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Integrated data-model-knowledge representation for natural resource entities

International Journal of Digital Earth 2022年第1期15卷 653-678页

作者： Yulin Ding Zhaowen Xu Qing Zhu Hankan Li Yan Luo Ying Bao Lingjun Tang Sen Zeng Faculty of Geosciences and Environmental Engineering Southwest Jiaotong UniversityChengduPeople's Republic of China municipal planning & land Estate information center Shenzhen Municipal Bureau of Planning and Natural ResourcesShenzhenPeople's Republic of China information center Department of Natural Resources of Sichuan ProvinceChengduPeople's Republic of China

The unified management and planning of national or provincial natural resources distributed both aboveground and underground have become increasingly *** depictions of natural resource elements and their interactions are key to achieving integrated and systematic management of natural ***,current spatiotemporal data models are based only on data descriptions,attribute records,and other model knowledge of a more general basis,without intuitively describing relationships between these elements and natural *** paper,therefore,proposes an integrated data-model-knowledge representation model to explicitly describe the time,space,and interaction of natural resource entities through an integrated knowledge ***,this study constructs a conceptual model using the aspects of semantics,scale,and data-model-knowledge,thereby explicitly describing the relationships of natural ***,a logical model of natural resource representation is proposed,that is integrated with time,space,attributes,and ***,taking the management of water resources as an example,this paper realizes the meticulous presentation of the levels of detail and rich semantic relations of natural resource *** findings of this study lay the foundation for a more efficient,precise,and lucid perception of the distribution laws and complicated interactional relationships of natural resources,both aboveground and underground.

关键词： Natural resources data-model-knowledge interactional relationships

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Estimation of the Impact of Traveler information Apps on Urban Air Quality Improvement

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Engineering 2018年第2期4卷 60-65页

作者： Wenke Huang Mingwei Hu Department of Transportation Engineering Shenzhen University Shenzhen 518000 China shenzhen Nanshan Urban planning and land Resource Research center Shenzhen 518000 China

With the rapid growth of vehicle population and vehicle miles traveled, automobile emission has become a severe issue in the metropolitan cities of China. There are policies that concentrate on the management of emission sources. However, improving the operation of the transportation system through apps on mobile devices, especially navigation apps, may have a unique role in promoting urban air quality. Real-time traveler information can not only help travelers avoid traffic congestion, hut also advise them to adjust their departure time, mode, or route, or even to cancel trips. Will such changes in personal travel patterns have a significant impact in decreasing emissions？ If so, to what extent will they impact urban air quality？ The aim of this study is to determine how urban traffic emission is affected by the use of navigation apps. With this work, we attempt to answer the question of whether the real-time traffic information provided by navigation apps can help to improve urban air quality. Some of these findings may provide references for the formulation of urban traffic and environmental policies.

关键词： Real-time traffic information Mobile devices Environmental benefits Agent-based model

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Video-based construction vehicles detection and its application in intelligent monitoring system

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CAAI Transactions on Intelligence Technology 2016年第2期1卷 162-172页

作者： Wenyang Ji Lingjun Tang Dedi Li Wenming Yang Qingmin Liao shenzhen Key Lab. of information Sci&Tech/shenzhen Engineering Lab. of IS&DCP Department of Electronic Engineering/Graduate School at shenzhen Tsinghua University China shenzhen municipal planning & land realestate information center China

While vehicle detection on highways has been reported before, to the best of our knowledge, intelligent monitoring system that aims at detecting hydraulic excavators and dump trucks on state-owned land has not been explored thoroughly yet. In this paper, we present an automatic, video-based algorithm for detecting hydraulic excavators and dump trucks. Derived from lessons learned from video processing, we proposed methods for foreground detection based on an improved frame difference algorithm, and then detected hydraulic excavators and dump trucks in the respective region of interest. From our analysis, we proposed methods based on inverse valley feature of mechanical arm and spatial-temporal reasoning for hydraulic excavator detection. In addition, we explored dump truck detection strategies that combine structured component projection with the spatial relationship. Experiments on real-monitoring sites demonstrated the promising performance of our system.

