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arXiv 2018年

作者： Gu, Jun Xu, Guangluan Zhang, Yue Sun, Xian Wen, Ran Wang, Lei Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing100190 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100049 China

Recently, deep convolutional neural networks (CNNs) have obtained promising results in image processing tasks including super-resolution (SR). However, most CNN-based SR methods treat low-resolution (LR) inputs and features equally across channels, rarely notice the loss of information flow caused by the activation function and fail to leverage the representation ability of CNNs. In this letter, we propose a novel single-image super-resolution (SISR) algorithm named Wider Channel Attention Network (WCAN) for remote sensing images. Firstly, the channel attention mechanism is used to adaptively recalibrate the importance of each channel at the middle of the wider attention block (WAB). Secondly, we propose the Local Memory Connection (LMC) to enhance the information flow. Finally, the features within each WAB are fused to take advantage of the network’s representation capability and further improve information and gradient flow. Analytic experiments on a public remote sensing data set (UC Merced) show that our WCAN achieves better accuracy and visual improvements against most state-of-the-art methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Image fusion

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An interactive system for eficient 3D furniture arrangement

An interactive system for eficient 3D furniture arrangement

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2017 Computer Graphics International Conference, CGI 2017

作者： Yan, Meng Chen, Xuejin Zhou, Jie CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Dept 6 P.O. Box 4 Hefei Anhui230026 China

ISBN: (纸本)9781450352284

We present an interactive example-based system for non-expert users to generate 3D indoor scenes intuitively. From a set of examples of an interior scene, we extract furniture layout constraints including pairwise and group relationships, ergonomic factors and user habits. Instead of inserting a single furniture object to a visual pleasing and functional position independently, we take advantages of manipulating a group of functionality-related furniture objects for smart editing. To deal with the arrangement problem which requires jointly optimizing a variety of functional and visual criteria, we introduce an efficient two-step pipeline consisting of rough arrangement and layout refinement. In the rough arrangement step, furniture objects are roughly placed according to pairwise relationships for accelerating the further optimization process. In the layout refinement step, we optimize the rough furniture layout to a semantical and functional layout considering spatial relationships, and ergonomic factors and avoiding collisions. User interactions are also allowed to move a specific object or a structural group while our system automatically refines the entire layout. The experimental results demonstrate that our system for scene generation measurably increases the visual quality and time efficiency compared with the completely manual scene editing or modeling. © 2017 ACM.

关键词： Virtual reality

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DEEP SEMANTIC SEGMENTATION OF AERIAL IMAGERY BASED ON MULTI-MODAL DATA

DEEP SEMANTIC SEGMENTATION OF AERIAL IMAGERY BASED ON MULTI-...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Kaiqiang Chen Kun Fu Xian Sun Michael Weinmann Stefan Hinz Boris Jutzi Martin Weinmann Key Laboratory of Spatial Information Processing and Application System Technology Chinese Academy of Sciences Beijing P.R. 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 focus on the use of multi-modal data to achieve a semantic segmentation of aerial imagery. Thereby, the multi-modal data is composed of a true orthophoto, the Digital Surface Model (DSM) and further representations derived from these. Taking data of different modalities separately and in combination as input to a Residual Shuffling Convolutional Neural Network (RSCNN), we analyze their value for the classification task given with a benchmark dataset. The derived results reveal an improvement if different types of geometric features extracted from the DSM are used in addition to the true orthophoto.

关键词： Semantics Image segmentation Feature extraction Labeling Vegetation mapping Buildings Benchmark testing

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An attention-based word-level interaction model: Relation detection for knowledge base question answering

arXiv

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arXiv 2018年

作者： Zhang, Hongzhi Xu, Guandong Liang, Xiao Huang, Tinglei Fu, Kun CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China School of Software and Advanced Analytics University of Technology Sydney Australia

Relation detection plays a crucial role in Knowledge Base Question Answering (KBQA) because of the high variance of relation expression in the question. Traditional deep learning methods follow an encoding-comparing paradigm, where the question and the candidate relation are represented as vectors to compare their semantic similarity. Max- or average- pooling operation, which compresses the sequence of words into fixed-dimensional vectors, becomes the bottleneck of information. In this paper, we propose to learn attention-based word-level interactions between questions and relations to alleviate the bottleneck issue. Similar to the traditional models, the question and relation are firstly represented as sequences of vectors. Then, instead of merging the sequence into a single vector with pooling operation, soft alignments between words from the question and the relation are learned. The aligned words are subsequently compared with the convolutional neural network (CNN) and the comparison results are merged finally. Through performing the comparison on low-level representations, the attention-based word-level interaction model (ABWIM) relieves the information loss issue caused by merging the sequence into a fixed-dimensional vector before the comparison. The experimental results of relation detection on both SimpleQuestions and WebQuestions datasets show that ABWIM achieves state-of-the-art accuracy, demonstrating its effectiveness. Copyright © 2018, The Authors. All rights reserved.

