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13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, WHISPERS 2023

作者： Chen, Lihan Tan, Kun Wang, Xue Pan, Chen China University of Mining and Technology Key Laboratory for Land Environment and Disaster Monitoring of Nasg Xuzhou221116 China Shanghai200241 China East China Normal University Key Lab. of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities Ministry of Natural Resources Shanghai200241 China East China Normal University School of Geographic Sciences Shanghai200241 China Shanghai Municipal Institute of Surveying and Mapping Shanghai200063 China

ISBN: (纸本)9798350395570

Soil organic matter (SOM) content plays an important part in soil environmental quality definition and should be estimated necessarily. The conventional methods for the SOM concentration assessment are mainly based on lab.ratory physicochemical analysis, which is costly and time consuming. Visible and near-infrared (Vis-NIR) spectroscopy offers the potential to quantify the SOM over large areas based on the soil spectral characteristics. Therefore, an innovative methodology using visible and near-infrared reflectance spectra are proposed in this work to monitoring the SOM rapidly and economically. A total of 91 soil samples and their spectral data collected in Yitong of China were utilized to characterize the relationship between the soil reflectance spectrum and SOM. First, continuum removal (CR) and competitive adaptive reweighted sampling (CARS) are introduced as the pretreatment method and wavebands selection method respectively, which can amplify the weak spectral characteristic. After the preprocessing phases, Partial Least Squares (PLS), Random Forest (RF) and XGBoost are carried out to estimate the SOM and the results show that XGBoost yields the best performance with R2 of 0.9968 on training set and 0.6831 on testing set. Finally, the distribution trend of SOM in the whole study area is mapped using the optimal CR-CARS-XGBoost model. © 2023 IEEE.

关键词： Soils

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Spatiotemporal distribution and inter-media transfer of polycyclic aromatic hydrocarbons in Shanghai, China: Historical patterns and future trends

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Science of the Total Environment 2024年 945卷 173938页

作者： Li, Ting Nie, Ning Miao, Yiyi Zhao, Dengzhong Liu, Min Key Laboratory of Geographic Information Science of the Ministry of Education School of Geographic Sciences East China Normal University Shanghai200241 China Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities Ministry of Natural Resources Shanghai200241 China Changjiang River Scientific Research Institute Wuhan430010 China

Polycyclic Aromatic Hydrocarbons (PAHs) represent pervasive pollutants, posing health risks in urban environments. It is essential to comprehend the spatiotemporal distributions, composition profiles, and inter-media transfer processes of PAHs in various environmental compartments, influenced by both natural changes and anthropogenic activities. This study integrates historical and future spatiotemporally changing environmental parameters, including climate data, GDP, population data, land-use types, and hydrological variables, into the Multimedia Urban Model (MUM). This integration enables the simulation of spatiotemporal distributions and inter-media transfer fluxes of PAHs among six different media from the 2010s to the 2100s under two distinct Shared Socio-economic Pathways (SSP) scenarios in the megacity of Shanghai, China. The MUM model, featuring diverse gridded parameters, effectively captures PAH concentrations and movement across environmental compartments. Results indicate a decreasing trend in PAHs concentrations in the 2100s compared to the 2010s, with PAH concentrations in water, sediment, vegetation, and organic film covering impermeable surfaces under the SSP3–7.0 scenario higher than those of the SSP1–2.6 scenario. Low molecular weight PAHs dominate in the sediment, water, and air, whereas high molecular weight PAHs prevail in the organic film, vegetation, and soil. Sediment and soil serve as the predominant sinks for PAHs. The primary transport processes for PAH movement include air-film, air-soil, film-water, soil-air, and water-air. Almost all transfer fluxes exhibit a declining trend in future periods except for the air-film transport pathway. The principal input and removal routes for PAHs in Shanghai involve the advection of air and water. The study provides essential insights into the environmental behavior of PAHs and informs targeted pollution control in Shanghai. Additionally, it serves as a technical reference for similar pollution predic

关键词： Soils

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Using Multidisciplinary analysis to Develop Adaptation Options against Extreme Coastal Floods

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International Journal of Disaster Risk Science 2022年第4期13卷 577-591页

