We have compiled the largest number of annual average ground temperature (1002) and active layer thickness (452) ground observation data in the Northern Hemisphere, and used four statistical learning models to integrate these ground observations with multi-source remote sensing data products. Through ensemble simulation, we obtained a dataset representing the annual average ground temperature, active layer thickness, permafrost occurrence probability, and permafrost hydrothermal zoning in the Northern Hemisphere's permafrost region from 2000 to 2016, with a spatial resolution of 1 kilometer. Verification shows that it has higher accuracy. It can provide data support for engineering planning, design, environmental simulation, and evaluation in the permafrost regions of the Northern Hemisphere, and can also serve as a data benchmark for assessing future permafrost changes and their impacts.
The largest number of annual average ground temperature (1002) and active layer thickness (452) ground observation data in the Northern Hemisphere.
Using statistical learning models to integrate ground observations and multi-source remote sensing data products.
The data quality is good.
| # | number | name | type |
| 1 | XDA19000000 | CASEarth:Big Earth Data for Three Poles | other |
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