Vegetation Resilience Dataset for Urban Green Spaces in Shanghai (2001-2022, V1.0)
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DOI:10.3974/geodb.2024.12.04.V1
Published:Dec. 2024
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Key Words：
Critical Slowing Down theory,green space,resilience
Abstract：
Based on MODIS NDVI data (MOD13Q1 V6, 250m resolution) from 2001 to 2022, combined with Dynamic World land use data and Amap administrative boundary data, the authors constructed a vegetation resilience dataset for urban green spaces in Shanghai using the theory of critical slowing down, through simplified STL method and moving average combined with harmonic analysis. The dataset includes the following data in Shanghai: (1) boundary of study area; (2) spatial distribution of green space coverage; (3) vegetation resilience based on AR(1) index using simplified STL method (STL_AR(1)); (4) vegetation resilience based on AR(1) index using moving average and harmonic analysis (V2_AR(1)); (5) vegetation resilience based on variance index using moving average and harmonic analysis (V2_VAR). The dataset is archived in .shp and .tif data formats, the raster data is in 250 m resolution. The dataset consists of 28 data files with data size of 812 KB (Compressed into one file with 726 KB).
Foundation Item：
Shanghai Construction Group Co., Ltd. (24JCSF-24); Zhejiang A&F University (2024LFR069)；
Data Citation：
1.Vegetation Resilience Dataset for Urban Green Spaces in Shanghai (2001-2022, V1.0)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2024. https://doi.org/10.3974/geodb.2024.12.04.V1.
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