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Prof. Bing Xu
Center for Earth System Science, Tsinghua University, MengMinWei Hall, Beijing 100084, China

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0 Climate Change
0 Ecological Modeling
0 Epidemiology
0 Remote Sensing
0 human health

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infectious disease
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Journal article
Published: 25 June 2021 in ISPRS Journal of Photogrammetry and Remote Sensing
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Urban land-use maps outlining the distribution, pattern, and composition of various land use types are critically important for urban planning, environmental management, disaster control, health protection, and biodiversity conservation. Recent advances in remote sensing and social sensing data and methods have shown great potentials in mapping urban land use categories, but they are still constrained by mixed land uses, limited predictors, non-localized models, and often relatively low accuracies. To inform these issues, we proposed a robust and cost-effective framework for mapping urban land use categories using openly available multi-source geospatial “big data”. With street blocks generated from OpenStreetMap (OSM) data as the minimum classification unit, we integrated an expansive set of multi-scale spatially explicit information on land surface, vertical height, socio-economic attributes, social media, demography, and topography. We further proposed to apply the automatic ensemble learning that leverages a bunch of machine learning algorithms in deriving optimal urban land use classification maps. Results of block-level urban land use classification in five metropolitan areas of the United States found the overall accuracies of major-class (Level-I) and minor-class (Level-II) classification could be high as 91% and 86%, respectively. A multi-model comparison revealed that for urban land use classification with high-dimensional features, the multi-layer stacking ensemble models achieved better performance than base models such as random forest, extremely randomized trees, LightGBM, CatBoost, and neural networks. We found without very-high-resolution National Agriculture Imagery Program imagery, the classification results derived from Sentinel-1, Sentinel-2, and other open big data based features could achieve plausible overall accuracies of Level-I and Level-II classification at 88% and 81%, respectively. We also found that model transferability depended highly on the heterogeneity in characteristics of different regions. The methods and findings in this study systematically elucidate the role of data sources, classification methods, and feature transferability in block-level land use classifications, which have important implications for mapping multi-scale essential urban land use categories.

ACS Style

Bin Chen; Ying Tu; Yimeng Song; David M. Theobald; Tao Zhang; Zhehao Ren; Xuecao Li; Jun Yang; Jie Wang; Xi Wang; Peng Gong; Yuqi Bai; Bing Xu. Mapping essential urban land use categories with open big data: Results for five metropolitan areas in the United States of America. ISPRS Journal of Photogrammetry and Remote Sensing 2021, 178, 203 -218.

AMA Style

Bin Chen, Ying Tu, Yimeng Song, David M. Theobald, Tao Zhang, Zhehao Ren, Xuecao Li, Jun Yang, Jie Wang, Xi Wang, Peng Gong, Yuqi Bai, Bing Xu. Mapping essential urban land use categories with open big data: Results for five metropolitan areas in the United States of America. ISPRS Journal of Photogrammetry and Remote Sensing. 2021; 178 ():203-218.

Chicago/Turabian Style

Bin Chen; Ying Tu; Yimeng Song; David M. Theobald; Tao Zhang; Zhehao Ren; Xuecao Li; Jun Yang; Jie Wang; Xi Wang; Peng Gong; Yuqi Bai; Bing Xu. 2021. "Mapping essential urban land use categories with open big data: Results for five metropolitan areas in the United States of America." ISPRS Journal of Photogrammetry and Remote Sensing 178, no. : 203-218.

Journal article
Published: 10 March 2021 in International Journal of Environmental Research and Public Health
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Mobility restrictions have been a heated topic during the global pandemic of coronavirus disease 2019 (COVID-19). However, multiple recent findings have verified its importance in blocking virus spread. Evidence on the association between mobility, cases imported from abroad and local medical resource supplies is limited. To reveal the association, this study quantified the importance of inter- and intra-country mobility in containing virus spread and avoiding hospitalizations during early stages of COVID-19 outbreaks in India, Japan, and China. We calculated the time-varying reproductive number (R t) and duration from illness onset to diagnosis confirmation (D oc), to represent conditions of virus spread and hospital bed shortages, respectively. Results showed that inter-country mobility fluctuation could explain 80%, 35%, and 12% of the variance in imported cases and could prevent 20 million, 5 million, and 40 million imported cases in India, Japan and China, respectively. The critical time for screening and monitoring of imported cases is 2 weeks at minimum and 4 weeks at maximum, according to the time when the Pearson’s Rs between R t and imported cases reaches a peak (>0.8). We also found that if local transmission is initiated, a 1% increase in intra-country mobility would result in 1430 (±501), 109 (±181), and 10 (±1) additional bed shortages, as estimated using the D oc in India, Japan, and China, respectively. Our findings provide vital reference for governments to tailor their pre-vaccination policies regarding mobility, especially during future epidemic waves of COVID-19 or similar severe epidemic outbreaks.

ACS Style

Zhehao Ren; Ruiyun Li; Tao Zhang; Bin Chen; Che Wang; Miao Li; Shuang Song; Yixiong Xiao; Bo Xu; Zhaoyang Liu; Chong Shen; Dabo Guan; Lin Hou; Ke Deng; Yuqi Bai; Peng Gong; Bing Xu. Reduction of Human Mobility Matters during Early COVID-19 Outbreaks: Evidence from India, Japan and China. International Journal of Environmental Research and Public Health 2021, 18, 2826 .

AMA Style

Zhehao Ren, Ruiyun Li, Tao Zhang, Bin Chen, Che Wang, Miao Li, Shuang Song, Yixiong Xiao, Bo Xu, Zhaoyang Liu, Chong Shen, Dabo Guan, Lin Hou, Ke Deng, Yuqi Bai, Peng Gong, Bing Xu. Reduction of Human Mobility Matters during Early COVID-19 Outbreaks: Evidence from India, Japan and China. International Journal of Environmental Research and Public Health. 2021; 18 (6):2826.

