{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T15:45:24Z","timestamp":1776181524459,"version":"3.50.1"},"reference-count":134,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2024,11,30]],"date-time":"2024-11-30T00:00:00Z","timestamp":1732924800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research &amp; Development Program of China","award":["2022YFC3800700"],"award-info":[{"award-number":["2022YFC3800700"]}]},{"name":"National Key Research &amp; Development Program of China","award":["42071321"],"award-info":[{"award-number":["42071321"]}]},{"name":"National Natural Science Foundation of China","award":["2022YFC3800700"],"award-info":[{"award-number":["2022YFC3800700"]}]},{"name":"National Natural Science Foundation of China","award":["42071321"],"award-info":[{"award-number":["42071321"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Extreme heat events, or heatwaves, exert significant impacts on human society, ecosystems, and the economy. The continuous development of remote sensing technology has facilitated the acquisition of high-quality data for assessing health risks associated with these extreme heat events. This study systematically reviews the evaluation factors and assessment framework for a spatially explicit assessment of heat-related health risks. The contribution of geospatial big data, with a particular focus on satellite observations, to these assessments was investigated. The Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat surface temperature (LST) are identified as the two most widely utilized data sources for mapping heat hazards. The incorporation of multi-sensor observations, along with the implementation of spatiotemporal fusion and downscaling techniques, enhances both the spatial resolution and temporal frequency of heat hazard characterization. It is essential to consider issues of justice and equality in heat-resilient planning and mitigation practices. Integrating heatwave risk assessment results with analyses of urban morphology, land use functions and infrastructure can provide critical information for government agencies to strategically plan urban layout, functions, and public service facilities while optimizing and enhancing urban green infrastructures.<\/jats:p>","DOI":"10.3390\/rs16234500","type":"journal-article","created":{"date-parts":[[2024,12,3]],"date-time":"2024-12-03T04:04:04Z","timestamp":1733198644000},"page":"4500","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Spatially Explicit Assessments of Heat-Related Health Risks: A Literature Review"],"prefix":"10.3390","volume":"16","author":[{"given":"Yu","family":"Yao","sequence":"first","affiliation":[{"name":"School of Land Science and Technology, China University of Geoscience, Beijing 100083, China"},{"name":"International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China"},{"name":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1647-1950","authenticated-orcid":false,"given":"Linlin","family":"Lu","sequence":"additional","affiliation":[{"name":"International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China"},{"name":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}]},{"given":"Jiaqi","family":"Guo","sequence":"additional","affiliation":[{"name":"International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China"},{"name":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"College of Geological Engineering and Geomatics, Chang\u2019an University, Xi\u2019an 710054, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0357-5312","authenticated-orcid":false,"given":"Shuangcheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Geological Engineering and Geomatics, Chang\u2019an University, Xi\u2019an 710054, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7620-4507","authenticated-orcid":false,"given":"Jie","family":"Cheng","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Institute of Remote Sensing Science and Engineering, Beijing Normal University, Beijing 100875, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1196-1248","authenticated-orcid":false,"given":"Aqil","family":"Tariq","sequence":"additional","affiliation":[{"name":"Department of Wildlife, Fisheries and Aquaculture, College of Forest Resources, Mississippi State University, Starkville, MS 39762, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9147-7792","authenticated-orcid":false,"given":"Dong","family":"Liang","sequence":"additional","affiliation":[{"name":"International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China"},{"name":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}]},{"given":"Yonghong","family":"Hu","sequence":"additional","affiliation":[{"name":"International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China"},{"name":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6322-8307","authenticated-orcid":false,"given":"Qingting","family":"Li","sequence":"additional","affiliation":[{"name":"Airborne