{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,7]],"date-time":"2026-06-07T04:52:25Z","timestamp":1780807945591,"version":"3.54.1"},"reference-count":60,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2024,1,7]],"date-time":"2024-01-07T00:00:00Z","timestamp":1704585600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key Research and Development Program of China","award":["2020YFA0714103"],"award-info":[{"award-number":["2020YFA0714103"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Accurately mapping urban built-up areas is critical for monitoring urbanization and development. Previous studies have shown that Night light (NTL) data is effective in characterizing the extent of human activity. But its inherently low spatial resolution and saturation effect limit its application in the construction of urban built-up extraction. In this study, we developed a new index called VNRT (Vegetation, Nighttime Light, Road, and Temperature) to address these challenges and improve the accuracy of built-up area extraction. The VNRT index is the first to fuse the Normalized Difference Vegetation Index (NDVI), NPP-VIIRS Nighttime NTL data, road density data, and land surface temperature (LST) through factor multiplication. To verify the good performance of VNRT in extracting built-up areas, the built-up area ranges of four national central cities in China (Chengdu, Wuhan, Xi\u2019an, and Zhengzhou) in 2019 are extracted by the local optimum thresholding method and compared with the actual validation points. The results show that the spatial distribution of VNRT is highly consistent with the actual built-up area. THE VNRT increases the variability between urban built-up areas and non-built-up areas, and can effectively distinguish some types of land cover that are easily ignored in previous urban indices, such as urban parks and water bodies. The VNRT index had the highest Accuracy (0.97), F1-score (0.94), Kappa coefficient (0.80), and overall accuracy (92%) compared to the two proposed urban indices. Therefore, the VNRT index could improve the identification of urban built-up areas and be an effective tool for long-term monitoring of regional-scale urbanization.<\/jats:p>","DOI":"10.3390\/ijgi13010021","type":"journal-article","created":{"date-parts":[[2024,1,8]],"date-time":"2024-01-08T05:21:38Z","timestamp":1704691298000},"page":"21","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A New Urban Built-Up Index and Its Application in National Central Cities of China"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-2100-7008","authenticated-orcid":false,"given":"Linfeng","family":"Wang","sequence":"first","affiliation":[{"name":"College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shengbo","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China"},{"name":"School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zibo","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yucheng","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,7]]},"reference":[{"key":"ref_1","unstructured":"UN-Habitat (2020). World Cities Report 2020, UN-Habitat. Available online: https:\/\/unhabitat.org\/sites\/default\/files\/2020\/10\/wcr_2020_report.pdf."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/10511482.2008.9521624","article-title":"The Impact of Urban Form on US Residential Energy Use","volume":"19","author":"Ewing","year":"2008","journal-title":"Hous. Policy Debate"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"570","DOI":"10.1126\/science.1111772","article-title":"Global Consequences of Land Use","volume":"309","author":"Foley","year":"2005","journal-title":"Science"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2092","DOI":"10.1111\/j.1365-2486.2006.01242.x","article-title":"Urban Ecosystems and the North American Carbon Cycle","volume":"12","author":"Pataki","year":"2006","journal-title":"Glob. Change Biol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"422","DOI":"10.2747\/0272-3638.13.5.422","article-title":"The Environmental Consequences of Urban-Growth\u2014Cross-National Perspectives on Economic-Development, Air-Pollution, and City Size","volume":"13","author":"Shukla","year":"1992","journal-title":"Urban Geogr."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Xia, N., Cheng, L., and Li, M. (2019). Mapping Urban Areas Using a Combination of Remote Sensing and Geolocation Data. Remote Sens., 11.","DOI":"10.3390\/rs11121470"},{"key":"ref_7","first-page":"432","article-title":"Comprehensive evaluation of the urban built-up areas mapping ability from Luojia 1-01 nighttime light imagery over China","volume":"52","author":"Hu","year":"2023","journal-title":"Acta Geod. Cart. Sin."