Chicago/Turabian Style

Zhehao Ren; Ruiyun Li; Tao Zhang; Bin Chen; Che Wang; Miao Li; Shuang Song; Yixiong Xiao; Bo Xu; Zhaoyang Liu; Chong Shen; Dabo Guan; Lin Hou; Ke Deng; Yuqi Bai; Peng Gong; Bing Xu. 2021. "Reduction of Human Mobility Matters during Early COVID-19 Outbreaks: Evidence from India, Japan and China." International Journal of Environmental Research and Public Health 18, no. 6: 2826.

Letter to the editor
Published: 03 March 2021 in Veterinary Medicine and Science
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The five avian influenza A/H9N2 viruses isolated from wild birds in Jiangxi, China in 2015 are novel reassortants which most likely evolved from multiple lineages. They shared a high similarity with isolates from poultry, suggesting a frequent contact and continuous viral circulation at the bird‐poultry interface. Given the continuous reassortment of H9N2 viruses, it will of substantial importance to implement routine surveillance in wild birds to successfully control avian influenza viruses and better the early warning system of the emerging reassortants with pandemic potential.

ACS Style

Tao Zhang; Ruiyun Li; Pinghua Zhong; Jianyu Chang; Bing Xu. Detection of novel reassortant H9N2 avian influenza viruses in wild birds in Jiangxi Province, China. Veterinary Medicine and Science 2021, 7, 1042 -1046.

AMA Style

Tao Zhang, Ruiyun Li, Pinghua Zhong, Jianyu Chang, Bing Xu. Detection of novel reassortant H9N2 avian influenza viruses in wild birds in Jiangxi Province, China. Veterinary Medicine and Science. 2021; 7 (3):1042-1046.

Chicago/Turabian Style

Tao Zhang; Ruiyun Li; Pinghua Zhong; Jianyu Chang; Bing Xu. 2021. "Detection of novel reassortant H9N2 avian influenza viruses in wild birds in Jiangxi Province, China." Veterinary Medicine and Science 7, no. 3: 1042-1046.

Research article
Published: 19 October 2020 in Landscape Ecology
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Characterized by intensive urban sprawl and continuous cropland shrinkage, the unprecedented urbanization process has profoundly reshaped China’s landscape over the past four decades. However, the interaction between urban expansion and cropland loss in China at a finer spatiotemporal resolution remains unclear. This study aims to quantify and compare the rates, patterns, dynamics, and interactions of urban expansion and cropland loss in 14 Chinese cities during 1980–2015. Multiple landscape metrics were calculated to quantify the magnitudes, rates, and patterns of urban expansion and cropland loss for each city. The standard deviation ellipse analysis and two quantitative indices (the dependence and the contribution of urban expansion on cropland loss) were used to characterize the relationship between urban expansion and cropland loss. The pattern of rapid urban expansion and extensive cropland loss was observed across all selected cities (except for Harbin), with the averaged expansion area of 764.17 km2 and averaged loss area of 650.83 km2 per city. The primary mode of urbanization was the edge-expansion (6889.22 km2, 60.01%), followed by the infilling (2767.32 km2, 24,11%) and the outlying (1822.72 km2, 15.88%). Urban expansion was identified to be the dominant driver of cropland loss, accounting for 84.99% of the newly expanded urban land and 74.36% of the lost cropland in total, thus leading to a more spatially irregular and fragmented distribution of the cropland. The balance between urbanization and land protection is still challenging. Here we advocate more effective policy-driven practices to protect China’s existing cropland for food security and sustainable development goals.

ACS Style

Ying Tu; Bin Chen; Le Yu; Qinchuan Xin; Peng Gong; Bing Xu. How does urban expansion interact with cropland loss? A comparison of 14 Chinese cities from 1980 to 2015. Landscape Ecology 2020, 36, 243 -263.

AMA Style

Ying Tu, Bin Chen, Le Yu, Qinchuan Xin, Peng Gong, Bing Xu. How does urban expansion interact with cropland loss? A comparison of 14 Chinese cities from 1980 to 2015. Landscape Ecology. 2020; 36 (1):243-263.

Chicago/Turabian Style

Ying Tu; Bin Chen; Le Yu; Qinchuan Xin; Peng Gong; Bing Xu. 2020. "How does urban expansion interact with cropland loss? A comparison of 14 Chinese cities from 1980 to 2015." Landscape Ecology 36, no. 1: 243-263.

Journal article
Published: 28 September 2020 in Proceedings of the National Academy of Sciences
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Emerging evidence suggests a resurgence of COVID-19 in the coming years. It is thus critical to optimize emergency response planning from a broad, integrated perspective. We developed a mathematical model incorporating climate-driven variation in community transmissions and movement-modulated spatial diffusions of COVID-19 into various intervention scenarios. We find that an intensive 8-wk intervention targeting the reduction of local transmissibility and international travel is efficient and effective. Practically, we suggest a tiered implementation of this strategy where interventions are first implemented at locations in what we call the Global Intervention Hub, followed by timely interventions in secondary high-risk locations. We argue that thinking globally, categorizing locations in a hub-and-spoke intervention network, and acting locally, applying interventions at high-risk areas, is a functional strategy to avert the tremendous burden that would otherwise be placed on public health and society.

ACS Style

Ruiyun Li; Bin Chen; Tao Zhang; Zhehao Ren; Yimeng Song; Yixiong Xiao; Lin Hou; Jun Cai; Bo Xu; Miao Li; Karen Kie Yan Chan; Ying Tu; Mu Yang; Jing Yang; Zhaoyang Liu; Chong Shen; Che Wang; Lei Xu; Qiyong Liu; Shuming Bao; Jianqin Zhang; Yuhai Bi; Yuqi Bai; Ke Deng; Wusheng Zhang; Wenyu Huang; Jason D. Whittington; Nils Chr. Stenseth; Dabo Guan; Peng Gong; Bing Xu. Global COVID-19 pandemic demands joint interventions for the suppression of future waves. Proceedings of the National Academy of Sciences 2020, 117, 26151 -26157.