关键词： State-owned land protection Construction vehicle detection Hydraulic excavator detection Dump truck detection Inverse-V feature Intelligentmonitoring system

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Review of constraints and critical success factors of developing urban underground space

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Underground Space 2023年第5期12卷 137-155页

作者： Yani Lai Yuling Wang Jing Cheng Xiangsheng Chen Quan Liu College of Civil and Transportation Engineering Shenzhen UniversityShenzhen 518055China LAY-OUT planning Consultants Co. Ltd.TAGEN Knowledge&Innovation CenterShenzhen 518034China

The development of urban underground space(UUS)is of great significance for sustainable urban development because it has potential to solve many urban ***,the development of UUS is limited because there are still a lot of constraints and *** better understand the constraining factors of developing UUS and improve the development and utilization of UUS,this study conducts a comprehensive survey of existing literature retrieved from the Web of Science Core Collection *** main constraining factors,including the limited geological conditions,high cost,lack of natural light and ventilation,high incidence,and difficulty in collecting data and information on UUS,have been discussed to better understand how they affect the development of *** on the survey,the critical success factors of developing UUS,such as the effective governance structure,planning system for integrating UUS into urban development,coordination of the design of ground and underground,delineation of land property rights of UUS,and application of information techniques in the use of UUS,have been identified and *** addition,knowledge gaps in the studies on development of UUS have been ***,the research trends and future directions have been proposed for better understanding and practice of UUS development.

关键词： Urban underground space Constraining factor Critical success factor Resources Metro Energy Infrastructure

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CW-YOLO: joint learning for mask wearing detection in low-light conditions

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Frontiers of Computer Science 2023年第6期17卷 191-193页

作者： Mingqiang GUO Hongting SHENG Zhizheng ZHANG Ying HUANG Xueye CHEN Cunjin WANG Jiaming ZHANG School of Computer Science China University of GeosciencesWuhan 430074China National Engineering Research center of Geographic information System Wuhan 430074China Wuhan Zondy Cyber Technology Co.Ltd. Wuhan 430074China shenzhen Data Management center of planning and Natural Resources Shenzhen 518000China Key Laboratory of Urban land Resources Monitoring and Simulation(Ministry of Natural Resources) Shenzhen 518000China College of Engineering Boston UniversityBoston 02215USA

1 Introduction With the rapid progress of Artificial Intelligence(AI)technology in object detection and face recognition,deep learning methods for face mask wearing detection have become increasingly mature and continuously take into account the needs of efficiency and ***,these conventional detection methods mostly ignore the complexity of real-world application scenarios,such as extremely darkness and gloomy *** unfavorable conditions lead to a series of image degradations that seriously hamper machine vision *** camera parameter adjustment,auxiliary lighting,or pre-processing enhancement[1]can weaken these negative effects to some extent to promote the detection,they will also result in increased hardware and time costs.

关键词： hardware lighting weather

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A Grad-CAM and capsule network hybrid method for remote sensing image scene classification

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Frontiers of Earth Science 2024年第3期18卷 538-553页

作者： Zhan HE Chunju ZHANG Shu WANG Jianwei HUANG Xiaoyun ZHENG Weijie JIANG Jiachen BO Yucheng YANG shenzhen Data Management center of planning and Natural Resources Key Laboratory of Urban Land Resources Monitoring and Simulation(Ministry of Natural Resources)Shenzhen 518000China Key Laboratory of Jianghuai Arable land Resources Protection and Eco-restoration(Ministry of Natural Resources) Hefei 230088China State Key Laboratory of Resources and Environmental information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China School of Civil Engineering Hefei University of TechnologyHefei 230009China

Remote sensing image scene classification and remote sensing technology applications are hot research *** CNN-based models have reached high average accuracy,some classes are still misclassified,such as“freeway,”“spare residential,”and“commercial_area.”These classes contain typical decisive features,spatial-relation features,and mixed decisive and spatial-relation features,which limit high-quality image scene *** address this issue,this paper proposes a Grad-CAM and capsule network hybrid method for image scene *** Grad-CAM and capsule network structures have the potential to recognize decisive features and spatial-relation features,*** using a pre-trained model,hybrid structure,and structure adjustment,the proposed model can recognize both decisive and spatial-relation features.A group of experiments is designed on three popular data sets with increasing classification *** the most advanced experiment,92.67%average accuracy is ***,83%,75%,and 86%accuracies are obtained in the classes of“church,”“palace,”and“commercial_area,”*** research demonstrates that the hybrid structure can effectively improve performance by considering both decisive and spatial-relation ***,Grad-CAM-CapsNet is a promising and powerful structure for image scene classification.

关键词： image scene classification CNN Grad-CAM CapsNet DenseNet

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California Simulation of Evapotranspiration of Applied Water and Agricultural Energy Use in California

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Journal of Integrative Agriculture 2013年第8期12卷 1371-1388页

作者： Morteza N Orang Richard L Snyder Shu Geng Quinn J Hart Sara Sarreshteh Matthias Falk Dylan Beaudette Scott Hayes Simon Eching California Department of Water Resources Department of land Air and Water ResourcesUniversity of California School of Environment and Energy Shenzhen Graduate SchoolPeking University

