4.6 Article

Spatial Distribution of Permafrost in the Xing'an Mountains of Northeast China from 2001 to 2018

Journal

LAND
Volume 10, Issue 11, Pages -

Publisher

MDPI
DOI: 10.3390/land10111127

Keywords

Xing'an permafrost; permafrost distribution; SFN; TTOP

Funding

  1. National Natural Science Foundation of China [41971151, 41901072]
  2. Key Joint Program of National Natural Science Foundation of China (NSFC)
  3. Heilongjiang Province for Regional Development [U20A2082]
  4. Natural Science Foundation of Jilin Province [20210101104JC]
  5. Natural Science Foundation of Heilongjiang Province [TD2019D002]

Ask authors/readers for more resources

In this study, high-resolution Xing'an permafrost map was estimated using the SFN model and TTOP model driven by remote sensing data sets from 2001 to 2018. The comparison of modeling results showed no significant difference between the two models, and both models efficiently estimated the permafrost distribution in Northeast China.
Permafrost is a key element of the cryosphere and sensitive to climate change. High-resolution permafrost map is important to environmental assessment, climate modeling, and engineering application. In this study, to estimate high-resolution Xing'an permafrost map (up to 1 km(2)), we employed the surface frost number (SFN) model and ground temperature at the top of permafrost (TTOP) model for the 2001-2018 period, driven by remote sensing data sets (land surface temperature and land cover). Based on the comparison of the modeling results, it was found that there was no significant difference between the two models. The performances of the SFN model and TTOP model were evaluated by using a published permafrost map. Based on statistical analysis, both the SFN model and TTOP model efficiently estimated the permafrost distribution in Northeast China. The extent of Xing'an permafrost distribution simulated by the SFN model and TTOP model were 6.88 x 10(5) km(2) and 6.81 x 10(5) km(2), respectively. Ground-surface characteristics were introduced into the permafrost models to improve the performance of models. The results provided a basic reference for permafrost distribution research at the regional scale.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available