Remote Sensing Center, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1016\/j.healthplace.2018.08.017","article-title":"Heatwave and health impact research: A global review","volume":"53","author":"Campbell","year":"2018","journal-title":"Health Place"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1038\/nclimate3322","article-title":"Global risk of deadly heat","volume":"7","author":"Mora","year":"2017","journal-title":"Nat. Clim. Change"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Li, Y., Akkus, C., Yu, X., Joyner, A., Kmet, J., Sweat, D., and Jia, C. (2019). Heatwave Events and Mortality Outcomes in Memphis, Tennessee: Testing Effect Modification by Socioeconomic Status and Urbanicity. Int. J. Environ. Res. Public Health, 16.","DOI":"10.3390\/ijerph16224568"},{"key":"ref_4","first-page":"185","article-title":"The potential impacts of climate variability and change on temperature-related morbidity and mortality in the United States","volume":"109","author":"McGeehin","year":"2001","journal-title":"Environ. Health Perspect."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Chen, K., Boomsma, J., and Holmes, H.A. (2023). A multiscale analysis of heatwaves and urban heat islands in the western US during the summer of 2021. Sci. Rep., 13.","DOI":"10.1038\/s41598-023-35621-7"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3145","DOI":"10.1080\/17538947.2023.2243901","article-title":"Street network patterns for mitigating urban heat islands in arid climates","volume":"16","author":"Chenary","year":"2023","journal-title":"Int. J. Digit. Earth"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1581","DOI":"10.1038\/s41467-020-15218-8","article-title":"Heat health risk assessment in Philippine cities using remotely sensed data and social-ecological indicators","volume":"11","author":"Estoque","year":"2020","journal-title":"Nat. Commun."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Intergovernmental Panel on Climate Change (IPCC) (2023). Climate Change 2021\u2014The Physical Science Basis: Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press.","DOI":"10.1017\/9781009157896"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"759","DOI":"10.1136\/jech-2012-201045","article-title":"IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX)","volume":"66","author":"Murray","year":"2012","journal-title":"J. Epidemiol. Community Health"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1889","DOI":"10.5194\/nhess-20-1889-2020","article-title":"Spatiotemporal changes of heat waves and extreme temperatures in the main cities of China from 1955 to 2014","volume":"20","author":"Li","year":"2020","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1080\/10106049.2012.715209","article-title":"Environmental public health applications using remotely sensed data","volume":"29","author":"Crosson","year":"2014","journal-title":"Geocarto Int."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1002\/gdj3.155","article-title":"Global near real-time daily apparent temperature and heat wave dataset","volume":"10","author":"Yin","year":"2023","journal-title":"Geosci. Data J."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1519","DOI":"10.1175\/1520-0477(1996)077<1519:TPHWHW>2.0.CO;2","article-title":"The Philadelphia hot weather-health watch warning system: Development and application, summer 1995","volume":"77","author":"Kalkstein","year":"1996","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1007\/s004840050119","article-title":"Applications of a universal thermal index: Physiological equivalent temperature","volume":"43","author":"Matzarakis","year":"1999","journal-title":"Int. J. Biometeorol."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Chen, Y., and Li, Y. (2017). An Inter-comparison of Three Heat Wave Types in China during 1961\u20132010: Observed Basic Features and Linear Trends. Sci. Rep., 7.","DOI":"10.1038\/srep45619"},{"key":"ref_16","unstructured":"Amarillo, T.X. (2023, December 09). What Is the Heat Index?, Available online: https:\/\/www.weather.gov\/ama\/heatindex."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"180206","DOI":"10.1038\/sdata.2018.206","article-title":"Data Descriptor: GHWR, a multi-method global heatwave and warm-spell record and toolbox","volume":"5","author":"Raei","year":"2018","journal-title":"Sci. Data"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"105255","DOI":"10.1016\/j.envsoft.2021.105255","article-title":"Heat wave tracker: A multi-method, multi-source heat wave measurement toolkit based on Google Earth Engine","volume":"147","author":"Zhang","year":"2022","journal-title":"Environ. Model. Softw."