five

Continuous Discontinuous Irrigated Areas in China Dataset (CDIA) (2000-2022)

收藏
Figshare2025-02-06 更新2026-04-28 收录
下载链接:
https://figshare.com/articles/dataset/Continuous_Discontinuous_Irrigated_Areas_in_China_Dataset_CDIA_2000-2022_/25912474
下载链接
链接失效反馈
官方服务:
资源简介:
The Continuous Discontinuous Irrigated Areas in China dataset (CDIA) provides information on irrigated areas in China from 2000 to 2022. It was generated using a novel sampling framework designed to accurately identify both continuous and discontinuous irrigated areas (i.e., pixels that were irrigated irregularly across different years). The dataset provides annual IA maps for China by applying 1,688 area-specific random forest models, which utilize remotely sensed data (e.g., vegetation indices, climate factors, and terrain factors) and government statistical data (GCD) as ancillary inputs.Key Features:Temporal Coverage: 2000-2022Spatial Resolution: 500 metersData Sources: Remotely sensed data, government censored data (GCD), and random forest modelSpatial Reference System: EPSG:4326 (WGS-1984)File Type: TIFF:Data Description:This dataset depicts the spatial distribution of irrigated areas in China from 2000 to 2022. It provides insights into the dynamics of irrigation practices across different regions of China. Users can explore the temporal and spatial patterns of irrigated areas and conduct analyses to understand IA changes over timeUsage:Researchers and policymakers can use this dataset for various purposes, including:Monitoring temporal changes of irrigated areas over ChinaAssessing the effectiveness of irrigation management policiesUnderstanding the impact of climate change on irrigation practicesIntegrating irrigation data into land use planning and agricultural development strategiesConducting predictive modeling of irrigation demand or optimizing irrigation schedulingLicense:The CDIA dataset is made available under CC BY-NC 4.0 license. Users are encouraged to cite the dataset appropriately when used in publications or research projects.
创建时间:
2025-02-06
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