2026-10-15T06:35:45Z https://www.scidb.cn/oai

10.57760/sciencedb.j00001.01205 2025-05-12T14:47:03Z

2025-05-12 A reconstruction dataset of land surface temperature at high spatial and temporal resolutions in Chengdu city, China from 2001 to 2022 doi:10.57760/sciencedb.j00001.01205 en The dataset is composed of four folders, and each folder is divided into 21 subfolders from 2000-2022. The data content and organization of each folder are as follows:(1) Folder 1 contains the different spatial resolution raw thermal infrared image applied to spatiotemporal fusion in study area. The medium spatial resolution satellite data includes Landsat TM, Landsat 8, Landsat 9, HJ-1B CCD, HJ-1B IRS. The folder size is 77.2 GB.(2) Folder 2 contains downscaling land surface temperature dataset at 30 m using machine learning algorithm. The folder size is 724 MB.(3) Folder 3 contains land surface temperature dataset with low spatial resolution. The folder size is 30.1 MB.(4) Folder 4 contains high spatiotemporal land surface temperature dataset by spatiotemporal fusion method in the study area. The folder size is 14.0 GB.The dataset totals 91.9 GB. machine learning algorithm; spatiotemporal fusion model; land surface temperature; Chengdu city mao kun Yao Yuan Wang Kun Luo Jiamin Yin Qiuyan Su Qin Chen Cheng PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset Science Data Bank