{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T18:16:18Z","timestamp":1782324978039,"version":"3.54.5"},"reference-count":63,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2021,7,10]],"date-time":"2021-07-10T00:00:00Z","timestamp":1625875200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>The remote-sensing ecological index (RSEI), which is built with greenness, moisture, dryness, and heat, has become increasingly recognized for its use in urban eco-environment quality assessment. To improve the reliability of such assessment, we propose a new RSEI-based urban eco-environment quality assessment method where the impact of RSEI indicators on the eco-environment quality and the seasonal change of RSEI are examined and considered. The northern Chinese municipal city of Tianjin was selected as a case study to test the proposed method. Landsat images acquired in spring, summer, autumn, and winter were obtained and processed for three different years (1992, 2005, and 2018) for a multitemporal analysis. Results from the case study show that both the contributions of RSEI indicators to eco-environment quality and RSEI values vary with the season and that such seasonal variability should be considered by normalizing indicator measures differently and using more representative remote-sensing images, respectively. The assessed eco-environment quality of Tianjin was, overall, improving owing to governmental environmental protection measures, but the damage caused by rapid urban expansion and sea reclamation in the Binhai New Area still needs to be noted. It is concluded that our proposed urban eco-environment quality assessment method is viable and can provide a reliable assessment result that helps gain a more accurate understanding of the evolution of the urban eco-environment quality over seasons and years.<\/jats:p>","DOI":"10.3390\/ijgi10070475","type":"journal-article","created":{"date-parts":[[2021,7,12]],"date-time":"2021-07-12T00:23:36Z","timestamp":1626049416000},"page":"475","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":66,"title":["Assessing the Urban Eco-Environmental Quality by the Remote-Sensing Ecological Index: Application to Tianjin, North China"],"prefix":"10.3390","volume":"10","author":[{"given":"Ting","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Public Policy and Management, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-5161-6021","authenticated-orcid":false,"given":"Ruiqing","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Resources and Environment, Huazhong Agricultural University, Shizishan Street 1, Wuhan 430070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yibo","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Public Administration, China University of Geosciences, Lumo Road 388, Wuhan 430074, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7763-1108","authenticated-orcid":false,"given":"Long","family":"Li","sequence":"additional","affiliation":[{"name":"School of Public Policy and Management, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China"},{"name":"Department of Geography & Earth System Science, Vrije Universiteit Brussel, 1050 Brussels, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Longqian","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Public Policy and Management, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"689","DOI":"10.1016\/j.rse.2012.06.006","article-title":"Monitoring land cover change in urban and peri-urban areas using dense time stacks of Landsat satellite data and a data mining approach","volume":"124","author":"Schneider","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1016\/j.landurbplan.2014.01.017","article-title":"Urban green space, public health, and environmental justice: The challenge of making cities \u201cjust green enough.\u201d","volume":"125","author":"Wolch","year":"2014","journal-title":"Landsc. Urban Plan."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"112236","DOI":"10.1016\/j.jenvman.2021.112236","article-title":"Modeling the impact of the COVID-19 lockdowns on urban surface ecological status: A case study of Milan and Wuhan cities","volume":"286","author":"Firozjaei","year":"2021","journal-title":"J. Environ. Manag."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1016\/j.jclepro.2017.12.273","article-title":"Urbanization for rural sustainability\u2014Rethinking China\u2019s urbanization strategy","volume":"178","author":"Li","year":"2018","journal-title":"J. Clean. Prod."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Psomiadis, E., Papazachariou, A., Soulis, K.X., Alexiou, D.S., and Charalampopoulos, I. (2020). Landslide mapping and susceptibility assessment using geospatial analysis and earth observation data. Land, 9.","DOI":"10.3390\/land9050133"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1007\/s11069-009-9403-2","article-title":"Landslide hazard zonation in high risk areas of Rethymno Prefecture, Crete Island, Greece","volume":"52","author":"Kouli","year":"2010","journal-title":"Nat. Hazards"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"564","DOI":"10.1007\/s10661-017-6267-x","article-title":"Multi-criteria evaluation of hydro-geological and anthropogenic parameters for the groundwater vulnerability assessment","volume":"189","author":"Kumar","year":"2017","journal-title":"Environ. Monit. Assess."