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Journal of Remote Sensing 2023年第1期3卷 19-34页

作者： Zhongbing Chang Lei Fan Jean-Pierre Wigneron Ying-Ping Wang Philippe Ciais Jérôme Chave Rasmus Fensholt Jing MChen Wenping Yuan Weimin Ju Xin Li Fei Jiang Mousong Wu Xiuzhi Chen Yuanwei Qin Frédéric Frappart Xiaojun Li Mengjia Wang Xiangzhuo Liu Xuli Tang Sanaa Hobeichi Mengxiao Yu Mingguo Ma Jianguang Wen Qing Xiao Weiyu Shi Dexin Liu Junhua Yan Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems South China Botanical GardenChinese Academy of SciencesGuangzhou 510650China University of Chinese Academy of Sciences Beijing 100049China Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station School of Geographical SciencesSouthwest UniversityChongqing 400715China INRAE UMR1391 ISPAUniversite de BordeauxF-33140 Villenave d’OrnonFrance CSIRO Oceans and Atmosphere AspendaleVIC 3195Australia Laboratoire des Sciences du Climat et de l’Environnement CEA/CNRS/UVSQ/Universite Paris SaclayGif-sur-YvetteFrance Laboratoire Evolution et Diversite Biologique Universite Paul SabatierToulouseFrance Department of Geosciences and Natural Resource Management University of CopenhagenCopenhagenDenmark Department of Geography and Program in Planning University of TorontoTorontoON M5S 3G3Canada College of Geographical Science Fujian Normal UniversityFuzhou 3500007FujianChina School of Atmospheric Sciences Sun Yat-sen UniversityZhuhai 519082GuangdongChina Southern Marine Science and Engineering Guangdong Laboratory Zhuhai 519000GuangdongChina Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology International Institute for Earth System ScienceNanjing UniversityNanjing 210023China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing 210023China Institute of Tibetan Plateau Research Chinese Academy of SciencesBeijing 100101China CAS Center for Excellence in Tibetan Plateau Earth Sciences Chinese Academy of SciencesBeijing 100101China Department of Microbiology and Plant Biology Center for Spatial AnalysisUniversity of OklahomaNormanOKUSA LEGOS Universite de ToulouseCNESCNRSIRDUPS-14 avenue Edouard Belin31400 ToulouseFrance State Key Laboratory of Remote Sensing Science Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China Climate Change Research Centre University of N

Over the past 2 to 3 decades,Chinese forests are estimated to act as a large carbon sink,yet the magnitude and spatial patterns of this sink differ considerably among *** 3 microwave(L-and X-band vegetation optical depth[VOD])and 3 optical(normalized difference vegetation index,leaf area index,and tree cover)remote-sensing vegetation products,this study compared the estimated live woody aboveground biomass carbon(AGC)dynamics over China between 2013 and *** results showed that tree cover has the highest spatial consistency with 3 published AGC maps(mean correlation value R=0.84),followed by L-VOD(R=0.83),which outperform the other *** AGC estimation model was proposed to combine all indices to estimate the annual AGC dynamics in China during 2013 to *** performance of the AGC estimation model was good(root mean square error=0.05 Pg C and R^(2)=0.90 with a mean relative uncertainty of 9.8% at pixel scale[0.25°]).Results of the AGC estimation model showed that carbon uptake by the forests in China was about+0.17 Pg C year^(-1) from 2013 to *** the regional level,provinces in southwest China including Guizhou(+22.35 Tg C year^(-1)),Sichuan(+14.49 Tg C year^(-1)),and Hunan(+11.42 Tg C year^(-1))provinces had the highest carbon sink rates during 2013 to *** of the carbon-sink regions have been afforested recently,implying that afforestation and ecological engineering projects have been effective means for carbon sequestration in these regions.

