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Siting of Dark Sky Reserves in China Based on Multi-source Spatial Data and Multiple Criteria Evaluation Method

Chinese Geographical Science 2019年第6期29卷 949-961页

作者： WEI Ye CHEN Zuoqi XIU Chunliang yu bailang LIU Hongxing Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains Ministry of EducationSchool of Geographical SciencesNortheast Normal UniversityChangchun 130024China Key Laboratory of Geographic Information Science(Ministry of Education) East China Normal UniversityShanghai 200241China School of Geographic Sciences East China Normal UniversityShanghai 200241China College of Jang Ho Architecture Northeastern UniversityShenyang 110169China Department of Geography University of AlabamaTuscaloosaAL 35487USA

With the rapid development of population and urbanization and the progress of lighting technology, the influence of artificial light sources has *** this context, the problem of light pollution has attracted wide *** studies have revealed that light pollution can affect biological living environments, human physical and mental health, astronomical observations and many other ***, organizations internationally have begun to advocate for measures to prevent light pollution, many of which are recognized by the International Dark-Sky Association(IDA).In addition to improving public awareness, legal protections, technical treatments and other means, the construction of Dark Sky Reserves(DSR) has proven to be an effective preventive *** far, as a pioneer practice in this field, the IDA has identified 11 DSRs *** on the DA requirements for DSRs, this paper utilizes NPP-VIIRS nighttime light data and other multi-source spatial data to analyze possible DSR sites in *** land of China was divided into more than ten thousand 30 km × 30 km fishnets, and constraint and suitable conditions were designated, respectively, as light and cloud conditions, and scale, traffic and attractiveness *** a multiple criteria evaluation, 1443 fishnets were finally selected as most suitable sites for the construction of *** found that less than 25% of China is not subject to light pollution, and less than 13% is suitable for DSR construction, primarily in western and northern areas, including Tibet, Xinjiang, Qinghai, Gansu and Inner Mongolia.

关键词： Dark Sky Reserves light pollution NPP-VIIRS siting multiple criteria evaluation China

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A multistage collaborative 3D GIS to support public participation

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International Journal of Digital Earth 2015年第3期8卷 212-234页

作者： Yingjie Hu Zhenhua Lv Jianping Wu Krzysztof Janowicz Xizhi Zhao bailang yu Key Laboratory of Geographic Information Science Ministry of EducationEast China Normal UniversityShanghaiPR China Department of Geography University of California Santa BarbaraSanta BarbaraCAUSA Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration East China Normal UniversityShanghaiPR China

This paper presents a collaborative 3D GIS to support public *** that public-involved decision-making is often a multistage process,the proposed system is designed to provide coherent support for collaborations in the different *** differentiate ubiquitous participation and intensive participation and identify their suitable application *** proposed system,then,supports both of the two types of participation by providing synchronous and asynchronous collabora-tion *** the concept of Digital Earth,the proposed system also features a virtual globe-based user *** an interface integrates a variety of data,functions,and services into a unified virtual environment which is delivered to both experts and public participants through the *** system has been designed as a general software framework and can be tailored for specific *** this study,we demonstrate it using a scene modeling case and provide a preliminary evaluation toward its usability.

关键词： public participation multistage decision-making 3D visualization virtual globe online collaboration Digital Earth

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Toward automatic estimation of urban green volume using airborne LiDAR data and high resolution Remote Sensing images

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Frontiers of Earth Science 2013年第1期7卷 43-54页

作者： Yan HUANG bailang yu Jianhua ZHOU Chunlin HU Wenqi TAN Zhiming HU Jianping WU Key Laboratory of Geographic Information Science (Ministry of Education) East China Normal University Shanghai 200241 China Shanghai Landscape and City Appearance Administration Information Center Shanghai 200040 China

Urban green volume is an important indicator for analyzing urban vegetation structure, ecological evaluation, and green-economic estimation. This paper proposes an object-based method for automated estimation of urban green volume combining three-dimensional （3D） information from airborne Light Detection and Ranging （LiDAR） data and vegetation information from high resolution remotely sensed images through a case study of the Lujiazui region, Shanghai, China. High resolution airborne near-infrared photographs are used for identifying the urban vegetation distribution. Airborne LiDAR data offer the possibility to extract individual trees and to measure the attributes of trees, such as tree height and crown diameter. In this study, individual trees and grassland are identified as the independent objects of urban vegetation, and the urban green volume is computed as the sum of two broad portions： individual trees volume and grassland volume. The method consists of following steps： generating and filtering the normalized digital surface model （nDSM）, extracting the nDSM of urban vegetation based on the Normalized Difference Vegetation Index （NDVI）, locating the local maxima points, segment- ing the vegetation objects of individual tree crowns and grassland, and calculating the urban green volume of each vegetation object. The results show the quantity and distribution characteristics of urban green volume in the Lujiazui region, and provide valuable parameters for urban green planning and management. It is also concluded from this paper that the integrated application of LiDAR data and image data presents an effective way to estimate urban green volume.

