permafrost presence/absence mapping of the qinghai-tibet plateau based on multi-source remote sensing data

Clicks: 323
ID: 181823
2018
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #51 of 499 articles by views in Journal of pharmacological sciences

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 499 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
The Qinghai-Tibet Plateau (QTP) is known as the Third Polar of the earth and the Water Tower of Asia, with more than 70% of the area on the QTP is covered by permafrost possibly. An accurate permafrost distribution map based on valid and available methods is indispensable for the local environment evaluation and engineering constructions planning. Most of the previous permafrost maps have employed traditional mapping method based on field surveys and borehole investigation data. However their accuracy is limited because it is extremely difficulties in obtaining mass data in the high-altitude and cold regions as the QTP; moreover, the mapping method, which would effectively integrate many factors, is still facing great challenges. With the rapid development of remote sensing technology in permafrost mapping, spatial data derived from the satellite sensors can recognize the permafrost environment features and quantitatively estimate permafrost distribution. Until now there is no map indicated permafrost presence/absence on the QTP that has been generated only by remote sensing data as yet. Therefore, this paper used permafrost-influencing factors and examined distribution features of each factor in permafrost regions and seasonally frozen ground regions. Then, using the Decision Tree method with the environmental factors, the 1 km resolution permafrost map over the QTP was obtained. The result shows higher accuracy compared to the previous published map of permafrost on the QTP and the map of the glaciers, frozen ground and deserts in China, which also demonstrates that making comprehensive use of remote sensing technology in permafrost mapping research is fast, macro and feasible. Furthermore, this result provides a simple and valid method for further permafrost research.
Reference Key
shi2018remotepermafrost Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Yaya Shi;Fujun Niu;Chengsong Yang;Tao Che;Zhanju Lin;Jing Luo
Journal Journal of pharmacological sciences
Year 2018
DOI
10.3390/rs10020309
URL
http://www.mdpi.com/2072-4292/10/2/309
Keywords
remote sensing permafrost distribution

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.