作者： Xinmeng Shan Jun Wang Jiahong Wen Hengzhi Hu Lei Wang Jie Yin Mengya Li Key Laboratory of Geographic Information Science Ministry of EducationEast China Normal UniversityShanghai 200241China School of Geographic Sciences East China Normal UniversityShanghai 200241China Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities Ministry of Natural ResourcesShanghai 200241China School of Environmental and Geographical Sciences Shanghai Normal UniversityShanghai 200234China Department of Hospitality Management Shanghai Business SchoolShanghai 200235China Department of Geography and Anthropology Louisiana State UniversityBaton RougeLA 70810USA

Long-term flood risk adaptation and decision making are complex because the future is full of deep *** and robustness can be used to deal with future *** study developed an integrated modeling framework that extends previous studies to the spatial domain to assess the future flood risks and the cost and benefit of three adaptation measures for four types of buildings in *** options analysis(ROA)and dynamic adaptive policy pathways(DAPP)were integrated to develop a dynamic adaptation pathway and identify robust adaptation *** results show that:(1)Sea level rise and land subsidence will significantly exacerbate the flood risks in Shanghai;(2)Among the three flood control measures,wet-floodproofing has the best economic performance in terms of both the net present value and the benefit/cost ratio,followed by dry-floodproofing,and elevation;(3)Dryfloodproofing can be used at the beginning of the future period(2030–2100),and it can be replaced by wet-floodproofing in 2035–2042;the elevation measure also shows good performance at the beginning of implementation,but its performance will decline after 2041–2045;(4)The combined strategy of dry-and wet-floodproofing in 2044–2046and a hybrid strategy combining the three measures should be the optimal solution for reducing the flood risks in 2047–*** methodology developed in this study can provide insights for coastal cities to formulate cost-effective and feasible adaptation strategies in a deeply uncertain future.

关键词： Adaptation options Building-level measures Climate change Coastal floods Cost-benefit analysis Shanghai

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Estimating China's poverty reduction efficiency by integrating multi-source geospatial data and deep learning techniques

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地球空间信息科学学报（英文版） 2024年第4期27卷 1000-1016页

作者： Yao Yao Jianfeng Zhou Zhenhui Sun Qingfeng Guan Zhiqiang Guo Yin Xu Jinbao Zhang Ye Hong Yuyang Cai Ruoyu Wang School of Geography and Information Engineering China University of GeosciencesWuhanChina Center for Spatial Information Science The University of TokyoChibaJapan Alibaba Group HangzhouChina Foshan Surveying Mapping and Geoinformation Research Institute FoshanChina Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities(Ministry of Natural Resources) School of Geographic SciencesEast China Normal UniversityShanghaChina School of Geography and Information Engineering China University of GeosciencesWuhanChina Institute of International Rivers and Eco-Security Yunnan UniversityKunmingChina Institute of Geography and Spatial Information School of Earth SciencesZhejiang UniversityHangzhouChina School of Geography and Planning Sun Yat-Sen UniversityGuangzhouChina Institute of Cartography and Geoinformation ETH ZurichZürichSwitzerland Department of Civil Environmental and Geomatic Engineering School of EngineeringUniversity College LondonLondonUK Centre for Public Health Queen's University BelfastBelfastNorthern IrelandUK

Poverty threatens human development especially for developing countries,so ending poverty has become one of the most important United Nations Sustainable Development Goals(SDGs).This study aims to explore China's progress in poverty reduction from 2016 to 2019 through time-series multi-source geospatial data and a deep learning *** poverty reduction efficiency(PRE)is measured by the difference in the out-of-poverty rates(which measures the probability of being not poor)of 2016 and *** study shows that the probability of poverty in all regions of China has shown an overall decreasing trend(PRE=0.264),which indicates that the progress in poverty reduction during this period is *** Hu Huanyong Line(Hu Line)shows an uneven geographical pattern of out-of-poverty rate between Southeast and Northwest *** 2016 to 2019,the centroid of China's out-of-poverty rate moved 105.786 km to the northeast while the standard deviation ellipse of the out-of-poverty rate moved 3 degrees away from the Hu Line,indicating that the regions with high out-of-poverty rates are more concentrated on the east side of the Hu Line from 2016 to *** results imply that the government's future poverty reduction policies should pay attention to the infrastructure construction in poor areas and appropriately increase the population density in poor *** study fills the gap in the research on poverty reduction under multiple scales and provides useful implications for the government's poverty reduction policy.

