Mapping Frozen Ground in the Qilian Mountains in 2004–2019 Using Google Earth Engine Cloud Computing

The permafrost in the Qilian Mountains (QLMs), the northeastern margin of the Qinghai–Tibet Plateau, changed dramatically in the context of climate warming and increasing anthropogenic activities, which poses significant influences on the stability of the ecosystem, water resources, and greenhouse g...

Full description

Bibliographic Details
Published in:Remote Sensing
Main Authors: Yuan Qi, Shiwei Li, Youhua Ran, Hongwei Wang, Jichun Wu, Xihong Lian, Dongliang Luo
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2021
Subjects:
Online Access:https://doi.org/10.3390/rs13010149
id ftmdpi:oai:mdpi.com:/2072-4292/13/1/149/
record_format openpolar
spelling ftmdpi:oai:mdpi.com:/2072-4292/13/1/149/ 2023-08-20T03:59:07+02:00 Mapping Frozen Ground in the Qilian Mountains in 2004–2019 Using Google Earth Engine Cloud Computing Yuan Qi Shiwei Li Youhua Ran Hongwei Wang Jichun Wu Xihong Lian Dongliang Luo agris 2021-01-05 application/pdf https://doi.org/10.3390/rs13010149 EN eng Multidisciplinary Digital Publishing Institute Remote Sensing in Geology, Geomorphology and Hydrology https://dx.doi.org/10.3390/rs13010149 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 13; Issue 1; Pages: 149 Qilian mountains permafrost Stefan Equation TTOP model climate change Google Earth Engine Text 2021 ftmdpi https://doi.org/10.3390/rs13010149 2023-08-01T00:48:21Z The permafrost in the Qilian Mountains (QLMs), the northeastern margin of the Qinghai–Tibet Plateau, changed dramatically in the context of climate warming and increasing anthropogenic activities, which poses significant influences on the stability of the ecosystem, water resources, and greenhouse gas cycles. Yet, the characteristics of the frozen ground in the QLMs are largely unclear regarding the spatial distribution of active layer thickness (ALT), the maximum frozen soil depth (MFSD), and the temperature at the top of the permafrost or the bottom of the MFSD (TTOP). In this study, we simulated the dynamics of the ALT, TTOP, and MFSD in the QLMs in 2004–2019 in the Google Earth Engine (GEE) platform. The widely-adopted Stefan Equation and TTOP model were modified to integrate with the moderate-resolution imaging spectroradiometer (MODIS) land surface temperature (LST) in GEE. The N-factors, the ratio of near-surface air to ground surface freezing and thawing indices, were assigned to the freezing and thawing indices derived with MODIS LST in considerations of the fractional vegetation cover derived from MODIS normalized difference vegetation index (NDVI). The results showed that the GEE platform and remote sensing imagery stored in Google cloud could be quickly and effectively applied to obtain the spatial and temporal variation of permafrost distribution. The area with TTOP < 0 °C is 8.4 × 104 km2 (excluding glaciers and lakes) and accounts for 46.6% of the whole QLMs, the regional mean ALT is 2.43 ± 0.44 m, while the regional mean MFSD is 2.54 ± 0.45 m. The TTOP and ALT increase with the decrease of elevation from the sources of the sub-watersheds to middle and lower reaches. There is a strong correlation between TTOP and elevation (slope = −1.76 °C km−1, p < 0.001). During 2004–2019, the area of permafrost decreased by 20% at an average rate of 0.074 × 104 km2·yr−1. The regional mean MFSD decreased by 0.1 m at a rate of 0.63 cm·yr−1, while the regional mean ALT showed an exception of a decreasing ... Text Active layer thickness permafrost MDPI Open Access Publishing Remote Sensing 13 1 149
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic Qilian mountains
permafrost
Stefan Equation
TTOP model
climate change
Google Earth Engine
spellingShingle Qilian mountains
permafrost
Stefan Equation
TTOP model
