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| 1 | Geospatial Service Web:towards integrated cyberinfrastructure for GIScience显示文摘A geospatial cyberinfrastructure is needed to support advanced GIScience research and education activities.However,the heterogeneous and distributed nature of geospatial resources creates enormous obstacles for building a unified and interoperable geospatial cyberinfrastructure.In this paper,we propose the Geospatial Service Web(GSW)to underpin the development of a future geospatial cyberinfrastructure.The GSW excels over the traditional spatial data infrastructure by providing a highly intelligent geospatial middleware to integrate various geospatial resources through the Internet based on interoperable Web service technologies.The development of the GSW focuses on the establishment of a platform where data,information,and knowledge can be shared and exchanged in an interoperable manner.Theoretically,we describe the conceptual framework and research challenges for GSW,and then introduce our recent research toward building a GSW.A research agenda for building a GSW is also presented in the paper. | GONG Jianya WU Huayi ZHANG Tong GUI Zhipeng LI Zhenlong YOU Lan SHEN Shengyu ZHENG Jie GENG Jing QI Kunlun YANG Wenjing LI Zhenqiang YU Jingmin | 2012 | Geo-Spatial Information Science2012，15，2： | 5 |
| 2 | Spatio-temporal-spectral-angular observation model that integrates observations from UAV and mobile mapping vehicle for better urban mapping显示文摘In a complex urban scene,observation from a single sensor unavoidably leads to voids in observations,failing to describe urban objects in a comprehensive manner.In this paper,we propose a spatio-temporal-spectral-angular observation model to integrate observations from UAV and mobile mapping vehicle platform,realizing a joint,coordinated observation operation from both air and ground.We develop a multi-source remote sensing data acquisition system to effectively acquire multi-angle data of complex urban scenes.Multi-source data fusion solves the missing data problem caused by occlusion and achieves accurate,rapid,and complete collection of holographic spatial and temporal information in complex urban scenes.We carried out an experiment on Baisha Town,Chongqing,China and obtained multi-sensor,multi-angle data from UAV and mobile mapping vehicle.We first extracted the point cloud from UAV and then integrated the UAV and mobile mapping vehicle point cloud.The inte-grated results combined both the characteristics of UAV and mobile mapping vehicle point cloud,confirming the practicability of the proposed joint data acquisition platform and the effectiveness of spatio-temporal-spectral-angular observation model.Compared with the observation from UAV or mobile mapping vehicle alone,the integrated system provides an effective data acquisition solution toward comprehensive urban monitoring. | Zhenfeng Shao Gui Cheng Deren Li Xiao Huang Zhipeng Lu Jian Liu | 2021 | Geo-Spatial Information Science2021，24，4： | 2 |
| 3 | Dust Distribution Study at the Blast Furnace Top Based on k-Sε-u_(p)Model显示文摘The dust distribution law acting at the top of a blast fumace(BF)is of great significance for understanding gas flow distribution and mitigating the negative influence of dust particles on the accuracy and service life of detection equipment.The harsh environment inside a BF makes it difficult to describe the dust disthibution.This paper adresses this problem by proposing a dust distribution k-Sε-u_(p)model based on interphase(gas-powder)coupling.The proposed model is coupled with a k-Sεmodel(which describes gas flow movement)and a u_(p)model(which depicts dust movement).First,the kinetic energy equation and turbulent dissipation rate equation in the k-Sεmodel are established based on the modeling theory and single Green-function two scale direct interaction approximation(SGF-TSDIA)theory.Second,a dust particle mnovement u_(p)model is built based on a force analysis of the dust and Newton's laws of motion.Finally,a coupling factor that descibes the interphase interaction is proposed,and the k-Sε-u_(p)model,with clear physical meaning.ligorous mathematical logic,and adequate generality,is dleveloped.Siumulation results and o-site verification show that the k-Sε-u_(p)model not only has high precision,but also reveals the aggregate distribution features of the dust,which are helpful in optimizing the installation position of the detection equipment and imnproving its accuracy and service life. | Zhipeng Chen Zhaohui Jiang Chunjie Yang Weihua Gui Youxian Sun | 2021 | IEEE/CAA Journal of Automatica Sinica2021，8，1： | 1 |