关键词： Knowledge based systems

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Corrigendum to “Terrestrial and groundwater storage characteristics and their quantification in the Chitral (Pakistan) and Kabul (Afghanistan) river basins using GRACE/GRACE-FO satellite data”

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Groundwater for Sustainable Development 2023年 23卷

作者： Aqil Tariq Shoaib Ali Iqra Basit Ahsan Jamil Nizom Farmonov Behnam Khorrami Muhammad Mohsin Khan Samira Sadri Muhammad Yousuf Jat Baloch Fakhrul Islam Muhammad Bilawal Junaid Wesam Atef Hatamleh Ubaid-ur-Rehman Janjua Department of Wildlife Fisheries and Aquaculture College of Forest Resources Mississippi State University 775 Stone Boulevard 39762-9690 MS USA State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan 430079 China School of Water Conservancy & Civil Engineering Northeast Agricultural University Harbin Heilongjiang 150030 China Department of Irrigation and Drainage Faculty of Agricultural Engineering and Technology University of Agriculture Faisalabad Faisalabad 38000 Pakistan Remote Sensing GIS and Climate Research Lab (National Center of GIS and Space Application) Centre for Remote Sensing University of the Punjab Lahore 54590 Pakistan Department of Plant and Environmental Sciences New Mexico State University 3170S Espina Street Las Cruces NM 88003 USA Department of Geoinformatics Physical and Environmental Geography University of Szeged Egyetem utca 2 Szeged 6722 Hungary Department of GIS The Graduate School of Applied and Natural Sciences Dokuz Eylul University 35220 Izmir Turkey Department of Agricultural Engineering Muhammad Nawaz Shareef University of Agriculture Multan Multan Pakistan Department of Water Resources Engineering Shahid Chamran University of Ahvaz Ahvaz *** Iran College of New Energy and Environment Jilin University Changchun 130021 China Department of Geology Khushal Khan Khattak University Karak Pakistan Department of Plant Production College of Food and Agriculture King Saud University Riyadh Saudi Arabia Department of Computer Science College of Computer and Information Sciences King Saud University P.O. Box 51178 Riyadh 11543 Saudi Arabia Department of Geography and Geospatial Sciences Geospatial Sciences Center of Excellence South Dakota State University Brookings South Dakota USA

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Building Extraction from High-Resolution Remotely Sensed Imagery Based on Multi-subgraph Matching

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Journal of the Indian Society of Remote Sensing 2018年第12期46卷 2003-2013页

作者： Wenzao Shi Zhengyuan Mao Jinqing Liu Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application College of Photonic and Electronic Engineering Fujian Normal University Fuzhou People’s Republic of China Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education Fujian Provincial Key Laboratory of Photonics Technology Fujian Normal University Fuzhou People’s Republic of China Key Lab of Spatial Data Mining and Information Sharing of Ministry of Education Fuzhou University Fuzhou People’s Republic of China National Engineering Research Centre of Geospatial Information Technology Fuzhou University Fuzhou People’s Republic of China Spatial Information Engineering Research Centre of Fujian Province Fuzhou University Fuzhou People’s Republic of China

Building extraction is still a difficult issue in the field of remote sensing. In order to extract the buildings with similar structures efficiently, an algorithm based on multi-subgraph matching is proposed using only the panchromatic high-resolution remotely sensed imagery (RSI). Firstly, scale-invariant feature transform feature is detected within both RSI and building template, and the corresponding graphs are constructed. Then, binary matching rules are defined to reconstruct the graphs to reduce the complexity. At last, according to the homogeneity of the building top, disconnected subgraphs are isolated from the reconstructed graphs. To improve the algorithm accuracy, the matched subgraphs are optimized on the basis of the differences in the structure and size. For verifying the validity of the proposed method, nine representatives are chosen from GF-2 images covering Guangzhou, China. Experimental results show that the precision and recall of the proposed method are 97.73% and 87.16%, respectively, and its overall performance F1 is higher than the three other similar methods.

