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Regulation effect of planted forests on land surface temperature in China

Agricultural and Forest Meteorology 2025年 372卷

作者： Zhijiang Zhang Kai Yang Lunche Wang Kai Cheng Chao Chen Chao Ding School of Geography Science and Geomatics Engineering Suzhou University of Science and Technology Suzhou 215009 China SuZhou Key Laboratory of Spatial Information Intelligent Technology and Application Suzhou University of Science and Technology Suzhou 215009 China School of Geography and Information Engineering China University of Geosciences Wuhan 430074 China Institute of Remote Sensing and Geographic Information System School of Earth and Space Sciences Peking University Beijing 100871 China Institute of Ecology College of Urban and Environmental Sciences Peking University Beijing 100871 China Department of Geographic Science Faculty of Arts and Sciences Beijing Normal University Zhuhai 519087 China

Afforestation has been regarded as a potentially effective strategy for the mitigation of climate warming. China has the largest planted forest area worldwide benefited by a series of large-scale afforestation and reforestation project since the 1970s. The planted forests (PF) have been widely reported as an enduring carbon sink. However, the climatic regulation effect of PF on climate through biophysical process remains unclear. To this end, we utilized satellite observations to quantify the impact of the conversion of grasslands (GRA), croplands (CRO) and natural forests (NF) to PF on land surface temperature (LST) between 2003 and 2012 and illustrated the underlying biophysical mechanisms based on a revised Intrinsic Biophysical Mechanism (IBM) method. The results indicated that afforestation of PF caused negligible daily cooling effect (−0.005 ± 0.002 K) compared with NF while induced obvious daily cooling effect compared with GRA (−0.253 ± 0.004 K) and CRO (−0.162 ± 0.002 K). We also demonstrated that the revised IBM attribution method is applicable in interpreting the biophysical mechanism of PF on LST. Attribution analysis revealed that the surface roughness and Bowen ratio dominated the cooling effect as the surface became rougher and more evaporative cooling after converting NF, GRA, or CRO to PF. The contributions of albedo were less stark compared with other components and presented a weak warming effect. Furthermore, the atmospheric feedback was proved that have a pronounced impact on LST and should be included in the attribution of LST change. This study focuses on the potential of PF afforestation to provide local climate adaptation benefits, filling the gaps of previous studies involved to biophysical effect failure in distinguishing NF and PF, and provides new guidance for local climate impact evaluation when implementing forestry projects.

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Development and implementation of a dynamic and 4D GIS based on semantic location model

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Geo-Spatial information Science 2019年第3期22卷 193-213页

作者： Xinyan Zhu Tao Hu Xinyue Ye Wei Guo Liang Huang Hanjiang Xiong Haojun Ai Bing She Qing Xiong Lian Duan State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanChina Collaborative Innovation Center of Geospatial Technology Wuhan UniversityWuhanChina Center for Geographic Analysis Harvard UniversityCambridgeMAUSA Department of Informatics New Jersey Institute of TechnologyNewarkNJUSA Intelligent Transportation System Research Center Wuhan University of TechnologyWuhanChina University of Michigan Ann ArborUSA Geography Science and Planning School Guangxi Normal UniversityNanningChina Key Laboratory of Environment Change and Resources Use in Beibu Gulf Guangxi Teachers Education UniversityNanningChina

In the big data era,robust solutions are obliged to be proposed to integrate and represent data from different formats and with different contents to assist the *** cartographic and geographic information systems have limited capabilities for solving these *** paper describes an automatic and comprehensive system that conducts data fusion from all potentially related *** this system,a new Semantic Location Model(SemLM)is established to present the semantic concepts and location feature and demonstrate how locations are *** the SemLM,various types of location descriptors in different application scenarios can be analyzed and ***,considering the challenges involved in data-intensive computation and visualization,this paper implements a Place-based Pan-information system(P2S)as an innovative 4D system that dynamically associates and visualizes place-based information,using public security as the case study.

