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Vulnerability Assessment Method for Immovable Cultural Relics Based on Artificial Neural Networks—An Example of a Heavy Rainfall Event in Henan Province

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International Journal of Disaster Risk Science 2023年第1期14卷 41-51页

作者： Can Xu Adu Gong Long Liang Xiaoke Song Yi Wang State key laboratory of remote sensing Science Beijing Normal UniversityBeijing100875China beijing key laboratory of environmental remote sensing and digital city Beijing Normal UniversityBeijing100875China Faculty of Geographical Science Beijing Normal UniversityBeijing100875China

Cultural relic conservation capability is an important issue in cultural relic conservation research,and it is critical to decrease the vulnerability of immovable cultural relics to rainfall hazards.Commonly used vulnerability assessment methods are subjective,are mostly applied to regional conditions,and cannot accurately assess the vulnerability of cultural relics.In addition,it is impossible to predict the future vulnerability of cultural relics.Therefore,this study proposed a machine learning-based vulnerability assessment method that not only can assess cultural relics individually but also predict the vulnerability of cultural relics under different rainfall hazard intensities.An extreme rainfall event in Henan Province in 2021 was selected as an example,with a survey report on the damage to cultural relics as a database.The results imply that the back propagation(BP)neural network-based method of assessing the vulnerability of immovable cultural relics is reliable,with an accuracy rate higher than 92%.Based on this model to predict the vulnerability of Zhengzhou city’s cultural relics,the vulnerability levels of cultural relics under different recurrence periods of heavy rainfall were obtained.Among them,the vulnerability of ancient sites is higher than those of other cultural relic types.The assessment model used in this study is suitable for predicting the vulnerability of immovable cultural relics to heavy rainfall hazards and can provide a technical means for cultural relic conservation studies.

关键词： Artificial neural networks Henan Province Immovable cultural relics Rainfall hazards Vulnerability assessment

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Efficient algorithm for improving the hotspot effect of the operational MODIS BRDF product

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遥感学报 2014年第4期18卷 804-825页

作者： DONG Yadong JIAO Ziti ZHANG Hu Li Jiayue JIAO Guangping SHI Hanyu School of Geography Beijing Normal University Beijing 100875 China State key laboratory of remote sensing Science Beijing 100875 China key laboratory of environmental remote sensing and digital city Beijing 100875 China

An algorithm for modeling bidirectional reflectance anisotropies of land surfaces has been developed as a surrogate for the operational MODIS Bidirectional Reflectance Distribution Function （BRDF） and albedo product for user community. This algorithm is a set of kernel-driven BRDF models extensively used in several space-borne remotely sensed BRDF/albedo products. Among these models, RossThick （RT）-LiSparseR （RTLSR） has been selected as the current operational MODIS BRDF/albedo algorithm. However, the hotspot effect has not been considered in RT kernel. As such, the use of an RTLSR model underestimates hotspot reflectance, thereby influencing the accuracy of the retrieval of vegetation structures, such as clumping index. On the basis of Breon＇s hotspot factor, Maignan corrected RT kernel to generate a RTMalgnan （RTM） kernel. For producers, a 13-year MODIS BRDF/albedo product is reprocessed using this corrected model, but this task is time consuming. For users, the direct use of this corrected model for MODIS observations is complicated because the equivalent inputs of the operational RTLSR algorithm are not easily available. In this study, a method was developed to correct the hotspot effect for the operational MODIS BRDF product, which is available for users. Based on the effective vaFldation using POLDER-3/BRDF data and the selected MODIS data, this study shows that （1） an improvement of approximately 10.12% of relative error between our method and the RTLSR model can be obtained by estimating the hotspot reflectance; （2） a relative error of approximately 2.10% occurs between this method and the RTM-LiSparseR （RTMLSR） model, but this difference is not significant; （3） relative error reaches approximately 4.99% between this method and the RTLSR model to simulate NDFID but decreases to approximately 1.32% between this method and the RTMLSR model.

