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IEEE International Symposium on Geoscience and remote sensing (IGARSS)

作者： Jian Zhu Qiang Zhang Yaming Zheng Center of Hyperspectral Imaging in Remote Sensing (CHIRS) Information Science and Technology College Dalian Maritime University Dalian China

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

In this work, we use the near real-time data of Himawari-8/9 geostationary satellite for the forest early fire detection at the minute level. By using the recursive Transformer model, this work comprehensively considers the temporal, spatial and spectral characteristics of fire point pixels, and takes into account MODIS land cover product information. The method reduces the interference factors such as cloud and terrain, and realizes the 10-mintue detection of forest early wildfire.

关键词： Measurement Wildfires Forestry Transformers Feature extraction Real-time systems Timing

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Adaptive digital beamforming for sar imaging in elevation 14

Adaptive digital beamforming for sar imaging in elevation

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14th European Conference on Synthetic Aperture Radar, EUSAR 2022

作者： Zhou, Yashi Wang, Wei Chen, Zhen Lv, Zheng Han, Xiaolei Liu, Jie Zhang, Qingjun Institute of Remote Sensing Satellite China Academy of Space Technology Beijing China Aerospace Information Research Institute Chinese Academy of Science Beijing China

ISBN: (纸本)9783800758234

Digital beamforming (DBF) spaceborne synthetic aperture radar (SAR) is a promising candidate for achieving high-resolution and ultra-wide-swath (HRWS) images. On reception, digital beamforming technology in elevation can signif-icantly improve the system performance such as its sensitivity, ambiguity level and the output signal-To-noise ratio (SNR) by Scan-On-Receive (SCORE). However, in the wide-swath realistic scenario characterized by mountains and relief, the effect of topographic height would result in a mismatch between the steering direction and the actual direction of arrival and further introduce the SCORE pattern loss (SPL). To solve this problem, this paper presents a comprehen-sive performance evaluation on SPL and proposes an adaptive DBF processing scheme based on the principle of spec-Tral estimation. Simulation results and real data validate the effectiveness of the processing scheme. © 2022 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Beamforming

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Global Soil Salinity Estimation at 10 m Using Multi-Source remote sensing

Journal of Remote Sensing

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Journal of remote sensing 2024年第1期4卷 612-631页

作者： Nan Wang Songchao Chen Jingyi Huang Frederic Frappart Ruhollah Taghizadeh Xianglin Zhang Jean-Pierre Wigneron Jie Xue Yi Xiao Jie Peng Zhou Shi Institute of Agricultural Remote Sensing and Information Technology Application College of Environmental and Resource SciencesZhejiang UniversityHangzhou 310058China Interactions Sol Plante Atmosphère Bordeaux Sciences AgroNational Research Institute for AgricultureFood and Environment33140Villenave d’OrnonFrance Zhejiang University-HangzhouGlobal Scientific and Technological Innovation Center Hangzhou 311200China Department of Soil Science University of Wisconsin-Madison1525 Observatory DriveMadisonWI 53706USA Department of Geosciences Soil Science and GeomorphologyUniversity of Tübingen72070 TübingenGermany College of Plant Science Tarim UniversityAlar 843300China Key Laboratory of Spectroscopy Sensing Ministry of AgricultureHangzhou 310058China

Salinization is a threat to global agricultural and soil resource *** investigations of global soil salinity are limited to coarse spatial resolution of the available datasets(>250 m)and semiqualitative classification rules(five ranks).Based on these two limitations,we proposed a framework to quantitatively estimate global soil salt content in five climate regions at 10 m by integrating Sentinel-1/2 remotely sensed images,climate,parent material,terrain data,and machine *** hyper-arid and arid region,models established using Sentinel-2 and other geospatial data showed the highest accuracy with R^(2) of 0.85 and 0.62,*** semi-arid,dry sub-humid,and humid regions,models performed best using Sentinel-1,Sentinel-2,and other geospatial data with R^(2) of 0.87,0.80,and 0.87,*** accuracy of the global models is considerable with field validation in Iran and Xinjiang,and compared with digitized salinity maps in California,Brazil,Turkey,South Africa,and *** proportion of extremely saline soils in Europe is 10.21%,followed by South America(5.91%),Oceania(5.80%),North America(4.05%),Asia(1.19%),and Africa(1.11%).Climatic conditions,groundwater,and salinity index are key covariates in global soil salinity *** of radar data improves estimation accuracy in wet *** map of global soil salinity at 10 m provides a detailed,high-precision basis for soil property investigation and resource management.

