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Author Correction: Rivers as the largest source of mercury to coastal oceans worldwide

Nature Geoscience 2021年 956页

作者： Maodian Liu Qianru Zhang Xuejun Wang Taylor Maavara Shaoda Liu Peter A. Raymond Ministry of Education Laboratory of Earth Surface Processes College of Urban and Environmental Sciences Peking University Beijing China School of the Environment Yale University New Haven CT USA School of Earth and Atmospheric Sciences Georgia Institute of Technology Atlanta GA USA State Key Laboratory of Water Environment Simulation School of Environment Beijing Normal University Beijing China

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Analysis of Topography and Composition of the Von Kármán Impact Crater

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IOP Conference Series: Earth and environmental Science 2021年第1期658卷

作者： Jinlong Hou Li Li Shiwei Li College of Resource Environment and Tourism Capital Normal University Beijing 100048 China State Key Laboratory Incubation Base of Urban Environmental Processes and Digital Simulation Beijing 100048 China Beijing Laboratory of Water Resources Security Beijing Municipal Education Commission Beijing 100048 China College of Geomatics Science and Technology Xi'an University of Science and Technology Xi'an 710054 China

The Vo n Kármán impact crater in the Chang'E-4 landing area is located in in the Northwestern South Pole-Aitken (SPA) basin on the back of the Moon, and the analysis of its topography and compositional characteristics is essential for the landing of the probe and the exploration of the lunar surface, which plays a fundamental role in obtaining information on the geomorphology and geology of the lunar surface. In this paper, the topography of the Vo n Kármán impact crater is analyzed based on DEM, slope and terrain roughness, then the compositional characteristics of the Von Kármán impact crater are analyzed according to TiO2 and FeO content through combining LRO LOLA data and Clementine UV-VIS data. This study is a basis for revealing the surface characteristics and structure of the Moon.

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Village-level multidimensional poverty measurement in China: Where and how

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Journal of Geographical Sciences 2018年第10期28卷 1444-1466页

作者：王艳慧陈烨烽迟瑶赵文吉胡卓玮段福洲 Beijing Key Laboratory of Resource Environment and Geographic Information System Capital Normal University Key Laboratory of 3-Dimensional Information Acquisition and Application Ministry of Education Capital Normal University State Key Laboratory Incubation Base of Urban Environmental Processes and Digital Simulation Capital Normal University

Village is an important implementation unit of national poverty alleviation and development strategies of rural China, and identifying the poverty degree, poverty type and poverty contributing factors of each poverty-stricken village is the precondition and guarantee of taking targeted measures in poverty alleviation strategies of China. To respond it, we construct a village-level multidimensional poverty measuring model, and use indicator contribution degree indices and linear regression method to explore poverty factors, while adopting Least Square Error(LSE) model and spatial econometric analysis model to identify the villages' poverty types and poverty difference. The case study shows that:(1) Spatially, there is obvious territoriality in the distribution of poverty-stricken villages, and the poverty-stricken villages are concentrated in contiguous poverty-stricken areas. The areas with the highest VPI, in a descending order, are Gansu, Yunnan, Guizhou, Guangxi, Hunan, Qinghai, Sichuan, and Xinjiang.(2) The main factors contributing to the poverty of poverty-stricken villages in rural China include road construction, terrain type, frequency of natural disasters, per capita net income, labor force ratio, and cultural quality of labor force. The main causes of poverty include underdeveloped road construction conditions, frequent natural disasters, low level of income, and labor conditions.(3) Chinese poverty-stricken villages include six main subtypes, and most poverty-stricken villages are affected by multiple poverty-forming factors, reflected by a relatively high proportion of the three-factor dominant type, four-factor coordinative type, and five-factor combinative type.(4) There exist significant poverty differences in terms of geographical location and policy support, and the governments still need to carry out targeted poverty alleviation measures according to local conditions. The research can not only draw a macro overall poverty-reduction outline of impo

关键词： poor village multidimensional poverty measurement poverty type poverty factors spatial econometric analysis

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Estimating the impact of urban expansion on land subsidence using time series of DMSP night-time light satellite imagery

Estimating the impact of urban expansion on land subsidence ...

