Remote. Sens.Pub Date : 2024-02-22DOI: 10.3390/rs16050762
Xuanru Zhao, Jinquan Cheng, Weijin Guan, Yuxuan Zhang, Bo Cao
{"title":"The Expanding of Proglacial Lake Amplified the Frontal Ablation of Jiongpu Co Glacier since 1985","authors":"Xuanru Zhao, Jinquan Cheng, Weijin Guan, Yuxuan Zhang, Bo Cao","doi":"10.3390/rs16050762","DOIUrl":"https://doi.org/10.3390/rs16050762","url":null,"abstract":"In High Mountain Asia, most glaciers and glacial lakes have undergone rapid variations throughout changes in the climate. Unlike land-terminating glaciers, lake-terminating glaciers show rapid shrinkage due to dynamic interactions between proglacial lakes and glacier dynamics. In this study, we conducted a detailed analysis of the changes in the surface elevation, velocity, and especially frontal ablation on Jiongpu Co lake-terminating glacier. The results show that the Jiongpu Co glacier has twice as much negative mass balance compared to other glaciers, and the annual surface velocity has anomalously increased (3.6 m a−1 per decade) while other glaciers show a decreased trend. The frontal ablation fraction in the net mass loss of the Jiongpu Co glacier increased from 26% to 52% with the accelerated expansion of the proglacial lake. All available evidence indicates the presence of positive feedback between the proglacial lake and its host glacier. Our findings highlight the existence of proglacial lake affects the spatial change patterns of the lake-terminating glacier. Furthermore, the ongoing enlargement of the lake area amplifies the changes associated with the evolution of the lake-terminating glacier.","PeriodicalId":20944,"journal":{"name":"Remote. Sens.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140439753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Remote. Sens.Pub Date : 2024-02-22DOI: 10.3390/rs16050769
Jinbiao Zhu, Bei Lin, Jie Pan, Yao Cheng, Xiaolan Qiu, Wen Jiang, Yuquan Liu, Mingqian Liu
{"title":"Unmanned Airborne Bistatic Interferometric Synthetic Aperture Radar Data Processing Method Using Bi-Directional Synchronization Chain Signals","authors":"Jinbiao Zhu, Bei Lin, Jie Pan, Yao Cheng, Xiaolan Qiu, Wen Jiang, Yuquan Liu, Mingqian Liu","doi":"10.3390/rs16050769","DOIUrl":"https://doi.org/10.3390/rs16050769","url":null,"abstract":"The bistatic Interferometric Synthetic Aperture Radar (InSAR) system can overcome the physical limitations imposed by the baseline of monostatic dual-antenna InSAR. It provides greater flexibility and can enhance elevation measurement accuracy through a well-designed baseline configuration. Unmanned aerial vehicles (UAVs) equipped with bistatic InSAR, having relatively low cost and high flexibility, are useful for mapping and land resource exploration. However, due to challenges including spatiotemporal synchronization and motion errors, there are limited reports on UAV-borne bistatic InSAR. This paper proposes a comprehensive method for processing data from small UAV-borne bistatic InSAR by integrating two-way synchronization chain signals. The proposed method includes compensation for time and phase synchronization errors, trajectory refinement with synchronized chain and Position and Orientation System (POS) data, high-precision bistatic InSAR imaging, and interferometric processing. Height inversion results based on the proposed method are also provided, which demonstrate the effectiveness of the proposed method in improving the accuracy of interferometric measurement at calibration points from 0.66 m to 0.42 m.","PeriodicalId":20944,"journal":{"name":"Remote. Sens.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140439831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Remote. Sens.Pub Date : 2024-02-22DOI: 10.3390/rs16050761
Jialiang Hou, Jia Luo, Xiaohua Xu
{"title":"Influences of Different Factors on Gravity Wave Activity in the Lower Stratosphere of the Indian Region","authors":"Jialiang Hou, Jia Luo, Xiaohua Xu","doi":"10.3390/rs16050761","DOIUrl":"https://doi.org/10.3390/rs16050761","url":null,"abstract":"The gravity wave (GW) potential energy (Ep) in the lower stratosphere (LS) of the altitude range between 20 and 30 km over the Indian region (60°E–100°E, 0°–30°N) is retrieved using the dry temperature profiles from the Constellation Observing System for Meteorology Ionosphere and Climate-2 (COSMIC-2) radio occultation (RO) mission from December 2019 to November 2021. Through correlation analysis and dominance analysis (DA) methods, the impacts of multiple influencing factors on the local LS GW activity are