关键词： estimation Remote microwave

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Gravitational Wave-Sensitive Photonic-Like Electronic Transport in Graphene for Efficient High-Frequency Gravitational Wave Detection

arXiv

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arXiv 2024年

作者： Shen, Shen Lin, Liangzhong Li, Linfu Liu, Jiang-Tao Wu, Xin Wu, Zhenhua School of Physics and Mechatronic Engineering Guizhou Minzu University Guiyang550025 China School of Physics Zhejiang University Hangzhou310027 China The Key Laboratory of Optoelectronic Technology & System Education Ministry of China Chongqing University Chongqing400044 China School of Information Engineering Zhongshan Polytechnic Zhongshan528400 China School of Mathematics Physics and Statistics Shanghai University of Engineering Science Shanghai201620 China School of Mathematics Physics and Statistics Center of Application and Research of Computational Physics Shanghai University of Engineering Science Shanghai201620 China

High-frequency gravitational waves are crucial for understanding the very early universe and distinguishing between various cosmological models, but detecting them remains a significant challenge. We investigated the effects of high-frequency gravitational waves on photonic-like electronic transport in graphene. The results show that, unlike the influence of gravitational waves on the propagation of light, the influence of gravitational waves on photonic-like electronic transport can accumulate not only in real space but also in k-space. This makes photonic-like electronic transport under gravitational waves similar to the propagation of light in a medium where the refractive index varies dramatically due to gravitational waves, and with shorter wavelengths. As a result, the relative intensity variation in photonic-like electronic transport under gravitational waves exceeds that of a laser interferometer with the same arm length by six orders of magnitude. At low temperatures, the influence of phonons on photon-like transport in the context of high-frequency gravitational waves can be ignored. These findings indicate a strong interaction between gravitational waves and electron transport, which helps to deepen the understanding of the interaction between gravitational waves and matter, and provides a different method for detecting high-frequency gravitational waves. Copyright © 2024, The Authors. All rights reserved.

关键词： Gravitational effects

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Coupled Pacific Rim megadroughts contributed to the fall of the MingDynasty’s capital in 1644 CE

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Science Bulletin 2024年第19期69卷 3106-3114页

作者： Feng Chen Tao Wang Xiaoen Zhao Jan Esper Fredrik Charpentier Ljungqvist Ulf Büntgen Hans W.Linderholm David Meko Hongna Xu Weipeng Yue Shijie Wang Yujiang Yuan Jingyun Zheng Wei Pan Fidel Roig Martín Hadad Mao Hu Jiachang Wei Fahu Chen Yunnan Key Laboratory of International Rivers and Transboundary Eco-Security Institute of International Rivers and Eco-SecurityYunnan UniversityKunming 650504China Southwest United Graduate School Kunming 650504China Climate Change Research Center and Nansen-Zhu International Research Centre Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Department of Geography Johannes Gutenberg UniversityMainz 55099Germany Global Change Research Institute(CzechGlobe) Czech Academy of SciencesBrno 60300Czech Republic Department of History Stockholm UniversityStockholm 10691Sweden Bolin Centre for Climate Research Stockholm UniversityStockholm 10691Sweden Swedish Collegium for Advanced Study LinneanumUppsala 75238Sweden Department of Geography University of CambridgeCambridge CB23ENUK Department of Geography Faculty of ScienceMasaryk UniversityBrno 61137Czech Republic Swiss Federal Research Institute(WSL) Birmensdorf 8903Switzerland Regional Climate Group Department of Earth SciencesUniversity of GothenburgGothenburg 40530Sweden Laboratory of Tree-Ring Research University of ArizonaTucson AZ 85721USA Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC FEMD) Nanjing University of Information Science and TechnologyNanjing 210044China Key Laboratory of Tree-ring Physical and Chemical Research Institute of Desert MeteorologyChina Meteorological AdministrationUrumqi 830002China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China Key Laboratory of Digital Human Technology R&D and Application of Yunnan Provincial Department of Education Yunnan UniversityKunming 650504China Laboratorio de Dendrocronología e Historia Ambiental IANIGLA-CCT CONICET-Universidad Nacional de CuyoMendoza 5500Argentina Hémera Centro de Observación de La Tierra Escuela de Ingeniería ForestalFacultad de CienciasUniversidad MayorHuechuraba 85