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2018 ISPRS TC III Mid-Term Symposium on Developments, Technologies and Applications in Remote Sensing

作者： Jiao, Shuai Yu, Jie Wang, Yanbing Zhu, Lin Zhou, Qi College of Resource Environment and Tourism Capital Normal University Beijing100048 China State Key Laboratory Incubation Base of Urban Environmental Processes and Digital Simulation Beijing100048 China Beijing Key Laboratory of Resource Environment and Geographic Information System Beijing100048 China National Geomatics Center of China Beijing100830 China

In recent decades, urbanization has resulted a massive increase in the amount of infrastructure especially large buildings in large cities worldwide. There has been a noticeable expansion of entire cities both horizontally and vertically. One of the common consequences of urban expansion is the increase of ground loads, which may trigger land subsidence and can be a potential threat of public safety. Monitoring trends of urban expansion and land subsidence using remote sensing technology is needed to ensure safety along with urban planning and development. The Defense Meteorological Satellite Program Operational Line scan System (DMSP/OLS) NightTime Light (NTL) images have been used to study urbanization at a regional scale, proving the capability of recognizing urban expansion patterns. In the current study, a normalized illuminated urban area dome volume (IUADV) based on inter-calibrated DMSP/OLS NTL images is shown as a practical approach for estimating urban expansion of Beijing at a single period in time and over subsequent years. To estimate the impact of urban expansion on land subsidence, IUADV was correlated with land subsidence rates obtained using the Stanford Method for Persistent Scatterers (StaMPS) approach within the Persistent Scatterers InSAR (PSInSAR) methodology. Moderate correlations are observed between the urban expansion based on the DMSP/OLS NTL images and land subsidence. The correlation coefficients between the urban expansion of each year and land subsidence tends to gradually decrease over time (Coefficient of determination R = 0.80-0.64 from year 2005 to year 2010), while the urban expansion of two sequential years exhibit an opposite trend (R = 0.29-0.57 from year 2005 to year 2010) except for the two sequential years between 2007 and 2008 (R = 0.14). © Authors 2018.

关键词： Satellite imagery

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Mapping wetlands of dongting lake in China using Landsat and Sentinel-1 time series at 30M

Mapping wetlands of dongting lake in China using Landsat and...

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2018 ISPRS TC III Mid-Term Symposium on Developments, Technologies and Applications in Remote Sensing

作者： Xing, Liwei Tang, Xinming Wang, Huabin Fan, Wenfeng Gao, Xinyuan Satellite Surveying and Mapping Application Center National Administration of Surveying Mapping and Geoinformation No.1 Baishengcun Zizhuyuan Road Haidian District Beijing100048 China State Key Laboratory Incubation Base of Urban Environmental Processes and Digital Simulation Capital Normal University No.105 Xisanhuan North Road Haidian District Beijing100048 China

Mapping and monitoring wetlands of Dongting lake using optical sensor data has been limited by cloud cover, and open access Sentinal-1 C-band data could provide cloud-free SAR images with both have high spatial and temporal resolution, which offer new opportunities for monitoring wetlands. In this study, we combined optical data and SAR data to map wetland of Dongting Lake reserves in 2016. Firstly, we generated two monthly composited Landsat land surface reflectance, NDVI, NDWI, TC-Wetness time series and Sentinel-1 (backscattering coefficient for VH and VV) time series. Secondly, we derived surface water body with two monthly frequencies based on the threshold method using the Sentinel-1 time series. Then the permanent water and seasonal water were separated by the submergence ratio. Other land cover types were identified based on SVM classifier using Landsat time series. Results showed that (1) the overall accuracies and kappa coefficients were above 86.6% and 0.8. (3) Natural wetlands including permanent water body (14.8%), seasonal water body (34.6%), and permanent marshes (10.9%) were the main land cover types, accounting for 60.3% of the three wetland reserves. Human-made wetlands, such as rice fields, accounted 34.3% of the total area. Generally, this study proposed a new flowchart for wetlands mapping in Dongting lake by combining multi-source remote sensing data, and the use of the two-monthly composited optical time series effectively made up the missing data due to the clouds and increased the possibility of precise wetlands classification. © Authors 2018. CC BY 4.0 License.

关键词： Landsat

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MAPPING WETLANDS OF DONGTING LAKE IN CHINA USING LANDSAT AND SENTINEL-1 TIME SERIES AT 30M

MAPPING WETLANDS OF DONGTING LAKE IN CHINA USING LANDSAT AND...

