Monitoring the Spatiotemporal Difference in Glacier Elevation on Bogda Mountain from 2000 to 2017

Du, Wentao; Shi, Ningke; Xu, Linjuan; Shi-qiong, Zhang; Ma, Dandan; Wang, Shuangting

doi:10.3390/ijerph18126374

Cited by 6 publications

(4 citation statements)

References 40 publications

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“…After analyzing parameters such as the relative incident angle of the InSAR satellite, and excluding areas with small or large incident angles, the monitoring accuracy of GSE can be better improved. Removing the special topography of the glacier area that has a large error with the SAR signal, for example, removing the area with a slope greater than 50 • in the glacier area, the results obtained are in good agreement with the GMB obtained by in situ measurements [25,26].…”

Section: Introductionsupporting

confidence: 68%

“…The terrain of alpine glaciers is complex and affected by the special imaging mechanism of radar side-looking imaging. It is easy to cause geometric distortions, such as perspective shrinkage, overlap, and shadow on the image, which will seriously affect the accuracy of Interferometry SAR (InSAR) results [25]. In the process of obtaining the DEM using InSAR, coherence is an important indicator for evaluating the interference results.…”

Section: Introductionmentioning

confidence: 99%

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Recent Seasonal Spatiotemporal Variations in Alpine Glacier Surface Elevation in the Pamir

Zheng

et al. 2022

Remote Sensing

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Climate change can lead to seasonal surface elevation variations in alpine glaciers. This study first uses DEM (Digital Elevation Model) of Pamir glaciers to develop a denoising model for laser altimetry of ICESat-2 footprints, which reduces the standard deviation of the differences between ICESat-2 footprints and corresponding datum DEM from 13.9 to 3.6 m. Second, the study constructs a calibration processing model for solving the problem that laser footprints obtained at different times have inconsistent plane positions. We calculates plane position and elevation differences between the two laser footprints in the local area of 0.05 × 0.05° from 2018 to 2021. The elevations constructed by laser footprints shows a strong correlation with the datum elevation over the different periods, and effectively preserve the time-series variation information of glacier surface elevation (GSE). Based on these two models, the spatiotemporal variations of the surface elevation of the Pamir glaciers is established as a function of seasons. There are three main conclusions: (1) The GSE in the Pamir increased slightly from 2018 to 2021 at an average rate of +0.02 ± 0.01 m/year. The time series with elevation increase was located exactly on the glacial ablation zone, and the time series with elevation decrease occurred on the glacial accumulation zone. Both observations demonstrate the surge state of the glacier. (2) The Pamir eastern (Zone I) and northwestern (Zone III) regions had large glacier accumulation areas. GSE in these two regions has increased in recent years at yearly rates of +0.25 ± 0.13 and +0.06 ± 0.04 m/year, respectively. In contrast, the GSE of small glaciers in Zones II and IV has decreased at a yearly rate of −0.96 ± 0.37 and −0.24 ± 0.18 m/year, respectively. Climate was the primary factor influencing the increase in GSE in Zones I and III. The westerly circulation had been reinforced in recent years, and precipitation had increased dramatically at a rate of +0.99 mm/year in the northwestern section of the Pamir; this was the primary cause of the increase in GSE. (3) The increased precipitation and decreased temperature were both important factors causing an overall +0.02 ± 0.01 m/year variation of GSE in this region. The GSE in the four sub-regions showed different variation trends because of variations in temperature and precipitation. The external causes that affected the increase in GSE in the region included an average yearly temperature decrease at the rate of 0.54 ± 0.36 °C/year and a total yearly precipitation increase of 0.46 ± 0.29 mm/year in the study area from 2018 to 2021.

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Section: Introductionsupporting

confidence: 68%

Section: Introductionmentioning

confidence: 99%

Recent Seasonal Spatiotemporal Variations in Alpine Glacier Surface Elevation in the Pamir

Zheng

et al. 2022

Remote Sensing

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“…Previous research has indicated that climatic factors play a pivotal role in driving transformations in lakes located at mid and high elevations. These particular lakes demonstrate a greater susceptibility to temperature fluctuations than that demonstrated by lakes found at lower elevations [66][67][68]. By analyzing the correlation of glacial lakes at different altitudes with the temperature and precipitation in this area, our results show that there is clear evidence of a positive association between the number of glacial lakes and the temperature in the ranges from 3.2 km to 3.3 km, and from 3.4 km to 3.5 km above sea level.…”

