Monthly average daytime as well as nighttime data of the Universal Thermal Climate Index (UTCI) for 354 cities in China. The time range of the data is from January 2012 to December 2021, with a temporal resolution of month-by-month. The spatial resolution is 1 km. The data is mainly based on the MYD07 atmosphere profile dataset and MYD11 land surface temperature dataset provided by MODIS, and incorporates the wind speed provided by ERA5 reanalysis data. The urban boundary is demarcated according to the 2018 data provided by Global Urban Boundary-GUB dataset. All the data are resampled to 1 km, in order to maintain the uniform spatial resolution. With the rapid urbanization and global warming, the data are useful for studying the spatiotemporal patterns of urban thermal comfortable and related analysis.
王 晨光 , WANG Chenguang, WANG Chenguang, 占 文凤 ZHAN Wenfeng
The data set contains annual NPP-VIIRS night time light data images of equatorial northern Africa and the Sahel region from 2013 to 2020. Based on the monthly average night time light image data of visible infrared imaging radiometer Suite (VIIRS) of national polar orbiting partnership (NPP) satellite, this dataset is generated by separating the unstable night light caused by biomass combustion from the stable night light information caused by human activities. The spatial resolution of the data is 500 m, and the grid data type is GeoTIFF. The grid pixel value is radiance, and the unit is 10 − 9 w ∙ cm − 2 ∙ SR − 1. The data set improves the ability of noctilucent images to identify small-scale, scattered and unstable urban information in northern equatorial Africa and Sahel to a certain extent, and can be further applied to the research on human activities in northern equatorial Africa and Sahel.
YUAN Xiaotian , JIA Li , JIANG Min
This data is the land cover data at 30m resolution of Southeast Asia in 2015. The data format of the data is NetCDF, and the variable name is "land cover type". The data was obtained by mosaicing and extracting the From-GLC data. Several land cover types, such as snow and ice that do not exist in Southeast Asia were eliminated.The legend were reintegrated to match the new data. The data provide information of 8 land cover types: cropland, forest, grassland, shrub, wetland, water, city and bare land. The overall accuracy of the data is 71% (Gong et al., 2019). The data can provide the land cover information of Southeast Asia for hydrological models and regional climate models.
LIU Junguo
This dataset is the data of human activities in the key areas of Qilian Mountain in 2018, spatial resolution 2m. This dataset focuses on mine mining, urban expansion, cultivated land development, hydropower construction, and tourism development in the key areas of Qilian Mountain.Through high-resolution remote sensing images, compare the changes before and after the statistics. For the maps of the landforms in the Qilian Mountains, check and verify them one by one; re-interpret the plots that are suspicious of the map; collect the relevant data in the field that cannot be reflected by the images, check and correct the location. At the same time, unified input and editing of map attribute information. Generating a data set of human activities in the key areas of the Qilian Mountains in 2018.
QI Yuan, ZHANG Jinlong, JIA Yongjuan, ZHOU Shengming, WANG Hongwei
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