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The ISPRS Technical Commission III Midterm Symposium on "Developments, Technologies and Applications in Remote Sensing"

作者： Liwei Xing Xinming Tang Huabin Wang Wenfeng Fan Xinyuan Gao Satellite Surveying and Mapping Application Center National Administration of SurveyingMapping and Geoinformation State Key Laboratory Incubation Base of Urban Environmental Processes and Digital Simulation Capital Normal University

Mapping and monitoring wetlands of Dongting lake using optical sensor data has been limited by cloud cover, and open access Sentinal-1 C-band data could provide cloud-free SAR images with both have high spatial and temporal resolution, which offer new opportunities for monitoring wetlands. In this study, we combined optical data and SAR data to map wetland of Dongting Lake reserves in 2016. Firstly, we generated two monthly composited Landsat land surface reflectance, NDVI, NDWI, TC-Wetness time series and Sentinel-1(backscattering coefficient for VH and VV) time series. Secondly, we derived surface water body with two monthly frequencies based on the threshold method using the Sentinel-1 time series. Then the permanent water and seasonal water were separated by the submergence ratio. Other land cover types were identified based on SVM classifier using Landsat time series. Results showed that(1) the overall accuracies and kappa coefficients were above 86.6% and 0.8.(3) Natural wetlands including permanent water body(14.8%), seasonal water body(34.6%), and permanent marshes(10.9%) were the main land cover types, accounting for 60.3% of the three wetland reserves. Human-made wetlands, such as rice fields, accounted 34.3% of the total area. Generally, this study proposed a new flowchart for wetlands mapping in Dongting lake by combining multi-source remote sensing data, and the use of the two-monthly composited optical time series effectively made up the missing data due to the clouds and increased the possibility of precise wetlands classification.

关键词： Wetlands Landsat Sentinel-1 Time series Dongting Lake SVM

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ESTIMATING THE IMPACT OF urban EXPANSION ON LAND SUBSIDENCE USING TIME SERIES OF DMSP NIGHT-TIME LIGHT SATELLITE IMAGERY

ESTIMATING THE IMPACT OF URBAN EXPANSION ON LAND SUBSIDENCE ...

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The ISPRS Technical Commission III Midterm Symposium on "Developments, Technologies and Applications in Remote Sensing"

作者： Shuai Jiao Jie Yu Yanbing Wang Lin Zhu Qi Zhou College of Resource Environment and Tourism Capital Normal University State Key Laboratory Incubation Base of Urban Environmental Processes and Digital Simulation Beijing Key Laboratory of Resource Environment and Geographic Information System National Geomatics Center of China

In recent decades, urbanization has resulted a massive increase in the amount of infrastructure especially large buildings in large cities worldwide. There has been a noticeable expansion of entire cities both horizontally and vertically. One of the common consequences of urban expansion is the increase of ground loads, which may trigger land subsidence and can be a potential threat of public safety. Monitoring trends of urban expansion and land subsidence using remote sensing technology is needed to ensure safety along with urban planning and development. The Defense Meteorological Satellite Program Operational Line scan System(DMSP/OLS) NightTime Light(NTL) images have been used to study urbanization at a regional scale, proving the capability of recognizing urban expansion patterns. In the current study, a normalized illuminated urban area dome volume(IUADV) based on inter-calibrated DMSP/OLS NTL images is shown as a practical approach for estimating urban expansion of Beijing at a single period in time and over subsequent years. To estimate the impact of urban expansion on land subsidence, IUADV was correlated with land subsidence rates obtained using the Stanford Method for Persistent Scatterers(Sta MPS) approach within the Persistent Scatterers In SAR(PSIn SAR) methodology. Moderate correlations are observed between the urban expansion based on the DMSP/OLS NTL images and land subsidence. The correlation coefficients between the urban expansion of each year and land subsidence tends to gradually decrease over time(Coefficient of determination R = 0.80 – 0.64 from year 2005 to year 2010), while the urban expansion of two sequential years exhibit an opposite trend(R = 0.29 – 0.57 from year 2005 to year 2010) except for the two sequential years between 2007 and 2008(R = 0.14).

