In recent years, large-scale urbanization development and construction has brought great impact on the ecological environment while promoting regional social and economic development. The quantitative evaluation of ecological and economic benefits in the process of urbanization through visual means can provide scientific reference for balancing economic benefits and ecological and environmental benefits. This study takes Chongqing City as the study area, using remote sensing interpretation data of land use, soil data, elevation data, meteorological data, social and economic statistics, combined with INVEST 3.3.1, Arc GIS 10.1, SPSS 19.0 and other software, on the basis of land use landscape pattern changes and urbanization land changes in the study area in 2000, 2005, 2010 and 2015 The six types of ecological benefits of purifying the environment and the two types of economic benefits of the primary industry and the secondary and tertiary industry were evaluated, and the spatio-temporal changes of the ecological and economic benefits of each land use landscape pattern, five functional areas, and 39 districts and counties in the study area in the four periods of 2000, 2005, 2010, and 2015 were compared and analyzed. The spatial resolution of this dataset is 25m * 25m. For the specific inversion method, refer to the reference "Research on the Profit and Loss of Ecological and Economic Benefits in the Urbanization Process of Chongqing Based on GIS and InVEST Model (Master's Thesis)".
The dataset consists of four folders, each of which contains the estimated results of ecological service functions of habitat protection, soil conservation, water conservation and carbon fixation for the four years of 2000/2005/2010/2015. The folder is named in Chinese and the file is named in "Chinese phonetic alphabet - year. tif".
Li, Y. (2022). Time series dataset of ecological service functions of Chongqing - Invest model (2000-2015). Upper Yangtze River Scientific Data Center, (Download the reference：
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| East: 110.41 | West: 105.28 |
|---|---|
| South: 28.07 | North: 32.31 |
