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 vertical temperature distribution in the permanently shaded region (PSR) has a significant impact on the temporal and spatial distribution of the cold trap. To obtain the vertical temperature profile of the PSR, an inversion method that fuses microwave and infrared brightness temperature (TB) data is proposed. In the inversion process, the infrared data were initially used to derive the optimal value of the H-parameter that controls the density profile. Subsequently, high-frequency (37 and 19.35 GHz) microwave TB data were used to ascertain the range of surface density, whereas low-frequency (3 GHz) microwave TB data were used to determine the range of bottom density. A fixed correction was applied to the 3-GHz brightness temperature data to account for the calibration error. Due to the inherent uncertainties associated with the thermal model, both the Hayne and Woods' models were used in the inversion process, yielding disparate results. The PSR in the Haworth impact crater was selected as a case study for the inversion. The Woods' model was found to provide a superior explanation for the microwave observation. The optimal surface density of the PSR of the Haworth crater was determined to be within the range of 1200-1300 kg m(-3), while the bottom density was within the range of 2100-2200 kg m(-3). The inverted vertical temperature distribution in the PSR of Haworth crater indicates that the depth of the cold trap can reach approximately 8.5 m. In addition, the impact of heat flow on microwave TB is discussed.

Predicting soil behavior under dynamic load due to earthquakes is pivotal for engineering structures and human life. Due to various limitations, such as insufficient computers and difficulties in generating models, the third-dimension effect is generally neglected in many studies. Conversely, the third-dimension effect in regions with high topographic differences, deep basins, three-dimensional heterogeneous and anisotropic environments, and alluvium is at a level that cannot be neglected. This study created a three-dimensional model of the northwest of Turkey for the first time by including surface topography. Soil properties were added to this model, and dynamic analysis was performed. This new model aims to increase the accuracy of ground motion predictions in Northwest Turkey. The accuracy of this model was analyzed using real earthquake data recorded in the study area. In addition, a new software (SiteEffect3D) with various features has been developed to create a three-dimensional mesh with topography using digital elevation model data and to perform dynamic analysis more effectively. This software has been tested comparatively with Plaxis 3D software using synthetic terrain models. The importance of this study is that in addition to its contributions to site response analysis and seismic hazard assessment, new software has been developed that can be used in similar studies. The findings will provide valuable information for seismic design and construction practices and facilitate the development of more effective strategies to reduce the potential damage from earthquakes in the region.

Soil directional emissivity plays a crucial role in canopy thermal-infrared (TIR) emissivity modeling over sparsely vegetated solo slopes. To our knowledge, the canopy emissivity model explicitly considers soil emissivity directionality, and topography does not exist. This study proposes a new canopy emissivity model under the framework of the four-stream approximation theory employed in the well-known 4SAIL model by incorporating soil directional emissivity and topography. The new model was validated by the discrete anisotropic radiative transfer (DART) model. The new model-simulated canopy emissivity data exhibited excellent consistency with the DART simulation data, and the bias, root mean square error (RMSE), and determination coefficient ( R-2 ) were -0.001, 0.003, and 0.97, respectively, under the different leaf area indices (LAIs), slopes, and view zenith angles (VZAs). Sensitivity analysis revealed that LAI and soil nadir emissivity explained most of the variance, with total sensitivity indices of 52.9% and 30.3%, respectively. The effects of soil directional emissivity, topography, and leaf angle distribution (LAD) on canopy emissivity were subsequently investigated, and the results indicated that the differences could reach more than 0.02 when soil directional emissivity and/or topography were neglected; moreover, the influence of LAD functions is not significant. The model proposed in this article provides a practical method for modeling mountainous area canopy emissivity and can improve estimates of surface broadband emissivity (BBE) and land surface temperature (LST).

A microwave radiation model with coherent surface scattering is developed for analyzing the topographic effects of the lunar permanently shadowed region (PSR) on microwave radiometric observations. The coherent surface scattering to the observer, which comes from the nearby surface due to the variation in the surface slope, is quantified by the ray-tracing method. In addition, the vertical distribution of temperatures of the PSR is estimated by a 1-D thermal model with 3-D shading and scattering effects. The impact of coherent scattering on microwave brightness temperatures (TBs) by a nadir-look radiometer becomes more noticeable with high-resolution microwave TB data, such as 4 pix/degrees by 4 pix/degrees in this study. The rise in TB at certain locations in PSR may reach up to similar to 8 K at 37 GHz. However, when compared with the low resolution of the TB by Chang'E-2, the averaged contribution of coherent surface scattering is less than 1 K. Meanwhile, there is a discrepancy between the model-generated microwave TB and the measured TB of Chang'E-2, both in small and large craters. This discrepancy may be explained by a calibration issue or the uncertainty of model parameters. Nonetheless, the trend in the model-generated TB is consistent with the measurements, indicating that the proposed model has the potential to predict TB effectively within the PSR.

The shape, size, and abundance of rocks on the Moon's surface are essential for understanding impact cratering and weathering processes, interpreting remote sensing observations, and ensuring landing safety and rover trafficability. In most previous studies, rock information was extracted from optical images using visual identification or automatic detection methods. However, optical images cannot provide 3-D information on rocks and cannot be used in lunar permanently shadowed regions (PSRs), where rock information is critical to deciphering anomalously high radar echoes in water ice deposit detection. In this study, we proposed an automatic method for extracting 3-D information about rocks from topography data based on the geometry and clustering tendency of lunar surface rocks. A geometric shape model for lunar surface rocks is first developed by analyzing 3196 rocks in elevation data. In the proposed approach, rocks are detected from topography data using multiscale 2-D continuous wavelet transform (2-D CWT) and Hopkins statistic, and then a 3-D shape parameter extraction method is introduced to obtain the shape information directly from the detected irregular rock boundary by a region growing-based algorithm. To demonstrate the accuracy of the method, we applied the proposed method to both the simulated and real-topography data with various spatial resolutions and vertical uncertainties. The results show that, compared with the ground truth and manual detection results, the detection rate of rocks >4 pixels in size varies from 50% to 90%, depending mainly on the vertical uncertainty of elevation data. In addition, for the first time, we provide 3-D information on surface rocks (>10 m) in lunar PSRs from topography data. Our analyses suggest that, for future missions to the lunar PSRs (e.g., China's Chang'E-7), the vertical uncertainty of elevation data needs to be better than 0.2 m in order to accurately gather 3-D information of rocks larger than 2 m. Our method can be utilized for extracting 3-D information on rocks from topography data, selecting landing sites, and guiding instrument design for future altimeters.

Permanently shadowed regions (PSRs) at the lunar poles pique scientific interest on account of their cold trapping of volatiles that is highly relevant in the current scope of lunar exploration. Interiors of PSRs are largely unknown due to the challenging illumination conditions. In this letter, we describe a method for synthesizing images at PSRs based on the knowledge of incident solar illumination geometry and local topography that reflects light into PSRs.