China? Insights from ecosystem service value
The rapid population and land urbanization not only promoted economic development but also affected the ecosystem service value (ESV). In the context of new-type urbanization and green development, it’s essential to investigate the impacts of urbanization on ESV in China. However, a comprehensive and dynamic framework to reveal the relationship between ESV and urbanization processes is lacking. This study adopted multi-source datasets to portray China’s urbanization process by integrating population, land, and economic urbanization, evaluated the ESV changes of 10 categories by gross ecosystem product (GEP) methods, and explored ESV changes within different urbanization scales and speeds. The results showed rapid urbanization in the population, land, and economic dimensions in China, with a faster process of economic urbanization. The ESV also exhibited an increasing trend, with higher levels in the southeastern coastal regions and lower levels in the northwestern regions. Urbanization had positive impacts on ESV across various research units, but the ESV exhibited heterogeneous changes across different urbanization scales, speeds, and their interactive effects. The response of ESV to dynamic urbanization processes was influenced by socio-economic, ecological, and policy factors; it is essential to combine targeted measures with general ecological product value realization methods in each unit to maximize social-economic-ecological benefits.
Urbanization / Urban-rural areas / Ecosystem service value / Social-economic-ecological benefits / China
| [1] |
|
| [2] |
|
| [3] |
|
| [4] |
Che, T., Dai, L., Li, X., 2015. Long-term series of daily snow depth dataset in China (1979–2023). National Tibetan Plateau/Third Pole Environment Data Center doi: 10.11888/Geogra.tpdc.270194. |
| [5] |
|
| [6] |
|
| [7] |
|
| [8] |
|
| [9] |
|
| [10] |
|
| [11] |
|
| [12] |
|
| [13] |
|
| [14] |
|
| [15] |
Didan, K., 2015. MOD13A3 MODIS/Terra vegetation indices monthly L3 global 1 km SIN grid V006. NASA EOSDIS Land Processes Distributed Active Archive Center. https://doi.org/10.5067/MODIS/MOD13A3.006. |
| [16] |
|
| [17] |
|
| [18] |
|
| [19] |
|
| [20] |
|
| [21] |
|
| [22] |
He, C., Liu, Z., Xu, M., Lu, W., 2022. Dataset of urban built-up area in China (1992–2020) V1.0. National Tibetan Plateau /Third Pole Environment Data Center. |
| [23] |
|
| [24] |
|
| [25] |
|
| [26] |
|
| [27] |
|
| [28] |
|
| [29] |
|
| [30] |
|
| [31] |
|
| [32] |
|
| [33] |
|
| [34] |
|
| [35] |
|
| [36] |
|
| [37] |
|
| [38] |
|
| [39] |
Millennium Ecosystem Assessment, 2005. Ecosystems and Human Well-being: Wetlands and Water. World Resources Institute. |
| [40] |
National Bureau of Statistics of China, 2021a. China Statistical Yearbook (2000–2021). China Statistics Press, Beijing (in Chinese). |
| [41] |
National Bureau of Statistics of China, 2021b. Communiqué of the Seventh National Population Census. China Statistics Press, Beijing (in Chinese). |
| [42] |
|
| [43] |
|
| [44] |
|
| [45] |
|
| [46] |
|
| [47] |
|
| [48] |
|
| [49] |
|
| [50] |
|
| [51] |
Running, S., Zhao, M., 2021. MODIS/Terra net primary production gap-filled yearly L4 global 500 m SIN grid V061. NASA EOSDIS land processes DAAC. https://doi.org/10.5067/MODIS/MOD17A3HGF.061. |
| [52] |
|
| [53] |
|
| [54] |
|
| [55] |
|
| [56] |
|
| [57] |
|
| [58] |
|
| [59] |
|
| [60] |
|
| [61] |
|
| [62] |
|
| [63] |
|
| [64] |
|
| [65] |
|
| [66] |
|
| [67] |
Xu, X., Liu, J., Zhang, S., 2018. China multi-period land use land cover remote sensing monitoring dataset (CNLUCC). https://doi.org/10.12078/2018070201. |
| [68] |
|
| [69] |
|
| [70] |
|
| [71] |
|
| [72] |
|
| [73] |
|
| [74] |
|
| [75] |
|
| [76] |
|
| [77] |
|
| [78] |
|
| [79] |
|
| [80] |
|
| [81] |
|
| [82] |
|
| [83] |
|
| [84] |
|
/
| 〈 |
|
〉 |