Permafrost Distribution along the Qinghai-Tibet Engineering Corridor, China Using High-Resolution Statistical Mapping and Modeling Integrated with Remote Sensing and GIS

Permafrost distribution in the Qinghai-Tibet Engineering Corridor (QTEC) is of growing interest due to the increase in infrastructure development in this remote area. Empirical models of mountain permafrost distribution have been established based on field sampled data, as a tool for regional-scale...

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Bibliographic Details
Published in:Remote Sensing
Main Authors: Fujun Niu, Guoan Yin, Jing Luo, Zhanju Lin, Minghao Liu
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2018
Subjects:
Q
Online Access:https://doi.org/10.3390/rs10020215
https://doaj.org/article/cd9e9dd7aa5349e9aef554f7f968ce2f
Description
Summary:Permafrost distribution in the Qinghai-Tibet Engineering Corridor (QTEC) is of growing interest due to the increase in infrastructure development in this remote area. Empirical models of mountain permafrost distribution have been established based on field sampled data, as a tool for regional-scale assessments of its distribution. This kind of model approach has never been applied for a large portion of this engineering corridor. In the present study, this methodology is applied to map permafrost distribution throughout the QTEC. After spatial modelling of the mean annual air temperature distribution from MODIS-LST and DEM, using high-resolution satellite image to interpret land surface type, a permafrost probability index was obtained. The evaluation results indicate that the model has an acceptable performance. Conditions highly favorable to permafrost presence (≥70%) are predicted for 60.3% of the study area, declaring a discontinuous permafrost distribution in the QTEC. This map is useful for the infrastructure development along the QTEC. In the future, local ground-truth observations will be required to confirm permafrost presence in favorable areas and to monitor permafrost evolution under the influence of climate change.