关键词： soil salt Sentinel machine learningin remote sensing machine learning global estimation soil salinity

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A Bi-direction LSTM Attention Fusion Model for the Missing POI Identification

Journal of Network Intelligence

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Journal of Network Intelligence 2022年第1期7卷 161-174页

作者： Liao, Lyuchao Lin, Jinmei Zhu, Yintian Bi, Shuoben Lin, Yuyuan Fujian Provincial Universities Key Laboratory of Industrial Control and Data Analysis Fujian Provincial Universities Engineering Research Center for Intelligent Driving Technology Fujian University of Technology Fuzhou350118 China School of Geography and Remote Sensing Nanjing University of Information Science and Technology Nanjing210044 China

Point-of-interest(POI) check-in data, collected from human mobility, pro-vides an excellent opportunity to understand users’ behavior. However, the collected data usually suffer from various quality issues, especially the missing geolocation informa-tion. The incomplete POI data will prevent a deep analysis of users’ preferences and movement patterns and limit its practical application. To address these issues, emerg-ing studies are conducted to predict the missing POIs. Nevertheless, existing methods generally employed history information from a single-direction perspective for POI recommendation or prediction. Considering that the missing POI identification tasks simultaneously require both former and later data of the missing target, we proposed a Bi-direction LSTM Attention Fusion model, named Bi-LAF, to combine users’ preferences with spatial-temporal patterns identifying the missing POI check-ins. Firstly, Bi-LAF integrates both Long Short-Term Memory(LSTM) and self-attention mechanisms to ex-plore and combine users’ preferences and the time patterns of missing POI. Then, we employ the Great Circle Distance(GCD) and time intervals of the successive moment to learn the relationships between missing POI and candidate POIs. Finally, users’ preferences and spatial-temporal relationships are spatialized to complete the identification task of missing POIs. The proposed model is evaluated on two real large-scale datasets, and the results show that Bi-LAF outperforms the state-of-the-art related methods. © 2022, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Long short-term memory

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Beyond pixels:Learning from multimodal hyperspectral superpixels for land cover classification

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science China(Technological sciences) 2022年第4期65卷 802-808页

作者： HONG DanFeng WU Xin YAO Jing ZHU XiaoXiang Key Laboratory of Computational Optical Imaging Technology Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100094China School of Computer Science(National Pilot Software Engineering School) Beijing University of Posts and TelecommunicationsBeijing 100876China Remote Sensing Technology Institute German Aerospace Center(DLR)Wessling 82234Germany Data Science in Earth Observation Technical University of MunichMunich 80333Germany

Despite tons of advanced classification models that have recently been developed for the land cover mapping task,the monotonicity of a single remote sensing data source,such as only using hyperspectral data or multispectral data,hinders the classification accuracy from being further improved and tends to meet the performance *** this reason,we develop a novel superpixel-based subspace learning model,called Supace,by jointly learning multimodal feature representations from HS and MS superpixels for more accurate LCC *** can learn a common subspace across multimodal RS data,where the diverse and complementary information from different modalities can be better combined,being capable of enhancing the discriminative ability of to-be-learned features in a more effective *** better capture semantic information of objects in the feature learning process,superpixels that beyond pixels are regarded as the study object in our Supace for *** experiments have been conducted on two popular hyperspectral and multispectral datasets,demonstrating the superiority of the proposed Supace in the land cover classification task compared with several well-known baselines related to multimodal remote sensing image feature learning.

关键词： classification hyperspectral image land cover multimodal multispectral image remote sensing subspace learning superpixels

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Classification of ice and water in the Arctic using radar altimeter and microwave radiometer data from HY-2B satellite

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Acta Oceanologica Sinica 2023年第5期42卷 179-191页

作者： Chengfei Jiang Mingsen Lin Ruixue Cao Hao Wei Lijian Shi Bin Cheng Yongjun Jia Qimao Wang School of Marine Science and Technology Tianjin UniversityTianjin 300072China National Satellite Ocean Application Service Ministry of Natural ResourcesBeijing 100081China Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou) Guangzhou 511458China Key Laboratory of Space Ocean Remote Sensing and Application State Oceanic AdministrationBeijing 100081China College of Ocean and Meteorology Guangdong Ocean UniversityZhanjiang 524088China Finnish Meteorological Institute Helsinki FI-00560Finland

Several Chinese marine satellites have been launched in recent *** sea ice and the ocean in the Arctic is of great importance for climate *** ice in the Arctic has changed rapidly during the past few decades with respect to the extent and *** this study,we applied combined passive and active microwave data from the Chinese HaiYang-2B(HY-2B)satellite to classify ice and sea water in the *** use data from a radar altimeter(RA)and a calibration microwave radiometer(CMR)to discriminate between ice and water by applying several approaches(1)the single parameter threshold criteria,(2)the multi-parameters linear segmentations and(3)the K-means *** results yielded by these methods were in good agreement(classification accuracy>95%)with the Satellite Application Facility on Ocean and Sea Ice products between November and *** other months(May–October),however,the agreement was less good(lowest classification accuracy approximate 85%in summer).A hybrid approach combined with graphical ice edges detection and microwave radar waveform analysis is therefore developed.A visual comparison with SAR images suggested the hybrid approach results greatly improved the ice and water discrimination in *** study demonstrated that multi-sensors(RA and CMR)configurations from HY satellites can offer comparable polar earth observation to the European Space Agency and NOAA satellite products.