Section: Response Of Glacial Lakes To Climate Changementioning

confidence: 86%

Spatio-Temporal Distribution Characteristics of Glacial Lakes in the Altai Mountains with Climate Change from 2000 to 2020

et al. 2023

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The evolution of a glacial lake is a true reflection of glacial and climatic change. Currently, the study of glacial lakes in the Altai Mountains is mainly concerned with the application of high-resolution remote sensing images to monitor and evaluate the potential hazards of glacial lakes. At present, there is no rapid and large-scale method to monitor the dynamical variation in glacial lakes in the Altai Mountains, and there is little research on predicting its future tendency. Based on the supervised classification results obtained by Google Earth Engine (GEE), combined with an analysis of meteorological data, we analyzed the spatial and temporal variations in glacial lakes in the Altai Mountains between 2000 and 2020, and used the MCE-CA-Markov model to predict their changes in the future. According to the results, as of 2020, there are 3824 glacial lakes in the Altai Mountains, with an area of 682.38 km2. Over the entire period, the glacial lake quantity growth rates and area were 47.82% and 17.07%, respectively. The distribution of glacial lakes in this region showed a larger concentration in the north than in the south. Most glacial lakes had areas smaller than 0.1 km2, and there was minimal change observed in glacial lakes larger than 0.2 km2. Analyzing the regional elevation in 100 m intervals, the study found that glacial lakes were predominantly distributed at elevations from 2000 m to 3000 m. Interannual rainfall and temperature fluctuations in the Altai Mountains have slowed since 2014, and the trends for the area and number of glacial lakes have stabilized. The growth of glacial lakes in both number and surface area is expected to continue through 2025 and 2030, although the pace of change will slow. In the context of small increases in precipitation and large increases in temperature, in the future, glacial lakes with faster surface area growth rates will be located primarily in the southern Altai Mountains.

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“…The alpine peaks southeast of Bogda were the high-value area, where permanent glaciers and snow are predominantly located. Glaciers are very sensitive to climate change, and climate change has caused a continued and accelerated retreat of Bogda glaciers in recent years [ 51 ]. With the accelerating rate of climate change, the LER in the Bogda alpine zone will likely continue to increase in the future.…”

Section: Discussionmentioning

confidence: 99%

Identification of Priority Conservation Areas for Natural Heritage Sites Integrating Landscape Ecological Risks and Ecosystem Services: A Case Study in the Bogda, China

Chen

Zheng

et al. 2022

IJERPH

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The conservation of World Natural Heritage Sites has become a global concern. The identification of priority conservation areas can preserve the value of heritage sites while promoting sustainable development, which is important for balancing the conservation and development of heritage sites. This paper proposes an integrated framework for the identification of priority conservation areas for natural heritage sites based on landscape ecological risks (LERs) and ecosystem services (ESs), taking the Bogda heritage site in Xinjiang, China as a case study. The innovative approach combined the natural and cultural elements of natural heritage sites and included the following steps: (1) the LER index, Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and questionnaire method were adopted to assess the LERs and ESs of Bogda heritage sites during 1990–2018; (2) ordered weighted averaging (OWA) was used to identify conservation priorities by weighing LERs and ESs; and (3) the optimal priority conservation area was determined by comparing the conservation efficiencies under different scenarios. The results revealed that the LER, carbon storage (CS), habitat quality (HQ), aesthetic value (AV), and recreational value (RV) showed significant spatiotemporal variation. The most suitable priority conservation area was located at the central forestlands and high-coverage grasslands, with conservation efficiencies of 1.16, 2.91, 1.96, 1.03, and 1.21 for LER, CS, HQ, AV, and RV, respectively. Our study demonstrated that integrating LERs and ESs is a comprehensive and effective approach to identifying conservation priorities for heritage sites. The results can provide decision support for the conservation of the Bogda heritage site and a methodological reference for identifying conservation priorities for natural heritage sites. Furthermore, this study is also an effective application of LERs and ESs in identifying priority conservation areas.

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Monitoring the Spatiotemporal Difference in Glacier Elevation on Bogda Mountain from 2000 to 2017

Cited by 6 publications

References 40 publications

Recent Seasonal Spatiotemporal Variations in Alpine Glacier Surface Elevation in the Pamir

Recent Seasonal Spatiotemporal Variations in Alpine Glacier Surface Elevation in the Pamir

Spatio-Temporal Distribution Characteristics of Glacial Lakes in the Altai Mountains with Climate Change from 2000 to 2020

Identification of Priority Conservation Areas for Natural Heritage Sites Integrating Landscape Ecological Risks and Ecosystem Services: A Case Study in the Bogda, China

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