{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T12:31:15Z","timestamp":1770726675338,"version":"3.49.0"},"reference-count":58,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2021,10,28]],"date-time":"2021-10-28T00:00:00Z","timestamp":1635379200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41801178, 41771203"],"award-info":[{"award-number":["41801178, 41771203"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Accurate quantification of vertical structure (or 3D structure) and its change of a city is essential for understanding the evolution of urban form, and its social and ecological consequences. Previous studies have largely focused on the horizontal structure (or 2D structure), but few on 3D structure, especially for long time changes, due to the absence of such historical data. Here, we present a new approach for 3D reconstruction of urban history, which was applied to characterize the urban 3D structure and its change from 1986 to 2017 in Shenzhen, a megacity in southern China. This approach integrates the contemporary building height obtained from the increasingly available data of building footprint with building age estimated based on the long-term observations from time-series Landsat imagery. We found: (1) the overall accuracy for building change detection was 87.80%, and for the year of change was 77.40%, suggesting that the integrated approach provided an effective method to cooperate horizontal (i.e., building footprint), vertical (i.e., building height), and temporal information (i.e., building age) to generate the historical data for urban 3D reconstruction. (2) The number of buildings increased dramatically from 1986 to 2017, by eight times, with an increased proportion of high-rise buildings. (3) The old urban areas continued to have the highest density of buildings, with increased average height of buildings, but there were two emerging new centers clustered with high-rise buildings. The long-term urban 3D maps allowed characterizing the spatiotemporal patterns of the vertical dimension at the city level, which can enhance our understanding on urban morphology.<\/jats:p>","DOI":"10.3390\/rs13214339","type":"journal-article","created":{"date-parts":[[2021,10,28]],"date-time":"2021-10-28T23:52:35Z","timestamp":1635465155000},"page":"4339","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Time-Series Landsat Data for 3D Reconstruction of Urban History"],"prefix":"10.3390","volume":"13","author":[{"given":"Wenjuan","family":"Yu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China"}]},{"given":"Chuanbao","family":"Jing","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China"},{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7323-4906","authenticated-orcid":false,"given":"Weiqi","family":"Zhou","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China"},{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Beijing Urban Ecosystem Research Station, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China"},{"name":"Beijing-Tianjin-Hebei Urban Megaregion National Observation and Research Station for Eco-Environmental Change, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China"}]},{"given":"Weimin","family":"Wang","sequence":"additional","affiliation":[{"name":"State Environmental Protection Scientific Observation and Research Station for Ecology and Environment of Rapid Urbanization Region, Shenzhen Environmental Monitoring Center, Shenzhen 518049, China"}]},{"given":"Zhong","family":"Zheng","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China"},{"name":"Beijing Urban Ecosystem Research Station, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China"},{"name":"Beijing-Tianjin-Hebei Urban Megaregion National Observation and Research Station for Eco-Environmental Change, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"16083","DOI":"10.1073\/pnas.1211658109","article-title":"Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools","volume":"109","author":"Seto","year":"2012","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Zhou, W., Yu, W., Qian, Y., Han, L., Pickett, S.T.A., Wang, J., Li, W., and Ouyang, Z. (2021). Beyond city expansion: Multi-scale environmental impacts of urban megaregion formation in China. Natl. Sci. Rev.","DOI":"10.1093\/nsr\/nwab107"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"112096","DOI":"10.1016\/j.rse.2020.112096","article-title":"Mapping horizontal and vertical urban densification in Denmark with Landsat time-series from 1985 to 2018: A semantic segmentation solution","volume":"251","author":"Chen","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"111859","DOI":"10.1016\/j.rse.2020.111859","article-title":"Continental-scale mapping and analysis of 3D building structure","volume":"245","author":"Li","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1016\/1352-2310(95)00266-9","article-title":"Urban design morphology and thermal performance","volume":"30","author":"Golany","year":"1996","journal-title":"Atmos. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1879","DOI":"10.1175\/BAMS-D-11-00019.1","article-title":"Local Climate Zones for Urban Temperature Studies","volume":"93","author":"Stewart","year":"2012","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s42949-020-00011-9","article-title":"Conceptual frameworks facilitate integration for transdisciplinary urban science","volume":"1","author":"Zhou","year":"2021","journal-title":"Npj Urban Sustain."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1177\/0885412215595439","article-title":"Compactness versus sprawl: A review of recent evidence from the United States","volume":"30","author":"Ewing","year":"2015","journal-title":"J. Plan. Lit."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1023\/A:1020512723753","article-title":"A gradient analysis of urban landscape pattern: A case study from the Phoenix metropolitan region, Arizona, USA","volume":"17","author":"Luck","year":"2002","journal-title":"Landsc. Ecol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"659","DOI":"10.1177\/0042098007087340","article-title":"Compact, dispersed, fragmented, extensive? A comparison of urban growth in twenty-five global cities using remotely sensed data, pattern metrics and census information","volume":"45","author":"Schneider","year":"2008","journal-title":"Urban Stud."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1080\/0042098042000309748","article-title":"Quantifying urban form: Compactness versus\u2019 sprawl\u2019","volume":"42","author":"Tsai","year":"2005","journal-title":"Urban Stud."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ecocom.2010.03.002","article-title":"Quantifying spatiotemporal patterns of urbanization: The case of the two fastest growing metropolitan regions in the United States","volume":"8","author":"Wu","year":"2011","journal-title":"Ecol. Complex."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.ecolind.2017.10.035","article-title":"Urban sprawl in a megaregion: A multiple spatial and temporal perspective","volume":"96","author":"Zhou","year":"2019","journal-title":"Ecol. Indic."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"107635","DOI":"10.1016\/j.buildenv.2021.107635","article-title":"The effects of 2D and 3D building morphology on urban environments: A multi-scale analysis in the Beijing metropolitan region","volume":"192","author":"Cao","year":"2021","journal-title":"Build. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"4789","DOI":"10.1016\/j.atmosenv.2009.07.061","article-title":"Urban morphology and air quality in dense residential environments in Hong Kong. Part I: District-level analysis","volume":"45","author":"Edussuriya","year":"2011","journal-title":"Atmos. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.isprsjprs.2019.04.010","article-title":"Investigating the effects of 3D urban morphology on the surface urban heat island effect in urban functional zones by using high-resolution remote sensing data: A case study of Wuhan, Central China","volume":"152","author":"Huang","year":"2019","journal-title":"Isprs J. Photogramm. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.pce.2019.01.008","article-title":"The higher, the cooler? Effects of building height on land surface termperature in residential areas of Beijing","volume":"110","author":"Zheng","year":"2019","journal-title":"Phys. Chem. Earth Parts A\/B\/C"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1016\/j.rse.2017.05.001","article-title":"Multi-level monitoring of subtle urban changes for the megacities of China using high-resolution multi-view satellite imagery","volume":"196","author":"Huang","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"570","DOI":"10.1016\/j.isprsjprs.2010.09.006","article-title":"An update on automatic 3D building reconstruction","volume":"65","author":"Haala","year":"2010","journal-title":"Isprs J. Photogramm. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/S0198-9715(99)00047-2","article-title":"Extracting urban features from LiDAR digital surface models","volume":"24","author":"Priestnall","year":"2000","journal-title":"Computers, Environment and Urban Syst."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1016\/j.rse.2014.11.001","article-title":"Urban land cover classification using airborne LiDAR data: A review","volume":"158","author":"Yan","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2043","DOI":"10.1007\/s10980-020-01032-6","article-title":"Identification of urban flight corridors for migratory birds in the coastal regions of Shenzhen city based on three-dimensional landscapes","volume":"36","author":"Liu","year":"2020","journal-title":"Landsc. Ecol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1262","DOI":"10.1175\/1520-0450(1999)038<1262:APOUAD>2.0.CO;2","article-title":"Aerodynamic properties of urban areas derived from analysis of surface form","volume":"38","author":"Grimmond","year":"1999","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1002","DOI":"10.1016\/j.rser.2015.10.104","article-title":"Review on the impact of urban geometry and pedestrian level greening on outdoor thermal comfort","volume":"54","author":"Jamei","year":"2016","journal-title":"Renew. Sust. Energy Rev."