关键词： Poverty reduction efficiency(PRE) driving forces multisource big data deep learning random forest(RF)

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Mathematical model for predicting fungal growth and decomposition rates based on improved Logistic equations

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International Journal of Agricultural and Biological Engineering 2023年第1期16卷 60-65页

作者： Jiayong Pan Wenxin Le Zi’ao Wang Jian Chen College of Engineering China Agricultural UniversityBeijing 100083China Shenzhen Key Laboratory of Intelligent Microsatellite Constellation Shenzhen 518107GuangdongChina Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities MNRShanghai 200063China Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural ResourcesShenzhen 518000GuangdongChina Jiangsu Province and Education Ministry Co-sponsored Synergistic Innovation Center of Modern Agricultural Equipment Jiangsu UniversityZhenjiang 212013China Key Laboratory of Smart Agricultural Technology in Tropical South China Ministry of Agriculture and Rural AffairsGuangzhou 510642China State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191China State Key Laboratory of Clean Energy Utilization Zhejiang UniversityHangzhou 310013China

As the function of the decomposition of fungi has been clearly researched in the global carbon cycle,it is obviously of value to explore the decomposition rate of fungal *** study analyzed the relationship between environmental factors and biodiversity step by *** order to explore the interaction between the fungi and the relationship between the decomposition rate of fungi with time,the model based on the Logistic model was built and the Lotka-Volterra model was employed in the condition of two kinds of fungi existing in an environment with limited *** changing trend of population number and decomposition rate of several fungi under different environmental conditions can be predicted through the *** illustrate the applicability of the model,Laetiporus conifericola and Hyphoderma setigerum were applied as *** results showed that the higher the degree of population diversity,the greater the decomposition rate,and the higher the decomposition efficiency of the *** rich species diversity is conducive to accelerating the decomposition of litter,lignocellulose,and the circulation of the entire *** on the above model and using the data from measuring the mycelial elongation rate of each isolate at 10℃,16℃,and 22℃ under standardized lab.ratory conditions,the growth patterns of the five fungi combinations were *** results revealed a general increase in growth rate with increasing temperature,which verifies the accuracy of the ***,it also revealed that the total decomposition rate after fungal incorporation was negatively correlated with the decomposition rate of a fungal single *** on the above model,predictions can be made for fungal growth in different environments,and suitable environments for fungal growth can be *** the future,the model can be further optimized,and lignin and cellulose decomposition factors can be added to fit the decomposition of *** application

关键词： Logistic equations fungal decomposition mathematical model

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Extracting Named Entity Using Entity lab.ling in Geological Text Using Deep Learning Approach

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Journal of Earth Science 2023年第5期34卷 1406-1417页

作者： Qinjun Qiu Miao Tian Zhong Xie Yongjian Tan Kai Ma Qingfang Wang Shengyong Pan Liufeng Tao State Key Laboratory of Geo-Information Engineering and Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of MNR Chinese Academy of Surveying and MappingBeijing 100036China Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities MNRShanghai 20063China Key Laboratory of Geological Survey and Evaluation of Ministry of Education China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges UniversityYichang 443002China College of Computer and Information Technology China Three Gorges UniversityYichang 443002China Chengdu Geological Environment Monitoring Station Chengdu 610036China Wuhan Zondy Cyber Science&Technology Co. Ltd.Wuhan 430074China

Artificial intelligence(AI) is the key to mining and enhancing the value of big data, and knowledge graph is one of the important cornerstones of artificial intelligence, which is the core foundation for the integration of statistical and physical representations. Named entity recognition is a fundamental research task for building knowledge graphs, which needs to be supported by a high-quality corpus, and currently there is a lack of high-quality named entity recognition corpus in the field of geology, especially in Chinese. In this paper, based on the conceptual structure of geological ontology and the analysis of the characteristics of geological texts, a classification system of geological named entity types is designed with the guidance and participation of geological experts, a corresponding annotation specification is formulated, an annotation tool is developed, and the first named entity recognition corpus for the geological domain is annotated based on real geological reports. The total number of words annotated was 698 512 and the number of entities was 23 345. The paper also explores the feasibility of a model pre-annotation strategy and presents a statistical analysis of the distribution of technical and term categories across genres and the consistency of corpus annotation. Based on this corpus, a Lite Bidirectional Encoder Representations from Transformers(ALBERT)-Bi-directional Long Short-Term Memory(BiLSTM)-Conditional Random Fields(CRF) and ALBERT-BiLSTM models are selected for experiments, and the results show that the F1-scores of the recognition performance of the two models reach 0.75 and 0.65 respectively, providing a corpus basis and technical support for information extraction in the field of geology.

