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  • MDPI AG  (14)
  • 1
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    Spatiotemporal Patterns and Regional Differences in Soil Thermal Conductivity on the Qinghai–Tibet Plateau
    MDPI AG ; 2023
    In:  Remote Sensing Vol. 15, No. 4 ( 2023-02-20), p. 1168-
    Details
    In: Remote Sensing, MDPI AG, Vol. 15, No. 4 ( 2023-02-20), p. 1168-
    Abstract: The Qinghai–Tibet Plateau is an area known to be sensitive to global climate change, and the problems caused by permafrost degradation in the context of climate warming potentially have far-reaching effects on regional hydrogeological processes, ecosystem functions, and engineering safety. Soil thermal conductivity (STC) is a key input parameter for temperature and surface energy simulations of the permafrost active layer. Therefore, understanding the spatial distribution patterns and variation characteristics of STC is important for accurate simulation and future predictions of permafrost on the Qinghai–Tibet Plateau. However, no systematic research has been conducted on this topic. In this study, based on a dataset of 2972 STC measurements, we simulated the spatial distribution patterns and spatiotemporal variation of STC in the shallow layer (5 cm) of the Qinghai–Tibet Plateau and the permafrost area using a machine learning model. The monthly analysis results showed that the STC was high from May to August and low from January to April and from September to December. In addition, the mean STC in the permafrost region of the Qinghai–Tibet Plateau was higher during the thawing period than during the freezing period, while the STC in the eastern and southeastern regions is generally higher than that in the western and northwestern regions. From 2005 to 2018, the difference between the STC in the permafrost region during the thawing and freezing periods gradually decreased, with a slight difference in the western hinterland region and a large difference in the eastern region. In areas with specific landforms such as basins and mountainous areas, the changes in the STC during the thawing and freezing periods were different or even opposite. The STC of alpine meadow was found to be most sensitive to the changes during the thawing and freezing periods within the permafrost zone, while the STC for bare land, alpine desert, and alpine swamp meadow decreased overall between 2005 and 2018. The results of this study provide important baseline data for the subsequent analysis and simulation of the permafrost on the Qinghai–Tibet Plateau.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs15041168
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2513863-7
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  • 2
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    Research Progress in the Field of Peatlands in 1990–2022: A Systematic Analysis Based on Bibliometrics
    MDPI AG ; 2024
    In:  Land Vol. 13, No. 4 ( 2024-04-19), p. 549-
    Details
    In: Land, MDPI AG, Vol. 13, No. 4 ( 2024-04-19), p. 549-
    Abstract: Peatlands are major natural carbon pool in terrestrial ecosystems globally and are essential to a variety of fields, including global ecology, hydrology, and ecosystem services. Under the context of climate change, the management and conservation of peatlands has become a topic of international concern. Nevertheless, few studies have yet systematized the overall international dynamics of existing peatland research. In this study, based on an approach integrating bibliometrics and a literature review, we systematically analyzed peatland research from a literature perspective. Alongside traditional bibliometric analyses (e.g., number of publications, research impact, and hot areas), recent top keywords in peatland research were found, including ‘oil palm’, ‘tropical peatland’, ‘permafrost’, and so on. Furthermore, six hot topics of peatland research were identified: (1) peatland development and the impacts and degradations, (2) the history of peatland development and factors of formation, (3) chemical element contaminants in peatlands, (4) tropical peatlands, (5) peat adsorption and its humic acids, and (6) the influence of peatland conservation on the ecosystem. In addition, this review found that the adverse consequences of peatland degradation in the context of climate change merit greater attention, that peatland-mapping techniques suitable for all regions are lacking, that a unified global assessment of carbon stocks in peatlands urgently needs to be established, spanning all countries, and that a reliable system for assessing peatland-ecosystem services needs to be implemented expeditiously. In this study, we argued that enhanced integration in research will bridge knowledge gaps and facilitate the systematic synthesis of peatlands as complex systems, which is an imperative need.
