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UAVs as remote sensing platforms in plant ecology:review of applications and challenges

Journal of Plant Ecology 2021年第6期14卷 1003-1023页

作者： Zhongyu Sun Xiaonian Wang Zhihui Wang Long Yang Yichun Xie Yuhui Huang Guangdong Open Laboratory of Geospatial Information Technology and Application Guangzhou Institute of GeographyGuangdong Academy of SciencesGuangzhou 510070China School of Geographical Sciences South China Normal UniversityGuangzhou 510631China Department of Geography and Geology Eastern Michigan UniversityYpsilantiMI 48197USA Guangdong Provincial Key Laboratory of Silviculture Protection and UtilizationGuangdong Academy of ForestryGuangzhou 510520China

Aims Unmanned aerial vehicles(UAVs),***,have recently emerged as cost-effective and flexible tools for acquiring remote sensing data with fine spatial and temporal *** provides a new method and opportunity for plant ecologists to study issues from individual to regional ***,as a new method,UAVs remote sensing applications in plant ecology are still *** needs of plant ecology research and the application development of UAVs remote sensing should be better *** This report provides a comprehensive review of UAV-based remote sensing applications in plant ecology to synthesize prospects of applying drones to advance plant ecology *** Findings Of the 400 references,59%were published in remote sensing journals rather than in plant ecology journals,reflecting a substantial gap between the interests of remote sensing experts and plant *** of the studies focused on UAV remote sensing’s technical aspects,such as data processing and remote sensing inversion,with little attention on answering ecological *** were 61%of studies involved community-scale *** and multispectral cameras were the most used sensors(75%).More ecologically meaningful parameters can be extracted from UAV data to better understand the canopy surface irregularity and community heterogeneity,identify geometrical characteristics of canopy gaps and construct canopy chemical assemblies from living vegetation *** cooperation between plant ecologists and remote sensing experts is needed to promote UAV remote sensing in advancing plant ecology research.

关键词： UAVs drones unmanned aircraft systems(UASs) plant ecology species identification community function

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OBJECT DETECTION WITH HEAD DIRECTION IN REMOTE SENSING IMAGES BASED ON ROTATIONAL REGION CNN

OBJECT DETECTION WITH HEAD DIRECTION IN REMOTE SENSING IMAGE...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Xue Yang Kun Fu Hao Sun Xian Sun Menglong Yan Wenhui Diao Zhi Guo Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China

Object detection has been playing a significant role in the field of remote sensing for a long time but it is still full of challenges. In this paper, we propose a novel detection framework based on rotational region convolution neural network to cope with the problem of non-maximum suppression in dense objects detection. The bounding boxes obtained by adopting our method is the minimum bounding rectangle of object with less redundant regions. Furthermore, we find the head direction of the object through prediction. There are three important changes to our framework over traditional detection methods, representation and regression of rotational bounding box, head direction prediction and rotational non-maximal suppression. Experiments based on remote sensing images from Google Earth for Object detection show that our detection method based on rotational region CNN has a competitive performance.

关键词： Object detection Rotating region Convolution neural network Prediction Non-maximal suppression

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An improved method to sort and pair TDOA based on the correlation between TDOAs

An improved method to sort and pair TDOA based on the correl...

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6th International Conference on Radar, RADAR 2011

作者： Ren, Wen-Juan Hu, Dong-Hui Ding, Chi-Biao Institute of Electronics Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing 100190 China Graduate School Chinese Academy of Sciences No. 19 North 4yh Ring Road West Haidian District Beijing 100190 China

ISBN: (纸本)9781424484416

In TDOA passive location system, the situations in which false TDOA combinations arose are sorted. For extracting the correct TDOA combination of the radiant source, an improved method to sort and pair TDOA is proposed in this paper. The method can eliminate the false TDOA combinations which are reduced by sub-PRI(pulse repetition interval) of the radiant source with high pulse repetition frequency(PRF) and the equality of multiple targets' TDOAs, and associate all TDOA combinations which belong to the same target. The method enhances the accuracy of extracting TDOA combination and reduces the computation load and the complexity of afterward processing. © 2011 IEEE.