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A Hyperspectral LiDAR with Eight Channels Covering from VIS to SWIR

A Hyperspectral LiDAR with Eight Channels Covering from VIS ...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Zhen Wang Yuwei Chen Chuanrong Li Mi Tian Mei Zhou Wenjing He Haohao Wu Huijing Zhang Lingli Tang Yiwu Wang Hui Zhou Eetu Puttonen Juha Hyyppa Academy of Opto-Electronics (AOE) Chinese Academy of Sciences (CAS) Beijing China Key Laboratory of Quantitative Remote Sensing Information Technology Chinese Academy of Sciences (CAS) Beijing China Earth Observation Technology Application Department (ETA) Chinese Academy of Sciences (CAS) Beijing China Joint Laboratory for Electro-optical Payload Information Acquisition and Quality Control Finnish Geospatial Research Institute (FGI) Masala Finland Department of Photogrammetry and Remote Sensing Finnish Geospatial Research Institute (FGI) Masala FI Finland

Hyperspectral LiDAR (HSL) possesses the advantages of the LiDAR and the hyperspectral detection, and detects ranging and spectrum information synchronously, by one HSL system. The data fusion is also avoided. At present, the spectrum range of reported HSLs usually covers only 500 nm-1000 nm (from visual (VIS) to near infrared (NIR) band). However, there is requirement to extend the spectrum range to short wave infrared (SWIR) band, which often contains more useful spectral information. In this paper, a HSL covering the spectrum from VIS to SWIR is reported. In the HSL, the echoes are divided into two sections and are detected by the different optoelectronic devices, of which the spectral response ranges are respectively compatible to the corresponding echoes. The HSL detection experiment in the laboratory was carried out. The waveforms of the echoes were analyzed, and the spectra of different targets were measured by the HSL. The experiment results demonstrate the capability of the prototyped HSL that obtaining the ranging information and the spectrum information of the targets in VIS-SWIR bands synchronously.

关键词： Laser radar Hyperspectral imaging Geologic measurements Reflectivity Measurement by laser beam Reflection

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Degradable film mulching increases soil carbon sequestration in major Chinese dryland agroecosystems

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Nature communications 2025年第1期16卷 5029页

作者： Zihan Liu Chenxu Zhao Nanhai Zhang Jing Wang Zhaoyang Li Yves Uwiragiye Nyumah Fallah Thomas W Crowther Yuanyuan Huang Yi Xu Sheng Zhang Yakov Kuzyakov Kadambot H M Siddique Zhikuan Jia Zucong Cai Scott X Chang Minggang Xu Christoph Müller Yi Cheng School of Geography Nanjing Normal University 210023 Nanjing China. College of Agronomy Northwest A&F University 712100 Yangling China. Co-Innovation Center for Sustainable Forestry in Southern China College of Forestry Nanjing Forestry University 210037 Nanjing China. Department of Environmental Systems Science Institute of Integrative Biology ETH Zurich Zurich 8092 Switzerland. Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences 100101 Beijing China. College of Agronomy and Biotechnology China Agricultural University 100193 Beijing China. Geo-Biosphere Interactions Department of Geosciences University of Tübingen Tübingen 72076 Germany. Institute of Soil Science Chinese Academy of Sciences 210008 Nanjing China. Department of Soil Science of Temperate Ecosystems Department of Agricultural Soil Science University of Göttingen Göttingen 37077 Germany. Peoples Friendship University of Russia (RUDN University) Moscow 117198 Russia. The UWA Institute of Agriculture The University of Western Australia Perth WA 6001 Australia. College of Agronomy Northwest A&F University 712100 Yangling China. jiazhk@***. Department of Renewable Resources University of Alberta Edmonton AB T6G 2E3 Canada. Shanxi Province Key Laboratory of Soil Environment and Nutrient Resources Engineer and Technology Academy of Ecology and Environment Shanxi Agricultural University 030031 Taiyuan China. State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China Key Laboratory of Arable Land Quality Monitoring and Evaluation Ministry of Agriculture and Rural Affairs Institute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural Sciences 100081 Beijing China. Liebig Centre of Agroecology and Climate Impact Research Justus Liebig University Giessen Giessen 35392 Germany. Institute of Plant Ecology Justus Liebig Univer