关键词： kernel-driven BRDF models AMBRALS BRDF hotspot MODIS BRDF/albedo product

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Vegetation physiological parameter setting in the Simple Biosphere model 2(SiB2) for alpine meadows in the upper reaches of Heihe river

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Science china Earth Sciences 2015年第5期58卷 755-769页

作者： LI Yuan SUN Rui LIU Shao Min State key laboratory of remote sensing Science Beijing Normal University and Institute of Remote Sensing and Digital Earth CAS School of Geography Beijing Normal University beijing key laboratory of environmental remote sensing and city digitalization Department of Civil Engineering Monash University

Land surface process modeling of high and cold area with vegetation cover has not yielded satisfactory results in previous applications. In this study, land surface energy budget is simulated using a land surface model for the A'rou meadow in the upper-reach area of the Heihe River Basin in the eastern Tibetan Plateau. The model performance is evaluated using the in-situ observations and remotely sensed data. Sensible and soil heat fluxes are overestimated while latent heat flux is underestimated when the default parameter setting is used. By analyzing physical and physiological processes and the sensitivities of key parameters, the inappropriate default setting of optimum growth and inhibition temperatures is identified as an important reason for the bias. The average daytime temperature during the period of fastest vegetation growth(June and July) is adopted as the optimum growth temperature, and the inhibition temperatures were adjusted using the same increment as the optimum temperature based on the temperature acclimation. These adjustments significantly reduced the biases in sensible, latent, and soil heat fluxes.

关键词：高寒草甸植被参数设置生理过程生物圈模式黑河上游 SIB2 最适生长温度土壤热通量

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Assessing the uncertainties of phytoplankton absorption-based model estimates of marine net primary productivity

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Acta Oceanologica Sinica 2017年第6期36卷 112-121页

作者： TAO Zui MA Sheng YANG Xiaofeng WANG Yan State key laboratory of remote sensing Science Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijing 100101China beijing North-Star digital remote sensing Technology Co.Ltd. Beijing 100120China State environmental Protection key laboratory of Numerical Modeling for Environment Impact Assessment Beijing 100012China

Satellite-derived phytoplankton pigment absorption （aph） has been used as a key predictor of phytoplankton photosynthetic efficiency to estimate global ocean net primary production （NPP）. In this study, an aph-based NPP model （AbPM） with four input parameters including the photosynthetically available radiation （PAR）, diffuse attenuation at 490 nm （Ka（490））, euphotic zone depth （Zeu） and the phytoplankton pigment absorption coefficient （aph） is compared with the chlorophyll-based model and carbon-based model. It is found that the AbPM has significant advantages on the ocean NPP estimation compared with the chlorophyll-based model and carbon- based model. For example, AbPM greatly outperformed the other two models at most monitoring sites and had the best accuracy, including the smallest values of RMSD and bias for the NPP estimate, and the best correlation between the observations and the modeled NPPs. In order to ensure the robustness of the model, the uncertainty in NPP estimates of the AbPM was assessed using a Monte Carlo simulation. At first, the frequency histograms of simple difference （fi）, and logarithmic difference （~LOG） between model estimates and in situ data confirm that the two input parameters （Zeu and PAR） approximate the Normal Distribution, and another two input parameters （aph and Ka（490）） approximate the logarithmic Normal Distribution. Second, the uncertainty in NPP estimates in the AbPM was assessed by using the Monte Carlo simulation. Here both the PB （percentage bias）, defined as the ratio of ANPP to the retrieved NPP, and the CV （coefficient of variation）, defined as the ratio of the standard deviation to the mean are used to indicate the uncertainty in the NPP brought by input parameter to AbPM model. The uncertainty related to magnitude is denoted by PB and the uncertainty related to scatter range is denoted by CV. Our investigations demonstrate that PB of NPP uncertainty brought by all parameters with an annual mean of 5.5% covered a range of -5%-15% for the global ocean. The PB uncer

