青藏高原中分辨率土地覆被数据（1980s-2020）

该数据集包含1980s和1990-2020年每5年1期的青藏高原30米土地覆被数据产品，即1980s、1990年、1995年、2000年、2005年、2010年、2015年、2020年共8期。该产品由中国科学院空天信息创新研究院牵头，中国科学院西北生态环境资源研究院和中国科学院水利部成都山地灾害与环境研究所参与共同完成。通过青藏高原土地覆被类型科考与遥感数据调查，制定了符合青藏高原生态环境特征的土地覆被分类系统，包括林地、草地、水体/湿地、耕地、建设用地、荒漠、冻原、裸地等8个一级类和42个二级类。采用面向对象分类、变化检测等方法，结合云计算、大数据、机器学习等技术，实现了1980s-2020年长时序、高精度的青藏高原土地覆被数据集，空间分辨率为30米。该数据集可为揭示青藏高原土地覆被量与质的时空格局，支持生态系统、生态资产与生态安全评估提供基础数据。

This dataset contains 30-meter land cover data products of the Qinghai-Tibet Plateau, with 8 temporal phases in total: the 1980s, 1990, 1995, 2000, 2005, 2010, 2015, and 2020. The data is updated every 5 years from 1990 to 2020, plus one phase for the 1980s. This product was jointly developed under the leadership of the Aerospace Information Research Institute, Chinese Academy of Sciences, with participation from the Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, and the Institute of Mountain Hazards and Environment, Chinese Academy of Sciences (affiliated with the Ministry of Water Resources). Through field surveys of land cover types on the Qinghai-Tibet Plateau and remote sensing data investigations, a land cover classification system tailored to the ecological environment characteristics of the plateau was established, which includes 8 first-level categories such as forest land, grassland, water bodies/wetlands, cultivated land, construction land, desert, tundra, and bare land, as well as 42 second-level subcategories. Adopting methods including object-oriented classification and change detection, and integrating technologies such as cloud computing, big data, and machine learning, this long-time-series, high-precision land cover dataset of the Qinghai-Tibet Plateau spanning the 1980s to 2020 was developed, with a spatial resolution of 30 meters. This dataset can provide fundamental data for revealing the spatio-temporal patterns of both quantity and quality of land cover on the Qinghai-Tibet Plateau, and supporting assessments of ecosystems, ecological assets, and ecological security.

搜集汇总

背景与挑战

背景概述

该数据集提供了1980年代至2020年青藏高原的30米分辨率土地覆被数据，每5年一期共8期，采用面向对象分类和机器学习技术生成，包含8个一级类和42个二级类的详细分类。数据集具有长时序和高精度特点，适用于揭示土地覆被时空格局及支持生态系统评估等研究。