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IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium最新文献

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Satellite-Based High-Spatial-Resolution and High-Quality Fine Particulate Matters Across China 基于卫星的中国细颗粒物高空间分辨率和高质量数据
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2020-09-26 DOI: 10.1109/IGARSS39084.2020.9323311
Jing Wei, Zhanqing Li
{"title":"Satellite-Based High-Spatial-Resolution and High-Quality Fine Particulate Matters Across China","authors":"Jing Wei, Zhanqing Li","doi":"10.1109/IGARSS39084.2020.9323311","DOIUrl":"https://doi.org/10.1109/IGARSS39084.2020.9323311","url":null,"abstract":"Atmospheric fine particulate matters (i.e., PM1, PM2.5) are highly related to climate change and human life. This study aims to produce ground-level PM1 and PM2.5 concentrations at a 1-km spatial resolution across China based on the newly released MODIS MAIAC AOD product using a newly developed space-time extremely randomized trees (STET) model. Daily PMl and PM2.5 concentrations were estimated from insitu surface PM2.5 measurements, meteorological and ancillary variables. The 10-fold cross-validation (CV) approach is selected for model validation. The results show that the STET model shows a high accuracy in daily PM1 (PM2.5) estimates in 2018 with a high coefficient of determination equal to 0.76 (0.89), a low root-mean-square error of $9.5 (10.3) mu mathrm{g}/mathrm{m}^{3}$, and a low mean prediction error of $5.9 (6.7) mu mathrm{g}/mathrm{m}^{3}$. The STET model is robust and can outperform most previous studies, benefitting from the ensemble regression approach and the synergy of space-time information. This high-resolution and high-quality PMx data set in China (i.e., ChinaHighPMx) may thus be very useful for related air pollution and human health studies, especially for urban areas.","PeriodicalId":444267,"journal":{"name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127157454","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}
引用次数: 0
Topic Model for Remote Sensing Data: A Comprehensive Review 遥感数据主题模型:综述
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2020-09-26 DOI: 10.1109/IGARSS39084.2020.9323178
Qiqi Zhu, J. Wan, Yanfei Zhong, Qingfeng Guan, Liangpei Zhang, Deren Li
{"title":"Topic Model for Remote Sensing Data: A Comprehensive Review","authors":"Qiqi Zhu, J. Wan, Yanfei Zhong, Qingfeng Guan, Liangpei Zhang, Deren Li","doi":"10.1109/IGARSS39084.2020.9323178","DOIUrl":"https://doi.org/10.1109/IGARSS39084.2020.9323178","url":null,"abstract":"From text analysis to image interpretation, the topic model (TM) always plays an important role. With its powerful semantic mining capabilities, it is able to capture the latent spectral and spatial information from remote sensing (RS) images. Recent years have witnessed widespread use of TM to solve the problems in RS image interpretation, i.e., semantic segmentation, target detection, and scene classification. However, there has not yet been a study expatiating and summarizing the current situation of RS applications with TM. This paper intends to systematically summarize the application of TM in RS images and to conduct several typical experiments for comparison. Specifically, the architecture of our work can be explained as follows: 1) the theory of TM; 2) the applications of RS based on TM; 3) experimental analysis of typical TM methods to provide reference for further understanding, and 4) summary and prospects for guiding further research into TM for RS data.","PeriodicalId":444267,"journal":{"name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127200236","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}
引用次数: 1
Retrieval of Arctic Particle Microphysics from Air-Borne LiDAR and Sun-Photometer Data 从机载激光雷达和太阳光度计数据中检索北极粒子微物理
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2020-09-26 DOI: 10.1109/IGARSS39084.2020.9323659
C. Böckmann, K. Nakoudi, C. Ritter, A. Herber
{"title":"Retrieval of Arctic Particle Microphysics from Air-Borne LiDAR and Sun-Photometer Data","authors":"C. Böckmann, K. Nakoudi, C. Ritter, A. Herber","doi":"10.1109/IGARSS39084.2020.9323659","DOIUrl":"https://doi.org/10.1109/IGARSS39084.2020.9323659","url":null,"abstract":"We investigate an Arctic haze event observed by an air-borne Lidar system and sun-photometer. From optical backscatter and extinction coefficients we retrieve by regularized inversion the particle microphysical properties. We found a stable bimodal size distribution.","PeriodicalId":444267,"journal":{"name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127215852","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}
引用次数: 1
Combined the Data-Driven with Model-Driven Stragegy: A Novel Framework for Mixed Noise Removal in Hyperspectral Image 数据驱动与模型驱动相结合的高光谱图像混合噪声去除新框架
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2020-09-26 DOI: 10.1109/IGARSS39084.2020.9323115
Qiang Zhang, Fujun Sun, Q. Yuan, Jie Li, Huanfeng Shen, Liangpei Zhang