关键词： marine net primary production phytoplankton pigment absorption satellite remote sensing uncertainty analysis Monte Carlo simulation

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Urbanization of county in china:Spatial patterns and influencing factors

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Journal of Geographical Sciences 2022年第7期32卷 1241-1260页

作者： ZHANG Hua CHEN Mingxing LIANG Chen beijing key laboratory of environmental remote sensing and digital Cities Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China key laboratory of Regional Sustainable Development Modeling Institute of Geographic Sciences and Natural Resources ResearchCASBeijing 100101China College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049China

This paper uses the fifth and sixth census data and 2018 demographic statistics to analyze the spatiotemporal evolution of the urbanization of county in china and the factors that influence the evolution.The paper reveals that the urbanization level of counties is a weak area in china’s overall urbanization.During the period from 2000 to 2010,the spatial patterns of the urbanization level of counties remained stable.Counties with high-level urbanization were concentrated in the coastal areas of the eastern region,while counties that experienced rapid urbanization were mainly located in the central and western regions.Regression analyses indicate that harsh natural endowments that constrain economic development are the most important factors that hinder the urbanization of county;these factors include marginalized locations far away from center cities,high altitudes,and a population with a low education level.This paper also compares two theoretical modes of new-type urbanization,nearby urbanization and remote urbanization,and argues that the new-type urbanization of county is the main form of nearby urbanization and provides an example of urbanization for developing countries worldwide.

关键词： new-type urbanization urbanization of county nearby urbanization spatial patterns influencing factors

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Simulation of Moon-based Earth observation optical image processing methods for global change study

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Frontiers of Earth Science 2020年第1期14卷 236-250页

作者： Tong LI Huadong GUO Li ZHANG Chenwei NIE Jingjuan LIAO Guang LIU key laboratory of digital Earth Science Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijing 100094China University of Chinese Academy of Sciences Beijing 100049China

Global change affected by multiple factors,the consequences of which continue to be far-reaching,has the characteristics of large spatial scale and long-time scale.The demand for Earth observation technology has been increasing for large-scale simultaneoiis observations and stable global observation over the long-term.A Moon-based observation platform,which uses sensors on the nearside lunar surface,is considered a reasonable solution.However,owing to a lack of appropriate processing methods for optical sensor data,global change study using this platform is not sufficient.This paper proposes two optical sensor imaging processing methods for the Moon-based platform:area imaging processing method(AIPM)and global imaging processing method(GIPM),primarily considering global change characteristics,optical sensor performance,and motion law of the Moon-based platform.First,the study proposes a simulation theory which includes the construction of a Moon-Sun elevation angle model and a global image mosaicking method.Then,coverage images of both image processing methods are simulated,and their features are quantitatively analyzed.Finally,potential applications are discussed.Results show that AEPM,whose coverage is mainly affected by lunar revolution,is approximately between 0%and 50%with a period of 29.5 days,which can help the study of large-scale instant change phenomena.GIPM,whose coverage is affected by Earth revolution,is conducive to the study of long term global-scale phenomena because of its sustained stable observation from 67°N-67°S on the Earth.AIPM and GIPM have great advantages in Earth observation of tripolar regions.The existence of top of the atmosphere(TOA)albedo balance line is verified from the GIPM perspective.These two imaging methods play a significant role in linking observations acquired from the Moon-based platform to Earth large-scale geoscience phenomena,and thus lay a foundation for using this platform to capture global environmental changes and new discoveries.

