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Effects of RapidEye Imagery's Red-edge Band and Vegetation Indices on Land Cover Classification in an Arid Region

Chinese geographical Science 2017年第5期27卷 827-835页

作者： LI Xianju CHEN Gang LIU Jingyi CHEN Weitao CHENG Xinwen LIAO Yiwei College of Computer Science and Hubei Key Laboratory of Intelligent Geo-Information Processing China University of GeosciencesWuhan 430074China College of Marine Science and Technology China University of GeosciencesWuhan 430074China Laboratory of Geographic Information and Spatial Analysis Department of Geography and PlanningQueen's UniversityKingston ON K7L3N6Canada Faculty of Information Engineering China University of GeosciencesWuhan 430074China School of Electrical and Electronic Engineering Huazhong University of Science and TechnologyWuhan 430074China

Land cover classification(LCC) in arid regions is of great significance to the assessment, prediction, and management of land desertification. Some studies have shown that the red-edge band of RapidE ye images was effective for vegetation identification and could improve LCC accuracy. However, there has been no investigation of the effects of RapidE ye images' red-edge band and vegetation indices on LCC in arid regions where there are spectrally similar land covers mixed with very high or low vegetation coverage information and bare land. This study focused on a typical inland arid desert region located in Dunhuang Basin of northwestern China. First, five feature sets including or excluding the red-edge band and vegetation indices were constructed. Then, a land cover classification system involving plant communities was developed. Finally, random forest algorithm-based models with different feature sets were utilized for LCC. The conclusions drawn were as follows: 1) the red-edge band showed slight contribution to LCC accuracy; 2) vegetation indices had a significant positive effect on LCC; 3) simultaneous addition of the red-edge band and vegetation indices achieved a significant overall accuracy improvement(3.46% from 86.67%). In general, vegetation indices had larger effect than the red-edge band, and simultaneous addition of them significantly increased the accuracy of LCC in arid regions.

关键词： arid region land cover classification RapidEye red-edge band vegetation indices random forest Dunhuang Basin

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Automated ortho-rectified SAR image of GF-3 satellite using Reverse-Range-Doppler method

Automated ortho-rectified SAR image of GF-3 satellite using ...

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IEEE International Symposium on geoscience and Remote Sensing (IGARSS)

作者： Jiayin Liu Xiaolan Qiu Wen Hong Institute of Electronics Chinese Academy of Sciences Beijing China Key Laboratory of Technology on Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China National Key Laboratory of Microwave Imaging Technology Beijing China

GF-3 is the Chinese Synthetic Aperture Radar (SAR) satellite mission with scientific and commercial applications, which will be launched in 2016. The ortho-rectification image combined with the DEM data can only be satisfied with the applications of the high resolution radar image, the data quantity with wide-breadth also put forward higher request to the automation processing. The Reverse-Range-Doppler method was used to ortho-rectified the SAR image of GF-3 satellite based on the Range-Doppler model in this paper. It not only ensures the correction precision, but also simplifies the iteration steps about DEM data, and improves the efficiency of automatic processing.

关键词： Synthetic aperture radar Mathematical model Satellites Doppler effect Space vehicles Earth Azimuth

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Phase Transition Analysis for Compressive Sensing Based DoA Estimation in Automotive Radar

Phase Transition Analysis for Compressive Sensing Based DoA ...

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International Radar Symposium (IRS)

作者： Yan Zhang Silin Gao Mingqian Liu Bingchen Zhang Yirong Wu Chinese Academy of Sciences Aerospace Information Research Institute Beijing China University of Chinese Academy of Sciences Beijing China Key Laboratory of Technology in Geo-spatial Information and Processing Application System Beijing China

ISBN: (数字)9788394942151

ISBN: (纸本)9781728157863

In automotive radar applications, the compressive sensing (CS) based DoA estimation is used in array signal processing in recent years. Sparse reconstruction has the potential to estimate the direction of arrival (DoA) with super resolution. However, failed results may be acquired via sparse reconstruction in inappropriate conditions, namely the critical condition determining success or failure must be taken into consideration. In this paper, the sparsity of the scenario and the signal-to-noise ratio (SNR) are analyzed as the main factors via phase transition diagrams. Other factors affecting the success or failure are also investigated, such as the array configuration and the sparse recovery algorithm. Simulated and experimental results demonstrate the critical conditions, in which the DoA estimation is successful or failed.