关键词： Time difference of arrival

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Beam quality improvement of the high-energy KTA-OPO based on a confocal unstable cavity with Gaussian reflectivity mirror

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Chinese Optics Letters 2023年第5期21卷 42-46页

作者：孟君李晨丛振华赵智刚王上刘高佑刘兆军 School of Information Science and Engineering Shandong UniversityQingdao 266237China Shandong Provincial Key Laboratory of Laser Technology and Application Qingdao 266237China Key Laboratory of Laser&Infrared System(Shandong University Ministry of EducationQingdao 266237China Center for Optics Research and Engineering Shandong UniversityQingdao 266237China

A high-energy 100-Hz optical parametric oscillator(OPO)based on a confocal unstable resonator with a Gaussian reflectivity mirror was demonstrated.A KTA-based OPO with a good beam quality was obtained when the magnification factor was 1.5,corresponding to the maximum signal(1.53μm)energy of 56 m J and idler(3.47μm)energy of 20 m J,*** beam quality factors(M^(2))were measured to be M^(2)_(x)=5.7,M^(2)_(y)=5.9 for signal and M^(2)_(x)=8.4,M^(2)_(y)=8.1 for idler *** experimental results indicated that the beam quality positively changed with the increase of magnification factors,accompanied by an acceptable loss of pulse energy.

关键词： optical parametric oscillators confocal unstable resonator beam quality

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Waterline mapping of inland great lake with subpixel accuracy from GF-3 SAR images 6

Waterline mapping of inland great lake with subpixel accurac...

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6th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2019

作者： Li, Ning Niu, Shilin Wang, Robert Wu, Lin Guo, Zhengwei College of Computer and Information Engineering Henan University Kaifeng475004 China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng475004 China Henan Engineering Research Center of Intelligent Technology and Application Kaifeng475004 China Department of Space Microwave Remote Sensing System Institute of Electronics Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781728129129

High-accuracy waterline mapping with Synthetic Aperture Radar (SAR) images is a challenging task because of the inhomogeneities of SAR imagery caused by the speckle noise and complex terrain. This paper presents a novel method for waterline mapping with subpixel accuracy. The proposed method mainly consists of three steps. Firstly, an improved Non-Local filter is adapted to suppress the speckle noise. Secondly, a Fuzzy C-Means (FCM) clustering algorithm is used to extract the pixel-level waterline. Thirdly, along the pixel-level waterline, a novel subpixel-scale waterline extraction method based on bicubic convolution and Geometric Active Contour (GAC) model is presented to further improve the accuracy of the waterline. Without loss of generality, the Danjiangkou reservoir (DJKR), which is the largest artificial freshwater lake in Asia, is selected as a study case. SAR images from Chinese GaoFen-3 (GF-3) satellite working on different modes are processed to demonstrate the effectiveness of the proposed method. © 2019 IEEE.

关键词： Synthetic aperture radar

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SPATIO-TEMPORAL ASSESSMENT OF ECOsystem SERVICES VALUE ON REGIONAL SCALE

SPATIO-TEMPORAL ASSESSMENT OF ECOSYSTEM SERVICES VALUE ON RE...

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World Automation Congress 2010

作者： JINGCHENG ZHANG YAN JIN WENJIANG HUANG XIAOHE GU JINGFENG HUANG JIHUA WANG National Engineering Research Center for Information Technology in Agriculture Ministry of Education Key Laboratory of Environmental Remediation and Ecological Health Zhejiang University Institute of Agricultural Remote Sensing and Information Application Zhejiang Academy of Surveying and Mapping Key Laboratory of Agricultural Remote Sensing and Information System of Zhejiang Province

Based on geographical informatics system(GIS)and remote sensing(RS)technologies,we developed an improved valuation model system of ecosystem services value(ESV)assessment and evaluated the value of Zhejiang Province from November2004 to December 2005 with monthly time *** parts of ecosystem services(ES)were included,and they were producing organic matter,atmospheric gas regulation,recycling nutrient matter,holding water resources and conserving soil and *** universal soil loss equation(USLE)was applied for estimating the service value of conserving soil and water which expected to improve the effect of *** the results,the overall value in the entire region was 1636.81xl08 RMB,with unbalanced constitution of 5 parts.A clear seasonal division was shown in the overall value and most *** distribution pattern in latitude,longitude,altitude was revealed *** parts of ecosystem services performed consistently response to both seasonal and spatial variation,except for the service of holding water resources and conserving soil and *** major characteristics of ESV distribution can be roughly explained by the distribution and variation pattern of NPP and other crucial meteorological *** assessment of ESV by integrating multi-sourced data can provide an relatively objective result and have some indications for natural resources management.