},{"key":"ref_19","first-page":"103604","article-title":"Spatial characterization of global heat waves using satellite-based land surface temperature","volume":"125","author":"Hu","year":"2023","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1038\/s41597-024-03074-w","article-title":"High resolution climate change observations and projections for the evaluation of heat-related extremes","volume":"11","author":"Williams","year":"2024","journal-title":"Sci. Data"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Yin, C., Yang, F., Wang, J., and Ye, Y. (2020). Spatiotemporal Distribution and Risk Assessment of Heat Waves Based on Apparent Temperature in the One Belt and One Road Region. Remote Sens., 12.","DOI":"10.3390\/rs12071174"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"987","DOI":"10.1007\/s13753-022-00449-8","article-title":"Heat Health Risk and Adaptability Assessments at the Subdistrict Scale in Metropolitan Beijing","volume":"13","author":"Su","year":"2022","journal-title":"Int. J. Disaster Risk Sci."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Feron, S., Cordero, R.R., Damiani, A., Llanillo, P.J., Jorquera, J., Sepulveda, E., Asencio, V., Laroze, D., Labbe, F., and Carrasco, J. (2019). Observations and Projections of Heat Waves in South America. Sci. Rep., 9.","DOI":"10.1038\/s41598-019-44614-4"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"064073","DOI":"10.1088\/1748-9326\/ac046e","article-title":"Increasing heat risk in China\u2019s urban agglomerations","volume":"16","author":"Zhang","year":"2021","journal-title":"Environ. Res. Lett."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1007\/s10584-015-1372-8","article-title":"New climate and socio-economic scenarios for assessing global human health challenges due to heat risk","volume":"130","author":"Dong","year":"2015","journal-title":"Clim. Change"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"146455","DOI":"10.1016\/j.scitotenv.2021.146455","article-title":"Differing spatial patterns of the urban heat exposure of elderly populations in two megacities identifies alternate adaptation strategies","volume":"781","author":"Park","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"929","DOI":"10.1016\/j.scitotenv.2015.12.021","article-title":"A comparison of urban heat islands mapped using skin temperature, air temperature, and apparent temperature (Humidex), for the greater Vancouver area","volume":"544","author":"Ho","year":"2016","journal-title":"Sci. Total Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"103831","DOI":"10.1016\/j.scs.2022.103831","article-title":"Diurnal heat exposure risk mapping and related governance zoning: A case study of Beijing, China","volume":"81","author":"Chen","year":"2022","journal-title":"Sustain. Cities Soc."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"045206","DOI":"10.1088\/1748-9326\/6\/4\/045206","article-title":"Estimation of surface air temperature over central and eastern Eurasia from MODIS land surface temperature","volume":"6","author":"Shen","year":"2011","journal-title":"Environ. Res. Lett."},{"key":"ref_30","first-page":"G03025","article-title":"A global comparison between station air temperatures and MODIS land surface temperatures reveals the cooling role of forests","volume":"116","author":"Mildrexler","year":"2011","journal-title":"J. Geophys. Res."},{"key":"ref_31","first-page":"9185","article-title":"A spatiotemporal analysis of the relationship between near-surface air temperature and satellite land surface temperatures using 17 years of data from the ATSR series","volume":"122","author":"Good","year":"2017","journal-title":"Atmospheres"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1002\/joc.2222","article-title":"Satellite monitoring of summer heat waves in the Paris metropolitan area","volume":"31","author":"Dousset","year":"2011","journal-title":"Int. J. Climatol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1007\/s00484-009-0256-x","article-title":"The urban heat island and its impact on heat waves and human health in Shanghai","volume":"54","author":"Tan","year":"2010","journal-title":"Int. J. Biometeorol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1186\/1476-072X-10-42","article-title":"Including the urban heat island in spatial heat health risk assessment strategies: A case study for Birmingham, UK","volume":"10","author":"Tomlinson","year":"2011","journal-title":"Int. J. Health Geogr."