    Type of Medium: Online Resource
    ISSN: 2073-445X
    URL: Article
    DOI: 10.3390/land13040549
    Language: English
    Publisher: MDPI AG
    Publication Date: 2024
    detail.hit.zdb_id: 2682955-1
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  • 3
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    Vegetation Mapping in the Permafrost Region: A Case Study on the Central Qinghai-Tibet Plateau
    MDPI AG ; 2022
    In:  Remote Sensing Vol. 14, No. 1 ( 2022-01-05), p. 232-
    Details
    In: Remote Sensing, MDPI AG, Vol. 14, No. 1 ( 2022-01-05), p. 232-
    Abstract: An accurate and detailed vegetation map is of crucial significance for understanding the spatial heterogeneity of subsurfaces, which can help to characterize the thermal state of permafrost. The absence of an alpine swamp meadow (ASM) type, or an insufficient resolution (usually km-level) to capture the spatial distribution of the ASM, greatly limits the availability of existing vegetation maps in permafrost modeling of the Qinghai-Tibet Plateau (QTP). This study generated a map of the vegetation type at a spatial resolution of 30 m on the central QTP. The random forest (RF) classification approach was employed to map the vegetation based on 319 ground-truth samples, combined with a set of input variables derived from the visible, infrared, and thermal Landsat-8 images. Validation using a train-test split (i.e., 70% of the samples were randomly selected to train the RF model, while the remaining 30% were used for validation and a total of 1000 runs) showed that the average overall accuracy and Kappa coefficient of the RF approach were 0.78 (0.68–0.85) and 0.69 (0.64–0.74), respectively. The confusion matrix showed that the overall accuracy and Kappa coefficient of the predicted vegetation map reached 0.848 (0.844–0.852) and 0.790 (0.785–0.796), respectively. The user accuracies for the ASM, alpine meadow, alpine steppe, and alpine desert were 95.0%, 83.3%, 82.4%, and 86.7%, respectively. The most important variables for vegetation type prediction were two vegetation indices, i.e., NDVI and EVI. The surface reflectance of visible and shortwave infrared bands showed a secondary contribution, and the brightness temperature and the surface temperature of the thermal infrared bands showed little contribution. The dominant vegetation in the study area is alpine steppe and alpine desert. The results of this study can provide an accurate and detailed vegetation map, especially for the distribution of the ASM, which can help to improve further permafrost studies.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs14010232
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
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  • 4
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    Spatial–Temporal and Driving Factors of Land Use/Cover Change in Mongolia from 1990 to 2021
    MDPI AG ; 2023
    In:  Remote Sensing Vol. 15, No. 7 ( 2023-03-29), p. 1813-
    Details
    In: Remote Sensing, MDPI AG, Vol. 15, No. 7 ( 2023-03-29), p. 1813-
    Abstract: During the past several decades, desertification and land degradation have become more and more serious in Mongolia. The drivers of land use/cover change (LUCC), such as population dynamics and climate change, are increasingly important to local sustainability studies. They can only be properly analyzed at small scales that capture the socio-economic conditions. Several studies have been carried out to examine the pattern of LUCC in Mongolia, but they have been focused on changes in single land types at a local scale. Although some of them were carried out at the national scale, the data interval is more than 10 years. A small-scale and year-by-year dataset of LUCC in Mongolia is thus needed for comprehensive analyses. We obtained year-by-year land use/cover changes in Mongolia from 1990 to 2021 using Landsat TM/OLI data. First, we established a random forest (RF) model. Then, in order to improve the classification accuracy of the misclassification of cropland, grassland, and built and barren areas, the classification and regression trees model (CART) was introduced for post-processing. The results show that 17.6% of the land surface has changed at least once among the six land categories from 1990 to 2021. While the area of barren land has significantly increased, the grassland and forest areas have exhibited a decreasing trend in the past 32 years. The other land types do not show promising changes. To determine the driving factors of LUCC, we applied an RF feature importance ranking to environmental factors, physical factors, socioeconomic factors, and accessibility factors. The mean annual precipitation (MAP), evapotranspiration (ET), mean annual air temperature (MAAT), DEM, GDP, and distance to railway are the main driving factors that have determined the distribution and changes in land types. Interestingly, unlike the global anti-V-shaped pattern, we found that the land use/cover changes show an N-shaped trend in Mongolia. These characteristics of land use/cover change in Mongolia are primarily due to the agricultural policies and rapid urbanization. The results present comprehensive land use/cover change information for Mongolia, and they are of great significance for policy-makers to formulate a scientific sustainable development strategy and to alleviate the desertification of Mongolia.