The California Simulation of Evapotranspiration of Applied Water （CaI-SIMETAW） model is a new tool developed by the California Department of Water Resources and the University of California, Davis to perform daily soil water balance and determine crop evapotranspiration （ETo）, evapotranspiration of applied water （ETaw）, and applied water （AW） for use in California water resources planning. ETaw is a seasonal estimate of the water needed to irrigate a crop assuming 100% irrigation efficiency. The model accounts for soils, crop coefficients, rooting depths, seepage, etc. that influence crop water balance. It provides spatial soil and climate information and it uses historical crop and land-use category information to provide seasonal water balance estimates by combinations of detailed analysis unit and county （DAU/County） over Califomia. The result is a large data base of ETc and ETaw that will be used to update information in the new California Water Plan （CWP）. The application uses the daily climate data, i.e., maximum （Tx） and minimum （Tn） temperature and precipitation （Pcp）, which were derived from monthly USDA-NRCS PRISM data （PRISM Group 2011） and daily US National Climate Data center （NCDC） climate station data to cover California on a 4 kmx4 km change grid spacing. The application uses daily weather data to determine reference evapotranspiration （ETo）, using the Hargreaves-Samani （HS） equation （Hargreaves and Samani 1982, 1985）. Because the HS equation is based on temperature only, ETo from the HS equation were compared with CIMIS ETo at the same locations using available CIMIS data to determine correction factors to estimate CIMIS ETo from the HS ETo to account for spatial climate differences. CaI-SIMETAW also employs near real-time reference evapotranspiration （ETo） information from Spatial CIMIS, which is a model that combines weather station data and remote sensing to provide a grid of ETo information. A second database containing the available soil water

关键词： soil water balance crop water requirements weather generator water resource planning crop coefficient energy use

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Quantitatively determine the dominant driving factors of the spatial–temporal changes of vegetation NPP in the Hengduan Mountain area during 2000-2015

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Journal of Mountain Science 2021年第2期18卷 427-445页

作者： CHEN Shu-ting GUO Bing ZHANG Rui ZANG Wen-qian WEI Cui-xia WU Hong-wei YANG Xiao ZHEN Xiao-yan LI Xing ZHANG Da-fu HAN Bao-min ZHANG Hai-ling School of Civil Architectural Engineering Shandong University of TechnologyZibo 255000China State Key Laboratory of Resources and Environmental information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China Key Laboratory of land use Ministry of Natural ResourcesChina Land Survey and Planning InstituteBeijing 100035China Key Laboratory for Digital land and Resources of Jiangxi Province East China University of TechnologyNanchang 330013China Key Laboratory of National Geographic Census and Monitoring Ministry of Natural ResourcesWuhan 430079China Aerospace information Research Institute Chinese Academy of SciencesBeijing 100101China Key Laboratory of Urbanland Resources Monitoring and Simulation Ministry of Natural ResourcesShenzhen 518000China Key Laboratory of Meteorology and Ecological Environment of Hebei Province Shijiazhuang 050021China land Satellite Remote Sensing Application center Ministry of Natural ResourcesBeijing 100048China College of Geological Engineering and Geomatics Chang'an UniversityXi'an 710054China

The Hengduan mountain area,located in the upper reaches of the Yangtze River of China,is an important ecological barrier that significantly impacts the climate and ecological environment of the surrounding region and western China as a *** paper introduces the gravity center model used to analyze the spatial-temporal variation patterns of vegetation Net Primary Productivity(NPP)from 2000 to 2015,which were determined by the use of MOD17 A3 NPP ***,the dominant driving factors of the spatial–temporal changes of vegetation NPP of the Hengduan Mountain area were quantitatively determined with a geographical detector over *** results revealed that:(1)From 2000 to 2015,there was an increasing trend of vegetation NPP in the Hengduan mountain *** the whole study region,the vegetation NPP with a mean value of 611.37 gC·m^(-2)·a^(-1) indicated a decreasing trend from southeast to northwest in terms of spatial distribution.(2)The gravity centers of vegetation NPP in 2000-2015 were mainly concentrated in Zhongdian *** the study period,the gravity center of vegetation NPP moved northward,which indicated that the increment and increasing rate of vegetation NPP in the northern parts were greater than that of the southern areas.(3)The vegetation NPP showed a moderately positive correlation with temperature,accumulated temperature(>10℃),and sunshine,while there was an overall negative relationship between NPP and precipitation.(4)The dominant factors and interactive dominant factors changed in different subregions over different segments of the study *** dominant factors of most sub-regions in Hengduan mountain were natural factors,and the climate change factors played an increasingly greater role over the 16 years of the study period.