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1080\/17538947.2020.1813210","article-title":"Impact of spatiotemporal land-use and land-cover changes on surface urban heat islands in a semiarid region using Landsat data","volume":"14","author":"Maskooni","year":"2021","journal-title":"Int. J. Digit. Earth"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"S89","DOI":"10.1007\/s11069-016-2291-3","article-title":"A common methodology for risk assessment and mapping for south-east Europe: An application for heat wave risk in Romania","volume":"82","author":"Promper","year":"2016","journal-title":"Nat. Hazards"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1186\/s12942-018-0135-y","article-title":"Spatially explicit assessment of heat health risk by using multi-sensor remote sensing images and socioeconomic data in Yangtze River Delta, China","volume":"17","author":"Chen","year":"2018","journal-title":"Int. J. Health Geogr."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"852","DOI":"10.1016\/j.scitotenv.2019.01.240","article-title":"Mapping heat-related health risks of elderly citizens in mountainous area: A case study of Chongqing, China","volume":"663","author":"Zhang","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"137226","DOI":"10.1016\/j.scitotenv.2020.137226","article-title":"Fine-scale mapping of an evidence-based heat health risk index for high-density cities: Hong Kong as a case study","volume":"718","author":"Song","year":"2020","journal-title":"Sci. Total Environ."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"105236","DOI":"10.1016\/j.scs.2024.105236","article-title":"Modes of summertime thermal urban stress over major cities in the Middle East: A comprehensive assessment of heat exposure risks","volume":"102","author":"Aboelkhair","year":"2024","journal-title":"Sustain. Cities Soc."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1186\/1476-072X-11-38","article-title":"Mapping heatwave health risk at the community level for public health action","volume":"11","author":"Buscail","year":"2012","journal-title":"Int. J. Health Geogr."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1080\/10106049.2013.799718","article-title":"Spatiotemporal variations in heat-related health risk in three Midwestern US cities between 1990 and 2010","volume":"29","author":"Johnson","year":"2014","journal-title":"Geocarto Int."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"709","DOI":"10.1007\/s00484-017-1319-z","article-title":"A heat vulnerability index to improve urban public health management in San Juan, Puerto Rico","volume":"62","author":"Otis","year":"2018","journal-title":"Int. J. Biometeorol."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1007\/s10584-019-02459-w","article-title":"Heat stress vulnerability and risk at the (super) local scale in six Brazilian capitals","volume":"154","author":"Lapola","year":"2019","journal-title":"Clim. Change"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"104831","DOI":"10.1016\/j.landurbplan.2023.104831","article-title":"Mapping urban heat islands and heat-related risk during heat waves from a climate justice perspective: A case study in the municipality of Padua (Italy) for inclusive adaptation policies","volume":"238","author":"Pappalardo","year":"2023","journal-title":"Landsc. Urban Plan."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Orusa, T., Viani, A., Moyo, B., Cammareri, D., and Borgogno-Mondino, E. (2023). Risk Assessment of Rising Temperatures Using Landsat 4-9 LST Time Series and Meta\u00ae Population Dataset: An Application in Aosta Valley, NW Italy. Remote Sens., 15.","DOI":"10.3390\/rs15092348"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Guo, J., Ren, H., Zheng, Y., Lu, S., and Dong, J. (2020). Evaluation of Land Surface Temperature Retrieval from Landsat 8\/TIRS Images before and after Stray Light Correction Using the SURFRAD Dataset. Remote Sens., 12.","DOI":"10.3390\/rs12061023"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1016\/j.isprsjprs.2021.02.005","article-title":"Evaluation of Landsat-8 TIRS data recalibrations and land surface temperature split-window algorithms over a homogeneous crop area with different phenological land covers","volume":"174","author":"Niclos","year":"2021","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.rse.2016.03.043","article-title":"A first satellite-based observational assessment of urban thermal anisotropy","volume":"181","author":"Hu","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1809","DOI":"10.1016\/j.scib.2023.06.032","article-title":"Global mapping of urban thermal anisotropy reveals substantial potential biases for remotely sensed urban climates","volume":"68","author":"Du","year":"2023","journal-title":"Sci. Bull."