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Dong, Y., Ren, Z., Fu, Y., Miao, Z.L., Yang, R., Sun, Y., and He, X. (2020). Recording Urban Land Dynamic and Its Effects during 2000\u20132019 at 15-m Resolution by Cloud Computing with Landsat Series. Remote Sens., 12.","DOI":"10.3390\/rs12152451"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2897","DOI":"10.1016\/j.rse.2010.07.008","article-title":"Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr\u2014Temporal segmentation algorithms","volume":"114","author":"Kennedy","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Li, D., Lu, D., Wu, M., Shao, X., and Wei, J. (2018). Examining Land Cover and Greenness Dynamics in Hangzhou Bay in 1985\u20132016 using Landsat time-series data. Remote Sens., 10.","DOI":"10.3390\/rs10010032"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.rse.2014.01.011","article-title":"Continuous change detection and classification of land cover using all available Landsat data","volume":"144","author":"Zhu","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.rse.2018.05.005","article-title":"Mapping the timing of cropland abandonment and recultivation in northern Kazakhstan using annual Landsat time series","volume":"213","author":"Dara","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"5493","DOI":"10.3390\/rs5115493","article-title":"Ten-Year Landsat Classification of Deforestation and Forest Degradation in the Brazilian Amazon","volume":"5","author":"Souza","year":"2013","journal-title":"Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"674","DOI":"10.1016\/j.rse.2018.07.030","article-title":"Mapping annual urban dynamics (1985\u20132015) using time series of Landsat data","volume":"216","author":"Li","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"564","DOI":"10.1038\/s41893-020-0521-x","article-title":"High-spatiotemporal-resolution mapping of global urban change from 1985 to 2015","volume":"3","author":"Liu","year":"2020","journal-title":"Nat. Sustain."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2015.12.027","article-title":"Characterizing the magnitude, timing and duration of urban growth from time series of Landsat-based estimates of impervious cover","volume":"175","author":"Song","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"111197","DOI":"10.1016\/j.rse.2019.05.016","article-title":"Towards a novel backdating strategy for creating built-up land time series data using contemporary spatial constraints","volume":"238","author":"Uhl","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"111802","DOI":"10.1016\/j.rse.2020.111802","article-title":"An automatic change detection method for monitoring newly constructed building areas using time-series multi-view high-resolution optical satellite images","volume":"224","author":"Huang","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Wen, D., Huang, X., Zhang, A., and Ke, X. (2019). Monitoring 3D Building Change and Urban Redevelopment Patterns in Inner City Areas of Chinese Megacities Using Multi-View Satellite Imagery. Remote Sens., 11.","DOI":"10.3390\/rs11070763"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.pce.2019.02.006","article-title":"Urban expansion in Shenzhen since 1970s: A retrospect of change from a village to a megacity from the space","volume":"110","author":"Yu","year":"2019","journal-title":"Phys. Chem. Earth Parts A\/B\/C"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"101854","DOI":"10.1016\/j.scs.2019.101854","article-title":"Analyzing the spatial factors related to the distributions of building heights in urban areas: A comparative case study in Guangzhou and Shenzhe","volume":"52","author":"Lin","year":"2020","journal-title":"Sustain. Cities Soc."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"112293","DOI":"10.1016\/j.rse.2021.112293","article-title":"A novel approach for quantifying high-frequency urban land cover changes at the block level with scarce clear-sky Landsat observations","volume":"255","author":"Jing","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Qian, Y., Zhou, W., Yu, W., Han, L., Li, W., and Zhao, W. (2020). Integrating backdating and transfer learning in an object-based framework for high resolution image classification and change analysis. Remote Sens., 12.","DOI":"10.3390\/rs12244094"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.isprsjprs.2011.11.002","article-title":"An assessment of the effectiveness of a random forest classifier for land-cover classification","volume":"67","author":"Ghimire","year":"2012","journal-title":"Isprs J. Photogramm."