关键词： Direction-of-arrival estimation Estimation Radar applications Compressed sensing Signal resolution Signal to noise ratio Automotive engineering

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RESIDUAL SHUFFLING CONVOLUTIONAL NEURAL NETWORKS for DEEP SEMANTIC IMAGE SEGMENTATION USING MULTI-MODAL DATA

RESIDUAL SHUFFLING CONVOLUTIONAL NEURAL NETWORKS for DEEP SE...

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2018 ISPRS TC II Mid-term Symposium "Towards Photogrammetry 2020"

作者： Chen, K. Weinmann, M. Gao, X. Yan, M. Hinz, S. Jutzi, B. Weinmann, M. Key Laboratory of Spatial Information Processing and Application System Technology Institute of Electronics Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Institute of Computer Science II University of Bonn Bonn Germany Institute of Photogrammetry and Remote Sensing Karlsruhe Institute of Technology Karlsruhe Germany

In this paper, we address the deep semantic segmentation of aerial imagery based on multi-modal data. Given multi-modal data composed of true orthophotos and the corresponding Digital Surface Models (DSMs), we extract a variety of hand-crafted radiometric and geometric features which are provided separately and in different combinations as input to a modern deep learning framework. The latter is represented by a Residual Shuffling Convolutional Neural Network (RSCNN) combining the characteristics of a Residual Network with the advantages of atrous convolution and a shuffling operator to achieve a dense semantic labeling. Via performance evaluation on a benchmark dataset, we analyze the value of different feature sets for the semantic segmentation task. The derived results reveal that the use of radiometric features yields better classification results than the use of geometric features for the considered dataset. Furthermore, the consideration of data on both modalities leads to an improvement of the classification results. However, the derived results also indicate that the use of all defined features is less favorable than the use of selected features. Consequently, data representations derived via feature extraction and feature selection techniques still provide a gain if used as the basis for deep semantic segmentation. © 2018 Copernicus GmbH. All rights reserved.

关键词： Aerial Imagery CNN Deep Learning Multi-Modal Data Residual Network Semantic Segmentation

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An efficient four-parameter affine motion model for video coding

arXiv

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arXiv 2017年

作者： Li, Li Li, Houqiang Liu, Dong Yang, Haitao Lin, Sixin Chen, Huanbang Wu, Feng CAS Key Laboratory of Technology Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei230027 China Media Technology Laboratory Central Research Institute Huawei Technologies Co. Ltd

In this paper, we study a simplified affine motion model based coding framework to overcome the limitation of translational motion model and maintain low computational complexity. The proposed framework mainly has three key contributions. First, we propose to reduce the number of affine motion parameters from 6 to 4. The proposed four-parameter affine motion model can not only handle most of the complex motions in natural videos but also save the bits for two parameters. Second, to efficiently encode the affine motion parameters, we propose two motion prediction modes, i.e., advanced affine motion vector prediction combined with a gradient-based fast affine motion estimation algorithm and affine model merge, where the latter attempts to reuse the affine motion parameters (instead of the motion vectors) of neighboring blocks. Third, we propose two fast affine motion compensation algorithms. One is the one-step sub-pixel interpolation, which reduces the computations of each interpolation. The other is the interpolation-precision-based adaptive block size motion compensation, which performs motion compensation at the block level rather than the pixel level to reduce the interpolation times. Our proposed techniques have been implemented based on the state-of-the-art high efficiency video coding standard, and the experimental results show that the proposed techniques altogether achieve on average 11.1% and 19.3% bits saving for random access and low delay configurations, respectively, on typical video sequences that have rich rotation or zooming motions. Meanwhile, the computational complexity increases of both encoder and decoder are within an acceptable range. Copyright © 2017, The Authors. All rights reserved.

