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application of Sentinel-1A Data in Offshore Wind Field Retrieval Within Guangdong Province 7th

Application of Sentinel-1A Data in Offshore Wind Field Retri...

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7th International Conference on Geoinformatics in Sustainable Ecosystem and Society, GSES 2019, and 1st International Conference on geospatial Artificial Intelligence for Urban Computing, GeoAI 2019

作者： Wu, Pinghao Zhong, Kaiwen Hu, Hongda Zhao, Yi Xu, Jianhui Wang, Yunpeng Guangzhou Institute of Geochemistry Chinese Academy of Sciences Guangzhou510640 China Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System Guangdong Open Laboratory of Geospatial Information Technology and Application Guangzhou Institute of Geography Guangzhou510070 China Guangzhou511458 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9789811561054

Offshore wind is an important source of information for monitoring the interaction between fishery and marine water vapor environment. In this paper, the CMOD5 function was used to invert the wind field in the coastal waters of Guangdong province in March, May, July and December 2017. Compared with the measured wind speed, the reasonable result of the inversion wind speed is generally higher, with the mean absolute deviation of 1.95 m/s, the root mean square error of 2.7 m/s, and the correlation coefficient of 0.8. Due to the measured data not exactly matching the satellite transit time, the error in December is large. The inversion results of Sentinel-1A images are consistent with the measured data generally, which verifies that the COMD5 function is applicable to the inversion of offshore high-resolution marine wind field in Guangdong province, and provides a possibility for the next step of estimating the wind energy resources and reserves in Guangdong province. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Remote sensing

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A total suspended sediment retrieval model for multiple estuaries and coasts by Landsat imageries

A total suspended sediment retrieval model for multiple estu...

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International Workshop on Earth Observation and Remote Sensing applications (EORSA)

作者： Chongyang Wang Dan Li Danni Wang Shuisen Chen Wei Liu Guangdong Open Laboratory of Geospatial Information Technology and Application University of Chinese Academy of Sciences Guangzhou Beijing China Guangdong Open Laboratory of Geospatial Information Technology and Application Guangzhou Institute of Geography Guangzhou China Department of Resources and the Urban Planning Sun Yat-Sen University Guangzhou China Guangdong Open Laboratory of Geospatial Information Technology and Application Guangdong Key Laboratory of Remote Sensing and Geographical Information System Technology Application Guangzhou Institute of Geography China

Based on 119 in-situ data from five estuaries and coasts of South China including Xunwen coast, estuary of Moyangjiang River, estuary and coast of Pearl River, estuary of Hanjiang River and estuary of Yangtze River, this paper aims to develop and establish a TSS retrieval model that applicable in different field conditions. After recalibrating and validating the form with the highest correlation coefficient between reflectance and TSS concentration and other TSS retrieval models that have been successful applied in many places, we found that the quadratic model of the ratio of logarithmic transformation of red band and near infrared band and logarithmic transformation of TSS concentration (QRLTSS) shows the highest performance. QRLTSS model based on Landsat OLI, ETM+ and TM can explained about 71% of the TSS concentration variation (4.3~577.2 mg/L) in the five regions and has a high and acceptable validation accuracy with root mean square error (RMSE) of 21.5-25mg/L and mean relative error (MRE) of 27.2-32.2%. We concluded that QRLTSS model can be used to quantify the TSS concentration of multiple estuaries and coasts of south China which would be helpful to understand the temporal and spatial variation of TSS in a large region. QRLTSS model should be applied to Landsat imagery for further validation in the future. The approach proposed in the paper also could promote the research work of establishing regional and uniform TSS retrieval model forward.

关键词： Geography Biological system modeling Solid modeling Rivers Satellites Earth Remote sensing

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Improving Wetland Mapping by Using Multi-Source Data Sets

Improving Wetland Mapping by Using Multi-Source Data Sets

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International Symposium on Image and Data Fusion (ISIDF)

作者： Luyan Ji Kang Jiang Xiurui Geng Hairong Tang Kai Yu Yongchao Zhao Key Laboratory of Technology in Geo-spatial information Processing and Application System Institute of Electronics Chinese Academy of Science Beijing China

To conserve and manage wetland resources, it is important to map wetlands and monitor their changes. However, wetland mapping is difficult because of spectral confusion with other landcover classes and spectral variability among different types of wetlands. This paper demonstrated a multi-source based approach for improving the accuracy of wetland mapping. According to the formation of wetland, variables derived from multi-source image date, and other ancillary GIS layers were first integrated to create the possible region for wetland (PRW). And then classification was conducted within the PRW to map wetlands. PRW could greatly reduce the amount of other land cover classes that participated in the classification, therefore reducing both the difficulty of wetland mapping and the commission error rate. In this study, we chose the test area in Dongzhai Harbor, Hainan Island, China, where the main wetland type is mangrove. The mapping was based on LANDSAT TM/ETM+ imagery combined with DEM data, and the ancillary GIS data included available water, soil and vegetation layers. The thematic accuracy of the mapping was assessed using high-resolution images from Google Earth and local wetlands databases. Classification of the 2001 Landsat ETM+ scene alone resulted in consumer's accuracy of 65% and Kappa coefficients of 0.69, whereas the multi-source based approach with the same training samples resulted in an accuracy of 86% and 0.80. The developed method is portable, relatively easy to implement, and should be applicable in other landcover classes and over larger extents.

