Institute of Tibetan Plateau Research, CAS

Address: 16 Lincui Road, Chaoyang District, Beijing 100101, P.R. China

E-mail: data@itpcas.ac.cn

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Data Release of Integrated Space-drone-ground Monitoring Network in Qilian Mountains in 2020

In July 2021, the datasets of the integrated space-drone-ground monitoring network in Qilian Mountains in 2020 and the observation datasets of the space-drone multi-source remote sensing monitoring system (81 in total), which is mainly based on drones, Gaofen satellite, and medium- and high-resolution satellites, were published in the National Tibetan Plateau/Third Pole Environment Data Center" (https://data.tpdc.ac.cn/en/). The released observation datasets of the integrated monitoring network of Qilian Mountains for 2018 and 2019 (152 in total) have been viewed more than 380,000 times and applied for use more than 13,000 times, which have received wide attention, application and praise from users.

The released ground observation dataset covers six major basins in the Qilian Mountains region (Heihe River Basin (14 stations), Qinghai Lake Basin (4 stations), Datong River Basin (1 station), Shule River Basin (2 stations), Shiyang River Basin (2 stations), and Qaidam Basin (1 station)), and has fine observations (sub-meter level) from drones at typical sample sites. The released datasets include: 1) 62 ground observation datasets from 24 stations in the Qilian Mountains in 2020, including surface fluxes such as sensible heat flux, latent heat flux and carbon flux; hydro-meteorological elements such as wind, temperature, humidity, precipitation, radiation, soil temperature and humidity profile, soil heat flux, photosynthetic effective radiation and surface radiation temperature; vegetation parameters such as vegetation phenology, cover and leaf area index and biological diversity survey data; 2) a total of 9 datasets of high-resolution ecological remote sensing products in the whole region of Qilian Mountains in 2020, including: basic products such as land cover/use, vegetation parameter products such as normalized vegetation index, vegetation cover, leaf area index and vegetation primary productivity (30m), hydrological products such as water index (30m), soil moisture (0.05°) and surface evapotranspiration (0.01°) and products of human activities (30m), etc; 3) a total of 7 datasets of ecological remote sensing products for the Qilian Mountains key regions in 2020, including: vegetation parameter products such as normalized vegetation index, vegetation cover, vegetation net primary productivity, grassland biomass, forest accumulation (8m), hydrological products such as glacier distribution (2m) and human activity products (2m, mining, hydropower construction, tourism development, etc.); 4) 3 datasets of UAV remote sensing products in 2020, including vegetation index, surface albedo and surface temperature (0.5m), etc. All the datasets are subject to uniform data processing and strict quality control, and have passed the peer review by the review experts. Users can apply for access through the National Tibetan Plateau/Third Pole Environment Data Center.

Integrated Space-drone-ground Monitoring Network in Qilian Mountain Region

The integrated monitoring network of Qilian Mountains is a combination of long-term ground-based cooperative observation, typical sample sites, high spatial and temporal resolution in key areas, and region-wide long time series remote sensing monitoring based on the Internet of Things. The generated multi-source, multi-scale, multi-factor integrated monitoring datasets in the Qilian Mountains will enhance the integrated monitoring capabilities for "mountain, water, forest, field, lake, grass and sand" system, help integrated analysis and assessment of the ecological environment, and provide scientific support for the ecological protection and restoration, national park construction in the Qilian Mountains area. The construction and operation of the integrated monitoring network in the Qilian Mountains is supported by the sub-project of Strategic Priority Research Program of the Chinese Academy of Sciences (grant no. XDA20100101), led by Prof. LIU Shaomin of Beijing Normal University.

Data available at:

https://data.tpdc.ac.cn/zh-hans/special/836a1603-47d0-494e-88c1-96723fd8e0bc/