AMA Style

Ruiyun Li, Bin Chen, Tao Zhang, Zhehao Ren, Yimeng Song, Yixiong Xiao, Lin Hou, Jun Cai, Bo Xu, Miao Li, Karen Kie Yan Chan, Ying Tu, Mu Yang, Jing Yang, Zhaoyang Liu, Chong Shen, Che Wang, Lei Xu, Qiyong Liu, Shuming Bao, Jianqin Zhang, Yuhai Bi, Yuqi Bai, Ke Deng, Wusheng Zhang, Wenyu Huang, Jason D. Whittington, Nils Chr. Stenseth, Dabo Guan, Peng Gong, Bing Xu. Global COVID-19 pandemic demands joint interventions for the suppression of future waves. Proceedings of the National Academy of Sciences. 2020; 117 (42):26151-26157.

Chicago/Turabian Style

Ruiyun Li; Bin Chen; Tao Zhang; Zhehao Ren; Yimeng Song; Yixiong Xiao; Lin Hou; Jun Cai; Bo Xu; Miao Li; Karen Kie Yan Chan; Ying Tu; Mu Yang; Jing Yang; Zhaoyang Liu; Chong Shen; Che Wang; Lei Xu; Qiyong Liu; Shuming Bao; Jianqin Zhang; Yuhai Bi; Yuqi Bai; Ke Deng; Wusheng Zhang; Wenyu Huang; Jason D. Whittington; Nils Chr. Stenseth; Dabo Guan; Peng Gong; Bing Xu. 2020. "Global COVID-19 pandemic demands joint interventions for the suppression of future waves." Proceedings of the National Academy of Sciences 117, no. 42: 26151-26157.

Journal article
Published: 07 September 2020 in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Land cover information is critically essential for nature conservation, social management, and sustainable development. Recent advances have shown great potentials of remote sensing data in generating high-resolution land cover maps, but it remains unclear how different models, data sources, and inclusive features affect the classification results. Informing these issues, here we developed a robust framework to improve the mapping results of 10-m resolution land cover classification in Guangdong Province, China using thousands of manually collected samples, multi-source remote sensing data (Sentinel-1, Sentinel-2, and Luojia-1), and the Random Forest (RF) algorithm with a free cloud-based platform of Google Earth Engine. Results showed that an overall accuracy of 86.12% and a Kappa coefficient of 0.84 could be achieved for land cover classification in Guangdong for 2019. We found that RF models achieved better performance than classification and regression trees (CART), minimum distance (MD), and support vector machine (SVM) models. We also found that features derived from Sentinel-1 data and Sentinel-2 spectral indices greatly contributed to the classification process, while the feature of Luojia-1 data was not as much important as other configurations. A comparison between our results and several existing land cover products in terms of classification accuracy and visual interpretation further validated the effectiveness and robustness of the proposed framework. Our experiments and findings not only systematically elucidate the role of classification methods and data sources in deriving more accurate and reliable land cover maps, but also provide certain guidelines for future land cover mapping from regional to global scales.

ACS Style

Ying Tu; Wei Lang; Le Yu; Ying Li; Junhao Jiang; Yawen Qin; Jiemin Wu; Tingting Chen; Bing Xu. Improved Mapping Results of 10 m Resolution Land Cover Classification in Guangdong, China Using Multisource Remote Sensing Data With Google Earth Engine. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2020, 13, 5384 -5397.

AMA Style

Ying Tu, Wei Lang, Le Yu, Ying Li, Junhao Jiang, Yawen Qin, Jiemin Wu, Tingting Chen, Bing Xu. Improved Mapping Results of 10 m Resolution Land Cover Classification in Guangdong, China Using Multisource Remote Sensing Data With Google Earth Engine. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2020; 13 (99):5384-5397.

Chicago/Turabian Style

Ying Tu; Wei Lang; Le Yu; Ying Li; Junhao Jiang; Yawen Qin; Jiemin Wu; Tingting Chen; Bing Xu. 2020. "Improved Mapping Results of 10 m Resolution Land Cover Classification in Guangdong, China Using Multisource Remote Sensing Data With Google Earth Engine." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 13, no. 99: 5384-5397.

Journal article
Published: 01 September 2020 in Journal of General Virology
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The predominance of H5N6 in ducks and continuous human cases have heightened its potential threat to public health in China. Therefore, the detection of emerging variants of H5N6 avian influenza viruses has become a priority for pandemic preparedness. Questions remain as to its origin and circulation within the wild bird reservoir and interactions at the wild–domestic interface. Samples were collected from migratory birds in Poyang Lake, Jiangxi Province, PR China during the routine bird ring survey in 2014–16. Phylogenetic and coalescent analyses were conducted to uncover the evolutionary relationship among viruses circulating in wild birds. Here, we report the potential origin and phylogenetic diversity of H5N6 viruses isolated from wild birds in Poyang Lake. Sequence analyses indicated that Jiangxi H5N6 viruses most likely evolved from Eurasian-derived H5Nx and H6N6 viruses through multiple reassortment events. Crucially, the diversity of the HA gene implies that these Jiangxi H5N6 viruses have diverged into two primary clades − clade 2.3.4.4 and clade 2.3.2.1 c. Phylogenetic analysis revealed two independent pathways of reassortment during 2014–16 that might have facilitated the generation of emerging variants within wild bird populations as well as inter-species infections. Our findings contribute to our understanding of the genetic diversification of H5N6 viruses in the wild bird population. These results highlight the necessity of large-scale surveillance of wild birds in the Poyang Lake area to address the threat of regional epizootic epidemics and attendant pandemics.

ACS Style

Tao Zhang; Kai Fan; Xue Zhang; Yujuan Xu; Jian Xu; Bing Xu; Ruiyun Li. Diversity of avian influenza A(H5N6) viruses in wild birds in southern China. Journal of General Virology 2020, 101, 902 -909.

AMA Style

Tao Zhang, Kai Fan, Xue Zhang, Yujuan Xu, Jian Xu, Bing Xu, Ruiyun Li. Diversity of avian influenza A(H5N6) viruses in wild birds in southern China. Journal of General Virology. 2020; 101 (9):902-909.