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Abdul-Rahman, A., Zlatanova, S., and Coors, V. (2007). Innovations in 3D geo information systems. Lecture Notes in Geoinformation and Cartography, Springer.","DOI":"10.1007\/978-3-540-36998-1"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.rse.2016.02.030","article-title":"A new approach for land cover classification and change analysis: Integrating backdating and an object-based method","volume":"177","author":"Yu","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1613","DOI":"10.3390\/s8031613","article-title":"Object-based land cover classification and change analysis in the Baltimore metropolitan area using multitemporal high resolution remote sensing data","volume":"8","author":"Zhou","year":"2008","journal-title":"Sensors"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1016\/j.isprsjprs.2017.06.013","article-title":"Change detection using landsat time series: A review of frequencies, preprocessing, algorithms, and applications","volume":"130","author":"Zhu","year":"2017","journal-title":"Isprs J. Photogramm. Remote Sens."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1016\/j.rse.2007.03.010","article-title":"Trajectory-based change detection for automated characterization of forest disturbance dynamics","volume":"110","author":"Kennedy","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.rse.2018.02.050","article-title":"Mapping agricultural land abandonment from spatial and temporal segmentation of Landsat time series","volume":"210","author":"Yin","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1845","DOI":"10.1007\/s10980-020-01104-7","article-title":"Quantifying highly dynamic urban landscapes: Integrating object-based image analysis with Landsat time series data","volume":"36","author":"Yu","year":"2021","journal-title":"Landsc. Ecol."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Herold, H., and Hecht, R. (2018). 3D Reconstruction of Urban History Based on Old Maps. Digital Research and Education in Architectural Heritage, Springer.","DOI":"10.1007\/978-3-319-76992-9_5"},{"key":"ref_50","unstructured":"Loga, T., and Bach, N. (2010). Use of Building Typologies for Energy Performance Assessment of National Building Stocks. Existent Experiences in European Countries and Common Approach, Institut Wohnen und Umwelt GmbH. First TABULA Synthesis Report."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"3181","DOI":"10.1016\/j.rse.2008.03.013","article-title":"An object-based change detection method accounting for temporal dependences in time series with medium to coarse spatial resolution","volume":"112","author":"Bontemps","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.isprsjprs.2018.07.003","article-title":"Stand age estimation of rubber (Hevea brasiliensis) plantations using an integrated pixel- and object-based tree growth model and annual Landsat time series","volume":"144","author":"Chen","year":"2018","journal-title":"Isprs J. Photogramm. Remote Sens."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1890\/130066","article-title":"Bringing an ecological view of change to Landsat-based remote sensing","volume":"12","author":"Kennedy","year":"2014","journal-title":"Front. Ecol. Environ."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"111558","DOI":"10.1016\/j.rse.2019.111558","article-title":"Transitioning from change detection to monitoring with remote sensing: A paradigm shift","volume":"238","author":"Woodcock","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1016\/j.scitotenv.2019.02.178","article-title":"Characterizing the spatial pattern of annual urban growth by using time series Landsat imagery","volume":"666","author":"Fu","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"5388","DOI":"10.1080\/01431161.2017.1339926","article-title":"Dynamic monitoring of land-use\/land-cover change and urban expansion in Shenzhen using Landsat imagery from 1988 to 2015","volume":"38","author":"Dou","year":"2017","journal-title":"Isprs J. Photogramm. Remote Sens."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1016\/j.landurbplan.2015.06.007","article-title":"Linking ecosysterm services and landscape patterns to assess urban ecosystem health: A case study in Shenzhen City, China","volume":"143","author":"Peng","year":"2015","journal-title":"Landsc. Urban Plan."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"021004","DOI":"10.1088\/1748-9326\/8\/2\/024004","article-title":"A global fingerprint of macro-scale changes in urban structure from 1999 to 2009","volume":"8","author":"Frolking","year":"2013","journal-title":"Environ. Res. Lett."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/21\/4339\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:22:08Z","timestamp":1760167328000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/21\/4339"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,28]]},"references-count":58,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2021,11]]}},"alternative-id":["rs13214339"],"URL":"https:\/\/doi.org\/10.3390\/rs13214339","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,10,28]]}}}