关键词： Place-based pan-information system(P2S) big data semantic location model ubiquitous information 4D map

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W-net: Simultaneous segmentation of multi-anatomical retinal structures using a multi-task deep neural network

arXiv

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arXiv 2020年

作者： Zhao, Hongwei Peng, Chengtao Liu, Lei Li, Bin School of Information Science and Technology University of Science and Technology of China Hefei Anhui230022 China Department of Precision Machinery and Instrumentation University of Science and Technology of China HefeiAnhui230022 China CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei Anhui230026 China

Segmentation of multiple anatomical structures is of great importance in medical image analysis. In this study, we proposed a W-net to simultaneously segment both the optic disc (OD) and the exudates in retinal images based on the multi-task learning (MTL) scheme. We introduced a class-balanced loss and a multi-task weighted loss to alleviate the imbalanced problem and to improve the robustness and generalization property of the W-net. We demonstrated the effectiveness of our approach by applying five-fold cross-validation experiments on two public datasets e_ophtha_EX and DiaRetDb1. We achieved F1-score of 94.76% and 95.73% for OD segmentation, and 92.80% and 94.14% for exudates segmentation. To further prove the generalization property of the proposed method, we applied the trained model on the DRIONS-DB dataset for OD segmentation and on the MESSIDOR dataset for exudate segmentation. Our results demonstrated that by choosing the optimal weights of each task, the MTL based W-net outperformed separate models trained individually on each task. Code and pre-trained models will be available at: https://***/FundusResearch/MTL_for_OD_and_***. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep neural networks

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A Method for Obtaining Contact Force between Catheter Tip and Vascular Wall in Master-slave Robotic system

A Method for Obtaining Contact Force between Catheter Tip an...

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IEEE International Conference on Mechatronics and Automation

作者： Xiaoliang Jin Shuxiang Guo Jian Guo Peng Shi Dapeng Song Faculty of Engineering and Design Kagawa University 2217-20 Hayashi-cho Takamatsu Kagawa Japan Key Laboratory of Convergence Medical Engineering System and Healthcare Technology the Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology Beijing China Tianjin Key Laboratory for Control Theory and Application in Complicated Systems and Intelligent Robot Laboratory Tianjin University of Technology Tianjin China

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

In the research of vascular interventional surgery robotic system, the force information acquisition of surgical tools (guidewires and catheters) has a significant affect on the safety of surgery, especially the contact force between the catheter tip and vascular wall. Therefore. In order to obtain this contact force, we noticed the pressure sensitive rubber because of its piezoresistive effect and easy processing into any shape. a force sensor based on the pressure sensitive rubber was developed in this paper. Once a force is applied on the force sensor attached to the catheter tip, the contact force can be approximated by the piezoresistive effect of the pressure sensitive rubber. The feasibility of the developed force sensor was verified by the experiments in “Vitro”. And the results showed that the force sensor was developed in this paper can accurately detect the contact force between the catheter tip and vascular wall at different positions in the vascular model, the extraction of contact force information of catheter tip is of great significance to the safety of surgery, and the application potential of pressure sensitive rubber.

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Transient Fault Diagnosis Algorithm based on Feature Classification and Its application in High-Power Laser facility

Transient Fault Diagnosis Algorithm based on Feature Classif...

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第32届中国控制与决策会议

作者： Qiang Ren Hang Gao Hailei Ren Baoran An Tianyou Yun Xiaoli Wang Institute of Computer Application China Academy of Engineering Physics State Key Laboratory of Complex Electromagnetic Environmental Effects on Electronics and Information System College of Electronic Science and TechnologyNational University of Defense Technology Institute of Fluid Physics China Academy of Engineering Physis

High-power laser facility plays an import role both in scientific research and military application,and the occurred faults are usually *** this paper,a transient fault diagnosis algorithm based on feature classification is proposed,and the algorithm has been applied in the high-power laser *** method extracts the features of input data with an autoencoder *** based on the extracted features,a multi-layer full connection neural network is adopted for fault *** comparing the results with those obtained by traditional fault diagnosis methods,the performance of the algorithm has been verified.