quantified and compared. The results demonstrate that in the central and northern part of Indian region, the three factors, including the convective activity (using outgoing long-wave radiation as the proxy) mainly caused by the Indian summer monsoon, the mean zonal wind speed between 15 and 17 km, the height range where the maximum tropical easterly jet (TEJ) wind speed appears, and the mean zonal wind speed between 20 and 30 km, have the greatest impacts on the LS GW activity. In the southern part of the Indian Peninsula and over the Indian Ocean, the mean zonal wind shear between 20 and 30 km plays a dominant role in the LS GW activity, which is due to the fact that the GW energy can be attenuated by large background wind shears. It can be concluded that the LS GW activity in the Indian region is mainly influenced by the Indian summer monsoon, the TEJ, and the wind activity in the LS, while over different local areas, differences exist in which factors are the dominant ones.","PeriodicalId":20944,"journal":{"name":"Remote. Sens.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140438979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Remote. Sens.Pub Date : 2024-02-22DOI: 10.3390/rs16050750
S. R. Suwanlee, Dusadee Pinasu, J. Som-ard, E. Mondino, F. Sarvia
{"title":"Estimating Sugarcane Aboveground Biomass and Carbon Stock Using the Combined Time Series of Sentinel Data with Machine Learning Algorithms","authors":"S. R. Suwanlee, Dusadee Pinasu, J. Som-ard, E. Mondino, F. Sarvia","doi":"10.3390/rs16050750","DOIUrl":"https://doi.org/10.3390/rs16050750","url":null,"abstract":"Accurately mapping crop aboveground biomass (AGB) in a timely manner is crucial for promoting sustainable agricultural practices and effective climate change mitigation actions. To address this challenge, the integration of satellite-based Earth Observation (EO) data with advanced machine learning algorithms offers promising prospects to monitor land and crop phenology over time. However, achieving accurate AGB maps in small crop fields and complex landscapes is still an ongoing challenge. In this study, the AGB was estimated for small sugarcane fields (<1 ha) located in the Kumphawapi district of Udon Thani province, Thailand. Specifically, in order to explore, estimate, and map sugarcane AGB and carbon stock for the 2018 and 2021 years, ground measurements and time series of Sentinel-1 (S1) and Sentinel-2 (S2) data were used and random forest regression (RFR) and support vector regression (SVR) applied. Subsequently, optimized predictive models used to generate large-scale maps were adapted. The RFR models demonstrated high efficiency and consistency when compared to the SVR models for the two years considered. Specifically, the resulting AGB maps displayed noteworthy accuracy, with the coefficient of determination (R2) as 0.85 and 0.86 with a root mean square error (RMSE) of 8.84 and 9.61 t/ha for the years 2018 and 2021, respectively. In addition, mapping sugarcane AGB and carbon stock across a large scale showed high spatial variability within fields for both base years. These results exhibited a high potential for effectively depicting the spatial distribution of AGB densities. Finally, it was shown how these highly accurate maps can support, as valuable tools, sustainable agricultural practices, government policy, and decision-making processes.","PeriodicalId":20944,"journal":{"name":"Remote. Sens.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140439115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Near-Field Imaging Method Based on the Near-Field Distance for an Aperture Synthesis Radiometer","authors":"Yuanchao Wu, Yinan Li, Guangnan Song, Haofeng Dou, Dandan Wen, Pengfei Li, Xiaojiao Yang, Rongchuan Lv, Hao Li","doi":"10.3390/rs16050767","DOIUrl":"https://doi.org/10.3390/rs16050767","url":null,"abstract":"For an aperture synthesis radiometer (ASR), the visibility and the modified brightness temperature (BT) are related to the Fourier transform when the distance between the system and the source is in the far-field region. BT reconstruction can be achieved using G-matrix imaging. However, for ASRs with large array sizes, the far-field condition is not satisfied when performing performance tests in an anechoic chamber due to size limitations. Using far-field imaging methods in near-field conditions can introduce errors in the images and fail to correctly reconstruct the BT. Most of the existing methods deal with visibilities, converting near-field visibilities to far-field