关键词： Arctic active microwave data passive microwave data sea ice seawater

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Significant chlorine emissions from biomass burning affect the long-term atmospheric chemistry in Asia

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National science Review 2024年第9期11卷 213-222页

作者： Di Chang Qinyi Li Zhe Wang Jianing Dai Xiao Fu Jia Guo Lei Zhu Dongchuan Pu Carlos A.Cuevas Rafael P.Fernandez Weigang Wang Maofa Ge Jimmy C.H.Fung Alexis K.H.Lau Claire Granier Guy Brasseur Andrea Pozzer Alfonso Saiz-Lopez Yu Song Tao Wang Atmospheric Chemistry Department Max Planck Institute for Chemistry Department of Atmospheric Chemistry and Climate Institute of Physical Chemistry Blas CabreraCSIC Department of Civil and Environmental Engineering The Hong Kong Polytechnic University Environment Research Institute Shandong University Division of Environment and Sustainability The Hong Kong University of Science and Technology Environmental Modeling Group Max Planck Institute for Meteorology Institute of Environment and Ecology Tsinghua Shenzhen International Graduate SchoolTsinghua University Environmental Central Facility Institute for the Environment The Hong Kong University of Science and Technology Atmospheric Chemistry Modeling& Remote Sensing Research Group Southern University of Science and Technology Institute for Interdisciplinary Science (ICB) National Research Council (CONICET)FCEN-UNCuyo Institute of Chemistry Chinese Academy of Sciences NOAA Chemical Sciences Laboratory/CIRES University of Colorado Laboratoire d’Aerologie CNRSUniversity of Toulouse UPS Atmospheric Chemistry Observation & Modeling Laboratory National Center for Atmospheric Research State Key Joint Laboratory of Environmental Simulation and Pollution Control Department of Environmental Science Peking University

Biomass burning（BB） is a major source of trace gases and particles in the atmosphere,influencing air quality,radiative balance,and *** studies have mainly focused on the BB emissions of carbon and nitrogen species with less attention on *** chlorine chemistry has significant effects on atmospheric chemistry and air ***,quantitative information on chlorine emissions from BB,particularly the long-term trend and associated atmospheric impacts,is limited both on regional and global ***,we report a long-term（20 01-2018） high-resolution BB emission inventory for the major chlorine-containing compounds（HCl,chloride,and CH3Cl） in Asia based on satellite *** estimate an average of 730 Gg yr-1chlorine emitted from BB activity in Asia,with China contributing the largest share at 24.2%(177 Gg yr-1),followed by Myanmar at 18.7% and India at 18.3%.Distinct seasonal patterns and significant spatial and interannual variability are observe d,mainly driven by human-mediated changes in agricultural *** incorporating the newly developed chlorine emission inventory into a global chemistry-climate model（CAM-Chem）,we find that the BB-chlorine emissions lead to elevated levels of HCl and CH3Cl(monthly average up to 2062 and 1421 parts per trillion by volume（pptv）,respectively),subsequently resulting in noticeable changes in oxidants（up to 3.1% in O3and 17% in OH radicals）.The results demonstrate that BB is not only a significant source of air pollutants but also of oxidants,suggesting a larger role of BB emissions in the atmospheric chemistry and oxidation process than previously *** light of the projected increase in BB activity toward the end of the century and the extensive control of anthropogenic emissions worldwide,the contribution of BB emissions may become fundamental to air quality composition in the future.

关键词： biomass burning emission chlorine emission inventory tropospheric halogen chemistry atmospheric oxidants CAM-Chem model

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Robust Synchronization Method for Burst OFDM Systems based on AGC Compensation 9

Robust Synchronization Method for Burst OFDM Systems based o...

