Modelling ground surface TEMPerature LINKed to remote sensing land surface temperature in mountain environments
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.
Șerban R D, Bertoldi G, Jin H, Șerban M, Luo D, Li X (2023)
More information: https://www.sciencedirect.com/science/article/pii/S034181622 ...
Ma Q, Jin H, Wu Q, Yurova A, Liang S, Serban RD, Lan Y (2023)
Advances in Climate Change Research
More information: https://www.sciencedirect.com/science/article/pii/S167492782 ...
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)
More information: https://www.mdpi.com/2072-4292/15/6/1547
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)
More information: https://www.mdpi.com/2072-4292/15/5/1335
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)
GIScience & Remote Sensing
More information: https://www.tandfonline.com/doi/full/10.1080/15481603.2023.2 ...
Wang Q, Jin H, Wu Q, Zhang T, Yuan Z, Li X, Ming J, Yang C, Serban RD, Huang Y (2022)
Permafrost and Periglacial Processes
More information: https://onlinelibrary.wiley.com/doi/full/10.1002/ppp.2146
State Key Laboratory of Frozen Soils Engineering, Northwest Institute of Eco-Environment and ...
School of Civil Engineering and Permafrost Institute, Northeast Forestry University
Biodiversity Monitoring South Tyrol
Biodiversity Monitoring South TyrolDuration: - Funding: Internal funding EURAC (Project)
LT(S)ER: Open air laboratory Matsch/Mazia
Long-term (socio-)ecological research in the open air laboratory Matsch/MaziaDuration: - Funding: Public institutions (Other projects ...
Effects of air pressure on upwards shifting alpine ecosystemsDuration: - Funding: Provincial Joint Programme – IT-FWF ...
REINFORCE: Integrated landscape management for resilient mountain forests under global changesDuration: - Funding: Excellence Science (Horizon 2020 ...