Historical documents provide evidence for regional droughts preceding the political turmoil and fall of Beijing in 1644 CE,when more than 20 million people died in northern China during the late Ming famine ***,the role climate and environmental changes may have played in this pivotal event in Chinese history remains ***,we provide tree-ring evidence of persistent megadroughts from1576 to 1593 CE and from 1628 to 1644 CE in northern China,which coincided with exceptionally cold summers just before the fall of *** analysis reveals that these regional hydroclimatic extremes are part of a series of megadroughts along the Pacific Rim,which not only impacted the ecology and society of monsoonal northern China,but likely also exacerbated external geopolitical and economic *** finding is corroborated by last millennium reanalysis data and numerical climate model simulations revealing internally driven Pacific sea surface temperature variations and the predominance of decadal scale La Ni?a-like conditions to be responsible for precipitation decreases over northern China,as well as extensive monsoon regions in the *** teleconnection patterns provide a mechanistic explanation for reoccurring drought spells during the late Ming Dynasty and the environmental framework fostering the fall of Beijing in 1644 CE,and the subsequent demise of the Ming Dynasty.

关键词： Paleoclimate Beijing Precipitation reconstruction Climate-society interactions Tree rings Ming Dynasty

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Gas phase multicomponent detection and analysis combining broadband dual-frequency comb absorption spectroscopy and deep learning

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Communications Engineering 2023年第1期2卷 54页

作者： Tian, Linbo Xia, Jinbao Kolomenskii, Alexandre A. Schuessler, Hans A. Zhu, Feng Li, Yanfeng He, Jingliang Dong, Qian Zhang, Sasa Key Laboratory of Education Ministry for Laser and Infrared System Integration Technology Shandong University 72 Binhai Road Qingdao 266237 China Shandong Provincial Key Laboratory of Laser Technology and Application Shandong University 72 Binhai Road Qingdao 266237 China State Key Laboratory of Crystal Materials Institute of Novel Semiconductors Shandong University Jinan 250100 China Department of Physics and Astronomy Texas A & amp M University College Station 77843-4242 TX United States School of Physics and Astronomy Sun Yat-sen University Guangdong Zhuhai 519082 China Department of Communications and Networking Xi’an Jiaotong-Liverpool University 111 Ren’ai Road Dushu Lake Higher Education Town SIP Suzhou 215123 China School of Information Science and Engineering Shandong University 72 Binhai Road Qingdao 266237 China

In absorption spectroscopy, analysis of multicomponent gas mixtures becomes challenging when absorption features overlap (blended spectra). Here we propose a gas sensor which can accurately identify the species and retrieve the concentrations of components in a gaseous mixture in a broad spectrum. The sensor integrates a mid-infrared dual-frequency comb laser source for spectrum acquisition and a deep learning algorithm for spectral analysis. The sensor was tested on gas phase mixtures of methane, acetone and water vapor. A prototype sensor was assessed in realistic scenarios in real time. We also systematically analyzed and presented explicit visualizations to explain the underlying working mechanism of the algorithms. © The Author(s) 2023.

关键词： Infrared spectroscopy Computer science

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Spatio-temporal Distribution of Drought in the Belt and Road Area During 1998–2015 Based on TRMM Precipitation Data

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Journal of Resources and Ecology 2017年第6期8卷 559-570页

作者： BAI Yongqing WANG Juanle WANG Yujie HAN Xuehua Bair Z. Tsydypov Altansukh Ochir Davaadorj Davaasuren State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China University of Chincse Academy of Sciences Beijing 100049 China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing 210023 China Shandong University of Technology Zibo Shandong 255012 China Baikal Institute of Nature Management Siberian Branch Russian Academy of Sciences U lan-Ude 670047 Russia School of Engineering and Applied Sciences National University of Mongolia Ulaanbaatar city 210646 Mongolia Department of the Geography School of the Art ＆ Sciences National University of Mongolia Ulaanbaatar city 210646 Mongolia