关键词： Moon-based Earth observation optical imaging processing method global change remote sensing simulation

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What Drives Migrants Back to Set up Firms?Return-home Entrepreneurial Intention of Rural Migrant Workers in china

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Chinese Geographical Science 2023年第2期33卷 205-220页

作者： ZHU Huasheng CHEN Yawei ZHANG Hua LIU Zhangfei beijing key laboratory of environmental remote sensing and digital Cities Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China Jiangsu Provincial Urban&Rural Development Research Center Nanjing 210036China College of Marxism Fuyang Normal UniveristyFuyang 236037China

The extant literature on international immigrants has discussed migrants’entrepreneurial activities in the context of Western countries but has paid little attention to return-home entrepreneurial intention(RHEI).Rural migrant workers(RMWs)in china,who used to promote rural development by remittances and were characterized by similarities with early international migrants,have gradually returned to their hometowns to initiate entrepreneurial activities.Based on the structured questionnaire conducted in 2015 and 2020in Anhui Province,china,this article combines the concept of mixed embeddedness with the idea of double-layered embeddedness and analyzes the impacts of the social,economic and institutional context in RMWs’hometowns and migration destinations on RMWs’RHEI by using binary logistic regression.The article shows that the social,economic,and institutional environments of RMWs’hometowns and migration destinations have effects on their RHEI.The embeddedness in the economic and informal institutional context in RMWs’RHEI is even more important than personal characteristics.Compared with migration destinations,RMWs’hometowns exert a more influential effect on their RHEI.However,that does not mean that the role of migration destinations can be undervalued.Actually,the better the social,economic,and institutional environments of migration destinations RMWs moved into is,the higher entrepreneurial intention they will have after returning to their hometowns.The article proposes a modified framework in combination of mixed embeddedness with double-layer embeddedness and proves that it is suitable for analyzing RMWs’RHEI.The framework has important implications for strengthening china’s RMWs to return home to start their own businesses.

关键词： return-home entrepreneurial intention(RHEI) rural migrant workers(RMWs) mixed embeddedness Anhui Province china

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Evaluating the suitability of TRMM satellite rainfall data for hydrological simulation using a distributed hydrological model in the Weihe River catchment in china

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Journal of Geographical Sciences 2015年第2期25卷 177-195页

作者： ZHAO Haigen State key laboratory of remote sensing Science Jointly Sponsored by Beijing Normal University and the Institute of Remote Sensing Applications of Chinese Academy of Sciences Beijing 100875 China Research Center for remote sensing and GIS Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities School of Geography Beijing Normal University Beijing100875 China South china Institute of environmental Sciences MEP Guangzhou 510655 China

The objective of this study is to quantitatively evaluate Tropical Rainfall Measuring Mission （TRMM） data with rain gauge data and further to use this TRMM data to drive a Dis- tributed Time-Variant Gain Model （DTVGM） to perform hydrological simulations in the semi-humid Weihe River catchment in china. Before the simulations, a comparison with a 10-year （2001-2010） daily rain gauge data set reveals that, at daily time step, TRMM rainfall data are better at capturing rain occurrence and mean values than rainfall extremes. On a monthly time scale, good linear relationships between TRMM and rain gauge rainfall data are found, with determination coefficients R2 varying between 0.78 and 0.89 for the individual stations. Subsequent simulation results of seven years （2001-2007） of data on daily hydro- logical processes confirm that the DTVGM when calibrated by rain gauge data performs better than when calibrated by TRMM data, but the performance of the simulation driven by TRMM data is better than that driven by gauge data on a monthly time scale. The results thus suggest that TRMM rainfall data are more suitable for monthly streamfiow simulation in the study area, and that, when the effects of recalibration and the results for water balance components are also taken into account, the TRMM 3B42-V7 product has the potential to perform well in similar basins.