Plastic film mulching (PM), which contributes to nearly half of the increased crop yields in dryland agroecosystems, exacerbates environmental burdens due to its non-degradable nature. Globally, there is a growing demand to replace non-degradable PM with degradable film mulching (DM), yet its impacts on soil organic carbon (SOC) in dryland agroecosystems remains unknown. Here, using multi-field studies and mesocosm experiments, we found that DM strongly increased but PM reduced SOC storage (0-1 m). This difference is likely attributable to the higher microbial C use efficiency in soil under DM, leading to increased microbial-derived C compared to PM. Under the high roading scenario for 2100, DM could reduce the decomposition of SOC (0-1 m) in China's drylands by 9.0 ± 1.0 Mg ha year (one standard error) compared with PM. Our findings highlight that DM is a promising alternative to PM for sequestrating SOC and alleviating C loss under climate change in dryland agroecosystems.

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Building area extraction from the high spatial resolution remote sensing imagery

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Earth Science Informatics 2018年第1期12卷 19-29页

作者： Shi, Wenzao Mao, Zhengyuan Liu, Jinqing Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application Fujian Normal University Fuzhou People’s Republic of China Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education Fujian Provincial Key Laboratory for Photonics Technology Fujian Normal University Fuzhou People’s Republic of China College of Photonic and Electronic Engineering Fujian Normal University Fuzhou China Key Lab of Spatial Data Mining & Information Sharing of Ministry of Education Fuzhou University Fuzhou People’s Republic of China National Engineering Research Centre of Geospatial Information Technology Fuzhou University Fuzhou People’s Republic of China Spatial Information Engineering Research Centre of Fujian Province Fuzhou University Fuzhou People’s Republic of China

An approach to building area extraction from high-resolution remote sensing imagery is proposed based on the local gradient orientation density function (LGODF) and the bimodal density function (BDF). Firstly, the LGODF is calculated by moving the window of 35 × 35 based on the gradient magnitude and the gradient direction of each pixel in the image. Then, the BDF is obtained by multiplying the movable bimodal Gaussian mixture function and LGODF in each window. Finally, peaks with difference of 90° are searched for in the BDF, and the central point of the corresponding windows are determined as building pixels. For the validity of the proposed method, seven representative sub-images from PLEIADES images covering Shenzhen China are selected. Experimental results reveal that the precision achieve 94.08% and the recall up to 96.70%.

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Using object-based analysis to derive surface complexity information for improved filtering of airborne laser scanning data

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Frontiers of Earth Science 2017年第1期11卷 11-19页

作者： Menglong YAN Thomas BLASCHKE Hongzhao TANG Chenchao XIAO Xian SUN Daobing ZHANG Kun FU Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing 100190 China Z GIS - Centre for Geoinformatics and Department for Geography and Geology University of Salzburg Salzburg A-5020 Austria Satellite Mapping Application Center State Bureau of Surveying and Mapping Beijing 100048 China China Aero Geophysical Survey and Remote Sensing Center for Land and Resources Beijing 100083 China

Airborne laser scanning （ALS） is a technique used to obtain Digital Surface Models （DSM） and Digital Terrain Models （DTM） efficiently, and filtering is the key procedure used to derive DTM from point clouds. Generating seed points is an initial step for most filtering algorithms, whereas existing algorithms usually define a regular window size to generate seed points. This may lead to an inadequate density of seed points, and further introduce error type I, especially in steep terrain and forested areas. In this study, we propose the use of object- based analysis to derive surface complexity information from ALS datasets, which can then be used to improve seed point generation. We assume that an area is complex if it is composed of many small objects, with no buildings within the area. Using these assumptions, we propose and implement a new segmentation algorithm based on a grid index, which we call the Edge and Slope Restricted Region Growing （ESRGG） algorithm. Surface complexity information is obtained by statistical analysis of the number of objects derived by segmentation in each area. Then, for complex areas, a smaller window size is defined to generate seed points. Experimental results show that the proposed algorithm could greatly improve the filtering results in complex areas, especially in steep terrain and forested areas.

关键词： airborne laser scanning object-based analysis surface complexity information filtering algorithm

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