{"title":"Combined the Data-Driven with Model-Driven Stragegy: A Novel Framework for Mixed Noise Removal in Hyperspectral Image","authors":"Qiang Zhang, Fujun Sun, Q. Yuan, Jie Li, Huanfeng Shen, Liangpei Zhang","doi":"10.1109/IGARSS39084.2020.9323115","DOIUrl":"https://doi.org/10.1109/IGARSS39084.2020.9323115","url":null,"abstract":"In this paper, we present a novel hyperspectral image (HSI) denoising method especially for mixed noise removal. The proposed method combines both data-driven with model-driven strategy via a deep spatio-spectral variational structure. The mixed noise estimation and removal are collaboratively derived through fusing the Bayesian spatio-spectral posterior and deep learning model. The framework can both utilize the logicality of traditional model-driven methods, and the high efficiency of data-driven methods for parameters optimizing. Simulated and actual experiments demonstrate that the presented method outperforms other existing methods for HSI mixed noise removal, on both reconstructing effects and time-consuming.","PeriodicalId":444267,"journal":{"name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127290019","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}
引用次数: 1
A Multi-Sensor Approach to Separate Palm Oil Plantations from Forest Cover Using NDFI and a Modified Pauli Decomposition Technique 基于NDFI和改进泡利分解技术的多传感器棕榈油种植园与森林覆盖分离方法
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2020-09-26 DOI: 10.1109/IGARSS39084.2020.9324567
E. Muñoz, A. Zozaya, E. Lindquist
{"title":"A Multi-Sensor Approach to Separate Palm Oil Plantations from Forest Cover Using NDFI and a Modified Pauli Decomposition Technique","authors":"E. Muñoz, A. Zozaya, E. Lindquist","doi":"10.1109/IGARSS39084.2020.9324567","DOIUrl":"https://doi.org/10.1109/IGARSS39084.2020.9324567","url":null,"abstract":"In this work, a multi-sensor approach to separate oil palm plantations from forest cover using NDFI and a modified Pauli Decomposition technique is presented. The main contribution of this research is the potential to reduce misclassification of both classes, in the context of automated-base supervised classification algorithms, to decrease uncertainties derived through the detection and mapping process of forest cover. The hereby proposed method includes the generation of a primary forest map cover defining thresholds from a high resolution multi -spectral satellite image, and then the palm oil plantation will be filtered out from this classification using scattering mechanisms by a Pauli Decomposition approach. Preliminary results shown the capabilities of this approach in order to generate complementary information to separate the oil palm plantations from the forest cover classification.","PeriodicalId":444267,"journal":{"name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127470296","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}
引用次数: 4
How Much Wavelet Decomposition can Improve the Detection of Surface Fractures in Remote Sensing Images? 小波分解能在多大程度上改善遥感图像表面裂缝的检测?
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2020-09-26 DOI: 10.1109/IGARSS39084.2020.9324506
E. Souza, Ademir Marques, Rafael Kenji Horota, L. S. Kupssinskü, Pedro Rossa, A. S. Aires, L. G. D. Silveira, M. Veronez, C. Cazarin
{"title":"How Much Wavelet Decomposition can Improve the Detection of Surface Fractures in Remote Sensing Images?","authors":"E. Souza, Ademir Marques, Rafael Kenji Horota, L. S. Kupssinskü, Pedro Rossa, A. S. Aires, L. G. D. Silveira, M. Veronez, C. Cazarin","doi":"10.1109/IGARSS39084.2020.9324506","DOIUrl":"https://doi.org/10.1109/IGARSS39084.2020.9324506","url":null,"abstract":"In this paper we propose a new approach to automatically detect and extract fractures as well as estimate the aperture measures from orbital/aerial images. We show, in a first step, the capability of a translation invariant wavelet multiscale decomposition (NDWT) to separate the information related to the fractures from other features in the image. In the second stage, the aperture size (widths of the fractures) in different positions are estimated across scales using curvature analysis. In a third step, the fractures can be automatically extracted using a growing algorithm. Besides the measures of the fracture apertures in an image of Thingvellir in Iceland, we showed the correlation between the fractures of interest extracted automatically and the respective extracted manually were high (0.9) while only 51 % of then were extracted using just curvature analysis and growing algorithm (without NDWT).","PeriodicalId":444267,"journal":{"name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","volume":"2441 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127479398","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}
引用次数: 1
Satellite Attitude Change Recognition Based on Multi-Frame Image by 3D Convolutional Neural Networks 基于多帧图像的三维卷积神经网络卫星姿态变化识别
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2020-09-26 DOI: 10.1109/IGARSS39084.2020.9323372
Haoxuan Yuan, Yun Zhang, Xiaodong Gong, Hongbo Li, Muqun Niu