| 4 | Text GCN-SW-KNN:a novel collaborative training multi-label classification method for WMS application themes by considering geographic semantics显示文摘Without explicit description of map application themes,it is difficult for users to discover desired map resources from massive online Web Map Services(WMS).However,metadata-based map application theme extraction is a challenging multi-label text classification task due to limited training samples,mixed vocabularies,variable length and content arbitrariness of text fields.In this paper,we propose a novel multi-label text classification method,Text GCN-SW-KNN,based on geographic semantics and collaborative training to improve classifica-tion accuracy.The semi-supervised collaborative training adopts two base models,i.e.a modified Text Graph Convolutional Network(Text GCN)by utilizing Semantic Web,named Text GCN-SW,and widely-used Multi-Label K-Nearest Neighbor(ML-KNN).Text GCN-SW is improved from Text GCN by adjusting the adjacency matrix of the heterogeneous word document graph with the shortest semantic distances between themes and words in metadata text.The distances are calculated with the Semantic Web of Earth and Environmental Terminology(SWEET)and WordNet dictionaries.Experiments on both the WMS and layer metadata show that the proposed methods can achieve higher F1-score and accuracy than state-of-the-art baselines,and demonstrate better stability in repeating experiments and robustness to less training data.Text GCN-SW-KNN can be extended to other multi-label text classification scenario for better supporting metadata enhancement and geospatial resource discovery in Earth Science domain. | Zhengyang Wei Zhipeng Gui Min Zhang Zelong Yang Yuao Mei Huayi Wu Hongbo Liu Jing Yu | 2021 | Big Earth Data2021，5，1： | 1 |
| 5 | Population spatialization with pixel-level attribute grading by considering scale mismatch issue in regression modeling显示文摘Population spatialization is widely used for spatially downscaling census population data to finer-scale.The core idea of modern population spatialization is to establish the association between ancillary data and population at the administrative-unit-level(AUlevel)and transfer it to generate the gridded population.However,the statistical characteristic of attributes at the pixel-level differs from that at the AU-level,thus leading to prediction bias via the cross-scale modeling(i.e.scale mismatch problem).In addition,integrating multi-source data simply as covariates may underutilize spatial semantics,and lead to incorrect population disaggregation;while neglecting the spatial autocorrelation of population generates excessively heterogeneous population distribution that contradicts to real-world situation.To address the scale mismatch in downscaling,this paper proposes a Cross-Scale Feature Construction(CSFC)method.More specifically,by grading pixel-level attributes,we construct the feature vector of pixel grade proportions to narrow the scale differences in feature representation between AU-level and pixel-level.Meanwhile,fine-grained building patch and mobile positioning data are utilized to adjust the population weighting layer generated from POI-density-based regression modeling.Spatial filtering is furtherly adopted to model the spatial autocorrelation effect of population and reduce the heterogeneity in population caused by pixel-level attribute discretization.Through the comparison with traditional feature construction method and the ablation experiments,the results demonstrate significant accuracy improvements in population spatialization and verify the effectiveness of weight correction steps.Furthermore,accuracy comparisons with WorldPop and GPW datasets quantitatively illustrate the advantages of the proposed method in fine-scale population spatialization. | Yuao Mei Zhipeng Gui Jinghang Wu Dehua Peng Rui Li Huayi Wu Zhengyang Wei | 2022 | Geo-Spatial Information Science2022，25，3： | 1 |
| 6 | Geospatial big data for urban planning and urban management显示文摘The recent ten years witnessed the great achievements on rich applications of Geospatial Big Data across a variety of disciplines.For example,a huge number of Landsat images are utilized in mapping high-resolution global forest cover and the global forest changes in the twenty-first century are explored(Hansen et al.2013),which is impossible without the support of geospatial big data and the related automatic processing techniques.Based on the huge enterprise registration data in China,the economic and social development situations and trends are revealed by the non-statistic data and novel approaches(Li et al.2018).City-wide fine-grained urban population distribution at building level is achieved by integrating and fusing multisource geospatial big data(Yao et al.2017),which is usually not desired in traditional research.Geospatial Big Data provides a new transforming paradigm of scientific research especially at the crossroads of broad disciplines,including but not limited to the humanities,the physical sciences,engineering,and so on. | Huayi Wu Zhipeng Gui Zelong Yang | 2020 | Geo-Spatial Information Science2020，23，4： | 1 |
| 7 | A performance,semantic and service quality-enhanced distributed search engine for improving geospatial resource discovery显示文摘 | Gui Zhipeng Yang Chaowei Xia Jizhe | 2013 | International Journal of Geographical Information Science2013，27，6： | 1 |