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1016\/j.biocon.2014.12.006","article-title":"Remote sensing change detection for ecological monitoring in United States protected areas","volume":"182","author":"Willis","year":"2015","journal-title":"Biol. Conserv."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"854","DOI":"10.1016\/j.jclepro.2016.07.011","article-title":"The synthetic geo-ecological environmental evaluation of a coastal coal-mining city using spatiotemporal big data: A case study in Longkou, China","volume":"142","author":"He","year":"2017","journal-title":"J. Clean. Prod."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Li, S., Bing, Z., and Jin, G. (2019). Spatially explicit mapping of soil conservation service in monetary units due to land use\/cover change for the three gorges reservoir area, China. Remote Sens., 11.","DOI":"10.3390\/rs11040468"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Zhang, L., Liu, L., Xia, Z., Li, W., and Fan, Q. (2016). Sparse trajectory prediction based on multiple entropy measures. Entropy, 18.","DOI":"10.3390\/e18090327"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3249","DOI":"10.1016\/j.rse.2011.07.008","article-title":"Impacts of landscape structure on surface urban heat islands: A case study of Shanghai, China","volume":"115","author":"Li","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1007\/s10980-009-9402-4","article-title":"Urban heat islands and landscape heterogeneity: Linking spatiotemporal variations in surface temperatures to land-cover and socioeconomic patterns","volume":"25","author":"Buyantuyev","year":"2010","journal-title":"Landsc. Ecol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"730","DOI":"10.1016\/j.ecolind.2018.05.055","article-title":"Prediction of ecological effects of potential population and impervious surface increases using a remote sensing based ecological index (RSEI)","volume":"93","author":"Xu","year":"2018","journal-title":"Ecol. Indic."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Xu, H., Wang, Y., Guan, H., Shi, T., and Hu, X. (2019). Detecting ecological changes with a remote sensing based ecological index (RSEI) produced time series and change vector analysis. Remote Sens., 11.","DOI":"10.3390\/rs11202345"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"5381","DOI":"10.1007\/s11356-018-3948-0","article-title":"A new remote sensing index based on the pressure-state-response framework to assess regional ecological change","volume":"26","author":"Hu","year":"2019","journal-title":"Environ. Sci. Pollut. Res."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.ecolind.2018.02.006","article-title":"A new remote sensing index for assessing the spatial heterogeneity in urban ecological quality: A case from Fuzhou City, China","volume":"89","author":"Hu","year":"2018","journal-title":"Ecol. Indic."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"118126","DOI":"10.1016\/j.jclepro.2019.118126","article-title":"Ecological environment quality assessment based on remote sensing data for land consolidation","volume":"239","author":"Shan","year":"2019","journal-title":"J. Clean. Prod."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Wen, X., Ming, Y., Gao, Y., and Hu, X. (2020). Dynamic monitoring and analysis of ecological quality of pingtan comprehensive experimental zone, a new type of sea island city, based on RSEI. Sustainability, 12.","DOI":"10.3390\/su12010021"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"154940","DOI":"10.1109\/ACCESS.2020.3018730","article-title":"Studying the Eco-Environmental Quality Variations of Jing-Jin-Ji Urban Agglomeration and Its Driving Factors in Different Ecosystem Service Regions from 2001 to 2015","volume":"8","author":"Ji","year":"2020","journal-title":"IEEE Access"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1080\/21642583.2020.1726230","article-title":"Evolution, development and evaluation of eco-transportation in Guangdong-Hong Kong-Macao Greater Bay Area","volume":"8","author":"Zhou","year":"2020","journal-title":"Syst. Sci. Control. Eng."},{"key":"ref_22","first-page":"200","article-title":"Ecological response to land use change: A case study from the Chaohu lake basin, China","volume":"49","author":"Wang","year":"2017","journal-title":"Bulg. Chem. Commun."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"104569","DOI":"10.1016\/j.landusepol.2020.104569","article-title":"Monitoring the effects of land consolidation on the ecological environmental quality based on remote sensing: A case study of Chaohu Lake Basin, China","volume":"95","author":"Guo","year":"2020","journal-title":"Land Use Policy"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"107214","DOI":"10.1016\/j.ecolind.2020.107214","article-title":"Estimation of remote sensing based ecological index along the Grand Canal based on PCA-AHP-TOPSIS methodology","volume":"122","author":"Li","year":"2021","journal-title":"Ecol. Indic."