},{"key":"ref_8","unstructured":"Yang, J. (2021). The Research on the Development Level Evaluation and Realization Path of Green Urbanization in China. [Ph.D. Thesis, Northwest University]."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Gamba, P., and Herold, M. (2009). Global Mapping of Human Settlement, CRC Press.","DOI":"10.1201\/9781420083408"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.rse.2012.04.018","article-title":"Quantitative Estimation of Urbanization Dynamics Using Time Series of DMSP\/OLS Nighttime Light Data: A Comparative Case Study from China\u2019s Cities","volume":"124","author":"Ma","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Liu, Y., Yang, Y., Jing, W., Yao, L., Yue, X., and Zhao, X. (2017). A New Urban Index for Expressing Inner-City Patterns Based on MODIS LST and EVI Regulated DMSP\/OLS NTL. Remote Sens., 9.","DOI":"10.3390\/rs9080777"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1080\/01431160304987","article-title":"Use of Normalized Difference Built-up Index in Automatically Mapping Urban Areas from TM Imagery","volume":"24","author":"Zha","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_13","first-page":"37","article-title":"An Effective Approach to Automatically Extract Urban Land-use from TM Imagery","volume":"7","author":"Zha","year":"2003","journal-title":"J. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1016\/j.rse.2005.11.016","article-title":"Remote Sensing Image-Based Analysis of the Relationship between Urban Heat Island and Land Use\/Cover Changes","volume":"104","author":"Chen","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_15","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_16","first-page":"928","article-title":"A novel method for identifying the boundary of urban built-up areas with POI data","volume":"71","author":"Xu","year":"2016","journal-title":"Acta Geogr. Sin."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"545","DOI":"10.14358\/PERS.69.5.545","article-title":"Building and Evaluating Models to Estimate Ambient Population Density","volume":"69","author":"Sutton","year":"2003","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1003","DOI":"10.1080\/01431160802430693","article-title":"Modelling the Population Density of China at the Pixel Level Based on DMSP\/OLS Non-Radiance-Calibrated Night-Time Light Images","volume":"30","author":"Zhuo","year":"2009","journal-title":"Int. J. Remote Sens."},{"key":"ref_19","first-page":"60","article-title":"Research and Application of Rapid Extraction Method of Urban Built\u2014Up Area by Using Night\u2014Time Light Data: Taking Sichuan Province as an Example","volume":"43","author":"Cao","year":"2020","journal-title":"Geomat. Spat. Inf. Technol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.isprsjprs.2021.01.002","article-title":"Characterizing Urban Land Changes of 30 Global Megacities Using Nighttime Light Time Series Stacks","volume":"173","author":"Zheng","year":"2021","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1016\/j.rse.2019.02.019","article-title":"A Simple Self-Adjusting Model for Correcting the Blooming Effects in DMSP-OLS Nighttime Light Images","volume":"224","author":"Cao","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"3057","DOI":"10.3390\/rs5063057","article-title":"Potential of NPP-VIIRS Nighttime Light Imagery for Modeling the Regional Economy of China","volume":"5","author":"Li","year":"2013","journal-title":"Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1080\/2150704X.2014.905728","article-title":"Evaluation of NPP-VIIRS Night-Time Light Composite Data for Extracting Built-up Urban Areas","volume":"5","author":"Shi","year":"2014","journal-title":"Remote Sens. Lett."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"3668","DOI":"10.1016\/j.rse.2008.05.009","article-title":"Regional Mapping of Human Settlements in Southeastern China with Multisensor Remotely Sensed Data","volume":"112","author":"Lu","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.rse.2012.10.022","article-title":"The Vegetation Adjusted NTL Urban Index: A New Approach to Reduce Saturation and Increase Variation in Nighttime Luminosity","volume":"129","author":"Zhang","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1038\/nature13462","article-title":"Strong Contributions of Local Background Climate to Urban Heat Islands","volume":"511","author":"Zhao","year":"2014","journal-title":"Nature"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.isprsjprs.2017.11.016","article-title":"A Temperature and Vegetation Adjusted NTL Urban Index for Urban Area Mapping and Analysis","volume":"135","author":"Zhang","year":"2018","journal-title":"ISPRS-J. Photogramm. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"094005","DOI":"10.1088\/1748-9326\/ab2740","article-title":"Enhanced Sensitivity of the Urban Heat Island Effect to Summer Temperatures Induced by Urban Expansion","volume":"14","author":"Gao","year":"2019","journal-title":"Environ. Res. Lett."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"696","DOI":"10.1021\/es2030438","article-title":"Surface Urban Heat Island across 419 Global Big Cities","volume":"46","author":"Peng","year":"2012","journal-title":"Environ. Sci. Technol."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Han, W., Tao, Z., Li, Z., Cheng, M., Fan, H., Cribb, M., and Wang, Q. (2023). Effect of Urban Built-Up Area Expansion on the Urban Heat Islands in Different Seasons in 34 Metropolitan Regions across China. Remote Sens., 15.","DOI":"10.3390\/rs15010248"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Li, F., Yan, Q., Bian, Z., Liu, B., and Wu, Z. (2020). A POI and LST Adjusted NTL Urban Index for Urban Built-Up Area Extraction. Sensors, 20.","DOI":"10.3390\/s20102918"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1422","DOI":"10.3390\/rs70201422","article-title":"Integrating Multiple Source Data to Enhance Variation and Weaken the Blooming Effect of DMSP-OLS Light","volume":"7","author":"Hao","year":"2015","journal-title":"Remote Sens."},{"key":"ref_33","first-page":"1","article-title":"Research on the Extraction Method of Urban Built-UP Areas with an Improved Night Light Index","volume":"19","author":"Chang","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"848","DOI":"10.1111\/tgis.12135","article-title":"Comparative Study of Approaches to Delineating Built-Up Areas Using Road Network Data","volume":"19","author":"Zhou","year":"2015","journal-title":"Trans. GIS"},{"key":"ref_35","unstructured":"Jia, T., and Jiang, B. (2010). Measuring Urban Sprawl Based on Massive Street Nodes and the Novel Concept of Natural Cities. arXiv."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1111\/1467-9671.00139","article-title":"Network Density and the Delimitation of Urban Areas","volume":"7","author":"Borruso","year":"2003","journal-title":"Trans. GIS"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Zhou, Q., and Guo, L. (2018). Empirical Approach to Threshold Determination for the Delineation of Built-up Areas with Road Network Data. PLoS ONE, 13.","DOI":"10.1371\/journal.pone.0194806"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1038\/srep00296","article-title":"Elementary Processes Governing the Evolution of Road Networks","volume":"2","author":"Strano","year":"2012","journal-title":"Sci. Rep."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"129488","DOI":"10.1016\/j.jclepro.2021.129488","article-title":"An Improved Approach for Monitoring Urban Built-up Areas by Combining NPP-VIIRS Nighttime Light, NDVI, NDWI, and NDBI","volume":"328","author":"Zheng","year":"2021","journal-title":"J. Clean. Prod."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1843","DOI":"10.1109\/TGRS.2019.2949797","article-title":"Building a Series of Consistent Night-Time Light Data (1992\u20132018) in Southeast Asia by Integrating DMSP-OLS and NPP-VIIRS","volume":"58","author":"Zhao","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Elvidge, C.D., Zhizhin, M., Ghosh, T., Hsu, F.-C., and Taneja, J. (2021). Annual Time Series of Global VIIRS Nighttime Lights Derived from Monthly Averages: 2012 to 2019. Remote Sens., 13.","DOI":"10.3390\/rs13050922"},{"key":"ref_42","unstructured":"Wang, Z., and Chen, S. (2022). Development of the Remote Sensing Datasets of the Annual Nighttime Light in China from 1992 to 2021. [Master\u2019s, Thesis, Jilin University]."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1886","DOI":"10.1016\/j.rse.2009.04.004","article-title":"Evaluation of Earth Observation Based Long Term Vegetation Trends\u2014Intercomparing NDVI Time Series Trend Analysis Consistency of Sahel from AVHRR GIMMS, Terra MODIS and SPOT VGT Data","volume":"113","author":"Fensholt","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"148334","DOI":"10.1016\/j.scitotenv.2021.148334","article-title":"Beyond Intensity of Urban Heat Island Effect: A Continental Scale Analysis on Land Surface Temperature in Major Chinese Cities","volume":"791","author":"Ren","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1139\/geomat-2021-0012","article-title":"Exploring Five Indicators for the Quality of OpenStreetMap Road Networks: A Case Study of