Chicago/Turabian Style

Tao Zhang; Kai Fan; Xue Zhang; Yujuan Xu; Jian Xu; Bing Xu; Ruiyun Li. 2020. "Diversity of avian influenza A(H5N6) viruses in wild birds in southern China." Journal of General Virology 101, no. 9: 902-909.

Journal article
Published: 18 July 2020 in Atmospheric Research
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Fine particulate matter (PM2.5) has been the focus of increasing public concerns because of its adverse effect on environment and health risks. However, existing efforts of mapping PM2.5 concentrations are always limited by coarse spatial resolutions and temporal frequencies. Addressing this shortcoming, here we explicitly estimated hourly PM2.5 concentrations at 1-km spatial resolution across China from March 2018 to February 2019 using a two-stage random forest model. In the first stage, we conducted a gap-filling method to generate full-coverage Aerosol Optical Depth (AOD) by fusing AOD data from satellite (Himawari-8 and MODIS) and weather forecast model (CAMS), and additional meteorological and geographical variables. Gap-filled AOD generated in Stage I was subsequently used to estimate hourly PM2.5 in Stage II. Results showed that our model achieved accurate and robust estimations of PM2.5 concentrations, with an overall cross-validated R2 of 0.85, root mean squared error of 11.02 μg/m3, and mean absolute error of 6.73 μg/m3. CAMS-simulated PM2.5, elevation, and gap-filled AOD were identified to be relatively important variables contributing to the model performance of PM2.5 estimation. The model performance varied over the daily temporal scale. Specifically, daily estimation model performed better in spring and winter but worse in summer and autumn. In this study, we provided an alternative to generate spatially and temporally explicit mapping of PM2.5 concentrations with fine resolutions, making it possible to achieve real-time monitoring of air pollutions. The detailed spatial heterogeneity and diurnal variability of PM2.5 concentrations will also be valuable and supportive for environmental exposure assessment and related policy-driven regulations.

ACS Style

Tingting Jiang; Bin Chen; Zhen Nie; Zhehao Ren; Bing Xu; Shihao Tang. Estimation of hourly full-coverage PM2.5 concentrations at 1-km resolution in China using a two-stage random forest model. Atmospheric Research 2020, 248, 105146 .

AMA Style

Tingting Jiang, Bin Chen, Zhen Nie, Zhehao Ren, Bing Xu, Shihao Tang. Estimation of hourly full-coverage PM2.5 concentrations at 1-km resolution in China using a two-stage random forest model. Atmospheric Research. 2020; 248 ():105146.

Chicago/Turabian Style

Tingting Jiang; Bin Chen; Zhen Nie; Zhehao Ren; Bing Xu; Shihao Tang. 2020. "Estimation of hourly full-coverage PM2.5 concentrations at 1-km resolution in China using a two-stage random forest model." Atmospheric Research 248, no. : 105146.

Conference paper
Published: 25 June 2020 in Communications in Computer and Information Science
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Since its Reform and Opening-Up, China has been undergoing an unprecedented urbanization process, primarily manifested by intensive urban sprawl and continuous farmland shrinkage. However, few studies have given heed to the interrelation of these two phenomena at a finer spatiotemporal resolution, and limited researches have well quantified what controls the temporal rates of urban-expansion driven farmland loss. By considering Beijing as a case study, here we quantified the rates, patterns, spatiotemporal dynamics and interactions of urban expansion and farmland loss from 1980 to 2015 using the annual land-use/land-cover data. Additionally, by introducing the Environmental Kuznets Curve hypothesis, we further explored the relationship between urban-expansion driven farmland loss and economic growth. Results showed that rapid urban expansion (1592.57 km2) and extensive farmland loss (1591.36 km2) were observed during the study period. Three urban growth modes coexisted, where the edge-expansion was dominant (780.98 km2, 49.06%), followed by the infilling (675.85 km2, 42.44%) and the outlying (135.72 km2, 8.50%). Urban expansion was identified to be the dominant driver of farmland loss (96.13%), leading to a more spatially irregular and fragmented distribution of the farmland extent. Lastly, an inverted U-shape relationship was verified between urban-expansion driven farmland loss and economic growth, which indicated a shift from extensive to intensive and economizing land-use patterns in the future.

ACS Style

Ying Tu; Bin Chen; Le Yu; Qinchuan Xin; Peng Gong; Bing Xu. Urban-Expansion Driven Farmland Loss Follows with the Environmental Kuznets Curve Hypothesis: Evidence from Temporal Analysis in Beijing, China. Communications in Computer and Information Science 2020, 394 -412.

AMA Style

Ying Tu, Bin Chen, Le Yu, Qinchuan Xin, Peng Gong, Bing Xu. Urban-Expansion Driven Farmland Loss Follows with the Environmental Kuznets Curve Hypothesis: Evidence from Temporal Analysis in Beijing, China. Communications in Computer and Information Science. 2020; ():394-412.

Chicago/Turabian Style

Ying Tu; Bin Chen; Le Yu; Qinchuan Xin; Peng Gong; Bing Xu. 2020. "Urban-Expansion Driven Farmland Loss Follows with the Environmental Kuznets Curve Hypothesis: Evidence from Temporal Analysis in Beijing, China." Communications in Computer and Information Science , no. : 394-412.