关键词： ontology geological reports named entity recognition geological corpus construction semi-automated annotation platforms deep learning

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Innovative remote sensing methodologies and applications in coastal and marine environments

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地球空间信息科学学报（英文版） 2024年第3期27卷 836-853页

作者： Qing Zhao Antonio Pepe Virginia Zamparelli Pietro Mastro Francesco Falab.lla Saygin Abdikan Caglar Bayik Fusun Balik Sanli Mustafa Ustuner Nevin Betul Avşar Jingjing Wang Peng Chen Zhengjie Li Adam T.Devlin Fabiana Calò Key Laboratory of Geographical Information Science Ministry of EducationEast China Normal UniversityShanghaiChina School of Geographic Sciences East China Normal UniversityShanghaiChina Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities Ministry of Natural ResourcesShanghaiChina Institute for Electromagnetic Sensing of the Environment(IREA) Italian National Research CouncilNapoliItaly School of Engineering University of BasilicataPotenzaItaly Institute for Electromagnetic Sensing of the Environment(IREA) Italian National Research CouncilNapoliItaly Institute for Electromagnetic Sensing of the Environment(IREA) Italian National Research CouncilNapoliItaly Institute of Methodologies for Environmental Analysis(IMAA) Italian National Research CouncilTito ScaloItaly Department of Geomatics Engineering Hacettepe UniversityAnkaraTurkey Department of Geomatics Engineering Zonguldak Bulent Ecevit UniversityZonguldakTurkey Department of Geomatic Engineering Yildiz Technical UniversityIstanbulTurkey Department of Geomatic Engineering Artvin Çoruh UniversityArtvinTurkey Department of Geomatics Engineering Izmir Katip Celebi UniversityİzmirTurkey School of Ocean and Earth Science and Technology University of Hawaii at MānoaHonoluluHIUSA

Remote sensing(RS)technologies are extensively exploited by scientists and a vast audience of local authorities,urban managers,and city *** regions,geohazard-prone areas,and highly populated cities represent natural lab.ratories to apply RS technologies and test new *** the last decades,many efforts have been spent on improving Earth's surface monitoring,including intensifying Earth Observation(EO)operations by the major national space *** oversee to plan and make operational constellations of satellite sensors providing the scientific community with extensive research and development oppor-tunities in the geoscience *** instance,within this framework,the European Space Agency(ESA)and the Ministry of Science and Technology of China(MOST)have sponsored,since the early 2000s,the DRAGON initiative jointly carried out by the European and Chinese RS scientific *** manuscript aims to provide a synthetic overview of some research activities and new methods recently designed and applied and trace the route for further *** main findings are related to ⅰ)the analysis of flood risk in China,ⅱ)the potential of new methods for the estimation and removal of ground displacement biases in small-baseline oriented interferometric Synthetic Aperture Radar(SAR)methods,ⅲ)the analy-sis of the inundation risk in low-lying regions using coherent and incoherent SAR methods;andⅳ)the use of SAR-based technologies for marine applications.

关键词： Disaster risk management Remote Sensing(RS) Earth Observation(EO) Synthetic Aperture Radar(SAR) flooding subsidence coastal/marine environments

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Taxi travel time based Geographically Weighted Regression Model (GWR) for modeling public housing prices in Singapore 29

Taxi travel time based Geographically Weighted Regression Mo...