Qu\u00e9bec, Canada","volume":"75","author":"Moradi","year":"2021","journal-title":"Geomatica"},{"key":"ref_46","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_47","doi-asserted-by":"crossref","unstructured":"Zheng, Y., Zhou, Q., He, Y., Wang, C., Wang, X., Wang, H., and Ghosh, T. (2021). An Optimized Approach for Extracting Urban Land Based on Log-Transformed DMSP-OLS Nighttime Light, NDVI, and NDWI. Remote Sens., 13.","DOI":"10.3390\/rs13040766"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"517","DOI":"10.5194\/essd-14-517-2022","article-title":"A Global Dataset of Annual Urban Extents (1992\u20132020) from Harmonized Nighttime Lights","volume":"14","author":"Zhao","year":"2022","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1080\/01431160304982","article-title":"Validation of Urban Boundaries Derived from Global Night-Time Satellite Imagery","volume":"24","author":"Henderson","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"6305","DOI":"10.1109\/TGRS.2017.2725917","article-title":"A New Approach for Detecting Urban Centers and Their Spatial Structure with Nighttime Light Remote Sensing","volume":"55","author":"Chen","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"8804","DOI":"10.1038\/s41598-023-36082-8","article-title":"Estimating Urban Spatial Structure Based on Remote Sensing Data","volume":"13","author":"Kii","year":"2023","journal-title":"Sci. Rep."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"17168","DOI":"10.3390\/rs71215863","article-title":"A Normalized Urban Areas Composite Index (NUACI) Based on Combination of DMSP-OLS and MODIS for Mapping Impervious Surface Area","volume":"7","author":"Liu","year":"2015","journal-title":"Remote Sens."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Li, F., Liu, X., Liao, S., and Jia, P. (2021). The Modified Normalized Urban Area Composite Index: A Satelliate-Derived High-Resolution Index for Extracting Urban Areas. Remote Sens., 13.","DOI":"10.3390\/rs13122350"},{"key":"ref_54","unstructured":"(2023). \u0622\u0630\u06cc\u0646 \u0646\u0648\u0631\u0648\u0632\u06cc; \u0627\u0644\u062f\u0648\u0632 \u0646\u0648\u0631\u0648\u0632\u06cc \u06a9\u0627\u0631\u0628\u0631\u062f \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u067e\u0646\u062c\u0631\u0629 \u0645\u062c\u0632\u0627 \u062f\u0631 \u0634\u0646\u0627\u0633\u0627\u06cc\u06cc \u062c\u0632\u0627\u06cc\u0631 \u062d\u0631\u0627\u0631\u062a\u06cc \u0634\u0647\u0631\u0633\u062a\u0627\u0646 \u06cc\u0632\u062f: Application of Split-Window Algorithm to Study Urban Heat Island in Yazd County. Water Soil Manag. Model. Mudil Saz\u012b Va Mud\u012briyyat-I \u0100b Va Kh\u0101k, 3, 115\u2013129."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"7466","DOI":"10.1109\/JSTARS.2021.3098787","article-title":"Boundary Extraction of Urban Built-Up Area Based on Luminance Value Correction of NTL Image","volume":"14","author":"Wang","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"4791","DOI":"10.1038\/s41598-017-04242-2","article-title":"The Role of City Size and Urban Form in the Surface Urban Heat Island","volume":"7","author":"Zhou","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"769","DOI":"10.1016\/0004-6981(73)90140-6","article-title":"City Size and the Urban Heat Island","volume":"7","author":"Oke","year":"1973","journal-title":"Atmos. Environ."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"103873","DOI":"10.1016\/j.landurbplan.2020.103873","article-title":"How to Effectively Mitigate Urban Heat Island Effect? A Perspective of Waterbody Patch Size Threshold","volume":"202","author":"Peng","year":"2020","journal-title":"Landsc. Urban Plan."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"129687","DOI":"10.1016\/j.jhydrol.2023.129687","article-title":"Revealing the Response of Urban Heat Island Effect to Water Body Evaporation from Main Urban and Suburb Areas","volume":"623","author":"Chen","year":"2023","journal-title":"J. Hydrol."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1007\/s40808-018-0456-7","article-title":"Modelling Urban Cooling Island Impact of Green Space and Water Bodies on Surface Urban Heat Island in a Continuously Developing Urban Area","volume":"4","author":"Ghosh","year":"2018","journal-title":"Model. Earth Syst. Environ."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/13\/1\/21\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T13:41:37Z","timestamp":1760103697000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/13\/1\/21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,7]]},"references-count":60,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,1]]}},"alternative-id":["ijgi13010021"],"URL":"https:\/\/doi.org\/10.3390\/ijgi13010021","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,7]]}}}