关键词： High-power laser facility transient fault diagnosis feature-extraction

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InSAR DEM Reconstruction Based on Backprojection Algorithm in Two Converse Flights 6

InSAR DEM Reconstruction Based on Backprojection Algorithm i...

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

作者： Hu, Xiaoning Xiang, Maosheng Wang, Bingnan Fu, Xikai University of Chinese Academy of Sciences National Key Laboratory of Science and Technology on Microwave Imaging Institute of Electronics Chinese Academy of Sciences Beijing100190 China National Key Laboratory of Science and Technology on Microwave Imaging Institute of Electronics Chinese Academy of Sciences Beijing100190 China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781728129129

Interferometric synthetic aperture radar (InSAR) can be used to extract digital elevation model (DEM) with high accuracy. However, the side looking geometry of synthetic aperture radar (SAR) may cause geometric distortions such as shadow and layover in the mountainous terrain, which will reduce the quality of generated DEM. Fusion of two or more different aspects of InSAR data can deal with this problem. We propose an InSAR DEM reconstruction method based on backprojection (BP) algorithm in two converse flights. This method utilizes the feature of BP algorithm that geocoding has been realized in imaging process to simplify the fusion process of multi-aspect InSAR data. In addition, an iterative DEM extraction method is introduced to improve DEM accuracy. Experimental results verify the effectiveness of the proposed method. © 2019 IEEE.

关键词： Synthetic aperture radar

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Classification of Cognitive Ability of Healthy Elderly Individuals Using Resting-State Functional Connectivity Magnetic Resonance Imaging and An Extreme Learning Machine

Research Square

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Research Square 2021年

作者： Yang, Zekun Ge, Manling Abdelkader, Nasreddine Belkacem Fu, Xiaoxuan Zhang, Qirui Chen, Shenghua Xie, Chong Song, Zibo Chen, Chao State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin300130 China Hebei Province Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability Hebei University of Technology Tianjin300130 China Department of Computer and Network Engineering College of Information Technology United Arab Emirates University Al Ain15551 United Arab Emirates Athinoula A. Martinos Center for Biomedical Imaging Department of Radiology Massachusetts General Hospital Harvard Medical School CharlestownMA02129 United States Department of Medical Imaging Jinling Hospital Nanjing University School of Medicine General Hospital of Eastern Theater Nanjing210002 China Key Laboratory of Complex System Control Theory and Application Tianjin University of Technology Tianjin300003 China

Purpose Quantitative determination of the correlation between cognitive ability and functional biomarkers in the elderly brain is essential. To identify biomarkers associated with cognitive performance in the elderly, this study combined an index model specific for resting-state functional connectivity (FC) magnetic resonance imaging (fcMRI) with a supervised machine learning method. Methods Performance scores on conventional cognitive test batteries and MRI data were obtained for 98 healthy elderly individuals and 90 healthy youth from two public databases. Based on the test scores, the elderly cohort was categorized into two groups: excellent and poor. An fcMRI index model was constructed for each elderly individual to determine the relative differences in FC among brain regions compared with that in the youth cohort. Brain areas sensitive to test scores could then be identified using the fcMRI indexes. To confirm the effectiveness of constructed model, the fcMRI indexes of these brain areas were used as feature matrix inputs for training an extreme learning machine. Classification accuracy was then tested in separate groups and confirmed by N-fold cross-validation. Results This learning study could effectively classify the cognitive status of healthy elderly individuals according to frontal lobe, temporal lobe, and parietal lobe FC values with a mean accuracy of 83.5%, which is substantially higher than that achieved using conventional correlation analysis. Conclusion This fcMRI classification study may facilitate early detection of age-related cognitive decline as well as help reveal the underlying pathological mechanisms. © 2021, CC BY.