关键词： Urban areas Vegetation mapping Remote sensing Environmental quality

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Impacts of slope climbing of urban expansion on global sustainable development

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The Innovation 2023年第6期4卷 19-20页

作者： Kaifang Shi bailang yu Jinj Ma Weidong Cao yuanzheng Cui KeyLaboratoryof Earth Surface Processes and Regional Response in the Yangtze Huaihe River Basin Anhui ProvinceSchool of Geography and TourismAnhui Normal UniversityWuhu 241002China State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhan 430079China Key Laboratory of Geographic Information Science(Ministry of Education) East China Normal UniversityShanghai 200241China Collge of Geography and Remote Sensing Hohai UniversityNanjing 210098China Key Laboratory of Watershed Geographic Sciences Nanjing Institute of Geography and LimnologyThe Chinese Academy of SciencesNanjing 210008China

The rapid pace of global urbanization is profoundly reshaping our planet and will have significant implicatins for global sustainable *** to the United Nations,urbanization is projected to surge from 56%in 2020to 67%by 2050,an 11%increase.'The expanding urban population has led to the con-version of an increasing amount of natural land into urban *** is anticipated that by 2030,urban areas across the globe will cover approximately 587 million km2,which is double the rate of population growth.2 In general,the availability of flat land resources suitable for both production and habitation is limited,and the relentless pace of urbanization consistently encroaches upon these ***,adopting the"slope climbing"model for urban expansion has been prevalent in numerous regions and nations as a strategy to address the conflict between urban expansion and the scarcity of flat land resources.

关键词： expansion urban planet

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A geospatial web portal for sharing and analyzing greenhouse gas data derived from satellite remote sensing images

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Frontiers of Earth Science 2013年第3期7卷 295-309页

作者： Hao LIN bailang yu Zuoqi CHEN Yingjie HU Yan HUANG Jianping WU Bin WU Rong GE Key Laboratory of Geographic Information Science (Ministry of Education) East China Normal University Shanghai 200241 China Department of Geography University of California Santa Barbara Santa Barbara CA 93106 USA

Greenhouse gas data collected by different institutions throughout the world have significant scientific values for global climate change studies. Due to the diversity of data formats and different specifications of data access interfaces, most of those data should be first downloaded onto a local machine before they can be used. To overcome this limitation, we present a geospatial web portal for sharing and analyzing greenhouse gas data derived from remote sensing images. As a proof-of-concept, a prototype has also been designed and implemented. The work：flow of the web portal contains four processes： data access, data analysis, results visualiza- tion, and results output. A large volume of greenhouse gas data have been collected, described, and indexed in the portal, and a variety of data analysis services, such as calculating the temporal variation of regionally averaged column CO2 values and analyzing the latitudinal variations of globally averaged column CO2 values, are integrated into this portal. With the integrated geospatial data and services, researchers can collect and analyze greenhouse gas data online, and can preview and download the analysis results directly from the web portal. The geospatial web portal has been implemented as a web application, and we also used a study case to illustrate this framework.

关键词： greenhouse gas data geospatial web portal online spatial analysis

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A New Method for Building-Level Population Estimation by Integrating LiDAR, Nighttime Light, and POI Data

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Journal of Remote Sensing 2021年第1期2021卷 163-179页

作者： Hongxing Chen Bin Wu bailang yu Zuoqi Chen Qiusheng Wu Ting Lian Congxiao Wang Qiaoxuan Li Jianping Wu Key Laboratory of Geographic Information Science(Ministry of Education) East China Normal UniversityShanghai 200241China School of Geographic Sciences East China Normal UniversityShanghai 200241China Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education National&Local Joint Engineering Research Center of Satellite Geospatial Information TechnologyFuzhou UniversityFuzhou 350108China The Academy of Digital China Fuzhou UniversityFuzhou 350108China Department of Geography University of TennesseeKnoxvilleTN 37996USA Department of Geography The University of Hong KongHong Kong 999077China