Drought is a worldwide natural disaster that has long affected agricultural production as well as social and economic activities. Frequent droughts have been observed in the Belt and Road area, in which much of the agricultural land is concentrated in fragile ecological environment. Based on the Tropical Rainfall Measuring Mission Satellite（TRMM） 3 B43 precipitation data, we used the Precipitation Abnormity Percentage drought model to study the monthly spatio-temporal distribution of drought in south region of N50° of the Belt and Road area. It was observed that drought during winter was mainly distributed in Northeast Asia, Southeast Asia, and South Asia, while it was mainly distributed in Central Asia and West Asia during summer. The occurrence of historical droughts indicates an obvious seasonal cycle. The regional variations in drought were analyzed using the Breaks for Additive Season and Trend tool（BFAST） in six sub-regions according to the spatial distribution of six economic corridors in the Belt and Road area. The average drought conditions over the 18 years show a slight decreasing trend in Northeast Asia, West Asia, North Africa, South Asia, Central and Eastern Europe, and a slight increasing trend in Central Asia. However, it was a fluctuating pattern of first increasing and then decreasing in Southeast Asia. The results indicate that the total drought area in the Belt and Road region showed a general decreasing trend at a rate of 40,260 km^2 per year from 1998 to 2015.

关键词： drought distribution the Belt and Road TRMM Precipitation Abnormity Percentage BFAST

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An improved semi-global matching method with optimized matching aggregation constraint

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IOP Conference Series: Earth and Environmental Science 2020年第1期569卷

作者： Xu Huang Yilong Han Kun Hu School of Geospatial Engineering and Science Sun Yat-sen University Rongyuan Road 4 Zhuhai China Wuhan Engineering Science and Information Institute Jiangda Road 30 Wuhan China School of Remote Sensing and Information Engineering Luoyu Road 129 Wuhan China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences No. 19 North 4th Ring Road West 100190 Beijing China

Stereo dense image matching (DIM) is a key technique in generating dense 3D point clouds at low cost, among which semi-global matching (SGM) is one of the best compromise between the matching accuracy and the time cost. Most commercial or open-source DIM software packages therefore adopt SGM as the core algorithm for the 3D point generation, which computes matching results in 2D image space by simply aggregating the matching results of multi-directional 1D paths. However, such aggregations of SGM did not consider the disparity consistency between adjacent pixels in 2D image space, which will finally decrease the matching accuracy. To achieve higher-accuracy while keep the high time efficiency of SGM, this paper proposes an improved SGM with a novel matching aggregation optimization constraint. The core algorithm formulates the matching aggregation as the optimization of a global energy function, and a local solution of the energy function is utilized to impose the disparity consistency between adjacent pixels, which is capable of removing noises in the matching aggregation results and increasing the final matching accuracy at low time cost. Experiments on aerial image dataset show that the proposed method outperformed the traditional SGM method and another improved SGM method. Compared with the traditional SGM, our proposed method can increase the average matching accuracy by at most 11%. Therefore, our proposed method can applied in some smart 3D applications, e.g. 3D change detection, city-scale reconstruction, and global survey mapping.

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Intelligent Identification of Building Patches and Assessment of Roof Greening Suitability in High-density Urban Areas:A Case Study of Chengdu

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Journal of Resources and Ecology 2022年第2期13卷 247-256页

作者： LUO Luhua CHEN Mingjie DONG Lulu SU Wei LI Xin HU Xiaodong ZHANG Xin LI Chen CHENG Weiming SHI Hanning LUO Jiancheng Faculty of Geomatics Lanzhou Jiaotong UniversityLanzhou 730070China National-Local Joint Engineering Research Center of Technological and Application for National Geographic State Monitoring Lanzhou 730070China Gansu Provincial Engineering Laboratory for National Geographic State Monitoring Lanzhou 730070China College of Geoscience and Surveying Engineering China University of Mining&Technology(Bejing)Beijing 100083China School of Earth Science and Engineering Hebei University of EngineeringHebei 056000China Tianjin University Urban Planning and Design Institute Co.Ltd Tianjin 300072China State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China The ImageSky International Co.Ltd SuzhouJiangsu 215000China Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100101China School of Architecture Tianjin UniversityTianjin 300072China

