A novel approach to retrieving the surface soil freeze/thaw state in the Qinghai-Tibetan Plateau using the seasonality of CYGNSS time series
Soil freeze–thaw (F/T) processes are a typical physical phenomenon on the Qinghai-Tibetan Plateau (QTP), significantly impacting regional climate change and the hydrological cycle. This study presents a Seasonal-Trend Decomposition using Loess and Long Short-Term Memory (STL-LSTM) method to detect s...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
|
| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843225000755 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Soil freeze–thaw (F/T) processes are a typical physical phenomenon on the Qinghai-Tibetan Plateau (QTP), significantly impacting regional climate change and the hydrological cycle. This study presents a Seasonal-Trend Decomposition using Loess and Long Short-Term Memory (STL-LSTM) method to detect spatiotemporal variations in soil F/T on the QTP using time series data from the Cyclone Global Navigation Satellite System (CYGNSS). The model was validated against ERA5 soil temperature data (0–7 cm) and independent in-situ observations, demonstrating good consistency. The SHapley Additive exPlanations (SHAP) model was integrated into the STL-LSTM framework to quantitatively evaluate the contributions of input features to F/T retrieval, revealing that time features contributes the most to retrieval results, followed by surface reflectivity. Moreover, spatiotemporal analysis of QTP F/T dynamics shows prominent seasonal patterns, with topography-induced shielding delaying thawing in central QTP regions and freezing trends extending from low (28°N) to high latitudes (36°N). The proposed method offers a new pathway for monitoring freeze–thaw transitions in high-latitude regions and holds potential for expansion into future high-frequency and multi-polarization GNSS-R missions. |
|---|---|
| ISSN: | 1569-8432 |