visibilities, which are suitable for point sources but not good for extended source correction. In this paper, two near-field imaging methods are proposed based on the near-field distance. These methods enable BT reconstruction in near-field conditions by generating improved resolving matrices: the near-field G-matrix and the F-matrix. These methods do not change the visibility measurements and can effectively image both the point source and the extended source in the near field. Simulations of point sources and extended sources in near-field conditions demonstrate the effectiveness of both methods, with F-matrix imaging outperforming near-field G-matrix imaging. The feasibility of both near-field imaging methods is further validated by carrying out experiments on a 10-element Y-array system.","PeriodicalId":20944,"journal":{"name":"Remote. Sens.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140440081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Remote. Sens.Pub Date : 2024-02-22DOI: 10.3390/rs16050775
Guoqing Zhang, Tianqi Liu, Zhonglin Ye
{"title":"Dynamic Screening Strategy Based on Feature Graphs for UAV Object and Group Re-Identification","authors":"Guoqing Zhang, Tianqi Liu, Zhonglin Ye","doi":"10.3390/rs16050775","DOIUrl":"https://doi.org/10.3390/rs16050775","url":null,"abstract":"In contemporary times, owing to the swift advancement of Unmanned Aerial Vehicles (UAVs), there is enormous potential for the use of UAVs to ensure public safety. Most research on capturing images by UAVs mainly focuses on object detection and tracking tasks, but few studies have focused on the UAV object re-identification task. In addition, in the real-world scenarios, objects frequently get together in groups. Therefore, re-identifying UAV objects and groups poses a significant challenge. In this paper, a novel dynamic screening strategy based on feature graphs framework is proposed for UAV object and group re-identification. Specifically, the graph-based feature matching module presented aims to enhance the transmission of group contextual information by using adjacent feature nodes. Additionally, a dynamic screening strategy designed attempts to prune the feature nodes that are not identified as the same group to reduce the impact of noise (other group members but not belonging to this group). Extensive experiments have been conducted on the Road Group, DukeMTMC Group and CUHK-SYSU-Group datasets to validate our framework, revealing superior performance compared to most methods. The Rank-1 on CUHK-SYSU-Group, Road Group and DukeMTMC Group datasets reaches 71.8%, 86.4% and 57.8%, respectively. Meanwhile, our method performance is explored on the UAV datasets of PRAI-1581 and Aerial Image, the infrared datasets of SYSU-MM01 and CM-Group and the NIR dataset of RBG-NIR Scene dataset; the unexpected findings demonstrate the robustness and wide applicability of our method.","PeriodicalId":20944,"journal":{"name":"Remote. Sens.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140439587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Remote. Sens.Pub Date : 2024-02-22DOI: 10.3390/rs16050772
Wenda Li, Tian Wu, Hong Liu
{"title":"Multi-Scale Acoustic Velocity Inversion Based on a Convolutional Neural Network","authors":"Wenda Li, Tian Wu, Hong Liu","doi":"10.3390/rs16050772","DOIUrl":"https://doi.org/10.3390/rs16050772","url":null,"abstract":"The full waveform inversion at this stage still has many problems in the recovery of deep background velocities. Velocity modeling based on end-to-end deep learning usually lacks a generalization capability. The proposed method is a multi-scale convolutional neural network velocity inversion (Ms-CNNVI) that incorporates a multi-scale strategy into the CNN-based velocity inversion algorithm for the first time. This approach improves the accuracy of the inversion by integrating a multi-scale strategy from low-frequency to high-frequency inversion and by incorporating a smoothing strategy in the multi-scale (MS) convolutional neural network (CNN) inversion process. Furthermore, using angle-domain reverse time migration (RTM) for dataset construction in Ms-CNNVI significantly improves the inversion efficiency. Numerical tests showcase the efficacy of the suggested approach.","PeriodicalId":20944,"journal":{"name":"Remote. Sens.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140441799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Remote. Sens.Pub Date : 2024-02-22DOI: 10.3390/rs16050773
Haitao Luo, Jinming Zhang, Xiongfei Liu, Lili Zhang, Junyi Liu