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs15071813
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
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  • 5
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    Evaluating the Impact of Soil Enthalpy upon the Thawing Process of the Active Layer in Permafrost Regions of the Qinghai–Tibet Plateau Using CLM5.0
    MDPI AG ; 2022
    In:  Remote Sensing Vol. 15, No. 1 ( 2022-12-31), p. 249-
    Details
    In: Remote Sensing, MDPI AG, Vol. 15, No. 1 ( 2022-12-31), p. 249-
    Abstract: The hydrothermal dynamics of the active layer is a key issue in the study of surface processes in permafrost regions. Even though the soil energy budget is controlled by thermal conduction and latent heat transfer, few studies have focused on their effects upon the active layer thickness (ALT). In the present study, the community land model (CLM) version 5.0 is used to simulate the soil temperature and moisture of the active layers at the Tanggula (TGL) and Beiluhe (BLH) stations in permafrost regions of the Qinghai–Tibet Plateau based on the theory of soil enthalpy in order to estimate the soil energy state and analyze the energy changes in the active layer during freezing and thawing. The results indicate that the soil enthalpy has significant seasonal variation characteristics, which accurately reflected the freezing and thawing processes of the active layer. The change in soil enthalpy is significantly related to the thawing depth of the active layer in TGL and BLH, and its changing process can be expressed as an exponential relationship. Near the surface, the variation of the energy due to temperature gradient and actual evaporation can also be expressed as an exponential relationship. The promoting effect of heat conduction on the ALT is greater than the inhibiting effect of latent heat transfer, with the energy contribution from the phase change accounting for about 20–40% of the energy due to the temperature gradient. The thawing depth increases by 14.16–18.62 cm as the energy due to the temperature gradient increases by 1 MJ/m2 and decreases by 2.75–7.16 cm as the energy due to the phase change increases by 1 MJ/m2. Thus, the present study quantifies the effects of soil energy upon the ALT and facilitates an understanding of the hydrothermal processes in soils in permafrost regions.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs15010249
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
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  • 6
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    Soil Texture and Its Relationship with Environmental Factors on the Qinghai–Tibet Plateau
    MDPI AG ; 2022
    In:  Remote Sensing Vol. 14, No. 15 ( 2022-08-06), p. 3797-
    Details
    In: Remote Sensing, MDPI AG, Vol. 14, No. 15 ( 2022-08-06), p. 3797-
    Abstract: Soil texture data are the basic input parameters for many Earth System Models. As the largest middle–low altitude permafrost regions on the planet, the land surface processes on the Qinghai–Tibet Plateau can affect regional and even global water and energy cycles. However, the spatial distribution of soil texture data on the plateau is largely unavailable due to the difficulty of obtaining field data. Based on collection data from field surveys and environmental factors, we predicted the spatial distribution of clay, silt, and sand contents at a 1 km resolution, from 0–5, 5–15, 15–30, 30–60, 60–100, and 100–200 cm soil depth layers. The random forest models were constructed to predict the soil texture according to the relationships between environmental factors and soil texture data. The results showed that the soil particles of the QTP are dominated by sand, which accounts for more than 70% of the total particles. As for the spatial distribution, silt and clay contents are high in the southeast plateau, and low values of silt and clay mainly appeared in the northwest plateau. Climate and NDVI values are the most important factors that affect the spatial distribution of soil texture on the QTP. The results of this study provide the soil texture data at different depths for the whole plateau at a spatial resolution of 1 km, and the dataset can be used as an input parameter for many Earth System Models.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs14153797