With the expansion of a city,the urban green space is occupied and the urban heat island effect is *** the roof surfaces of urban buildings is an effective way to increase the area of urban green space and improve the urban ecological *** provide effective data support for urban green space planning,this paper used high-resolution images to(1)obtain accurate building spots on the map of the study area through deep learning assisted manual correction;and(2)establish an evaluation index system of roof greening including the characteristics of the roof itself,the natural environment and the human society *** weight values of attributes not related to the roof itself were calculated by Analytic Hierarchy Process(AHP).The suitable green roof locations were evaluated by spatial join,weighted superposition and other spatial analysis *** the areas within the Chengdu city’s third ring road as the study area,the results show that an accurate building pattern obtained by deep learning greatly improves the efficiency of the *** roof surfaces unsuitable for greening can be effectively classified by the method of feature extraction,with an accuracy of 86.58%.The roofs suitable for greening account for 48.08%,among which,the high-suitability roofs,medium-suitability roofs and low-suitability roofs represent 45.32%,38.95%and 15.73%.The high-suitability green buildings are mainly distributed in the first ring district and the western area outside the first ring district in *** paper is useful for solving the current problem of the more saturated high-density urban area and allowing the expansion of the urban ecological environment.

关键词： deep learning roof greening suitability assessment spatial join weighted overlay

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Distance Measurement system Based on Binocular Stereo Vision

引用

IOP Conference Series. Earth and Environmental Science 2019年第5期252卷 052051-052051页

作者： Sun, Xiyan Ji, Yuanfa Jiang, Yingzhou Fu, Wentao Yan, Suqing Chen, Qidong Yu, Baoguo Gan, Xingli Guangxi Key Laboratory of Precision Navigation Technology and Application Guilin University of Electronic Technology Guilin 541004 China National & Local Joint Engineering Research Center of Satellite Navigation and Location Service Guilin 541004 China Guangxi Experiment Center of Information Science Guilin University of Electronic Technology Guilin 541004 China Guangxi Key Laboratory of Precision Navigation Technology and Application Guilin University of Electronic Technology Guilin 541004 China National & Local Joint Engineering Research Center of Satellite Navigation and Location Service Guilin 541004 China Key laboratory of radio wave environment and modeling technology Qingdao 266000 China State key laboratory of satellite navigation system and equipment technology Shijiazhuang 050000 China

Binocular stereo vision uses two cameras of the same specification instead of human eyes for measurement and judgment. The basic principle of binocular vision ranging is to simultaneously capture the image of the measured object by using two left and right cameras. The objectmeasuredisdifferent, andthe positions under the different camera screensaredifferent, this difference in position is called disparity. The three-dimensional information of the object is obtained according to the principle of disparity. The binocular stereo vision ranging system, which combines the advantages of high efficiency and high precision, is ideal for non-contact detection and quality control. This paper proposes a method combining MATLAB calibration and OpenCV matching to achieve binocular stereo vision. Using the MATLAB calibration tool to perform stereo calibration of the camera, combined with OpenCV for stereo rectification and stereo matching, the disparity value is obtained, and the distance from the target to the camera is calculated by disparity. Simulations show that this method can satisfy the distance measurement.