{"title":"Large-Scale 3D Reconstruction from Multi-View Imagery: A Comprehensive Review","authors":"Haitao Luo, Jinming Zhang, Xiongfei Liu, Lili Zhang, Junyi Liu","doi":"10.3390/rs16050773","DOIUrl":"https://doi.org/10.3390/rs16050773","url":null,"abstract":"Three-dimensional reconstruction is a key technology employed to represent virtual reality in the real world, which is valuable in computer vision. Large-scale 3D models have broad application prospects in the fields of smart cities, navigation, virtual tourism, disaster warning, and search-and-rescue missions. Unfortunately, most image-based studies currently prioritize the speed and accuracy of 3D reconstruction in indoor scenes. While there are some studies that address large-scale scenes, there has been a lack of systematic comprehensive efforts to bring together the advancements made in the field of 3D reconstruction in large-scale scenes. Hence, this paper presents a comprehensive overview of a 3D reconstruction technique that utilizes multi-view imagery from large-scale scenes. In this article, a comprehensive summary and analysis of vision-based 3D reconstruction technology for large-scale scenes are presented. The 3D reconstruction algorithms are extensively categorized into traditional and learning-based methods. Furthermore, these methods can be categorized based on whether the sensor actively illuminates objects with light sources, resulting in two categories: active and passive methods. Two active methods, namely, structured light and laser scanning, are briefly introduced. The focus then shifts to structure from motion (SfM), stereo matching, and multi-view stereo (MVS), encompassing both traditional and learning-based approaches. Additionally, a novel approach of neural-radiance-field-based 3D reconstruction is introduced. The workflow and improvements in large-scale scenes are elaborated upon. Subsequently, some well-known datasets and evaluation metrics for various 3D reconstruction tasks are introduced. Lastly, a summary of the challenges encountered in the application of 3D reconstruction technology in large-scale outdoor scenes is provided, along with predictions for future trends in development.","PeriodicalId":20944,"journal":{"name":"Remote. Sens.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140440253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Remote. Sens.Pub Date : 2024-02-22DOI: 10.3390/rs16050768
Yanmei Xie, Caihong Ma, Yindi Zhao, Dongmei Yan, Bo Cheng, Xiaolin Hou, Hongyu Chen, Bihong Fu, Guangtong Wan
{"title":"The Potential of Using SDGSAT-1 TIS Data to Identify Industrial Heat Sources in the Beijing-Tianjin-Hebei Region","authors":"Yanmei Xie, Caihong Ma, Yindi Zhao, Dongmei Yan, Bo Cheng, Xiaolin Hou, Hongyu Chen, Bihong Fu, Guangtong Wan","doi":"10.3390/rs16050768","DOIUrl":"https://doi.org/10.3390/rs16050768","url":null,"abstract":"It is crucial to detect and classify industrial heat sources for sustainable industrial development. Sustainable Development Science Satellite 1 (SDGSAT-1) thermal infrared spectrometer (TIS) data were first introduced for detecting industrial heat source production areas to address the difficulty in identifying factories with low combustion temperatures and small scales. In this study, a new industrial heat source identification and classification model using SDGSAT-1 TIS and Landsat 8/9 Operational Land Imager (OLI) data was proposed to improve the accuracy and granularity of industrial heat source recognition. First, multiple features (thermal and optical features) were extracted using SDGSAT-1 TIS and Landsat 8/9 OLI data. Second, an industrial heat source identification model based on a support vector machine (SVM) and multiple features was constructed. Then, industrial heat sources were generated and verified based on the topological correlation between the identification results of the production areas and Google Earth images. Finally, the industrial heat sources were classified into six categories based on point-of-interest (POI) data. The new model was applied to the Beijing–Tianjin–Hebei (BTH) region of China. The results showed the following: (1) Multiple features enhance the differentiation and identification accuracy between industrial heat source production areas and the background. (2) Compared to active-fire-point (ACF) data (375 m) and Landsat 8/9 thermal infrared sensor (TIRS) data (100 m), nighttime SDGSAT-1 TIS data (30 m) facilitate the more accurate detection of industrial heat source production areas. (3) Greater than 2~6 