关键词： land subsidence urban expansion DMSP/OLS NTL PSIn SAR

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OPTIMAL FEATURES SELECTION FOR WETLANDS CLASSIFICATION USING LANDSAT TIME SERIES

OPTIMAL FEATURES SELECTION FOR WETLANDS CLASSIFICATION USING...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Liwei Xing Huabin Wang Wenfeng Fan Chen Chen Tao Li Guanghui Wang Haoran Zhai State Key Laboratory Incubation Base of Urban Environmental Processes and Digital Simulation Capital Normal University Beijing P.R. China National Administration of Surveying Satellite Surveying and Mapping Application Center Beijing P.R. China

Accurate wetlands distribution maps could provide important information for wetland management and protection. While, wetlands have significantly inner-annual variation which makes accurate wetland mapping challenging. Time series data with high temporal resolution, such as MODIS are wildly used in monitoring wetlands, but the coarse resolution cannot precisely identify detail of the wetlands and smaller wetlands. In addition, optimal features for wetlands classification is still unclear. In this study, Landsat monthly composited time series were used to identify wetlands. Firstly, we generated the Landsat 30m land surface reflectance, NDVI, NDWI and TC-Wetness time series by compositing the Landsat7 ETM+ and Landsat8 OLI data. Then the extension of the Jeffries-Matusita Distance (J_(Bh)) and the Random Forest (RF) algorithm were used to select the optimal features for accurate wetlands classification. Finally, the optimal features were used for wetlands classification based on the RF algorithm. The results showed that: (1) the optimal features included NDVI in May and August, TC-Wetness in May and NDWI in June and August which can effectively separate seasonal and permanent marshes, rice fields, grass and drylands;(2) the overall accuracy and Kappa coefficient calculated using the optimal features were 90.05% and 0.88 respectively which were similar to the wetlands classification result derived by the entire Landsat time series data. The optimal features could improve efficiency and decrease data redundancy.

关键词： Wetlands Artificial satellites Earth Remote sensing Reflectivity Land surface Time series analysis

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A novel elevation phase elimination method for PSInSAR in urban area with high buildings 22

A novel elevation phase elimination method for PSInSAR in ur...

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22nd International Congress on Modelling and simulation: Managing Cumulative Risks through Model-Based processes, MODSIM 2017 - Held jointly with the 25th National Conference of the Australian Society for Operations Research and the DST Group led Defence Operations Research Symposium, DORS 2017

作者： Jiao, Shuai Gong, Huili Yu, Jie Milas, Anita Simic Chang, Zhanqiang Zhang, Jing Zhu, Lin Xie, Donghai Wang, Yanbing College of Resource Environment and Tourism Capital Normal University Beijing100048 China State Key Laboratory Incubation Base of Urban Environmental Processes and Digital Simulation Beijing100048 China Beijing Key Laboratory of Resource Environment and Geographic Information System Beijing100048 China School of Earth Environment and Society Bowling Green State University Ohio United States

ISBN: (纸本)9780987214379

The terrain phase elimination is a key step in the Permanent Scatterer Interferometric SAR technique (PSInSAR) for monitoring land deformation. The Shuttle Radar Topography Mission digital elevation model (SRTM DEM) is widely used. In high-rise urban areas, there are main effects that high buildings have on land subsidence where SRTM DEM is applied: after temporal and spatial filtering, a portion of the terrain phase errors propagates in the residual phase, which directly affects the precision of the land subsidence estimation. In this study, we propose a new method to minimize the errors. We have created a digital surface model (DSM) by overlying SRTM DEM with the layer of the building height obtained by SAR tomography. To validate the proposed approach, the land subsidence was calculated using the SRTM DEM and DSM correction methods. Based on the benchmarks used in the comparison, we show that the elevation phase elimination using DSM leads to more precise measurements of land subsidence rates. © 2017 Proceedings - 22nd International Congress on Modelling and simulation, MODSIM 2017. All rights reserved.

关键词： Risk assessment

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Design and Development of Visualization System for Marine Early Warning Products based on GIS

Design and Development of Visualization System for Marine Ea...

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2015 5th International Conference on Computer Sciences and Automation Engineering(ICCSAE 2015)

作者： Aifen Zhong Yonghua Sun Zhenjun Cai Cankun Yang State Key Laboratory Incubation Base of Urban Environmental Processes and Digital Simulation Capital Normal University College of Resources Environment & Tourism Capital Normal University

General marine environmental early warning data have not formed a unified standard, due to the different angles and dimensions in expression of marine environment. General formats of these data are text type, binary type, and mixed type. These data types cannot be read and processed by the GIS platform, so it is necessary to normalize these data to standard format supported by GIS platform. This paper studied the visualization system for marine early warning products which based on MFC framework and Arc Engine development kit and used GDAL and Net CDF function libraries, solved the problem of heterogeneous data sources and realized data production, results presentations, automatic drawing, 3D profile analysis and other functions. It will provide convenience for the comprehensive operation of different types data and improve the visual expression effect for marine early warning products and marine management at the same time.

关键词： Visualization System Data Normalization Marine Early Warning Products GIS

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