关键词： Remote sensing Accuracy Satellites Earth Training Monitoring Databases

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A COOPERATIVE MULTITEMPORAL SEGMENTATION METHOD FOR SAR AND OPTICAL IMAGES CHANGE DETECTION

A COOPERATIVE MULTITEMPORAL SEGMENTATION METHOD FOR SAR AND ...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Ling Wan Yuming Xiang Hongjian You Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing China

This paper proposes an extension version of our previous work MS-CC to achieve optical and SAR images change detection. The proposed method introduces a cooperative multitemporal segmentation, whose merging process considers the heterogeneity of SAR and optical images as parallel information, making sure that the multitemporal information can be fully utilized without interfering with each other. Then, the change detection strategy based on compound classification is carried out on the segmentation results, obtaining the multi-scale change detection maps. Experimental validation is conducted with GoaFen3 and Google Earth data.

关键词： Image segmentation Optical imaging Radar polarimetry Optical sensors Compounds Interference Stacking

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Unambiguous parameter estimation of radial velocity approach for airborne SAR-GMTI

Unambiguous parameter estimation of radial velocity approach...

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Asian and Pacific Conference on Synthetic Aperture Radar (APSAR)

作者： Ruipeng Xu Dandan Zhang Lijia Huang Donghui Hu Chibiao Ding Key Laboratory of Geo-spatial Information Processing and Application System Technology Institute of Electronics Chinese Academy of Sciences Beijing China

The ambiguous Doppler centroid causes incorrect estimation result of the radial velocity. For moving targets with fast radial velocity, an unambiguous estimation approach of the radial velocity is introduced for the airborne SAR system in this paper. First, two channels carried different wavelength can be constructed by range multilook processing (RMLP). Second, the instantaneous frequency curve of the moving target is obtained by polynomial fitting for each channel, where the linear term denotes the baseband Doppler centroid. Considering the fact that the difference of the estimated baseband Doppler centroid in two channels is equal to the difference of the absolute Doppler centroid, the unambiguous radial velocity can be estimated using it. Third, the range walk and the Doppler shift which are produced by the fast radial velocity can be eliminated by compensating a phase in the range-frequency and azimuth-time domain. As a result, the moving target will be reimaged and relocated after azimuth compression. The proposed approach will be applied to both single — and multi-channel SAR system. The simulation results validate the effectiveness of the proposed method.

关键词： Doppler effect Estimation Baseband Azimuth Accuracy Fitting Polynomials

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A STUDY ON THE FREQUENCY AND AZIMUTH COHERENCE OF HIGH-RESOLUTION SAR IMAGE

A STUDY ON THE FREQUENCY AND AZIMUTH COHERENCE OF HIGH-RESOL...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Wenji Xing Xiaolan Qiu Chibiao Ding The Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing China

High-resolution SAR has large transmitting bandwidth and wide synthetic aperture. How to understand and take advantage of the variation characteristics of SAR scattering characteristics with angle and frequency is a topic that worth studying. This article establishes a coherence matrix of sub-band and sub-aperture SAR images, and analyzes its ability to classify scattering mechanism. Experiments are conducted using the TerraSAR-X high-resolution data of different scenarios, and some meaningful results are got, which may provide some support to the analysis and application of high-resolution SAR data.

关键词： Coherence Entropy Azimuth Radar polarimetry Synthetic aperture radar Image resolution

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SemanticAnchors: Sequential Fusion using Lidar Point Cloud and Anchors with Semantic Annotations for 3D Object Detection

SemanticAnchors: Sequential Fusion using Lidar Point Cloud a...

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IEEE Conference on Industrial Electronics and applications (ICIEA)

作者： Zhentong Gao Qiantong Wang Zongxu Pan Hui Long Yuxin Hu Zheng Li Key Laboratory of Technology in Geo-spatial Information Processing and Application System Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665409858

3D object detection is an important task in autonomous driving scenario, which is the basis of perception and understanding of 3D scenes. LiDAR and camera are two commonly used sensors in 3D object detection tasks. However, using a single sensor to collect data will make some objects difficult to detect because both sensors have insurmountable shortcomings. Unexpectedly, LiDAR-only detection methods tend to show better performance than the multi-sensor methods in public benchmarks. This shows that people need to further explore the methods of combining the data of the two sensors. Recently, PointPainting has been presented to combine the data of LiDAR and camera more efficiently by attaching the result of image semantic segmentation to point cloud data as new channels. In this paper, we propose an error anchor punishment mechanism based on image semantic segmentation results. After the semantic augmentation of the point cloud data, we judge whether the semantic result of each point is correct by traversing the groundtruth boxes. Further, we assign different weights to each anchor according to the error points contained in each anchor. Experimental results on the KITTI valid set show that SemanticAnchors achieves better performance in both 3D and birds eyes view benchmarks. In particular, our method adds little extra computation and achieves performance improvement in all categories.