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
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  • 7
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    Evaluation of the Performance of CLM5.0 in Soil Hydrothermal Dynamics in Permafrost Regions on the Qinghai–Tibet Plateau
    MDPI AG ; 2022
    In:  Remote Sensing Vol. 14, No. 24 ( 2022-12-08), p. 6228-
    Details
    In: Remote Sensing, MDPI AG, Vol. 14, No. 24 ( 2022-12-08), p. 6228-
    Abstract: Soil hydrothermal dynamics are crucial processes for understanding the internal physical conditions of the active layer in permafrost regions. It is very difficult to obtain data in permafrost regions, especially on the Qinghai–Tibet Plateau (QTP). Land surface modes (LSMs) provide an effective tool for soil hydrothermal dynamics. However, it is necessary to evaluate the simulation performance before using them. Here, we used two in situ sites along with the latest version of the Community Land Model (CLM5.0) to evaluate the simulated performance in the soil hydrothermal parameters of the model in permafrost regions on the QTP. Meanwhile, the effects of soil properties, thermal roughness length, and the freeze–thaw process on the simulation results were investigated. The results showed that CLM5.0 can capture the dynamic changes in soil hydrothermal changes well in permafrost regions on the QTP. Soil moisture and thermal conductivity were more sensitive to soil properties and the freeze–thaw process, while the thermal roughness length had a greater effect on soil temperature. Notably, although we improved the soil properties and thermal roughness length, there were still some errors, especially in the soil moisture and soil thermal conductivity. It may be caused by inappropriate hydrothermal parameterizations of the model, especially the soil thermal conductivity, hydraulic conductivity, unfrozen water scheme, and snow schemes. There is an urgent need for collaboration between experts in permafrost science, hydrological science, and modelers to develop the appropriate schemes for permafrost regions and enhance the LSMs.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs14246228
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
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  • 8
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    The Impact of Permafrost Degradation on Lake Changes in the Endorheic Basin on the Qinghai–Tibet Plateau
    MDPI AG ; 2020
    In:  Water Vol. 12, No. 5 ( 2020-05-01), p. 1287-
    Details
    In: Water, MDPI AG, Vol. 12, No. 5 ( 2020-05-01), p. 1287-
    Abstract: Lakes on the Qinghai–Tibetan Plateau (QTP) have experienced significant changes, especially the prevailing lake expansion since 2000 in the endorheic basin. The influence of permafrost thawing on lake expansion is significant but rarely considered in previous studies. In this study, based on Landsat images and permafrost field data, the spatial-temporal area changes of lakes of more than 5 km2 in the endorheic basin on the QTP during 2000–2017 is examined and the impact of permafrost degradation on lake expansion is discussed. The main results are that permafrost characteristics and its degradation trend have close relationships with lake changes. Lake expansion in the endorheic basin showed a southwest–northeast transition from shrinking to stable to rapidly expanding, which corresponded well with the permafrost distribution from island-discontinuous to seasonally frozen ground to continuous permafrost. A dramatic lake expansion in continuous permafrost showed significant spatial differences; lakes expanded significantly in northern and eastern continuous permafrost with a higher ground ice content but slightly in southern continuous permafrost with a lower ground ice content. This spatial pattern was mainly attributed to the melting of ground ice in shallow permafrost associated with accelerating permafrost degradation. Whereas, some lakes in the southern zones of island-discontinuous permafrost were shrinking, which was mainly because the extended taliks arising from the intensified permafrost degradation have facilitated surface water and suprapermafrost groundwater discharge to subpermafrost groundwater and thereby drained the lakes. Based on observation and simulated data, the melting of ground ice at shallow depths below the permafrost table accounted for 21.2% of the increase in lake volume from 2000 to 2016.