Journal article
Published: 14 June 2020 in Remote Sensing
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Nighttime light remote sensing has aroused great popularity because of its advantage in estimating socioeconomic indicators and quantifying human activities in response to the changing world. Despite many advances that have been made in method development and implementation of nighttime light remote sensing over the past decades, limited studies have dived into answering the question: Where does nighttime light come from? This hinders our capability of identifying specific sources of nighttime light in urbanized regions. Addressing this shortcoming, here we proposed a parcel-oriented temporal linear unmixing method (POTLUM) to identify specific nighttime light sources with the integration of land use data. Ratio of root mean square error was used as the measure to assess the unmixing accuracy, and parcel purity index and source sufficiency index were proposed to attribute unmixing errors. Using the Visible Infrared Imaging Radiometer Suite (VIIRS) nighttime light dataset from the Suomi National Polar-Orbiting Partnership (NPP) satellite and the newly released Essential Urban Land Use Categories in China (EULUC-China) product, we applied the proposed method and conducted experiments in two China cities with different sizes, Shanghai and Quzhou. Results of the POTLUM showed its relatively robust applicability of detecting specific nighttime light sources, achieving an rRMSE of 3.38% and 1.04% in Shanghai and Quzhou, respectively. The major unmixing errors resulted from using impure land parcels as endmembers (i.e., parcel purity index for Shanghai and Quzhou: 54.48%, 64.09%, respectively), but it also showed that predefined light sources are sufficient (i.e., source sufficiency index for Shanghai and Quzhou: 96.53%, 99.55%, respectively). The method presented in this study makes it possible to identify specific sources of nighttime light and is expected to enrich the estimation of structural socioeconomic indicators, as well as better support various applications in urban planning and management.

ACS Style

Zhehao Ren; Yufu Liu; Bin Chen; Bing Xu. Where Does Nighttime Light Come From? Insights from Source Detection and Error Attribution. Remote Sensing 2020, 12, 1922 .

AMA Style

Zhehao Ren, Yufu Liu, Bin Chen, Bing Xu. Where Does Nighttime Light Come From? Insights from Source Detection and Error Attribution. Remote Sensing. 2020; 12 (12):1922.

Chicago/Turabian Style

Zhehao Ren; Yufu Liu; Bin Chen; Bing Xu. 2020. "Where Does Nighttime Light Come From? Insights from Source Detection and Error Attribution." Remote Sensing 12, no. 12: 1922.

Original article
Published: 28 May 2020 in MicrobiologyOpen
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Two novel reassortant avian influenza A (H3N6) viruses were isolated from swan goose in Poyang Lake, Jiangxi Province, China, in 2014. Phylogenetic analyses indicated that these viruses are most likely derived from the Eurasian‐originated H3Ny (N3, N6, N8) and H5N6 viruses circulating among wild and domestic birds. It is noteworthy that H9N2 viruses have contributed PB1 gene to these novel H3N6 viruses. Our findings provide phylogenetic evidence to elucidate the ongoing viral reassortment in the wild bird population in southern China. Active surveillance of avian influenza viruses in Poyang Lake is warranted.

ACS Style

Ruiyun Li; Tao Zhang; Jian Xu; Jianyu Chang; Bing Xu. Isolation of two novel reassortant H3N6 avian influenza viruses from long‐distance migratory birds in Jiangxi Province, China. MicrobiologyOpen 2020, 9, e1060 .

AMA Style

Ruiyun Li, Tao Zhang, Jian Xu, Jianyu Chang, Bing Xu. Isolation of two novel reassortant H3N6 avian influenza viruses from long‐distance migratory birds in Jiangxi Province, China. MicrobiologyOpen. 2020; 9 (8):e1060.

Chicago/Turabian Style

Ruiyun Li; Tao Zhang; Jian Xu; Jianyu Chang; Bing Xu. 2020. "Isolation of two novel reassortant H3N6 avian influenza viruses from long‐distance migratory birds in Jiangxi Province, China." MicrobiologyOpen 9, no. 8: e1060.

Journal article
Published: 08 May 2020 in Remote Sensing
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A heavy workload is required for sample collection for urban land use classification, and researchers are in urgent need of sampling strategies as a guide to achieve more effective work. In this paper, we make use of an urban land use survey to obtain a complete sample set of a city, test the impact of different training and validation sample sizes on the accuracy, and summarize the sampling strategy. The following conclusions are drawn based on our systematic analysis in Shenzhen. (1) For the best classification accuracy, the number of training samples should be no less than 40% of the total number of parcels or no less than 5500 parcels. For the best labor cost performance, the number should be no less than 7% or no less than 900. (2) The accuracy evaluation is stable and reliable and requires validation sample numbers of no less than 10% of the total or no less than 1200. (3) Samples with a purity of 60–90% are preferred, and the classification effectiveness is better in samples with a purity greater than 90% under the same number. (4) If spatial equilibrium sampling cannot be carried out, sampling areas with complex land use patterns should be preferred.

ACS Style

Mo Su; Renzhong Guo; Bin Chen; Wuyang Hong; Jiaqi Wang; Yimei Feng; Bing Xu. Sampling Strategy for Detailed Urban Land Use Classification: A Systematic Analysis in Shenzhen. Remote Sensing 2020, 12, 1497 .

AMA Style

Mo Su, Renzhong Guo, Bin Chen, Wuyang Hong, Jiaqi Wang, Yimei Feng, Bing Xu. Sampling Strategy for Detailed Urban Land Use Classification: A Systematic Analysis in Shenzhen. Remote Sensing. 2020; 12 (9):1497.

Chicago/Turabian Style

Mo Su; Renzhong Guo; Bin Chen; Wuyang Hong; Jiaqi Wang; Yimei Feng; Bing Xu. 2020. "Sampling Strategy for Detailed Urban Land Use Classification: A Systematic Analysis in Shenzhen." Remote Sensing 12, no. 9: 1497.

Research article
Published: 08 May 2020 in Virologica Sinica
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The spread of H5 highly pathogenic avian influenza viruses poses serious threats to the poultry industry, wild bird ecology and human health. Circulation of H5 viruses between poultry and wild birds is a significant public health threat in China. Thus, viral migration networks in this region need to be urgently studied. Here, we conducted molecular genetic analyses of the hemagglutinin genes of H5 highly pathogenic avian influenza viruses in multiple hosts from 2000 to 2018 in China. Our aim was to clarify the roles of different hosts in the evolution of H5 viruses. We used a flexible Bayesian statistical framework to simulate viral space diffusion and continuous-time Markov chains to infer the dynamic evolutionary process of spatiotemporal dissemination. Bayesian phylogeographic analysis of H5 viruses showed for the first time that H5 viruses in poultry and wild birds were present in Guangdong Province. Furthermore, Guangdong, Jiangsu, Shanghai and Hunan acted as the epicenters for the spread of various H5 subtypes viruses in poultry, and Henan, Shanghai, Hong Kong and Inner Mongolia acted as epicenters for the spread of various H5 subtypes viruses in wild birds. Thus, H5 viruses exhibited distinct evolutionary dynamics in poultry and wild birds. Our findings extend our understanding of the transmission and spread of highly pathogenic H5 avian influenza viruses in China.