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Liao, W., and Jiang, W. (2020). Evaluation of the spatiotemporal variations in the eco-environmental quality in China based on the remote sensing ecological index. Remote Sens., 12.","DOI":"10.3390\/rs12152462"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Qureshi, S., Alavipanah, S.K., Konyushkova, M., Mijani, N., Fathololomi, S., Firozjaei, M.K., Homaee, M., Hamzeh, S., and Kakroodi, A.A. (2020). A remotely sensed assessment of surface ecological change over the Gomishan Wetland, Iran. Remote Sens., 12.","DOI":"10.3390\/rs12182989"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"112138","DOI":"10.1016\/j.jenvman.2021.112138","article-title":"Spatiotemporal ecological vulnerability analysis with statistical correlation based on satellite remote sensing in Samara, Russia","volume":"285","author":"Boori","year":"2021","journal-title":"J. Environ. Manag."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"143755","DOI":"10.1016\/j.scitotenv.2020.143755","article-title":"A novel method to quantify urban surface ecological poorness zone: A case study of several European cities","volume":"757","author":"Firozjaei","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"107375","DOI":"10.1016\/j.ecolind.2021.107375","article-title":"Land Surface Ecological Status Composition Index (LSESCI): A novel remote sensing-based technique for modeling land surface ecological status","volume":"123","author":"Fathololoumi","year":"2021","journal-title":"Ecol. Indic."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"51295","DOI":"10.1109\/ACCESS.2019.2911627","article-title":"Eco-environmental quality assessment in china\u2019s 35 major cities based on remote sensing ecological index","volume":"7","author":"Yue","year":"2019","journal-title":"IEEE Access"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1038\/nature16986","article-title":"Sensitivity of global terrestrial ecosystems to climate variability","volume":"531","author":"Seddon","year":"2016","journal-title":"Nature"},{"key":"ref_32","unstructured":"(2021, May 11). Tianjin Weather. Available online: https:\/\/weather.cma.cn\/web\/weather\/54517."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"125369","DOI":"10.1016\/j.jclepro.2020.125369","article-title":"Sustainability assessment and key factors identification of first-tier cities in China","volume":"281","author":"Yi","year":"2021","journal-title":"J. Clean. Prod."},{"key":"ref_34","unstructured":"(2021, May 11). 2019 Official List of New First-Tier Cities: Where Does Your City Rank?. Available online: https:\/\/www.yicai.com\/news\/100200192.html."},{"key":"ref_35","unstructured":"Tianjin Municipal People\u2019s Government (1992). Tianjin Economic Yearbook 1992, Tianjin Statistical Yearbooks Press. [1st ed.]."},{"key":"ref_36","unstructured":"Tianjin Municipal People\u2019s Government (2019). Yearbook of Tianjin 2019, Tianjin Statistical Yearbooks Press. [1st ed.]."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1016\/j.ecolind.2016.09.047","article-title":"Total-factor ecology efficiency of regions in China","volume":"73","author":"Yue","year":"2017","journal-title":"Ecol. Indic."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"12619","DOI":"10.3390\/rs61212619","article-title":"Radiometric cross calibration of landsat 8 Operational Land Imager (OLI) and landsat 7 enhanced thematic mapper plus (ETM+)","volume":"6","author":"Mishra","year":"2014","journal-title":"Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"3714","DOI":"10.1080\/01431161.2015.1070322","article-title":"Comparing the spectral signal of burned surfaces between Landsat 7 ETM+ and Landsat 8 OLI sensors","volume":"36","author":"Koutsias","year":"2015","journal-title":"Int. J. Remote Sens."},{"key":"ref_40","first-page":"48","article-title":"Monitoring Vegetation Systems in the Great Plains with ERTS","volume":"1","author":"Rouse","year":"1973","journal-title":"Proc. Third ERTS Symp."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"840","DOI":"10.1002\/esp.4284","article-title":"Dating lava flows of tropical volcanoes by means of spatial modeling of vegetation recovery","volume":"43","author":"Li","year":"2018","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Zhou, X., Li, L., Chen, L., Liu, Y., Cui, Y., Zhang, Y., and Zhang, T. (2019). Discriminating urban forest types from Sentinel-2A image data through linear spectral mixture analysis: A case study of Xuzhou, East China. Forests, 10.","DOI":"10.3390\/f10060478"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Li, L., Zhou, X., Chen, L., Chen, L., Zhang, Y., and Liu, Y. (2020). Estimating urban vegetation biomass from sentinel-2A image data. Forests, 11.","DOI":"10.3390\/f11020125"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1016\/0034-4257(85)90102-6","article-title":"A TM Tasseled Cap equivalent transformation for reflectance factor data","volume":"17","author":"Crist","year":"1985","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1080\/2150704X.2014.915434","article-title":"Derivation of a tasselled cap transformation based on Landsat 8 at-satellite reflectance","volume":"5","author":"Baig","year":"2014","journal-title":"Remote Sens. Lett."