Xuanru Zhao, Jinquan Cheng, Weijin Guan, Yuxuan Zhang, Bo Cao
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.
在亚洲高山地区，大多数冰川和冰川湖在整个气候变化过程中都经历了快速变化。与陆地末端冰川不同，湖泊末端冰川由于冰川湖泊与冰川动力学之间的动态相互作用而呈现出快速收缩的现象。在这项研究中，我们详细分析了琼布库湖末端冰川的表面高程、速度，特别是锋面消融的变化。结果表明，与其他冰川相比，琼布错冰川的质量平衡为负值的两倍，年表面速度异常增加（每十年增加 3.6 m a-1），而其他冰川则呈下降趋势。随着前冰湖的加速扩张，琼布错冰川净质量损失中的锋面消融部分从 26% 增加到 52%。所有现有证据都表明，冰川湖与其所在冰川之间存在正反馈作用。我们的研究结果突出表明，冰川湖的存在会影响湖泊末端冰川的空间变化规律。此外，湖泊面积的不断扩大放大了与湖泊末端冰川演变相关的变化。
{"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":"9 2","pages":"762"},"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}
Jinbiao Zhu, Bei Lin, Jie Pan, Yao Cheng, Xiaolan Qiu, Wen Jiang, Yuquan Liu, Mingqian Liu
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.
{"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":"22 2","pages":"769"},"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}
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.
利用 "气象电离层和气候星座观测系统-2（COSMIC-2）"射电掩星（RO）任务在2019年12月至2021年11月期间的干温度剖面图，对印度地区（60°E-100°E，0°-30°N）20至30千米高度范围内平流层下部的重力波势能（Ep）进行了检索。通过相关性分析和优势分析（DA）方法，量化和比较了多种影响因素对局地LS GW活动的影响。结果表明，在印度中北部地区，主要由印度夏季季风引起的对流活动（以出射长波辐射为代表）、热带东风喷流（TEJ）最大风速出现的高度范围15-17千米之间的平均带状风速以及20-30千米之间的平均带状风速这三个因素对LS GW活动的影响最大，而在印度半岛南部地区，主要由印度夏季季风引起的对流活动（以出射长波辐射为代表）、热带东风喷流（TEJ）最大风速出现的高度范围15-17千米之间的平均带状风速以及20-30千米之间的平均带状风速这三个因素对LS GW活动的影响最小。在印度半岛南部和印度洋上空，20 至 30 千米之间的平均带状风切变对 LS GW 活动起着主导作用，这是因为大的背景风切变会削弱 GW 能量。由此可以得出结论，印度地区的 LS 全球风暴活动主要受印度夏季季风、TEJ 和 LS 风活动的影响，而在不同的局部地区，哪些因素是主导因素则存在差异。
{"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":"6 S1","pages":"761"},"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}
S. R. Suwanlee, Dusadee Pinasu, J. Som-ard, E. Mondino, F. Sarvia
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.
{"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":"11 2","pages":"750"},"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}
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.
对于孔径合成辐射计（ASR）来说，当系统与光源之间的距离处于远场区域时，可见度和修正亮度温度（BT）与傅立叶变换有关。BT 重建可通过 G 矩阵成像来实现。然而，对于阵列尺寸较大的 ASR，由于尺寸限制，在电波暗室中进行性能测试时无法满足远场条件。在近场条件下使用远场成像方法会在图像中引入误差，无法正确重建 BT。现有的大多数方法都是处理可见度，将近场可见度转换为远场可见度，这些方法适用于点源，但不利于扩展源校正。本文提出了两种基于近场距离的近场成像方法。这些方法通过生成改进的解析矩阵：近场 G 矩阵和 F 矩阵，在近场条件下进行 BT 重建。这些方法不会改变可见度测量值，能有效地对近场中的点源和扩展源进行成像。在近场条件下对点源和扩展源的模拟证明了这两种方法的有效性，其中 F 矩阵成像优于近场 G 矩阵成像。通过在 10 元 Y 阵列系统上进行实验，进一步验证了这两种近场成像方法的可行性。
{"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":"79 7","pages":"767"},"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}
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.
在当代，由于无人驾驶飞行器（UAV）的迅速发展，利用无人驾驶飞行器确保公共安全的潜力巨大。大多数关于无人机图像捕捉的研究主要集中在物体检测和跟踪任务上，但很少有研究关注无人机物体再识别任务。此外，在现实场景中，物体经常成群结队地聚集在一起。因此，重新识别无人机物体和群组是一项重大挑战。本文提出了一种基于特征图框架的新型动态筛选策略，用于无人机物体和群组的重新识别。具体来说，本文提出的基于图的特征匹配模块旨在通过使用相邻的特征节点来增强群组上下文信息的传输。此外，还设计了一种动态筛选策略，尝试修剪未被识别为同一群体的特征节点，以减少噪声（其他群体成员但不属于该群体）的影响。为了验证我们的框架，我们在 Road Group、DukeMTMC Group 和 CUHK-SYSU-Group 数据集上进行了广泛的实验，结果表明与大多数方法相比，我们的框架性能更优。在 CUHK-SYSU-Group、Road Group 和 DukeMTMC Group 数据集上的 Rank-1 分别达到 71.8%、86.4% 和 57.8%。同时，我们还在 PRAI-1581 和 Aerial Image 的无人机数据集、SYSU-MM01 和 CM-Group 的红外数据集以及 RBG-NIR Scene 数据集的近红外数据集上对我们的方法进行了性能测试，意外的发现证明了我们方法的鲁棒性和广泛适用性。
{"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":"60 9","pages":"775"},"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}
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.
{"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":"28 9","pages":"772"},"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}
Haitao Luo, Jinming Zhang, Xiongfei Liu, Lili Zhang, Junyi Liu
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.
{"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":"66 3","pages":"773"},"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}
Yanmei Xie, Caihong Ma, Yindi Zhao, Dongmei Yan, Bo Cheng, Xiaolin Hou, Hongyu Chen, Bihong Fu, Guangtong Wan
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.
{"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":"18 10","pages":"768"},"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}
Wentao Lian, Congming Dai, Shunping Chen, Yuxuan Zhang, Fan Wu, Cong Zhang, Chen Wang, Heli Wei
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
{"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":"110 1","pages":"770"},"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}
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