| 8 | A Novel Sensing Imaging Equipment Under Extremely Dim Light for Blast Furnace Burden Surface:Starlight High-Temperature Industrial Endoscope显示文摘Blast furnace(BF)burden surface contains the most abundant,intuitive and credible smelting information and acquiring high-definition and high-brightness optical images of which is essential to realize precise material charging control,optimize gas flow distribution and improve ironmaking efficiency.It has been challengeable to obtain high-quality optical burden surface images under high-temperature,high-dust,and extremelydim(less than 0.001 Lux)environment.Based on a novel endoscopic sensing detection idea,a reverse telephoto structure starlight imaging system with large field of view and large aperture is designed.Combined with a water-air dual cooling intelligent self-maintenance protection device and the imaging system,a starlight high-temperature industrial endoscope is developed to obtain clear optical burden surface images stably under the harsh environment.Based on an endoscope imaging area model,a material flow trajectory model and a gas-dust coupling distribution model,an optimal installation position and posture configuration method for the endoscope is proposed,which maximizes the effective imaging area and ensures large-area,safe and stable imaging of the device in a confined space.Industrial experiments and applications indicate that the proposed method obtains clear and reliable large-area optical burden surface images and reveals new BF conditions,providing key data support for green iron smelting. | Zhipeng Chen Xinyi Wang Weihua Gui Jilin Zhu Chunhua Yang Zhaohui Jiang | 2024 | IEEE/CAA Journal of Automatica Sinica2024，11，4： | 0 |
| 9 | A miniaturized transit-time ultrasonic flowmeter based on ScAIN piezoelectric micromachined ultrasonic transducers for small-diameter applications显示文摘Transit-time ultrasonic flowmeters(TTUFs)are among the most widely used devices for flow measurements.However,traditional TTUFs are usually based on a bulk piezoelectric transducer,which limits their application in small-diameter channels.In this paper,we developed a miniaturized TTUF based on scandium-doped aluminum nitride(ScAIN)piezoelectric micromachined ultrasonic transducers(PMUTs).The proposed TTUF contains two PMUT-based transceivers and a T-type channel.The PMUTs contain 13×13 square cells with dimensions of 2.8×2.8 mm^(2).To compensate for the acoustic impedance mismatch with liquid,a layer of polyurethane is added to the surface of the PMUTs as a matching layer.The PMUT-based transceivers show good transmitting sensitivity(with 0.94 MPaN surface pressure)and receiving sensitivity(1.79 mV/kPa)at a frequency of 1 MHz in water.Moreover,the dimensions of the Ttype channel are optimized to achieve a measurement sensitivity of 82 ns/(m/s)and a signal-to-noise ratio(SNR)better than 15 dB.Finally,we integrate the fabricated PMUTs into the TDC-GP30 platform.The experimental results show that the developed TTUF provides a wide range of flow measurements from 2 to 300 L/h in a channel of 4 mm diameter,which is smaller than most reported channels.The accuracy and repeatability of the TTUF are within 0.2%and 1%,respectively.The proposed TTUF shows great application potential in industrial applications such as medical and Chemical applications. | Yunfei Gao Minkan Chen Zhipeng Wu Lei Yao Zhihao Tong Songsong Zhang Yuandong Alex Gui Liang Lou | 2023 | Microsystems & Nanoengineering2023，9，2： | 0 |
| 10 | Adopting cloud computing to optimize spatial web portals for better performance to support Digital Earth and other global geospatial initiatives显示文摘A spatial web portal(SWP)provides a web-based gateway to discover,access,manage,and integrate worldwide geospatial resources through the Internet and has the access characteristics of regional to global interest and spiking.Although various technologies have been adopted to improve SWP performance,enabling high-speed resource access for global users to better support Digital Earth remains challenging because of the computing and communication intensities in the SWP operation and the dynamic distribution of end users.This paper proposes a cloud-enabled framework for high-speed SWP access by leveraging elastic resource pooling,dynamic workload balancing,and global deployment.Experimental results demonstrate that the new SWP framework outperforms the traditional computing infrastructure and better supports users of a global system such as Digital Earth.Reported methodologies and framework can be adopted to support operational geospatial systems,such as monitoring national geographic state and spanning across regional and global geographic extent. | Jizhe Xia Chaowei Yang Kai Liu Zhipeng Gui Zhenlong Li Qunying Huang Rui Li | 2015 | International Journal of Digital Earth2015，8，6： | 0 |
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