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"112682","DOI":"10.1016\/j.rse.2021.112682","article-title":"On the land emissivity assumption and Landsat-derived surface urban heat islands: A global analysis","volume":"265","author":"Chakraborty","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_52","first-page":"861","article-title":"Trading greens for heated surfaces: Land surface temperature and perceived health risk in Greater Accra Metropolitan Area, Ghana","volume":"26","author":"Gyimah","year":"2023","journal-title":"Egypt. J. Remote Sens. Space Sci."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Dai, X., Liu, Q., Huang, C., and Li, H. (2021). Spatiotemporal Variation Analysis of the Fine-Scale Heat Wave Risk along the Jakarta-Bandung High-Speed Railway in Indonesia. Int. J. Environ. Res. Public Health, 18.","DOI":"10.3390\/ijerph182212153"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1605","DOI":"10.1109\/LGRS.2015.2414897","article-title":"Downscaling GOES Land Surface Temperature for Assessing Heat Wave Health Risks","volume":"12","author":"Jiang","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/j.uclim.2018.08.005","article-title":"A conceptual framework for environmental risk and social vulnerability assessment in complex urban settings","volume":"26","author":"Karimi","year":"2018","journal-title":"Urban Clim."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"104701","DOI":"10.1016\/j.landurbplan.2023.104701","article-title":"Observed inequality in thermal comfort exposure and its multifaceted associations with greenspace in United States cities","volume":"233","author":"Wu","year":"2023","journal-title":"Landsc. Urban Plan."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"111847","DOI":"10.1016\/j.ecolind.2024.111847","article-title":"Understanding fine-scale heat health risks and the role of green infrastructure based on remote sensing and socioeconomic data in the megacity of Beijing, China","volume":"160","author":"Zha","year":"2024","journal-title":"Ecol. Indic."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Morabito, M., Crisci, A., Gioli, B., Gualtieri, G., Toscano, P., Di Stefano, V., Orlandini, S., and Gensini, G.F. (2015). Urban-Hazard Risk Analysis: Mapping of Heat-Related Risks in the Elderly in Major Italian Cities. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0127277"},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Zheng, M., Zhang, J., Shi, L., Zhang, D., Pangali Sharma, T.P., and Prodhan, F.A. (2020). Mapping Heat-Related Risks in Northern Jiangxi Province of China Based on Two Spatial Assessment Frameworks Approaches. Int. J. Environ. Res. Public Health, 17.","DOI":"10.3390\/ijerph17186584"},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Chen, D., Xu, X., Sun, Z., Liu, L., Qiao, Z., and Huang, T. (2020). Assessment of Urban Heat Risk in Mountain Environments: A Case Study of Chongqing Metropolitan Area, China. Sustainability, 12.","DOI":"10.3390\/su12010309"},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Wu, X., Liu, Q., Huang, C., and Li, H. (2022). Mapping Heat-Health Vulnerability Based on Remote Sensing: A Case Study in Karachi. Remote Sens., 14.","DOI":"10.3390\/rs14071590"},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Hulley, G., Shivers, S., Wetherley, E., and Cudd, R. (2019). New ECOSTRESS and MODIS Land Surface Temperature Data Reveal Fine-Scale Heat Vulnerability in Cities: A Case Study for Los Angeles County, California. Remote Sens., 11.","DOI":"10.3390\/rs11182136"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"105300","DOI":"10.1016\/j.scs.2024.105300","article-title":"Spatially explicit assessment of the heat-related health risk in the Yangtze River Delta, China, using multisource remote sensing and socioeconomic data","volume":"104","author":"Wu","year":"2024","journal-title":"Sustain. Cities Soc."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"104402","DOI":"10.1016\/j.scs.2023.104402","article-title":"Investigating urban heat-related health risks based on local climate zones: A case study of Changzhou in China","volume":"91","author":"Ma","year":"2023","journal-title":"Sustain. Cities Soc."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Guo, X., Huang, G., Jia, P., and Wu, J. (2019). Estimating Fine-Scale Heat Vulnerability in Beijing Through Two Approaches: Spatial Patterns, Similarities, and Divergence. Remote Sens., 11.","DOI":"10.3390\/rs11202358"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"105740","DOI":"10.1016\/j.scs.2024.105740","article-title":"Spatial distribution of old neighborhoods based on heat-related health risks assessment: A case study of Changsha City, China","volume":"114","author":"Xie","year":"2024","journal-title":"Sustain. Cities Soc."