关键词： Vegetation NPP Spatial-temporal distribution Driving factors Geographic detector land use change

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Quantitative distinction of the relative actions of climate change and human activities on vegetation evolution in the Yellow River Basin of China during 1981-2019

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Journal of Arid land 2023年第1期15卷 91-108页

作者： LIU Yifeng GUO Bing LU Miao ZANG Wenqian YU Tao CHEN Donghua School of Civil Architectural Engineering Shandong University of TechnologyZibo 255000China Key Laboratory of Urban land Resources Monitoring and Simulation Ministry of Natural ResourcesShenzhen 518000China Key Laboratory of National Geographic Census and Monitoring Ministry of Natural ResourcesWuhan 430072China Aerospace information Research Institute Chinese Academy of SciencesBeijing 100101China State Key Laboratory of Resources and Environmental information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China Key Laboratory of Agricultural Remote Sensing Ministry of Agriculture and Rural Affairs/Institute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural SciencesBeijing 100081China Zhongke Langfang Institute of Spatial information Applications Langfang 065000China College of Computer and information Engineering Chuzhou UniversityChuzhou 239000China

Under the combined influence of climate change and human activities,vegetation ecosystem has undergone profound *** can be seen that there are obvious differences in the evolution patterns and driving mechanisms of vegetation ecosystem in different historical ***,it is urgent to identify and reveal the dominant factors and their contribution rates in the vegetation change *** on the data of climate elements(sunshine hours,precipitation and temperature),human activities(population intensity and GDP intensity)and other natural factors(altitude,slope and aspect),this study explored the spatial and temporal evolution patterns of vegetation NDVI in the Yellow River Basin of China from 1989 to 2019 through a residual method,a trend analysis,and a gravity center model,and quantitatively distinguished the relative actions of climate change and human activities on vegetation evolution based on Geodetector *** results showed that the spatial distribution of vegetation NDVI in the Yellow River Basin showed a decreasing trend from southeast to *** 1981-2019,the temporal variation of vegetation NDVI showed an overall increasing *** gravity centers of average vegetation NDVI during the study period was distributed in Zhenyuan County,Gansu Province,and the center moved northeastwards from 1981 to *** 1981-2000 and 2001-2019,the proportion of vegetation restoration areas promoted by the combined action of climate change and human activities was the *** the study period(1981-2019),the dominant factors influencing vegetation NDVI shifted from natural factors to human *** results could provide decision support for the protection and restoration of vegetation ecosystem in the Yellow River Basin.

关键词： vegetation evolution driving mechanisms climate change human activities relative actions Geodetector Yellow River Basin

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Spatially Heterogeneous Response of Carbon Storage to land Use Changes in Pearl River Delta Urban Agglomeration, China

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Chinese Geographical Science 2023年第2期33卷 271-286页

作者： LIU Wei LIU Dianfeng LIU Yang School of Resource and Environmental Science Wuhan UniversityWuhan 430079China Key Laboratory of Digital Cartography and land information Application Engineering Ministry of Natural ResourcesWuhan 430079China Guangzhou Urban planning and Design Survey Research Institute Guangzhou 510060China Guangdong Enterprise Key Laboratory for Urban Sensing Monitoring and Early WarningGuangzhou 510060China

Carbon storage of terrestrial ecosystems plays a vital role in advancing carbon neutrality. Better understanding of how land use changes affect carbon storage in urban agglomeration will provide valuable guidance for policymakers in developing effective regional conservation policies. Taking the Pearl River Delta Urban Agglomeration(PRDUA) in China as an example, we examined the heterogeneous response of carbon storage to land use changes in 1990–2018 from a combined view of administrative units and physical entities. The results indicate that the primary change in land use was due to the expansion of construction land(5897.16 km2). The carbon storage in PRDUA decreased from 767.34 Tg C in 1990 to 725.42 Tg C in 2018 with a spatial pattern of high wings and the low middle. The carbon storage loss was largely attributed to construction land expansion(55.74%), followed by forest degradation(54.81%). Changes in carbon storage showed significant divergences in different sized cities and hierarchical boundaries. The coefficients of geographically weighted regression(GWR) reveal that the alteration in carbon storage in Guangzhou City was more responsive to changes in construction land(-0.11) compared to other cities, while that in shenzhen was mainly affected by the dynamics of forest land(8.32). The change in carbon storage was primarily influenced by the conversion of farmland within urban extent(5.05) and the degradation of forest land in rural areas(5.82). Carbon storage changes were less sensitive to the expansion of construction land in the urban center, urban built-up area, and ex-urban built-up area, with the corresponding GWR coefficients of 0.19, 0.04, and 0.02. This study necessitates the differentiated protection strategies of carbon storage in urban agglomerations.

关键词： land use change carbon storage Integrated Valuation of Ecosystem Services and Trade-offs(InVEST)model hierarchical urban boundaries Pearl River Delta Urban Agglomeration(PRDUA) China

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