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- 10747392 type article assertion.
- 10747392 type FAIRDigitalObject assertion.
- 10747392 comment "The freeze-thaw cycle of near-surface soils significantly affects energy and water exchanges between the atmosphere and land surface. Passive microwave remote sensing is commonly used to observe the freeze-thaw state. However, existing algorithms face challenges in accurately monitoring near-surface soil freeze/thaw in alpine zones. This article proposes a framework for enhancing freeze/thaw detection capability in alpine zones, focusing on band combination selection and parameterization. The proposed framework was tested in the three river source region (TRSR) of the Qinghai-Tibetan Plateau. Results indicate that the framework effectively monitors the freeze/thaw state, identifying horizontal polarization brightness temperature at 18.7 GHz (TB18.7H) and 23.8 GHz (TB23.8H) as the optimal band combinations for freeze/thaw discrimination in the TRSR. The framework enhances the accuracy of the freeze/thaw discrimination for both 0 and 5-cm soil depths. In particular, the monitoring accuracy for 0-cm soil shows a more significant improvement, with an overall discrimination accuracy of 90.02%, and discrimination accuracies of 93.52% for frozen soil and 84.68% for thawed soil, respectively. Furthermore, the framework outperformed traditional methods in monitoring the freeze-thaw cycle, reducing root mean square errors for the number of freezing days, initial freezing date, and thawing date by 16.75, 6.35, and 12.56 days, respectively. The estimated frozen days correlate well with both the permafrost distribution map and the annual mean ground temperature distribution map. This study offers a practical solution for monitoring the freeze/thaw cycle in alpine zones, providing crucial technical support for studies on regional climate change and land surface processes. The findings show that the use of satellite microwave signals at 18.7 GHz and 23.8 GHz provides highly accurate tracking of ground freezing and thawing in mountain regions. This method reaches 90% accuracy at the soil surface and identifies seasonal changes much more reliably than older tools. These precise measurements help track how environmental changes affect water and land in cold, high-altitude climates." assertion.
- 10747392 creator 0000-0001-5419-8735 assertion.
- 10747392 creator 0000-0002-0611-1364 assertion.
- 10747392 creator 0000-0002-2480-9774 assertion.
- 10747392 creator 0000-0002-4135-7634 assertion.
- 10747392 creator 0000-0002-9506-5311 assertion.
- 10747392 creator 0000-0003-0438-9124 assertion.
- 10747392 subject c_331559 assertion.
- 10747392 language en assertion.
- 10747392 publisher 03ttqt747 assertion.
- 10747392 startDate "2023-08-01" assertion.
- 10747392 endDate "2024-11-08" assertion.
- 10747392 hasMetadata RAQKvNcrwTdNEghRkA70GwLnTHlEinTGFnSDhYkWbScSc assertion.
- 10747392 contactPoint "xzhou@mtech.edu" assertion.