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"104643","DOI":"10.1016\/j.landurbplan.2022.104643","article-title":"How urban ecological land affects resident heat exposure: Evidence from the mega-urban agglomeration in China","volume":"231","author":"Feng","year":"2023","journal-title":"Landsc. Urban Plan."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"109728","DOI":"10.1016\/j.isci.2024.109728","article-title":"Shared insights for heat health risk adaptation in metropolitan areas of developing countries","volume":"27","author":"Yu","year":"2024","journal-title":"iScience"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"2721","DOI":"10.1038\/s41467-021-22799-5","article-title":"Disproportionate exposure to urban heat island intensity across major US cities","volume":"12","author":"Hsu","year":"2021","journal-title":"Nat. Commun."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1038\/s41612-024-00708-z","article-title":"Urbanization-induced warming amplifies population exposure to compound heatwaves but narrows exposure inequality between global North and South cities","volume":"7","author":"Gao","year":"2024","journal-title":"npj Clim. Atmos. Sci."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"4294","DOI":"10.1016\/j.rinp.2017.10.056","article-title":"Urban heat wave hazard and risk assessment","volume":"7","author":"Jedlovec","year":"2017","journal-title":"Results Phys."},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Nath, B., Ni-Meister, W., and \u00d6zdogan, M. (2021). Fine-Scale Urban Heat Patterns in New York City Measured by ASTER Satellite-The Role of Complex Spatial Structures. Remote Sens., 13.","DOI":"10.20944\/preprints202108.0399.v1"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"101748","DOI":"10.1016\/j.uclim.2023.101748","article-title":"Key areas and measures to mitigate heat exposure risk in highly urbanized city: A case study of Beijing, China","volume":"53","author":"Jiang","year":"2024","journal-title":"Urban Clim."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Zhang, X., Ye, R., and Fu, X. (2023). Assessment of Urban Local High-Temperature Disaster Risk and the Spatially Heterogeneous Impacts of Blue-Green Space. Atmosphere, 14.","DOI":"10.3390\/atmos14111652"},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Abrar, R., Sarkar, S.K., Nishtha, K.T., Talukdar, S., Rahman, A., Islam, A.R.M.T., and Mosavi, A. (2022). Assessing the Spatial Mapping of Heat Vulnerability under Urban Heat Island (UHI) Effect in the Dhaka Metropolitan Area. Sustainability, 14.","DOI":"10.3390\/su14094945"},{"key":"ref_76","doi-asserted-by":"crossref","unstructured":"Su, R., Yang, C., Xu, Z., Luo, T., and Yang, L. (2024). Assessment of Fine-Scale Urban Heat Health Risk and Its Potential Driving Factors Based on Local Climate Zones in Shenzhen, China. ISPRS Int. J. Geo-Inf., 13.","DOI":"10.3390\/ijgi13100367"},{"key":"ref_77","doi-asserted-by":"crossref","unstructured":"Shan, Z., An, Y., Xu, L.e., and Yuan, M. (2022). High-Temperature Disaster Risk Assessment for Urban Communities: A Case Study in Wuhan, China. Int. J. Environ. Res. Public Health, 19.","DOI":"10.3390\/ijerph19010183"},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"101169","DOI":"10.1016\/j.uclim.2022.101169","article-title":"Mapping urban socio-economic vulnerability related to heat risk: A grid-based assessment framework by combing the geospatial big data","volume":"43","author":"Sun","year":"2022","journal-title":"Urban Clim."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"573","DOI":"10.1016\/j.envint.2019.01.057","article-title":"Exploring the mechanisms of heat wave vulnerability at the urban scale based on the application of big data and artificial societies","volume":"127","author":"He","year":"2019","journal-title":"Environ. Int."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1080\/14498596.2017.1290558","article-title":"Determining extreme heat vulnerability of Harare Metropolitan City using multispectral remote sensing and socio-economic data","volume":"63","author":"Mushore","year":"2018","journal-title":"J. Spat. Sci."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"105875","DOI":"10.1016\/j.scs.2024.105875","article-title":"Assessing heat vulnerability and multidimensional inequity: Lessons from indexing the performance of Australian capital cities","volume":"115","author":"Li","year":"2024","journal-title":"Sustain. Cities Soc."