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29th International Conference on Geoinformatics, Geoinformatics 2022

作者： Wang, Yi'an Cai, Fangyi Cheng, Shih-Fen Wu, Bo Cao, Kai School of Geographic Sciences East China Normal University Shanghai China East China Normal University Key Laboratory of Geographic Information Science Ministry of Education Shanghai China East China Normal University Key Lab. of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities Ministry of Natural Resources Shanghai China National University of Singapore Department of Geography Singapore School of Computing and Information Systems Singapore Management University Singapore School of Geography and Environment Jiangxi Normal University Jiangxi Nanchang China

ISBN: (数字)9798350309881

ISBN: (纸本)9798350309881

In this research, a taxi travel time based Geographically Weighted Regression model (GWR) is proposed and utilized to model the public housing price in the case study of Singapore. In addition, a comparison between the proposed taxi data driven GWR and other models, such as ordinary least squares model (OLS), GWR model based on Euclidean distance and GWR model based on public transport travel time, have also been carried out. Results indicates that taxi travel time based GWR model has better fitting performance than the OLS model, and slightly better than the Euclidean distance-based GWR model, however, it is not as good as the GWR model based on public transport travel time according to the metric of Adjusted R2. These experiments indicate that the public transport travel time may has a major part to play in modeling the public housing resale prices compared to taxi travel time or driving time, and both the taxi travel time and public transport travel time can better explain the public housing resale prices in Singapore compared to Euclidean distance in the GWR modeling. © 2022 IEEE.

关键词： Travel time

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dataset of Urban Plant Color Evaluation and Residents'Anxiety in Shanghai(2017)

全球变化数据仓储（中英文）

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全球变化数据仓储（中英文） 2023年第3期 14-15页

作者： WU Jiayu WANG Shiyi LI Hong TA Na Institute of Landscape Architecture Zhejiang UniversityHangzhou 310058China Key Laboratory of Geographic Information Science Ministry of EducationEast China Normal UniversityShanghai 200241China School of Geographic Sciences East China Normal UniversityShanghai 200241China Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities Ministry of Natural ResourcesShanghai 200241China

Based on the questionnaire survey of residents'activity logs conducted in Shanghai from March to July in 2017,buffer zones were established with the center of the buffer zone in the residential area and workplace respectively,and the radius of the buffer zone was chosen to be 500 m and 1000 *** green view index(GVI),as well as the foliage color and flower color diversity were evaluated for each buffer *** Anxiety was assessed using the Depression-Anxiety-Stress Scale(DASS-21).The dataset includes:(1)results of individual anxiety level evaluation and economic and social characteristics;(2)results of plant color evaluation(centered on residential areas);(3)results of plant color evaluation(centered on workplace);(4)descriptive analysis of samples;(5)average plant color evaluation and comparison between groups;(6)Results of ordinal logistic regression models on plant color and anxiety;(7)the counts for plant foliage color in concentrated construction area of Shanghai;(8)the counts for plant flower colors;(9)the average green view *** dataset is archived *** *** formats,and consists of 4 data files with data size of 450 KB(compressed into one single file with 159 KB).The analysis paper based on the dataset will be published in coordination with Acta Geographica Sinica,Vol.78,No.4,2023.

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GIS Based FLMP Solving in Densely Populated City Areas: a Case Study in Singapore

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Journal of Geodesy and Geoinformation Science 2022年第2期5卷 111-123页

作者： Yu Ning Hazel ANG Kai CAO Department of Geography National University of SingaporeSingapore 139649Singapore School of Geographic Sciences East China Normal UniversityShanghai 200241China Key Laboratory of Geographic Information Science(Ministry of Education) East China Normal UniversityShanghai 200241China Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities(Ministry of Natural Resources) Shanghai 200241China

With continual population growth in the densely populated cities,e.g.,Singapore,traffic congestion is the main transportation *** such,Public Transport is deemed as the most sustainable mode of ***,pubic transport is often plagued with the First and Last Mile Problem(FLMP),reducing its appeal especially in the densely populated city *** FLMP leads to a wide range of complications,in particular,human congestion in public *** this research,after a comprehensive discussion of FLMP problem in densely populated city areas,a case study in Singapore,i.e.,the Kent Ridge Campus of National University of Singapore(KRC-NUS),has been conducted based on the survey and spatio-temporal *** addition to the investigation of FLMP status in the case study area,a new campus shuttle bus route from an alternative MRT station(Haw Par Villa Station)has also been proposed based on the Tabu Search to alleviate the human congestion and current FLMP status for *** research not only has successfully addressed the FLMP in the case study area,but also can be a good reference for other areas in densely populated cities to help mitigate FLMPs.

关键词： GIS First and Last Mile Problem Tabu Search Public Transport Singapore

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