关键词： Motion estimation

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A space-based radar nonlinear tracking method for air targets based on VB-PHD filter

A space-based radar nonlinear tracking method for air target...

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Signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Linlin Fang Lihua Zhong Bing Han Yuxin Hu Aerospace Information Research Institute Chinese Academy of Sciences Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems Chinese Academy of Sciences Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Space-based radar has better coverage and is not limited by the curvature of the earth. Aircraft target tracking is particularly important in space-based radar system. However, the long observation distance and strong nonlinear observation increases the challenge of target tracking. Therefore, we proposed a space-based radar nonlinear tracking method for air targets based on variational Bayesian probability hypothesis density (VB-PHD) filter. The relationship between state and observation is established. Then, the VB method is adopted to deal with uncertainty of measurement noise variances. Besides, the cubature filter is introduced to deal with the strongly nonlinear models, and the recursion process is completed by using the third-order spherical radial volume rule. Finally, simulation scenarios with different measurement noise parameters were constructed, and the tracking result comparisons show that it effectively solves nonlinear problems, and tracking precision can be significantly improved.

关键词： Solid modeling Target tracking Uncertainty Spaceborne radar Simulation Noise Measurement uncertainty Radar tracking Bayes methods Noise measurement

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Radial Velocity Ambiguity Resolution Method in Azimuth Multichannel HRWS SAR

Radial Velocity Ambiguity Resolution Method in Azimuth Multi...

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IEEE International Conference on Radar

作者： Junying Yang Xiaolan Qiu Mingyang Shang Lihua Zhong Yini Lv Chibiao Ding Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Aerospace Information Research Institute Chinese Academy of Sciences Beijing China National Key Laboratory of Microwave Imaging Technology Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665468893

For moving targets in synthetic aperture radar (SAR) images, the obvious features are defocusing and dislocation. To estimate motion parameters accurately is a premise for the precise imaging of moving targets. However, when the radial velocity of the target exceeds the maximum detectable unambiguous velocity, the estimated value by the existing methods is no longer the real value. A radial velocity ambiguity resolution method based on Imaging Space-Time Adaptive processing (ISTAP) is proposed in this paper. The proposed method has no search or iterative process and is suitable for the azimuth multichannel SAR with low pulse repetition frequency (PRF). Finally, the simulated data from an x-band azimuth six-channel SAR system verify the feasibility of the proposed method.

关键词： Baseband Image resolution Azimuth Energy resolution Imaging Estimation Radar imaging

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Visual analyses of music history: A user-centric approach

arXiv

引用

arXiv 2017年

作者： Zhang, Jingxian Liu, Dong Media Lab Massachusetts Institute of Technology CambridgeMA02139 United States CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei230027 China

Music history, referring to the records of users' listening or downloading history in online music services, is the primary source for music service providers to analyze users' preferences on music and thus to provide personalized recommendations to users. In order to engage users into the service and to improve user experience, it would be beneficial to provide visual analyses of one user's music history as well as visualized recommendations to that user. In this paper, we take a user-centric approach to the design of such visual analyses. We start by investigating user needs on such visual analyses and recommendations, then propose several different visualization schemes, and perform a pilot study to collect user feedback on the designed schemes. We further conduct user studies to verify the utility of the proposed schemes, and the results not only demonstrate the effectiveness of our proposed visualization, but also provide important insights to guide the visualization design in the future. Copyright © 2017, The Authors. All rights reserved.