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"102067","DOI":"10.1016\/j.uclim.2024.102067","article-title":"Framework of street grid-based urban heat vulnerability assessment: Integrating entropy weight method and BPNN model","volume":"56","author":"Guo","year":"2024","journal-title":"Urban Clim."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"103291","DOI":"10.1016\/j.apgeog.2024.103291","article-title":"Resisting the heat wave: Revealing inequalities in matching between heat exposure risk and healthcare services in a megacity","volume":"167","author":"Cheng","year":"2024","journal-title":"Applied Geogr."},{"key":"ref_84","doi-asserted-by":"crossref","unstructured":"Zhang, J., Zhang, H., and Qi, R. (2024). A study of size threshold for cooling effect in urban parks and their cooling accessibility and equity. Sci. Rep., 14.","DOI":"10.1038\/s41598-024-67277-2"},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"103174","DOI":"10.1016\/j.scs.2021.103174","article-title":"Mapping local climate zones and their associated heat risk issues in Beijing: Based on open data","volume":"74","author":"Zhou","year":"2021","journal-title":"Sustain. Cities Soc."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"103792","DOI":"10.1016\/j.scs.2022.103792","article-title":"Heat vulnerability caused by physical and social conditions in a mountainous megacity of Chongqing, China","volume":"80","author":"Xiang","year":"2022","journal-title":"Sustain. Cities Soc."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"109400","DOI":"10.1016\/j.buildenv.2022.109400","article-title":"Diurnal dynamics of heat exposure in Xi\u2019an: A perspective from local climate zone","volume":"222","author":"Yuan","year":"2022","journal-title":"Build. Environ."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"108123","DOI":"10.1016\/j.isci.2023.108123","article-title":"Diurnal urban heat risk assessment and real-time population data in Seoul","volume":"26","author":"Yoo","year":"2023","journal-title":"iScience"},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.apgeog.2012.04.006","article-title":"Developing an applied extreme heat vulnerability index utilizing socioeconomic and environmental data","volume":"35","author":"Johnson","year":"2012","journal-title":"Appl. Geogr."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"1730","DOI":"10.1289\/ehp.0900683","article-title":"Mapping Community Determinants of Heat Vulnerability","volume":"117","author":"Reid","year":"2009","journal-title":"Environ. Health Perspect."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1186\/s12940-015-0081-0","article-title":"County-level heat vulnerability of urban and rural residents in Tibet, China","volume":"15","author":"Bai","year":"2016","journal-title":"Environ. Health"},{"key":"ref_92","first-page":"1041","article-title":"Incorporating social vulnerability to assess population health risk due to heat stress in China","volume":"70","author":"Xie","year":"2015","journal-title":"Acta Geogr. Sin."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"102507","DOI":"10.1016\/j.scs.2020.102507","article-title":"Spatiotemporal assessment of extreme heat risk for high-density cities: A case study of Hong Kong from 2006 to 2016","volume":"64","author":"Hua","year":"2021","journal-title":"Sustain. Cities Soc."},{"key":"ref_94","doi-asserted-by":"crossref","unstructured":"Rathi, S.K., Chakraborty, S., Mishra, S.K., Dutta, A., and Nanda, L. (2022). A Heat Vulnerability Index: Spatial Patterns of Exposure, Sensitivity and Adaptive Capacity for Urbanites of Four Cities of India. Int. J. Environ. Res. Public Health, 19.","DOI":"10.3390\/ijerph19010283"},{"key":"ref_95","doi-asserted-by":"crossref","unstructured":"Li, F., Yigitcanlar, T., Nepal, M., Thanh, K., and Dur, F. (2022). Understanding Urban Heat Vulnerability Assessment Methods: A PRISMA Review. Energies, 15.","DOI":"10.3390\/en15196998"},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"1355","DOI":"10.1007\/s00484-020-01916-x","article-title":"An energy budget model for estimating the thermal comfort of children","volume":"64","author":"Cheng","year":"2020","journal-title":"Int. J. Biometeorol."},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1016\/j.amepre.2008.08.021","article-title":"Climate Change and Extreme Heat Events","volume":"35","author":"Luber","year":"2008","journal-title":"Am. J. Prev. Med."},{"key":"ref_98","first-page":"519","article-title":"Local Extreme Heat Planning: An Interactive Tool to Examine a Heat Vulnerability Index for Philadelphia, Pennsylvania","volume":"97","author":"Hammer","year":"2020","journal-title":"J. Urban Health-Bull. N. Y. Acad. Med."