关键词： rainfall TRMM distributed hydrological model DTVGM hydrological simulation Weihe River catchment

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Space view of the decadal variation for typical air pollutants in the Pearl River Delta （PRD） region in china

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Frontiers of environmental Science & Engineering 2016年第5期10卷 129-142页

作者： Zifeng WANG Min SHAO Liangfu CHEN Minghui TAO Liuju ZHONG Duohong CHEN Meng FAN Yang WANG Xinhui WANG State key laboratory of remote sensing Science Jointly Sponsored by Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences and Beijing Normal University Beijing 100101 China College of environmental Sciences and Engineering Peking University Beijing 100876 China Guangdong environmental Monitoring Center Guangzhou 510308 China

The Pearl River Delta （PRD） is one of the most industrialized, urbanized and populated regions in china, and thus has been long suffering from severe air pollutions. Space data provide a unique perspective for investigating the atmospheric environment at a regional scale. By utilizing multiple satellite retrievals from 2005 to 2013, this study presented, for the first time, the spatial patterns and temporal trends of typical air pollutants over PRD and its vicinity. As viewed from space, aerosol optical depth （AOD）, NO2 and SO2 all had their higher values at the central part of PRD, and showed clear descending gradients as moving to the outskirt of this region. As to the inter-annual variation, all these pollutants had decreasing trends in PRD during the study period, which generally agreed with the relevant in situ measurements. However, the satellite retrievals differed from ground measurements when addressing NO2 and SO2 in the vicinity of PRD. This work also provides the inter-comparison among PRD and three other metropolitan clusters in china： PRD had relatively high AOD, moderate NO2 and low SO2 levels, and it was the only region achieving the effective reduction of NO2 and SO2 during last decade. Unlike the previous three pollutants, HCHO observed by satellite showed very special patterns： it had a relatively homogeneous spatial distribution over both of PRD and its vicinity, and presented an opposite increasing trend from 2005 to 2010. Moreover, PRD had the highest HCHO level among all the metropolitan clusters, hinting a considerable contribution of biogenic origins of HCHO in PRD.

关键词： The Pearl River Delta （PRD） Satellite monitoring Regional air quality Long-term trend HCHO

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Quantifying spatial distribution of interrill and rill erosion in a loess at different slopes using structure from motion(SfM)photogrammetry

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International Soil and Water Conservation Research 2022年第3期10卷 393-406页

作者： Tao He Yang Yang Yangzi Shi Xiaozhen Liang Suhua Fu Gege Xie Baoyuan Liu Yingna Liu State key laboratory of Earth Surface Processes and Resource Ecology Faculty of Geographical ScienceBeijing Normal UniversityBeijing100875China School of Geography Faculty of Geographical ScienceBeijing Normal UniversityBeijing100875China beijing key laboratory of environmental remote sensing and digital Cities Faculty of Geographical ScienceBeijing Normal UniversityBeijing100875China State key laboratory of Soil Erosion and Dryland Farming on the Loess Plateau Chinese Academy of Sciences and Ministry of Water ResourcesYangling712100China

The spatial distribution of interrill and rill erosion is essential for unravelling soil erosion principles and the application of soil and water conservation practices.To quantify interrill and rill erosion and their spatial development,four 30-min rainfalls at 90 mm h^(-1)intensity were consecutively simulated on runoff plots packed with a loess at six slopes of 10°,15°,20°,25°,30°and 35°.The soil surface was measured using the structure from motion(SfM)photogrammetry upon each simulation run,and the runoff and sediment samples were collected and measured at every 10 min.Rills did not develop until the third simulation run.During the initial two runs,the lower third section was more severely eroded than the upper and middle thirds along the slope direction,yet the interrill erosion was statistically uniform from left to right.Rills tended to emerge by both sidewalls and in the lower portion in the third run.The corresponding rill erosion increased with slope from 10°to 20°and then decreased for the slopes steeper,which was consistent with the slope trend of the sediment yield directly measured.The rills expanded substantially primarily via head retreat and to a lesser extent via sideward erosion after receiving another 30-min rainfall.Rill erosion contributed 69.3%of the total erosion loss,and shifted the critical slope corresponding to the maximum loss from 20°to 25°.These findings demonstrate the significance of rill erosion not only in total soil loss but also in its relation to slope,as well as the effectiveness of SfM photogrammetry in quantifying interrill and rill erosion.

关键词： Interrill and rill erosion Spatial distribution Structure from motion(SfM) photogrammetry Slope Rainfall simulation

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