Modellazione della temperatura del suolo in ambienti montani

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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.

Spatial variations in ground surface temperature at various scales on the northeastern Qinghai-Tibet Plateau, China
Șerban R D, Bertoldi G, Jin H, Șerban M, Luo D, Li X (2023)
Articolo su rivista

Ulteriori informazioni: https://www.sciencedirect.com/science/article/pii/S034181622 ...


Changes in hydrological processes in the headwater area of Yellow River, China during 1956–2019 under the influences of climate change, permafrost thaw and dam
Ma Q, Jin H, Wu Q, Yurova A, Liang S, Serban RD, Lan Y (2023)
Articolo su rivista
Advances in Climate Change Research

Ulteriori informazioni: https://www.sciencedirect.com/science/article/pii/S167492782 ...


Impacts of National Highway G214 on Vegetation in the Source Area of Yellow and Yangtze Rivers on the Southern Qinghai Plateau, West China
Jin X, Tang J, Luo, Wang Q, He R, Serban RD, Li Y, Serban M, Li X, Wang H, Li X, Wang W, Wu Q, Jin H (2023)
Articolo su rivista
Remote Sensing

Ulteriori informazioni: https://www.mdpi.com/2072-4292/15/6/1547


Monitoring ground surface deformation of ice-wedge polygon areas in Saskylakh, NW Yakutia, using Interferometric Synthetic Aperture Radar (InSAR) and Google Earth Engine (GEE)
Wang W, Jin H, Zhang Z, Zhelezniak M, Spektor V, Șerban RD, Li A, Tumskoy V, Jin X, Yang S, Zhang S, Li X, Șerban M, Wu Q, Wen Y (2023)
Articolo su rivista
Remote Sensing

Ulteriori informazioni: https://www.mdpi.com/2072-4292/15/5/1335


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 R D, Yang S, Wang W (2023)
Articolo su rivista
GIScience & Remote Sensing

Ulteriori informazioni: https://www.tandfonline.com/doi/full/10.1080/15481603.2023.2 ...


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)
Articolo su rivista
Permafrost and Periglacial Processes

Ulteriori informazioni: https://onlinelibrary.wiley.com/doi/full/10.1002/ppp.2146


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

Project Team
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Raul David Serban

Raul David Serban

Vice Manager


1 - 4

Biodiversity Monitoring South Tyrol

Monitoraggio della Biodiversità in Alto Adige

Duration: - Funding: Internal funding EURAC (Project)

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