关键词： Point cloud compression Training Three-dimensional displays Laser radar Semantic segmentation Semantics Object detection

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An Approach for Spaceborne InSAR DEM Inversion Integrated with Stereo-SAR Method

An Approach for Spaceborne InSAR DEM Inversion Integrated wi...

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Asian and Pacific Conference on Synthetic Aperture Radar (APSAR)

作者： Fangfang Li Yueting Zhang Xiaolan Qiu Key Laboratory of Geo-spatial Information Processing and Application System Technology Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728129129

ISBN: (纸本)9781728129136

Spaceborne Interferometric Synthetic Aperture Radar (InSAR) has the capability of high precise topographic mapping for large area. However, on the one hand, digital elevation models (DEM) inversion needs at least one ground control points (GCP) to obtain absolute interferometric phase as the unwrapped phase is just a relative value. On the other hand, the baseline value used for DEM inversion also needs to be calibrated using GCPs due to the measure error. In practice, it is difficult to manually deploy GCPs especially in the area of steep topography. At present, with the improvement of orbital measure accuracy and system time accuracy for spaceborne SAR satellite, high precise absolute 3D location information of some stable point scatterers can be obtained by stereo SAR using data from different viewing angles. Therefore, this paper combines stereo SAR with InSAR. These point scatters are used as GCPs to calibrate baseline and estimate absolute phase. As a result, high accurate DEM generation without GCPs can be achieved. The experiment using TerraSAR-X data verifies the effectiveness of this method.

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ON THE USE OF CNN FOR AUTOMATED QUALITY ASSESSMENT OF GF-3 POLARIMETRIC DATA

ON THE USE OF CNN FOR AUTOMATED QUALITY ASSESSMENT OF GF-3 P...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Songtao Shangguan Xiaolan Qiu Bin Lei The Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing China

With the needs of quality assessment for massive GF-3 polarimetric data, a method based on common distribution targets has been proposed by Sha Jiang. However, it needs manually selection of those woodlands, and cannot be performed automatically. In this paper, an automated GF-3 full-polarization SAR data quality assessment method is conducted using a classic Convolution Neural Network (VGG-16). The network is pre-trained by Radarsat-2 PolSAR data and then trained by selected typical GF-3 scenes. It is supposed to learn the features of the targets, which satisfies the azimuthal symmetry and backscatter reciprocity and fulfills the quality assessment work. Several typical GF-3 strips data are used to test the method. Experiments show that the network can predict the plots of targets from a new scene under the interference of polarimetric distortion and noise. And, the quality assessment results by the network are consistent with the manual assessment results, which shows the effectiveness of the method.

关键词： Quality assessment Distortion Data integrity Strips Manuals Forestry Radar polarimetry

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SAR Change Detection Based on keypoint Graph Structure and Cosegmentation-Based Refinement

SAR Change Detection Based on Keypoint Graph Structure and C...

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Geology, Mapping and Remote Sensing (ICGMRS), International Conference on

作者： Jingxing Zhu Rui Liu Niangang Jiao Feng Wang Hongjian You Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Aerospace information Research Institute Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350365719

ISBN: (纸本)9798350365726

Change detection between high-resolution Synthetic Aperture Radar (SAR) images remains a challenging task. Due to the effectively integration of structure and intensity information, graph-based methods have made some progress in SAR change detection. But it still faces the issues of robustness of graph construction and incomplete change detection outcomes. To tackle these challenges, we propose an improved keypoint-based graph structure change detection approach. First, we propose a keypoint extraction strategy guided by a coarse change map to better describe potential change areas. Second, we construct stable graph structures on these keypoints with employing a robust distance measurement that considers the statistical properties of SAR images. Then, the keypoint difference image (KDI) is derived through measuring the consistency of graph structures between pre-and post-time SAR images. Next, keypoint change map (KCM) is generated through clustering KDI by k-means. Finally, we use co-segmentation superpixel mask to refine the KCM and obtain accurate and complete binary change map. We validate the effective of proposed framework on GF-3 dataset. Experimental results demonstrate the superior performance of our method compared to alternative method.

关键词： Image segmentation Geology Noise Focusing Speckle Radar polarimetry Robustness

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