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9th International Conference on Computer and Communications, ICCC 2023

作者： Han, Yue Li, Lintao Lv, Jiayi Yang, Mei Shang, Jiadong Wang, Pu Beijing Institute of Technology School of Cyberspace Science and Technology Beijing China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing China Beijing Institute of Technology School of Information and Electronics Beijing China Beijing Institute of Fashion Technology School of Arts and Sciences Beijing China Beijing Institute of Remote Sensing Equipment Advanced Communication General Technology Research Office Beijing China

ISBN: (纸本)9798350317251

This paper introduces a novel low latency burst short frame orthogonal frequency division multiplexing (OFDM) synchronization approach utilizing automatic gain control (AGC) gain compensation. By eradicating the guard sequence to expedite the process and leveraging AGC feedback gain values to correct distorted training sequence, our method simultaneously diminishes the time cost and enhances the synchronization performance. Simulation results show that in comparison to non-compensated methods, the proposed synchronization approach can amplify the signal-to-noise ratio by about 1 dB for the same normalized mean square error. Moreover, the frequency synchronization performance closely mirrors those sequences with a higher point count. Given the same frequency synchronization performance, the sequence length required by the proposed method is only 64% of the non-compensated methods, resulting in an estimated time resource savings during synchronization. © 2023 IEEE.

关键词： Synchronization

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MDBs Versus MIBs in Case of Multiple Hypotheses: A Study in Context of Deformation Analysis 10th

MDBs Versus MIBs in Case of Multiple Hypotheses: A Study in ...

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10th Hotine-Marussi Symposium on Mathematical Geodesy, 2022

作者： Zaminpardaz, Safoora Teunissen, Peter J. G. School of Science RMIT University MelbourneVIC Australia Department of Geoscience and Remote Sensing Delft University of Technology Delft Netherlands GNSS Research Centre School of Earth and Planetary Sciences Curtin University of Technology PerthWA Australia Department of Infrastructure Engineering The University of Melbourne MelbourneVIC Australia

ISBN: (纸本)9783031553592

Statistical testing procedures employed in geodetic quality control often consist of two steps: detection and identification. In the detection step, the null hypothesis (working model) H0 undergoes a validity check. If the outcome of the detection step is the rejection of H0, identification of potential source of model error is exercised through a search among the specified alternative hypotheses. The testing performance is thus not only led by its ability to detect biases but to correctly identify them as well. The detection capability of a testing regime is usually assessed by its Minimal Detectable Bias (MDB) given a certain correct detection probability. The information provided by the MDB only concerns correct detection and not correct identification. The testing identification performance should be evaluated by its Minimal Identifiable Bias (MIB) given a certain correct identification probability. In this contribution, we demonstrate the difference between MDB and MIB. It is hereby highlighted that a small MDB (or a high probability of correct detection) does not necessarily imply a small MIB (or a high probability of correct identification). The factors driving the difference between detection and identification performance are illustrated using a simple example. Our analysis is then continued in the framework of deformation monitoring. © The Author(s) 2023.

关键词： Well testing

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Multi-Panel Extra-Large Scale MIMO Based Joint Activity Detection and Channel Estimation for Near-Field Massive IoT Access

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China Communications 2023年第5期20卷 232-243页

作者： Zhen Gao Hanlin Xiu Yikun Mei Anwen Liao Malong Ke Chun Hu Mohamed-Slim Alouini School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China MIIT Key Laboratory of Complex-Field Intelligent Sensing Beijing Institute of TechnologyBeijing 100081China The Advanced Technology Research Institute of Beijing Institute of Technology Jinan 250307China Yangtze Delta Region Academy of Beijing Institute of Technology(Jiaxing) Jiaxing 314019China Electrical Engineering Program Division of Physical Sciences and EngineeringKing Abdullah University of Science and TechnologyThuwal 23955Saudi Arabia

The extra-large scale multiple-input multiple-output(XL-MIMO)for the beyond fifth/sixth generation mobile communications is a promising technology to provide Tbps data transmission and stable access ***,the extremely large antenna array aperture arouses the channel near-field effect,resulting in the deteriorated data rate and other challenges in the practice communication ***,multi-panel MIMO technology has attracted extensive attention due to its flexible configuration,low hardware cost,and wider *** combining the XL-MIMO and multi-panel array structure,we construct multi-panel XL-MIMO and apply it to massive Internet of Things(IoT)***,we model the multi-panel XL-MIMO-based near-field channels for massive IoT access scenarios,where the electromagnetic waves corresponding to different panels have different angles of arrival/departure(AoAs/AoDs).Then,by exploiting the sparsity of the near-field massive IoT access channels,we formulate a compressed sensing based joint active user detection(AUD)and channel estimation(CE)problem which is solved by AMP-EM-MMV *** simulation results exhibit the superiority of the AMP-EM-MMV based joint AUD and CE scheme over the baseline algorithms.

关键词： extra-large scale MIMO massive IoT access active user detection channel estimation multipanel approximate message passing

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