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NTIRE 2020 Challenge on Image and Video Deblurring

arXiv

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arXiv 2020年

作者： Seungjun, Nah Sanghyun, Son Radu, Timofte Kyoung Mu, Lee Tseng, Yu Xu, Yu-Syuan Chiang, Cheng-Ming Tsai, Yi-Min Brehm, Stephan Scherer, Sebastian Xu, Dejia Chu, Yihao Sun, Qingyan Jiang, Jiaqin Duan, Lunhao Yao, Jian Purohit, Kuldeep Suin, Maitreya Rajagopalan, A.N. Ito, Yuichi Hrishikesh, P.S. Puthussery, Densen Akhil, K.A. Jiji, C.V. Kim, Guisik Deepa, P.L. Xiong, Zhiwei Huang, Jie Liu, Dong Kim, Sangmin Nam, Hyungjoon Kim, Jisu Jeong, Jechang Huang, Shihua Fan, Yuchen Yu, Jiahui Yu, Haichao Huang, Thomas S. Zhou, Ya Li, Xin Liu, Sen Chen, Zhibo Dutta, Saikat Das, Sourya Dipta Garg, Shivam Sprague, Daniel Patel, Bhrij Huck, Thomas Department of ECE ASRI SNU Korea Republic of Computer Vision Lab ETH Zurich Switzerland MediaTek Inc University of Augsburg Chair for Multimedia Computing and Computer Vision Lab Germany Peking University China Beijing University of Posts and Telecommunications China Beijing Jiaotong University China Wuhan University China Indian Institute of Technology Madras India Vermilion College of Engineering Trivandrum India CVML Chung-Ang University Korea Republic of APJ Abdul Kalam Technological University India University of Science and Technology of China China Image Communication Signal Processing Laboratory Hanyang University Korea Republic of Southern University of Science and Technology China University of Illinois at Urbana-Champaign United States CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China China IIT Madra Jadavpur University India University of Texas Austin United States Duke University Computer Science Department United States

Motion blur is one of the most common degradation artifacts in dynamic scene photography. This paper reviews the NTIRE 2020 Challenge on Image and Video Deblurring. In this challenge, we present the evaluation results from 3 competition tracks as well as the proposed solutions. Track 1 aims to develop single-image deblurring methods focusing on restoration quality. On Track 2, the image deblurring methods are executed on a mobile platform to find the balance of the running speed and the restoration accuracy. Track 3 targets developing video deblurring methods that exploit the temporal relation between input frames. In each competition, there were 163, 135, and 102 registered participants and in the final testing phase, 9, 4, and 7 teams competed. The winning methods demonstrate the state-of-the-art performance on image and video deblurring tasks. Copyright © 2020, The Authors. All rights reserved.

关键词： Image enhancement

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LUneXt: Simple and Efficient U-shaped Network Design for Medical Image Segmentation with Nonlinear Activation

Computing Open

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Computing Open 2024年第2期computing-open卷

作者： Guanghong Deng Bing Yu Wenlong Jing Yong Li Xiaodan Zhao GuangDong Engineering Technology Research Center of UAV Remote Sensing Network Guangzhou iMapCloud Intelligent Technology Co. Ltd. Guangzhou 510095 P. R. China Guangdong Province Engineering Laboratory for Geographic Spatiotemporal Big Data Key Laboratory of Guangdong for Utilization of Remote Sensing and Geographical Information System Guangdong Open Laboratory of Geospatial Information Technology and Application Guangzhou Institute of Geography Guangdong Academy of Sciences Guangzhou 510070 P. R. China Foshan iMapCloud Intelligent Technology Co. Ltd. Foshan 528251 P. R. China

Medical image segmentation has always been a challenging task. This paper proposes a new LUneXt medical image segmentation model based on the characteristics analysis of medical image data sets and testing of different nonlinear activation units. Both normalized activations for the original negative input image activation have good optimization capabilities for the tokenization module parameters proposed in the original UneXt model. Using different activation coefficients for different foreground and background areas has achieved better results. The experimental results of this paper on the Breast Ultrasound Images (BUSI) data set reached an intersection over union (IoU) value of 62.64%, a Dice value of 76.12%, and a single inference speed of 807.57 ms. The experimental IoU value of the International Skin Imaging Collaboration (ISIC 2018) data set reached 82.95%, and the Dice value reached 90.50%. The single inference speed reached 842.58 ms. The LUneXt model is more robust than other models. While improving model performance, it does not introduce higher computational complexity and does not have a major impact on the processing speed of a single image.

关键词： Image segmentation medical images neural networks activation function

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