关键词： Remote Sensing Net Primary Production(NPP) Universal Soil Loss Equation(USLE) Ecosystem Services Value

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RELAXATION LABELLING BASED LAND MASKING IN SAR IMAGES

RELAXATION LABELLING BASED LAND MASKING IN SAR IMAGES

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IEEE International Geoscience and Remote Sensing Symposium

作者： Zongxu Pan Lei Liu Bin Lei Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Chinese Academy of Sciences Beijing China

In this paper, a relaxation labelling based land masking method is proposed for separating sea and land in SAR images. Land masking, also known as sea-land segmentation, is a part of ship detection system for SAR images to avoid detecting false alarms in the land. Relaxation labeling is an iterative method, which can separate foreground pixels from background ones using the neighborhood information of pixels in the image. When relaxation labelling converges, the segmented result is often unsatisfactory, since it tends to label more foreground pixels. To overcome this issue, a loss composed of the background probability distribution diversity and the gradient magnitude of the result is introduced to indicate when to stop the iteration. Experimental results on several Gaofen-3 SAR images demonstrate the effectiveness of the proposed method.

关键词： Labeling Image segmentation Synthetic aperture radar Marine vehicles Probability distribution Morphology Iterative methods

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Visual analyses of music history: A user-centric approach

arXiv

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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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HIGH QUALITY REMOTE SENSING IMAGE SUPER-RESOLUTION USING DEEP MEMORY CONNECTED NETWORK

HIGH QUALITY REMOTE SENSING IMAGE SUPER-RESOLUTION USING DEE...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Wenjia Xu Guangluan Xu Yang Wang Xian Sun Daoyu Lin Yirong Wu Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China

Single image super-resolution is an effective way to enhance the spatial resolution of remote sensing image, which is crucial for many applications such as target detection and image classification. However, existing methods based on the neural network usually have small receptive fields and ignore the image detail. We propose a novel method named deep memory connected network (DMCN) based on a convolutional neural network to reconstruct high-quality super-resolution images. We build local and global memory connections to combine image detail with environmental information. To further reduce parameters and ease time-consuming, we propose down-sampling units, shrinking the spatial size of feature maps. We test DMCN on three remote sensing datasets with different spatial resolution. Experimental results indicate that our method yields promising improvements in both accuracy and visual performance over the current state-of-the-art.

关键词： Spatial resolution Remote sensing Image reconstruction Training Convolutional neural networks Satellites

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SPHR-SAR-Net: Superpixel High-resolution SAR Imaging Network Based on Nonlocal Total Variation

arXiv

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arXiv 2023年

作者： Zhou, Guoru Xu, Zhongqiu Fan, Yizhe Zhang, Zhe Qiu, Xiaolan Zhang, Bingchen Fu, Kun Wu, Yirong The Key Laboratory of Technology in Geo-spatial Information Processing Application System Chinese Academy of Sciences Beijing China Suzhou Key Laboratory of Microwave Imaging Processing and Application Technology Suzhou Aerospace Information Research Institute Jiangsu Suzhou China Aerospace Information Research Institute Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China

High-resolution is a key trend in the development of synthetic aperture radar (SAR), which enables the capture of fine details and accurate representation of backscattering properties. However, traditional high-resolution SAR imaging algorithms face several challenges. Firstly, these algorithms tend to focus on local information, neglecting non-local information between different pixel patches. Secondly, speckle is more pronounced and difficult to filter out in high-resolution SAR images. Thirdly, the process of high-resolution SAR imaging generally involves high time and computational complexity, making real-time imaging difficult to achieve. To address these issues, we propose a Superpixel High-Resolution SAR Imaging Network (SPHR-SAR-Net) for rapid despeckling in high-resolution SAR mode. Based on the concept of superpixel techniques, we initially combine nonconvex and non-local total variation as compound regularization. This approach more effectively despeckles and manages the relationship between pixels while reducing bias effects caused by convex constraints. Subsequently, we solve the compound regularization model using the Alternating Direction Method of Multipliers (ADMM) algorithm and unfold it into a Deep Unfolded Network (DUN). The network’s parameters are adaptively learned in a data-driven manner, and the learned network significantly increases imaging speed. Additionally, the Deep Unfolded Network is compatible with high-resolution imaging modes such as spotlight, staring spotlight, and sliding spotlight. In this paper, we demonstrate the superiority of SPHR-SAR-Net through experiments in both simulated and real SAR scenarios. The results indicate that SPHR-SAR-Net can rapidly perform high-resolution SAR imaging from raw echo data, producing accurate imaging results. Copyright © 2023, The Authors. All rights reserved.

关键词： Synthetic aperture radar

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