five

Sanjiang Plain Water-related Ecosystem Services Original Dataset

收藏
DataCite Commons2026-04-29 更新2026-05-04 收录
下载链接:
https://data.mendeley.com/datasets/z3yccs33pb/1
下载链接
链接失效反馈
官方服务:
资源简介:
This dataset comprises comprehensive resources for analyzing water-related ecosystem services, structured into five key components: (1)Original Raster Datasets for Water-related Ecosystem Service Analysis High-resolution raster data capturing spatial patterns of water-related ecosystem services (e.g., water purification, water yield, and soil retention) across the Sanjiang Plain. (2)InVEST Model Inputs and Parameters Processed raster datasets optimized for InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model simulations, accompanied by parameter tables in CSV format. These include biophysical parameters (e.g., land cover coefficients, soil retention rates) and model configuration files for reproducible ecosystem service quantification. (3)Tradeoff Analysis Data Raw datasets designed to evaluate trade-offs between competing ecosystem services (e.g., agricultural production vs. water purification), including multi-temporal raster layers and statistical metadata for cross-service correlation analysis. (4)Driver Analysis and Threshold Effect Data Longitudinal datasets containing time-series observations of key drivers (e.g., precipitation variability, land-use change) and corresponding ecosystem response metrics. This component supports threshold effect identification through nonlinear regression and breakpoint detection techniques. (5)Land-Use Optimization Support Data Root Mean Square Error (RMSE)-validated datasets for future land-use scenario optimization. All components are georeferenced to the Sanjiang Plain study area and include comprehensive metadata for reproducible research. The dataset follows FAIR (Findable, Accessible, Interoperable, Reusable) principles, with standardized file formats (GeoTIFF, CSV).
提供机构:
Mendeley Data
创建时间:
2026-04-29
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作