Building-level population data are of vital importance in disaster management,homeland security,and public *** sensed data,especially LiDAR data,which allow measures of three-dimensional morphological information,have been shown to be useful for fine-scale population ***,studies using LiDAR data for population estimation have noted a nonstationary relationship between LiDAR-derived morphological indicators and populations due to the unbalanced characteristic of population *** this article,we proposed a framework to estimate population at the building level by integrating POI data,nighttime light(NTL)data,and LiDAR *** objects were first derived using LiDAR data and aerial ***,three categories of building-level features,including geometric features,nighttime light intensity features,and POI features,were,respectively,extracted from LiDAR data,Luojia1-01 NTL data,and POI ***,a welltrained random forest model was built to estimate the population of each individual *** District in Shanghai,China,was chosen to validate the proposed method.A comparison between the estimation result and reference data shows that the proposed method achieved a good accuracy with R^(2)=0:65 at the building level and R^(2)=0:79 at the community *** NTL radiance intensity was found to have a positive relationship with population in residential areas,while a negative relationship was found in office and commercial *** study has shown that by integrating both the three-dimensional morphological information derived from LiDAR data and the human activity information extracted from POI and NTL data,the accuracy of building-level population estimation can be improved.

关键词： POI LiDAR estimation

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利用NPP-VIIRS夜间灯光遥感数据分析城市蔓延对雾霾污染的影响

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武汉大学学报（信息科学版） 2021年第5期46卷 777-789页

作者：伍亿真施开放余柏蒗李川龙西南大学地理科学学院重庆400715 西南大学西南山地生态循环农业国家级培育基地重庆400715 西南大学重庆金佛山喀斯特生态系统国家野外科学观测研究站重庆400715 华东师范大学地理信息科学教育部重点实验室上海200241 西南大学资源环境学院重庆400715

雾霾污染已经成为中国乃至全球重点关注的生态环境问题之一。与此同时,中国的雾霾污染与城市蔓延在某种程度上相伴而生。城市蔓延是否加剧了中国的雾霾污染目前还没有明确的答案。因此,利用美国国家极地轨道合作卫星搭载的可见光红外成... 详细信息

雾霾污染已经成为中国乃至全球重点关注的生态环境问题之一。与此同时,中国的雾霾污染与城市蔓延在某种程度上相伴而生。城市蔓延是否加剧了中国的雾霾污染目前还没有明确的答案。因此,利用美国国家极地轨道合作卫星搭载的可见光红外成像辐射仪(national polar-orbiting partnership.s visible infrared imaging radiometer suite,NPP-VIIRS)获取的夜间灯光数据,在量化城市蔓延的基础上构建面板数据模型,探究城市蔓延是否会对城市雾霾污染产生影响,并利用中介效应模型验证城市蔓延影响雾霾污染的驱动机制。研究结果表明,夜间灯光数据可以有效地量化与表征城市蔓延,且中国的城市蔓延在一定程度上加剧了雾霾污染。此外,城市蔓延主要通过集聚效应、土地城镇化效应、产业结构效应等途径影响雾霾污染。

关键词：城市蔓延雾霾污染细颗粒物(PM2.5) 夜间灯光遥感 NPP-VIIRS

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地理大数据揭示中国主要城市建成环境物质存量的空间格局

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Engineering 2024年第3期34卷 143-153页

作者： Zhou Huang Yi Bao Ruichang Mao Han Wang Ganmin Yin Lin Wan Houji Qi Qiaoxuan Li Hongzhao Tang Qiance Liu Linna Li bailang yu Qinghua Guo yu Liu Huadong Guo Gang Liu Institute of Remote Sensing and Geographical Information Systems School of Earth and Space SciencesPeking UniversityBeijing 100871China International Research Center of Big Data for Sustainable Development Goals Beijing 100094China SDU Life Cycle Engineering Department of Green TechnologyUniversity of Southern DenmarkOdense 5230Denmark Department of Construction Management School of Civil EngineeringTsinghua UniversityBeijing 100084China School of Computer Science China University of GeosciencesWuhan 430074China School of Geographical Sciences East China Normal UniversityShanghai 200062China Land Satellite Remote Sensing Application Center Ministry of Natural ResourcesBeijing 100048China Institute of Geographic Sciences and Natural Resources Research Chinese Academy of SciencesBeijing 100101China Department of Geography California State UniversityLong BeachCA 90840USA Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094China College of Urban and Environmental Sciences Peking UniversityBeijing 100871China