ACS Style

Xiaowen Li; Xueying Li; Bing Xu. Phylogeography of Highly Pathogenic H5 Avian Influenza Viruses in China. Virologica Sinica 2020, 35, 548 -555.

AMA Style

Xiaowen Li, Xueying Li, Bing Xu. Phylogeography of Highly Pathogenic H5 Avian Influenza Viruses in China. Virologica Sinica. 2020; 35 (5):548-555.

Chicago/Turabian Style

Xiaowen Li; Xueying Li; Bing Xu. 2020. "Phylogeography of Highly Pathogenic H5 Avian Influenza Viruses in China." Virologica Sinica 35, no. 5: 548-555.

Articles
Published: 28 April 2020 in International Journal of Remote Sensing
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Night-time lights (NTLs) collected from the Defense Meteorological Satellite Program‘s Operational Linescan System (DMSP-OLS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) of the Suomi National Polar Partnership satellite have been widely used in multiple disciplines. However, the defects of DMSP and VIIRS data itself, and the inconsistency between them, hinder their applications in long-term finer studies. Despite some effective efforts, existing relevant researches are still limited by the shortcomings of data inaccessibility, data deficiency neglection, and spatial resolution degradation. To resolve these issues, a novel cross-sensor calibration method was developed in this article by considering three Chinese metropolises (Beijing, Shanghai, and Guangzhou) as the study area. First, the original DMSP NTL images for 2000–2013 were calibrated through stepwise calibration, background noise removal and vegetation adjustment. Second, stable VIIRS annual composites for 2012–2019 were produced after seasonal noise removal, yearly aggregation, background noise removal, vegetation adjustment, and outliers correction. Third, a power regression model was applied to align pixel values of the processed DMSP and the processed VIIRS data for the overlapped years, and consistent NTLs for 2000–2019 were further generated using the regression results. The evaluations based on statistical coefficients, spatial patterns, profile curves, dynamic changes, and correlations with socioeconomic statistics, indicated the robustness and effectiveness of the proposed approach in filling the gaps between DMSP and VIIRS data. The consistent, continuous, and stable NTL time series could serve as input data for further applications, such as urban dynamics capture, economic growth estimation, and population distribution mapping.

ACS Style

Ying Tu; Hanlin Zhou; Wei Lang; Tingting Chen; Xun Li; Bing Xu. A novel cross-sensor calibration method to generate a consistent night-time lights time series dataset. International Journal of Remote Sensing 2020, 41, 5482 -5502.

AMA Style

Ying Tu, Hanlin Zhou, Wei Lang, Tingting Chen, Xun Li, Bing Xu. A novel cross-sensor calibration method to generate a consistent night-time lights time series dataset. International Journal of Remote Sensing. 2020; 41 (14):5482-5502.

Chicago/Turabian Style

Ying Tu; Hanlin Zhou; Wei Lang; Tingting Chen; Xun Li; Bing Xu. 2020. "A novel cross-sensor calibration method to generate a consistent night-time lights time series dataset." International Journal of Remote Sensing 41, no. 14: 5482-5502.

Review
Published: 08 April 2020 in Environment International
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Air pollution over China has attracted wide interest from public and academic community. PM2.5 is the primary air pollutant across China. Quantifying interactions between meteorological conditions and PM2.5 concentrations are essential to understand the variability of PM2.5 and seek methods to control PM2.5. Since 2013, the measurement of PM2.5 has been widely made at 1436 stations across the country and more than 300 papers focusing on PM2.5-meteorology interactions have been published. This article is a comprehensive review on the meteorological impact on PM2.5 concentrations. We start with an introduction of general meteorological conditions and PM2.5 concentrations across China, and then seasonal and spatial variations of meteorological influences on PM2.5 concentrations. Next, major methods used to quantify meteorological influences on PM2.5 concentrations are checked and compared. We find that causality analysis methods are more suitable for extracting the influence of individual meteorological factors whilst statistical models are good at quantifying the overall effect of multiple meteorological factors on PM2.5 concentrations. Chemical Transport Models (CTMs) have the potential to provide dynamic estimation of PM2.5 concentrations by considering anthropogenic emissions and the transport and evolution of pollutants. We then comprehensively examine the mechanisms how major meteorological factors may impact the PM2.5 concentrations, including the dispersion, growth, chemical production, photolysis, and deposition of PM2.5. The feedback effects of PM2.5 concentrations on meteorological factors are also carefully examined. Based on this review, suggestions on future research and major meteorological approaches for mitigating PM2.5 pollution are made finally.

ACS Style

Ziyue Chen; Danlu Chen; Chuanfeng Zhao; Mei-Po Kwan; Jun Cai; Yan Zhuang; Bo Zhao; Xiaoyan Wang; Bin Chen; Jing Yang; Ruiyuan Li; Bin He; Bingbo Gao; Kaicun Wang; Bing Xu. Influence of meteorological conditions on PM2.5 concentrations across China: A review of methodology and mechanism. Environment International 2020, 139, 105558 .

AMA Style

Ziyue Chen, Danlu Chen, Chuanfeng Zhao, Mei-Po Kwan, Jun Cai, Yan Zhuang, Bo Zhao, Xiaoyan Wang, Bin Chen, Jing Yang, Ruiyuan Li, Bin He, Bingbo Gao, Kaicun Wang, Bing Xu. Influence of meteorological conditions on PM2.5 concentrations across China: A review of methodology and mechanism. Environment International. 2020; 139 ():105558.

