Modelling ground surface TEMPerature LINKed to remote sensing land surface temperature in mountain environments

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Ground surface temperature (GST), measured at 5 cm into the ground, is a key parameter controlling all the subsurface biophysical processes at the complex land-atmosphere interaction. GST is important for multiple geosciences and agricultural applications, being essential for understanding the climate change impacts on various environments. Due to the high heterogeneity of land surfaces, it remains a challenge to monitor the GST small-scale variability over large areas. MODerate resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) product provides the global daily temperature at the top of the surface cover at 1-km spatial resolution. However, the remote sensing LST cannot directly express the GST. This gap will address by exploiting the relationship between GST and LST, and developing a data-based model to derive the GST from MODIS LST. An innovative multidisciplinary and interdisciplinary approach will be used by combining (i) remote sensing, (ii) thermo-hydrological dynamics, and (iii) cutting-edge numerical modelling (GEOtop model and machine learning algorithms). The model will simplify and improve the spatiotemporal observations of the soil subsurface temperature with a significant socio-economic benefit for a broad set of end users (e.g. policy makers, farmers, scientists). The model will be developed at a local scale (Mazia Valley, Italian Alps) and applied at a regional scale (Qinghai-Tibet Plateau - QTP) to test its worldwide applicability. The host provides the research infrastructure (computational power), the necessary data (in-situ GST and MODIS LST), and expertise in numerical modelling for developing and validating the model.

Collected observation will contribute to the International Long Term Ecological Research (ILTER) and soil and near-surface temperature (SoilTemp) monitoring networks.

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Impacts of National Highway G214 on Vegetation in the Source Area of Yellow and Yangtze Rivers on the Southern Qinghai Plateau, West China
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Changes in carbon stock in the Xing’an permafrost regions in Northeast China from the late 1980s to 2020
Wang H, Jin H, Li X, Zhou L, Qi Y, Huang C, He R, Zhang J, Yang R, Luo D, Șerban RD, Yang S, Wang W (2023)
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Spatial variations in ground surface temperature at various scales on the northeastern Qinghai-Tibet Plateau, China
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Șerban RD, Șerban M, Bertoldi G (2023)

Conference: 21th Congress of the International Union for Quaternary Research | Rome | 14.7.2023 - 20.7.2023

Assessing the simulation of ground surface temperature with the physical model GEOtop
Șerban RD, Bertoldi G (2023)

Conference: 6th European Conference on Permafrost | Puigcerdà | 18.6.2023 - 22.6.2023

Evaluation of ground surface deformation in discontinuous permafrost regions along the China-Russia Crude Oil Pipelines in Northeast China using InSAR and ground surveys
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Șerban RD, Șerban M (2023)

Conference: EGU23 General Assembly | Vienna | 23.4.2023 - 28.4.2023

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Serban RD, Bertoldi G, Jin H, Șerban M (2023)

Conference: European Young Geomorphologists Meeting | Chamonix-Courmayeur | 9.6.2023 - 11.6.2023

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The vertical distribution of soil organic carbon and nitrogen in a permafrost-affected wetland on the Qinghai–Tibet Plateau: Implications for Holocene development and environmental change
Wang Q, Jin H, Wu Q, Zhang T, Yuan Z, Li X, Ming J, Yang C, Serban RD, Huang Y (2022)
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Ground surface temperature variation across scales on northeastern Qinghai-Tibet Plateau
Șerban RD, Bertoldi G, Jin H, Șerban M (2022)

Conference: 10th International Conference on Geomorphology | Coimbra | 12.9.2022 - 16.9.2022

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Conference: International Symposium on Ice, Snow and Water in a Warming World | Reykjavík | 21.8.2023 - 26.8.2023

Our partners
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  • State Key Laboratory of Frozen Soils Engineering, Northwest Institute of Eco-Environment and ...

  • School of Civil Engineering and Permafrost Institute, Northeast Forestry University