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Updated: Dec 18, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
[Spatial-temporal evolution of ecological land and influence factors in Wuhan urban agglome-ration based on
Yan-Wen Liu1,2, Cheng-Wu Liu3, Zong-Yi He1
1School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China.
Abstract:
Ecological land is essential to sustainable development of urban agglomeration. Based on the results of remote sensing image interpretation, we analyzed the spatial-temporal evolution of ecological land in 32 research units of ecological land in Wuhan urban agglomeration in 2000-2005, 2005-2010 and 2010-2015, using the land use transition matrix, exploratory regression analysis, the ordinary least squares (OLS) model, and geographically weighted regression (GWR) model. Then, the best regression model was selected after perfecting the traditional index system of influencing factors by data of the location and quantitative information of companies, enterprises and life services, etc., and conducting exploratory regression analysis. Finally, we analyzed the influencing factors and spatial differentiation rules of different research periods with GWR model. The results showed that, from 2000 to 2015, the amount of transition from ecological land use to non-ecological land use in the urban agglomeration showed an inverted U-shaped change pattern, and the space showing the expanding trend from point to surface. Land use patterns of 8.4% area had changed in the urban agglomeration, among which the conversion of cultivated land, forest land, grassland, water body and unused land to non-ecological land accounted for 41.9% of the total area. The spatial pattern gradually expanded from the central urban area of Wuhan to the periphery of the municipal sub-center and county-level towns. The total number of passing models in the three stages of exploratory regression analysis was 326. The GWR and OLS regression were used for comparative analysis of all models. The adjusted R2 in the three stages of selected models were 0.83, 0.91 and 0.76, respectively. The former improved by 0.02, 0.03 and 0.02, and the AICc decreased by 2.88, 3.42 and 0.83, respectively. The results of GWR model showed substantially spatial differentiation of influencing factors of ecological land evolution in Wuhan urban agglomeration, and that the influence patterns was dominated by gradual transition in different directions in space, with other patterns such as "V" distribution. The effects of spatial factors were significant. The potential information of spatial data enhanced the interpretation of ecological land evolution within the urban agglomeration.
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