Chicago/Turabian Style

Ziyue Chen; Danlu Chen; Chuanfeng Zhao; Mei-Po Kwan; Jun Cai; Yan Zhuang; Bo Zhao; Xiaoyan Wang; Bin Chen; Jing Yang; Ruiyuan Li; Bin He; Bingbo Gao; Kaicun Wang; Bing Xu. 2020. "Influence of meteorological conditions on PM2.5 concentrations across China: A review of methodology and mechanism." Environment International 139, no. : 105558.

Journal article
Published: 02 April 2020 in Science of Remote Sensing
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Satellite-based human settlement extraction methods have limited practical applications, due to merely studying the difference between human settlements and other land cover/use types in physical attributes (e.g., spectral signature and land surface temperature) instead of considering basic anthropogenic attributes (e.g., human distribution and human activities). To deal with this challenge, we proposed a novel method to accurately extract human settlements by integrating mobile phone locating-request (MPL) data and remotely sensed data. In this study, human settlements for selected cities were mapped at a medium resolution (30 ​m) by redistributing the MPL data using Landsat Normalized Difference Vegetation Index (NDVI) adjusted weights, with an overall accuracy of above 90.0%. Additionally, by extending the proposed method to the MPL and Moderate Resolution Imaging Spectroradiometer (MODIS) data, a coarse-resolution (250 ​m) map of human settlements in China was created with an overall accuracy of 95.2%. Compared with the widely used nighttime light based methods, the proposed method could solve the long-existing problems such as data saturation and blooming effects, as well as characterizing human settlements with fine spatial details. Our study provides an alternative approach to human settlement extraction by combining its physical and anthropogenic attributes, and it can be easily adjusted with multi-scale remotely sensed data and applied to human settlement extraction at different scales.

ACS Style

Bin Chen; Yimeng Song; Bo Huang; Bing Xu. A novel method to extract urban human settlements by integrating remote sensing and mobile phone locations. Science of Remote Sensing 2020, 1, 100003 .

AMA Style

Bin Chen, Yimeng Song, Bo Huang, Bing Xu. A novel method to extract urban human settlements by integrating remote sensing and mobile phone locations. Science of Remote Sensing. 2020; 1 ():100003.

Chicago/Turabian Style

Bin Chen; Yimeng Song; Bo Huang; Bing Xu. 2020. "A novel method to extract urban human settlements by integrating remote sensing and mobile phone locations." Science of Remote Sensing 1, no. : 100003.

Letter
Published: 25 March 2020 in Remote Sensing
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Understanding distributions of urban land use is of great importance for urban planning, decision support, and resource allocation. The first mapping results of essential urban land use categories (EULUC) in China for 2018 have been recently released. However, such kind of national maps may not sufficiently meet the growing demand for regional analysis. To address this shortcoming, here we proposed a segmentation-based framework named EULUC-seg to improve the mapping results of EULUC at the city scale. An object-based segmentation approach was first applied to generate the basic mapping units within urban parcels. Multiple features derived from high-resolution remotely sensed and social sensing data were updated and then recalculated within each unit. Random forest was adopted as the machine learning algorithm for classifying urban land use into five Level I classes and twelve Level II classes. Finally, an accuracy assessment was carried out based on a collection of manually interpreted samples. Results showed that our derived map achieved an overall accuracy of 87.58% for Level I, and 73.53% for Level II. The accurate and refined map of EULUC-seg is expected to better support various applications in the future.

ACS Style

Ying Tu; Bin Chen; Tao Zhang; Bing Xu. Regional Mapping of Essential Urban Land Use Categories in China: A Segmentation-Based Approach. Remote Sensing 2020, 12, 1058 .

AMA Style

Ying Tu, Bin Chen, Tao Zhang, Bing Xu. Regional Mapping of Essential Urban Land Use Categories in China: A Segmentation-Based Approach. Remote Sensing. 2020; 12 (7):1058.

Chicago/Turabian Style

Ying Tu; Bin Chen; Tao Zhang; Bing Xu. 2020. "Regional Mapping of Essential Urban Land Use Categories in China: A Segmentation-Based Approach." Remote Sensing 12, no. 7: 1058.

Short communication
Published: 10 December 2019 in Science Bulletin
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ACS Style

Peng Gong; Bin Chen; Xuecao Li; Han Liu; Jie Wang; Yuqi Bai; Jingming Chen; Xi Chen; Lei Fang; Shuailong Feng; Yongjiu Feng; Yali Gong; Hao Gu; Huabing Huang; Xiaochun Huang; Hongzan Jiao; Yingdong Kang; Guangbin Lei; Ainong Li; Xiaoting Li; Xun Li; Yuechen Li; Zhilin Li; Zhongde Li; Chong Liu; Chunxia Liu; Maochou Liu; Shuguang Liu; Wanliu Mao; Changhong Miao; Hao Ni; Qisheng Pan; Shuhua Qi; Zhehao Ren; Zhuoran Shan; Shaoqing Shen; Minjun Shi; Yimeng Song; Mo Su; Hoi Ping Suen; Bo Sun; Fangdi Sun; Jian Sun; Lin Sun; Wenyao Sun; Tian Tian; Xiaohua Tong; Yihsing Tseng; Ying Tu; Hong Wang; Lan Wang; Xi Wang; Zongming Wang; Tinghai Wu; Yaowen Xie; Jian Yang; Jun Yang; Man Yuan; Wenze Yue; Hongda Zeng; Kuo Zhang; Neng Zhang; Tao Zhang; Yu Zhang; Feng Zhao; Yichen Zheng; Qiming Zhou; Nicholas Clinton; Zhiliang Zhu; Bing Xu. Mapping essential urban land use categories in China (EULUC-China): preliminary results for 2018. Science Bulletin 2019, 65, 182 -187.