关键词： Visualization

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Torque work of origin-destination flows: Quantifying urban place centrality from a physical perspective

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Computers, Environment and Urban systems 2025年 121卷

作者： Xiaorui Yan Tao Pei Ci Song Zidong Fang Xiaohan Liu Tianyu Liu Linfeng Jiang Ying Gao Guangdong Li Jie Huang Yaqin Sun State Key Laboratory of Resources and Environmental Information System Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing China College of Earth and Environmental Sciences Lanzhou University Lanzhou China Key Laboratory of Regional Sustainable Development Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China School of Environment and Spatial Informatics China University of Mining and Technology Xuzhou China

Quantifying urban place centrality, defined as its relative importance in serving its peripheral areas, provides insights into urban structures, optimizes resource allocation, and supports strategic urban planning. Centrality is shaped by three aspects: service volume, spatial reach, and directional diversity. However, existing measures often assess these factors separately and few integrate them simultaneously. Additionally, centrality analyses often overlook local perspectives and intra-day dynamics. To this end, we propose a novel origin-destination flow-based centrality measure, namely Total Torque Work (TTW), that integrates these three aspects into a single value, conceptualized as “Torque work of flow”, where flow volume, length, and direction correspond to the force magnitude, lever arm, and angular displacement. The effectiveness of the TTW is validated by simulation experiments. We apply this measure to analyze macro- and micro-centralities in Beijing, using taxi and shared bike flow data. Macro-centrality shows a monocentric structure, with higher values near railway stations, airports, and business and commercial centers. Micro-centrality is more polycentric, with subway stations exhibiting higher centrality. Time series clustering identifies three temporal patterns in both macro- and micro-centralities: two “daytime-dominant” patterns linked to multifunctional activities and commuting, and a “nighttime-dominant” pattern in residential areas. The study concludes with several implications for urban planning, emphasizing the importance of incorporating multi-spatiotemporal scales.

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Detection and analysis of landslide geomorphology based on UAV vertical photogrammetry

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Journal of Mountain Science 2024年第4期21卷 1190-1214页

作者： BI Rui GAN Shu YUAN Xiping LI Kun LI Raobo LUO Weidong CHEN Cheng GAO Sha HU Lin ZHU Zhifu School of Land and Resources Engineering Kunming University of Science and TechnologyKunming 650093China Plication Engineering Research Center of Spatial Information Surveying and Mapping Technology in Plateau and Mountainous Areas Set by Universities in Yunnan Province Kunming 650093China West Yunnan University of Applied Sciences Key Laboratory of Mountain Real Scene Point Cloud Data Processing and Application for Universities in Yunnan ProvinceDali 671006China

High-resolution landslide images are required for detailed geomorphological analysis in complex topographic environment with steep and vertical landslide *** study proposed a vertical route planning method for unmanned aerial vehicles(UAVs),which could achieve rapid image collection based on strictly calculated route *** effectiveness of this method was verified using a DJI Mavic 2 Pro,obtaining high-resolution landslide images within the Dongchuan debris flow gully,in the Xiaojiang River Basin,Dongchuan District,Yunnan,China.A three-dimensional(3D)model was constructed by the structure-from-motion and multi-view stereo(SfM-MVS).Micro-geomorphic features were analyzed through visual interpretation,geographic information system(GIS),spatial analysis,and mathematical statistics *** results demonstrated that the proposed method could obtain comprehensive vertical information on landslides while improving measurement *** 3D model was constructed using the vertically oriented flight route to achieve centimeter-level accuracy(horizontal accuracy better than 6 cm,elevation accuracy better than 3 cm,and relative accuracy better than 3.5 cm).The UAV technology could further help understand the micro internal spatial and structural characteristics of landslides,facilitating intuitive acquisition of surface *** slope of landslide clusters ranged from 36°to 72°,with the majority of the slope facing east and *** elevation levels were relatively consistent while middle to lower elevation levels gradually decreased from left to right with significant variations in lower elevation *** the rainy season,surface runoff was abundant,and steep topography exacerbated changes in surface *** route method is suitable for unmanned aerial vehicle(UAV)landslide surveys in complex mountainous *** geomorphological analysis methods used will provide references for identifying and describing topographic

关键词： UAV Landslide Vertical route SfM-MVS Topographic features

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