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"4269","DOI":"10.1080\/01431160802039957","article-title":"A new index for delineating built-up land features in satellite imagery","volume":"29","author":"Xu","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_47","first-page":"163","article-title":"Evaluation of the DisTrad thermal sharpening methodology for urban areas","volume":"19","author":"Essa","year":"2012","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1109\/TGRS.2008.2007125","article-title":"Revision of the single-channel algorithm for land surface temperature retrieval from landsat thermal-infrared data","volume":"47","author":"Cristobal","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"434","DOI":"10.1016\/j.rse.2004.02.003","article-title":"Land surface temperature retrieval from LANDSAT TM 5","volume":"90","author":"Sobrino","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1016\/j.isprsjprs.2009.03.007","article-title":"Thermal infrared remote sensing for urban climate and environmental studies: Methods, applications, and trends","volume":"64","author":"Weng","year":"2009","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"613","DOI":"10.14358\/PERS.71.5.613","article-title":"Remote sensing of urban heat islands by day and night","volume":"71","author":"Nichol","year":"2005","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Liu, W., Li, L., Chen, L., Wen, M., Wang, J., Yuan, L., Liu, Y., and Li, H. (2020). Testing a comprehensive volcanic risk assessment of tenerife by volcanic hazard simulations and social vulnerability analysis. ISPRS Int. J. Geo-Inf., 9.","DOI":"10.3390\/ijgi9040273"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"102271","DOI":"10.1016\/j.scs.2020.102271","article-title":"Coupling coordination evaluation and sustainable development pattern of geo-ecological environment and urbanization in Chongqing municipality, China","volume":"61","author":"Yang","year":"2020","journal-title":"Sustain. Cities Soc."},{"key":"ref_54","first-page":"736","article-title":"Tasseled cap transformation for assessing hurricane landfall impact on a coastal watershed","volume":"73","author":"Mostafiz","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"126995","DOI":"10.1016\/j.jclepro.2021.126995","article-title":"Spatiotemporal change detection of ecological quality and the associated affecting factors in Dongting Lake Basin, based on RSEI","volume":"302","author":"Yuan","year":"2021","journal-title":"J. Clean. Prod."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"126838","DOI":"10.1016\/j.ufug.2020.126838","article-title":"Quantifying landscape-metrics impacts on urban green-spaces and water-bodies cooling effect: The study of Nanjing, China","volume":"55","author":"Sun","year":"2020","journal-title":"Urban For. Urban Green."},{"key":"ref_57","unstructured":"Jensen, J.R. (2013). Remote Sensing of the Environment. Remote Sensing of the Environment: Pearson New International Edition: An Earth Resource Perspective, Pearson Education Limited. [2nd ed.]."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Cui, Y., Li, L., Chen, L., Zhang, Y., Cheng, L., Zhou, X., and Yang, X. (2018). Land-use carbon emissions estimation for the Yangtze River Delta Urban Agglomeration using 1994-2016 Landsat image data. Remote Sens., 10.","DOI":"10.3390\/rs10091334"},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Li, H., Li, L., Chen, L., Zhou, X., Cui, Y., Liu, Y., and Liu, W. (2019). Mapping and characterizing spatiotemporal dynamics of impervious surfaces using landsat images: A case study of Xuzhou, East China from 1995 to 2018. Sustainability, 11.","DOI":"10.3390\/su11051224"},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Hu, S., Chen, L., Li, L., Zhang, T., Yuan, L., Cheng, L., Wang, J., and Wen, M. (2020). Simulation of land use change and ecosystem service value dynamics under ecological constraints in Anhui province, China. Int. J. Environ. Res. Public Health, 17.","DOI":"10.3390\/ijerph17124228"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"111476","DOI":"10.1016\/j.rse.2019.111476","article-title":"Decadal vegetation succession from MODIS reveals the spatio-temporal evolution of post-seismic landsliding after the 2008 Wenchuan earthquake","volume":"236","author":"Yunus","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.landurbplan.2014.10.010","article-title":"A comparative study of urban expansion in Beijing, Tianjin and Shijiazhuang over the past three decades","volume":"134","author":"Wu","year":"2015","journal-title":"Landsc. Urban Plan."},{"key":"ref_63","unstructured":"(2021, May 11). The Two-City Green Space Ecological Barrier Project Is Taking Shape, Available online: http:\/\/www.tj.gov.cn\/sy\/zwdt\/bmdt\/202007\/t20200730_3236789.html."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/10\/7\/475\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:28:53Z","timestamp":1760164133000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/10\/7\/475"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,10]]},"references-count":63,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2021,7]]}},"alternative-id":["ijgi10070475"],"URL":"https:\/\/doi.org\/10.3390\/ijgi10070475","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,10]]}}}