climate change
Google Earth Engine
Yuan Qi
Shiwei Li
Youhua Ran
Hongwei Wang
Jichun Wu
Xihong Lian
Dongliang Luo
Mapping Frozen Ground in the Qilian Mountains in 2004–2019 Using Google Earth Engine Cloud Computing
topic_facet Qilian mountains
permafrost
Stefan Equation
TTOP model
climate change
Google Earth Engine
description The permafrost in the Qilian Mountains (QLMs), the northeastern margin of the Qinghai–Tibet Plateau, changed dramatically in the context of climate warming and increasing anthropogenic activities, which poses significant influences on the stability of the ecosystem, water resources, and greenhouse gas cycles. Yet, the characteristics of the frozen ground in the QLMs are largely unclear regarding the spatial distribution of active layer thickness (ALT), the maximum frozen soil depth (MFSD), and the temperature at the top of the permafrost or the bottom of the MFSD (TTOP). In this study, we simulated the dynamics of the ALT, TTOP, and MFSD in the QLMs in 2004–2019 in the Google Earth Engine (GEE) platform. The widely-adopted Stefan Equation and TTOP model were modified to integrate with the moderate-resolution imaging spectroradiometer (MODIS) land surface temperature (LST) in GEE. The N-factors, the ratio of near-surface air to ground surface freezing and thawing indices, were assigned to the freezing and thawing indices derived with MODIS LST in considerations of the fractional vegetation cover derived from MODIS normalized difference vegetation index (NDVI). The results showed that the GEE platform and remote sensing imagery stored in Google cloud could be quickly and effectively applied to obtain the spatial and temporal variation of permafrost distribution. The area with TTOP < 0 °C is 8.4 × 104 km2 (excluding glaciers and lakes) and accounts for 46.6% of the whole QLMs, the regional mean ALT is 2.43 ± 0.44 m, while the regional mean MFSD is 2.54 ± 0.45 m. The TTOP and ALT increase with the decrease of elevation from the sources of the sub-watersheds to middle and lower reaches. There is a strong correlation between TTOP and elevation (slope = −1.76 °C km−1, p < 0.001). During 2004–2019, the area of permafrost decreased by 20% at an average rate of 0.074 × 104 km2·yr−1. The regional mean MFSD decreased by 0.1 m at a rate of 0.63 cm·yr−1, while the regional mean ALT showed an exception of a decreasing ...
format Text
author Yuan Qi
Shiwei Li
Youhua Ran
Hongwei Wang
Jichun Wu
Xihong Lian
Dongliang Luo
author_facet Yuan Qi
Shiwei Li
Youhua Ran
Hongwei Wang
Jichun Wu
Xihong Lian
Dongliang Luo
author_sort Yuan Qi
title Mapping Frozen Ground in the Qilian Mountains in 2004–2019 Using Google Earth Engine Cloud Computing
title_short Mapping Frozen Ground in the Qilian Mountains in 2004–2019 Using Google Earth Engine Cloud Computing
title_full Mapping Frozen Ground in the Qilian Mountains in 2004–2019 Using Google Earth Engine Cloud Computing
title_fullStr Mapping Frozen Ground in the Qilian Mountains in 2004–2019 Using Google Earth Engine Cloud Computing
title_full_unstemmed Mapping Frozen Ground in the Qilian Mountains in 2004–2019 Using Google Earth Engine Cloud Computing
title_sort mapping frozen ground in the qilian mountains in 2004–2019 using google earth engine cloud computing
publisher Multidisciplinary Digital Publishing Institute
publishDate 2021
url https://doi.org/10.3390/rs13010149
op_coverage agris
genre Active layer thickness
permafrost
genre_facet Active layer thickness
permafrost
op_source Remote Sensing; Volume 13; Issue 1; Pages: 149
op_relation Remote Sensing in Geology, Geomorphology and Hydrology
https://dx.doi.org/10.3390/rs13010149
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/rs13010149
container_title Remote Sensing
container_volume 13
container_issue 1
container_start_page 149
_version_ 1774715257338462208