关键词： Magnetic resonance imaging

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Region Normalization for Image Inpainting

arXiv

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arXiv 2019年

作者： Yu, Tao Guo, Zongyu Jin, Xin Wu, Shilin Chen, Zhibo Li, Weiping Zhang, Zhizheng Liu, Sen CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China China

Feature Normalization (FN) is an important technique to help neural network training, which typically normalizes features across spatial dimensions. Most previous image inpainting methods apply FN in their networks without considering the impact of the corrupted regions of the input image on normalization, e.g. mean and variance shifts. In this work, we show that the mean and variance shifts caused by full-spatial FN limit the image inpainting network training and we propose a spatial region-wise normalization named Region Normalization (RN) to overcome the limitation. RN divides spatial pixels into different regions according to the input mask, and computes the mean and variance in each region for normalization. We develop two kinds of RN for our image inpainting network: (1) Basic RN (RN-B), which normalizes pixels from the corrupted and uncorrupted regions separately based on the original inpainting mask to solve the mean and variance shift problem;(2) Learnable RN (RN-L), which automatically detects potentially corrupted and uncorrupted regions for separate normalization, and performs global affine transformation to enhance their fusion. We apply RN-B in the early layers and RN-L in the latter layers of the network respectively. Experiments show that our method outperforms current state-of-the-art methods quantitatively and qualitatively. We further generalize RN to other inpainting networks and achieve consistent performance improvements. Our code is available at https://***/geekyutao/RN. Copyright © 2019, The Authors. All rights reserved.

关键词： Pixels

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DRBOX FAMILY: A GROUP OF OBJECT DETECTION TECHNIQUES FOR REMOTE SENSING IMAGES

DRBOX FAMILY: A GROUP OF OBJECT DETECTION TECHNIQUES FOR REM...

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IEEE International Geoscience and Remote Sensing Symposium

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

Objects in remote sensing images are difficult to detect due to arbitrarily rotated angles and the wide variance of scales. As bounding box plays an important role in object detection, we proposes a new bounding box type named rotated bounding box (rBox). With the application of rBox, we have proposed a series of detection techniques (DrBox, DrBoxLight, DrBoxSemi, DrBoxPro) to effectively handle the situation where the orientation angles of the objects are arbitrary. This article is a brief overview of these techniques. The original DrBox detector applies VGG-net as its main network framework, with image pyramid input to address multi-scale problem. DrBoxLight is a mini version of DrBox, which applies MobileNet and knowledge distillation to be deployed on embedded devices. DrBoxSemi is a semi-supervised version of DrBox, so annotation of all training samples is no longer necessary. DrBoxPro is the most important update for DrBox with professional designing of abundant prior-rBoxes on feature pyramid networks. In our experiments, we demonstrated how rBox helps to improve the performance of object detection compared with traditional bounding boxes. Besides, we evaluated the performance of our DrBox family on a series of object detection tasks.

关键词： Object detection Remote sensing images Rotated object Deep learning

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Robust Beamformer based on Magnitude Response Constraint and Sparse Constraint

Robust Beamformer based on Magnitude Response Constraint and...

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2019 IEEE International Conference on Signal, information and Data Processing, ICSIDP 2019

作者： Lei, Songlin Qiu, Xiaolan DIng, Chibiao Zhang, Yueting Aerospace Information Research Institute Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Technology in Geo-spatial Information Processing and Application System CAS China Institute of Electronics Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781728123455

Beamformer with magnitude response constraint can flexibly control the response region by specified beamwidth and response ripple, which has a significant performance against steering vector mismatch. However, a high sidelobe level of the beam is accompanied, resulting in performance degradation. To solve this problem, a novel robust beamformer based on magnitude response constraint and sparse constraint is proposed. This method adds the sparse constraint, that is, Lp-norm to the beamformer with magnitude response constraint, then the non-convex cost function can be formulated as a semidefinite programming (SDP) problem, finally the matrix decomposition theory is used to get the array weight vector. Simulation results demonstrate that the proposed method can not only produce large controlled region against steering vector mismatch and reduce the sidelobe level of the beampattern, but also achieve good performance in Signal to Interference plus Noise Ratio (SINR) enhancement. © 2019 IEEE.

关键词： Vectors

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