times more industrial heat sources were detected in the BTH region using our model than were reported by Ma and Liu. Some industrial heat sources with low heat emissions and small areas (53 thermal power plants) were detected for the first time using TIS data. (4) The production areas of cement plants exhibited the highest brightness temperatures, reaching 301.78 K, while thermal power plants exhibited the lowest brightness temperatures, averaging 277.31 K. The production areas and operational statuses of factories could be more accurately identified and monitored with the proposed approach than with previous methods. A new way to estimate the thermal and air pollution emissions of industrial enterprises is presented.","PeriodicalId":20944,"journal":{"name":"Remote. Sens.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140440881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Remote. Sens.Pub Date : 2024-02-22DOI: 10.3390/rs16050770
Wentao Lian, Congming Dai, Shunping Chen, Yuxuan Zhang, Fan Wu, Cong Zhang, Chen Wang, Heli Wei
{"title":"Investigation of Light-Scattering Properties of Non-Spherical Sea Salt Aerosol Particles at Varying Levels of Relative Humidity","authors":"Wentao Lian, Congming Dai, Shunping Chen, Yuxuan Zhang, Fan Wu, Cong Zhang, Chen Wang, Heli Wei","doi":"10.3390/rs16050770","DOIUrl":"https://doi.org/10.3390/rs16050770","url":null,"abstract":"In the marine environment, sea salt aerosol particles transition from cubic or rectangular shapes when dry to various non-spherical shapes like ellipsoids and cylinders under different humidities. The complex humidity conditions and particle morphologies pose challenges to simulating the optical scattering properties of non-spherical sea salt aerosols. This study, addressing real environmental scenarios, employs the randomly oriented T-matrix computational method to calculate the optical scattering and polarization characteristics of sea salt aerosols at a wavelength of 1.06 μm under three relative humidity conditions (50%, 80%, and 95%) and three particle morphologies (spheroid, circular cylinder, and Chebyshev particle shapes). The results show the following: (1) In terms of optical scattering properties, the greater the non-sphericity of particles under the same humidity conditions, the larger the deviation between non-spherical and spherical models. For spheroid and circular cylinder sea salt aerosols, the error in the extinction efficiency factor mainly lies within 10–30%, reaching up to 120%; the error in the asymmetry factor is primarily between 3 and 25%, with a maximum of 75%, and the error in the forward-scattering phase function is mainly within 10–60%, reaching up to 180%. Chebyshev particle-shaped sea salt aerosols exhibit smaller deviations in optical scattering properties compared to equivalent spherical models, generally within the 5–25% range. Under different humidity conditions, the scattering characteristic parameters of sea salt aerosol particles for various non-spherical models show a positive correlation with relative humidity. When relative humidity is below 70%, the optical scattering properties of differently shaped sea salt aerosols are less affected by relative humidity. Above 70% relative humidity, the optical scattering properties of sea salt aerosols of different shapes become more sensitive to changes in relative humidity. (2) Regarding polarization properties, the greater the humidity, the more significant the impact on polarization properties, and as humidity increases, sea salt aerosols with higher non-sphericity exhibit more complex changes in polarization characteristics. The differences in shapes of non-spherical models mainly affect the numerical values of polarization properties. Under the same humidity conditions, spheroid polarization characteristics are significantly different from other models. In terms of depolarization ratio for aerosols, circular cylinder sea salt aerosols show the highest depolarization ratio at various relative humidities, followed by spheroid, with Chebyshev-shaped having the least. The effect of relative humidity on the depolarization ratio varies with the scattering angle. The higher the relative humidity, the more complex the variation in the depolarization ratio with scattering angle, with more pronounced oscillations in the curve, and the less non-spherical the shape, the more","PeriodicalId":20944,"journal":{"name":"Remote. Sens.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140439770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}