The patterns of material accumulation in buildings and infrastructure accompanied by rapid urbanization offer an important,yet hitherto largely missing stock perspective for facilitating urban system engineering and informing urban resources,waste,and climate ***,our existing knowledge on the patterns of built environment stocks across and particularly within cities is limited,largely owing to the lack of sufficient high spatial resolution *** study leveraged multi-source big geodata,machine learning,and bottom-up stock accounting to characterize the built environment stocks of 50 cities in China at 500 m fine-grained *** per capita built environment stock of many cities(261 tonnes per capita on average)is close to that in western cities,despite considerable disparities across cities owing to their varying socioeconomic,geomorphology,and urban form *** is mainly owing to the construction boom and the building and infrastructure-driven economy of China in the past ***’s urban expansion tends to be more“vertical”(with high-rise buildings)than“horizontal”(with expanded road networks).It trades skylines for space,and reflects a concentration-dispersion-concentration pathway for spatialized built environment stocks development within cities in *** results shed light on future urbanization in developing cities,inform spatial planning,and support circular and low-carbon transitions in cities.

关键词： Urban system engineering Built environment stock Spatial pattern Urban sustainability Big geodata

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基于移动激光扫描点云特征图像和SVM的建筑物立面半自动提取方法

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地球信息科学学报 2016年第7期18卷 878-885页

作者：彭晨余柏蒗吴宾吴健平华东师范大学地理信息科学教育部重点实验室上海200241

建筑物立面是城市地物的重要组成部分,而移动激光扫描是获取城市地物三维信息的重要手段之一。本文提出了一种基于移动激光扫描点云的建筑物立面半自动提取算法。该方法首先构建研究区水平网格;然后计算局部点云几何特征,并且将特征投... 详细信息

建筑物立面是城市地物的重要组成部分,而移动激光扫描是获取城市地物三维信息的重要手段之一。本文提出了一种基于移动激光扫描点云的建筑物立面半自动提取算法。该方法首先构建研究区水平网格;然后计算局部点云几何特征,并且将特征投影到水平网格生成点云特征图像;接着基于支持向量机(Support Vector Machine,SVM)对建筑物立面网格进行粗提取;最后使用网格属性(形状系数、网格面积、最大高程)对粗提取结果进行过滤,并将结果反投影到三维空间中得到精确的建筑物立面。以卡内基梅隆大学的移动激光扫描点云进行试验后表明,本算法能够较好地提取出建筑物立面,提取精度为84%,召回率为90%,数据修正后精度为88%,召回率为91%。通过与现有算法对比,本文提出的算法具有较高精度。

关键词：移动激光扫描系统建筑物立面提取点云特征图像支持向量机(SVM)

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一种应用机载LiDAR数据和高分辨率遥感影像提取城市绿地信息的方法

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中国图象图形学报 2010年第5期15卷 782-789页

作者：余柏蒗刘红星吴健平华东师范大学地理信息科学教育部重点实验室上海200062 Department of Geography Texas A&M UniversityCollege Stationtexasusa77843

提出了一种新的面向对象的城市绿地信息两阶段提取方法。该方法分阶段使用高分辨率遥感影像的光谱和2维形态信息以及机载LiDAR数据的3维形态信息作为分类依据。第1阶段,影像首先被分割为对象,对象被分类为无阴影的植被、阴影下的植被、... 详细信息

提出了一种新的面向对象的城市绿地信息两阶段提取方法。该方法分阶段使用高分辨率遥感影像的光谱和2维形态信息以及机载LiDAR数据的3维形态信息作为分类依据。第1阶段,影像首先被分割为对象,对象被分类为无阴影的植被、阴影下的植被、水体、建筑物、空地和阴影6类地物;无阴影的植被和阴影下的植被合并为城市绿地对象,在第2阶段,将LiDAR数据产生的归一化数字表面模型nDSM与绿地对象叠加,计算每个对象的3维形态属性,进一步将绿地对象细分为草坪、灌木和乔木。以美国休斯敦中心城区为例,介绍了方法流程。精度分析表明,绿地的分类精度达到93.46%;方法中的主要误差来源于遥感影像当中的建筑物阴影以及生成数字地形模型时所产生的误差。

关键词：城市绿地面向对象分类两阶段分类 LiDAR 高分辨率遥感影像

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