AMA Style

Peng Gong, Bin Chen, Xuecao Li, Han Liu, Jie Wang, Yuqi Bai, Jingming Chen, Xi Chen, Lei Fang, Shuailong Feng, Yongjiu Feng, Yali Gong, Hao Gu, Huabing Huang, Xiaochun Huang, Hongzan Jiao, Yingdong Kang, Guangbin Lei, Ainong Li, Xiaoting Li, Xun Li, Yuechen Li, Zhilin Li, Zhongde Li, Chong Liu, Chunxia Liu, Maochou Liu, Shuguang Liu, Wanliu Mao, Changhong Miao, Hao Ni, Qisheng Pan, Shuhua Qi, Zhehao Ren, Zhuoran Shan, Shaoqing Shen, Minjun Shi, Yimeng Song, Mo Su, Hoi Ping Suen, Bo Sun, Fangdi Sun, Jian Sun, Lin Sun, Wenyao Sun, Tian Tian, Xiaohua Tong, Yihsing Tseng, Ying Tu, Hong Wang, Lan Wang, Xi Wang, Zongming Wang, Tinghai Wu, Yaowen Xie, Jian Yang, Jun Yang, Man Yuan, Wenze Yue, Hongda Zeng, Kuo Zhang, Neng Zhang, Tao Zhang, Yu Zhang, Feng Zhao, Yichen Zheng, Qiming Zhou, Nicholas Clinton, Zhiliang Zhu, Bing Xu. Mapping essential urban land use categories in China (EULUC-China): preliminary results for 2018. Science Bulletin. 2019; 65 (3):182-187.

Chicago/Turabian Style

Peng Gong; Bin Chen; Xuecao Li; Han Liu; Jie Wang; Yuqi Bai; Jingming Chen; Xi Chen; Lei Fang; Shuailong Feng; Yongjiu Feng; Yali Gong; Hao Gu; Huabing Huang; Xiaochun Huang; Hongzan Jiao; Yingdong Kang; Guangbin Lei; Ainong Li; Xiaoting Li; Xun Li; Yuechen Li; Zhilin Li; Zhongde Li; Chong Liu; Chunxia Liu; Maochou Liu; Shuguang Liu; Wanliu Mao; Changhong Miao; Hao Ni; Qisheng Pan; Shuhua Qi; Zhehao Ren; Zhuoran Shan; Shaoqing Shen; Minjun Shi; Yimeng Song; Mo Su; Hoi Ping Suen; Bo Sun; Fangdi Sun; Jian Sun; Lin Sun; Wenyao Sun; Tian Tian; Xiaohua Tong; Yihsing Tseng; Ying Tu; Hong Wang; Lan Wang; Xi Wang; Zongming Wang; Tinghai Wu; Yaowen Xie; Jian Yang; Jun Yang; Man Yuan; Wenze Yue; Hongda Zeng; Kuo Zhang; Neng Zhang; Tao Zhang; Yu Zhang; Feng Zhao; Yichen Zheng; Qiming Zhou; Nicholas Clinton; Zhiliang Zhu; Bing Xu. 2019. "Mapping essential urban land use categories in China (EULUC-China): preliminary results for 2018." Science Bulletin 65, no. 3: 182-187.

Journal article
Published: 10 December 2019 in Remote Sensing
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Global urbanization is occurring rapidly, and numerous moderate resolution remote sensing data are being used to monitor this process. Landsat 8 OLI and Sentinel-2 MSI data are combined in many applications but few studies haves focused on either urban change or consistency between these two data in time series. To evaluate the varying correlation between the two sensors in a time series, the correlation coefficient (R) and root-mean-square deviation (RMSD) of seven band pairs and three indices (NDVI, NDBI, and MNDWI) were calculated in this study and the results of the built-up area identified by IBI derived from the above three indices were compared. It was found that the correlation between the two sensors (R > 0.8534, p < 0.0001) was good in most bands but not as good for indices (in half of the results, R < 0.9). Meanwhile, the correlation of the two sensors of both bands and indices fluctuated between seasons and the comparative results of built-up area identification between the two data are relative to this variation. Therefore, when the OLI and MSI data are used in future collaboration applications, the data and threshold selection should consider the consistency and the fluctuation between the two data, especially in both time series studies and urban detection.

ACS Style

Zhen Nie; Karen Kie Yan Chan; Bing Xu. Preliminary Evaluation of the Consistency of Landsat 8 and Sentinel-2 Time Series Products in An Urban Area—An Example in Beijing, China. Remote Sensing 2019, 11, 2957 .

AMA Style

Zhen Nie, Karen Kie Yan Chan, Bing Xu. Preliminary Evaluation of the Consistency of Landsat 8 and Sentinel-2 Time Series Products in An Urban Area—An Example in Beijing, China. Remote Sensing. 2019; 11 (24):2957.

Chicago/Turabian Style

Zhen Nie; Karen Kie Yan Chan; Bing Xu. 2019. "Preliminary Evaluation of the Consistency of Landsat 8 and Sentinel-2 Time Series Products in An Urban Area—An Example in Beijing, China." Remote Sensing 11, no. 24: 2957.

Article
Published: 14 November 2019 in Microbiology Resource Announcements
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Here, we report the detection of a reassortant avian influenza A(H3N8) virus isolated from a wild bird in Poyang Lake, Jiangxi, China, in 2014. Phylogenetic analyses indicated that this virus is most likely derived from the Eurasian-origin H3Ny and HxN8 viruses and two strains endemic to China, namely, H5N1 and H5N6.

ACS Style

Ruiyun Li; Tao Zhang; Jian Xu; Jianyu Chang; Bing Xu. Novel Reassortant Avian Influenza A(H3N8) Virus Isolated from a Wild Bird in Jiangxi, China. Microbiology Resource Announcements 2019, 8, 1 .

AMA Style

Ruiyun Li, Tao Zhang, Jian Xu, Jianyu Chang, Bing Xu. Novel Reassortant Avian Influenza A(H3N8) Virus Isolated from a Wild Bird in Jiangxi, China. Microbiology Resource Announcements. 2019; 8 (46):1.

Chicago/Turabian Style

Ruiyun Li; Tao Zhang; Jian Xu; Jianyu Chang; Bing Xu. 2019. "Novel Reassortant Avian Influenza A(H3N8) Virus Isolated from a Wild Bird in Jiangxi, China." Microbiology Resource Announcements 8, no. 46: 1.