    Type of Medium: Online Resource
    ISSN: 2073-4441
    URL: Article
    DOI: 10.3390/w12051287
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2521238-2
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  • 9
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    Activity and Kinematics of Two Adjacent Freeze–Thaw-Related Landslides Revealed by Multisource Remote Sensing of Qilian Mountain
    MDPI AG ; 2022
    In:  Remote Sensing Vol. 14, No. 19 ( 2022-10-10), p. 5059-
    Details
    In: Remote Sensing, MDPI AG, Vol. 14, No. 19 ( 2022-10-10), p. 5059-
    Abstract: The increase in temperatures and changing precipitation patterns resulting from climate change are accelerating the occurrence and development of landslides in cold regions, especially in permafrost environments. Although the boundary regions between permafrost and seasonally frozen ground are very sensitive to climate warming, slope failures and their kinematics remain barely characterized or understood in these regions. Here, we apply multisource remote sensing and field investigation to study the activity and kinematics of two adjacent landslides (hereafter referred to as “twin landslides”) along the Datong River in the Qilian Mountains of the Qinghai-Tibet Plateau. After failure, there is no obvious change in the area corresponding to the twin landslides. Based on InSAR measurements derived from ALOS PALSAR-1 and -2, we observe significant downslope movements of up to 15 mm/day within the twin landslides and up to 5 mm/day in their surrounding slopes. We show that the downslope movements exhibit distinct seasonality; during the late thaw and early freeze season, a mean velocity of about 4 mm/day is observed, while during the late freeze and early thaw season the downslope velocity is nearly inactive. The pronounced seasonality of downslope movements during both pre- and post-failure stages suggest that the occurrence and development of the twin landslide are strongly influenced by freeze–thaw processes. Based on meteorological data, we infer that the occurrence of twin landslides are related to extensive precipitation and warm winters. Based on risk assessment, InSAR measurements, and field investigation, we infer that new slope failure or collapse may occur in the near future, which will probably block the Datong River and cause catastrophic disasters. Our study provides new insight into the failure mechanisms of slopes at the boundaries of permafrost and seasonally frozen ground.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs14195059
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
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  • 10
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    Assessment of Different Complementary-Relationship-Based Models for Estimating Actual Terrestrial Evapotranspiration in the Frozen Ground Regions of the Qinghai-Tibet Plateau
    MDPI AG ; 2022
    In:  Remote Sensing Vol. 14, No. 9 ( 2022-04-25), p. 2047-
    Details
    In: Remote Sensing, MDPI AG, Vol. 14, No. 9 ( 2022-04-25), p. 2047-
    Abstract: Actual evapotranspiration (ETa) is important since it is an important link to water, energy, and carbon cycles. Approximately 96% of the Qinghai-Tibet Plateau (QTP) is underlain by frozen ground, however, the ground observations of ETa are particularly sparse–which is especially true in the permafrost regions–leading to great challenge for the accurate estimation of ETa. Due to the impacts of freeze-thaw cycles and permafrost degradation on the regional ET process, it is therefore urgent and important to find a reasonable approach for ETa estimation in the regions. The complementary relationship (CR) approach is a potential method since it needs only routine meteorological variables to estimate ETa. The CR approach, including the modified advection-aridity model by Kahler (K2006), polynomial generalized complementary function by Brutsaert (B2015) and its improved versions by Szilagyi (S2017) and Crago (C2018), and sigmoid generalized complementary function by Han (H2018) in the present study, were assessed against in situ measured ETa at four observation sites in the frozen ground regions. The results indicate that five CR-based models are generally capable of simulating variations in ETa, whether default and calibrated parameter values are employed during the warm season compared with those of the cold season. On a daily basis, the C2018 model performed better than other CR-based models, as indicated by the highest Nash-Sutcliffe efficiency (NSE) and lowest root mean square error (RMSE) values at each site. On a monthly basis, no model uniformly performed best in a specific month. On an annual basis, CR-based models estimating ETa with biases ranging from −94.2 to 28.3 mm year−1, and the H2018 model overall performed best with the smallest bias within 15 mm year−1. Parameter sensitivity analysis demonstrated the relatively small influence of each parameter varying within regular fluctuation magnitude on the accuracy of the corresponding model.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs14092047
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
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