{"title":"Satellite Attitude Change Recognition Based on Multi-Frame Image by 3D Convolutional Neural Networks","authors":"Haoxuan Yuan, Yun Zhang, Xiaodong Gong, Hongbo Li, Muqun Niu","doi":"10.1109/IGARSS39084.2020.9323372","DOIUrl":"https://doi.org/10.1109/IGARSS39084.2020.9323372","url":null,"abstract":"The recognition of satellite's attitude change plays an important role in the detection, tracking and recognition of space targets, as well as the evaluation, verification of space events and environmental monitoring and prediction. In this paper, 3D-CNN model is used to extract features from spatial and temporal dimensions, and then 3D convolution is carried out to capture motion information from multiple consecutive frames. Four common attitude changes of three different kinds of satellites are simulated, which are orbit change, spin, reconnaissance and maneuver. A proper number of consecutive frames are sent into packets and sent to the network for training. The experimental result shows that 3D-CNN model has a competitive performance.","PeriodicalId":444267,"journal":{"name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124695390","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}
引用次数: 0
The Transmission Interface Design of Hall-effect sensor
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2020-09-26 DOI: 10.1109/IGARSS39084.2020.9324190
Hua Fan, Yongqing Zeng
{"title":"The Transmission Interface Design of Hall-effect sensor","authors":"Hua Fan, Yongqing Zeng","doi":"10.1109/IGARSS39084.2020.9324190","DOIUrl":"https://doi.org/10.1109/IGARSS39084.2020.9324190","url":null,"abstract":"In order to adapt to the need of high sensitivity, high accuracy, high data transmission speed and low power consumption in Hall-effect sensor application field, a sensor microsystem including a high-precision Hall voltage sensor, a 24-bit analog-to-digital converter, a FPGA chip and a LCD1602 is designed in order to detect and display the external magnetic field strength in real time. In this paper, we discussed the hardware and software design of Hall-effect microsystem sensors in details. Finally, system debugging and performance analysis have been given.","PeriodicalId":444267,"journal":{"name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124794460","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}
引用次数: 0
Large Scale Assessment of Free Global DEMs Through the Google Earth Engine Platform 利用谷歌地球引擎平台对自由全球dem进行大规模评估
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2020-09-26 DOI: 10.1109/IGARSS39084.2020.9324100
R. Ravanelli, A. Nascetti, M. Crespi
{"title":"Large Scale Assessment of Free Global DEMs Through the Google Earth Engine Platform","authors":"R. Ravanelli, A. Nascetti, M. Crespi","doi":"10.1109/IGARSS39084.2020.9324100","DOIUrl":"https://doi.org/10.1109/IGARSS39084.2020.9324100","url":null,"abstract":"The aim of this study is to compare and analyze the accuracy of freely available global DEMs. Four DEMs generated using optical and SAR satellite imagery - ASTER GDEM, SRTM DEM, ALOS AW3D30, Tandem-X 90m - were analyzed over the territories of four U.S. states (approximately 927000 km2) that are characterized by different morphologies and land covers. The accuracy assessment procedure was implemented within the Google Earth Engine (GEE) platform, designed to manage and analyze Geo Big Data. The outcomes highlight a good agreement among the statistical parameters at a global level for each wide area analyzed. The accuracy, as expected, decreases with the increase of the slopes, and ALOS AW3D30 displays the overall best performance, with an accuracy ranging between 2.5 m in flat areas and about 10 m in hilly/mountainous areas.","PeriodicalId":444267,"journal":{"name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124871681","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}
引用次数: 2
Unambiguous Signal Reconstruction Algorithm for High Squint Multichannel SAR Mounted on High Speed Maneuvering Platforms 高速机动平台上高斜视多通道SAR的无二义信号重构算法
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2020-09-26 DOI: 10.1109/IGARSS39084.2020.9323280
Ning Li, Guangcai Sun, M. Xing
{"title":"Unambiguous Signal Reconstruction Algorithm for High Squint Multichannel SAR Mounted on High Speed Maneuvering Platforms","authors":"Ning Li, Guangcai Sun, M. Xing","doi":"10.1109/IGARSS39084.2020.9323280","DOIUrl":"https://doi.org/10.1109/IGARSS39084.2020.9323280","url":null,"abstract":"High squint multichannel (HSMC) synthetic aperture radar (SAR) mounted on high speed maneuvering platforms is an available mode to achieve wide swath imaging. However, the traditional multichannel reconstruction methods are not suitable because of range-dependent and time-variant steering vector caused by the nonlinear trajectory. To address the issue, a novel unambiguous signal reconstruction algorithm is proposed in this paper. According to the geometry model, the properties of range-dependent and time-variant steering vector are analyzed. Then, a range-dependent and time-variant inter-channel phase compensation method is proposed to correct the space time spectrum, and the constant steering vector is obtained. Before the reconstruction, the range walk correction (RWC) is performed to remove the mismatch between the reconstruction filters and the squinted signal. Furthermore, a modified spatial domain filter is proposed to reconstruct the unambiguous Doppler spectrum. Finally, simulation results are presented to validate the proposed approach.","PeriodicalId":444267,"journal":{"name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124934512","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}
引用次数: 2
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