},{"key":"ref_99","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.apgeog.2018.04.015","article-title":"Spatiotemporal analysis of regional socio-economic vulnerability change associated with heat risks in Canada","volume":"95","author":"Ho","year":"2018","journal-title":"Appl. Geogr."},{"key":"ref_100","doi-asserted-by":"crossref","unstructured":"Alonso, L., and Renard, F. (2020). A Comparative Study of the Physiological and Socio-Economic Vulnerabilities to Heat Waves of the Population of the Metropolis of Lyon (France) in a Climate Change Context. Int. J. Environ. Res. Public Health, 17.","DOI":"10.3390\/ijerph17031004"},{"key":"ref_101","doi-asserted-by":"crossref","first-page":"1948","DOI":"10.1007\/s42452-020-03750-7","article-title":"Health effects of heat vulnerability in Rio de Janeiro: A validation model for policy applications","volume":"2","author":"Prosdocimi","year":"2020","journal-title":"SN Appl. Sci."},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"149417","DOI":"10.1016\/j.scitotenv.2021.149417","article-title":"Approaches for identifying heat-vulnerable populations and locations: A systematic review","volume":"799","author":"Cheng","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_103","doi-asserted-by":"crossref","first-page":"606","DOI":"10.1289\/ehp.1307868","article-title":"Predicting Hospitalization for Heat-Related Illness at the Census-Tract Level: Accuracy of a Generic Heat Vulnerability Index in Phoenix, Arizona (USA)","volume":"123","author":"Chuang","year":"2015","journal-title":"Environ. Health Perspect."},{"key":"ref_104","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1111\/disa.12177","article-title":"Assessing climate change and health vulnerability at the local level: Travis County, Texas","volume":"40","author":"Prudent","year":"2016","journal-title":"Disasters"},{"key":"ref_105","doi-asserted-by":"crossref","unstructured":"Lu, L., Weng, Q., Xiao, D., Guo, H., Li, Q., and Hui, W. (2020). Spatiotemporal Variation of Surface Urban Heat Islands in Relation to Land Cover Composition and Configuration: A Multi-Scale Case Study of Xi\u2019an, China. Remote Sens., 12.","DOI":"10.3390\/rs12172713"},{"key":"ref_106","doi-asserted-by":"crossref","first-page":"2358867","DOI":"10.1080\/17538947.2024.2358867","article-title":"Measuring the cooling effects of green cover on urban heat island effects using Landsat satellite imagery","volume":"17","author":"Na","year":"2024","journal-title":"Int. J. Digit. Earth"},{"key":"ref_107","first-page":"165","article-title":"Health related urban heat wave vulnerability assessment: Research progress and framework","volume":"34","author":"Xie","year":"2015","journal-title":"Prog. Geogr."},{"key":"ref_108","doi-asserted-by":"crossref","unstructured":"Azhar, G., Saha, S., Ganguly, P., Mavalankar, D., and Madrigano, J. (2017). Heat Wave Vulnerability Mapping for India. Int. J. Environ. Res. Public Health, 14.","DOI":"10.3390\/ijerph14040357"},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1289\/ehp.1104625","article-title":"Neighborhood Effects on Heat Deaths: Social and Environmental Predictors of Vulnerability in Maricopa County, Arizona","volume":"121","author":"Harlan","year":"2013","journal-title":"Environ. Health Perspect."},{"key":"ref_110","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/j.envint.2013.03.005","article-title":"Identification of heat risk patterns in the U.S. National Capital Region by integrating heat stress and related vulnerability","volume":"56","author":"Aubrecht","year":"2013","journal-title":"Environ. Int."},{"key":"ref_111","doi-asserted-by":"crossref","first-page":"448","DOI":"10.1016\/j.apgeog.2008.10.005","article-title":"Vulnerability to environmental hazards in the Ciudad Juarez (Mexico)-El Paso (USA) metropolis: A model for spatial risk assessment in transnational context","volume":"29","author":"Collins","year":"2009","journal-title":"Appl. Geogr."},{"key":"ref_112","doi-asserted-by":"crossref","first-page":"7626","DOI":"10.1021\/es901041p","article-title":"An Index for Assessing Demographic Inequalities in Cumulative Environmental Hazards with Application to Los Angeles, California","volume":"43","author":"Su","year":"2009","journal-title":"Environ. Sci. Technol."},{"key":"ref_113","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1080\/00330124.2011.600225","article-title":"Vulnerability to Extreme Heat in Metropolitan Phoenix: Spatial, Temporal, and Demographic Dimensions","volume":"64","author":"Chow","year":"2012","journal-title":"Prof. Geogr."},{"key":"ref_114","doi-asserted-by":"crossref","first-page":"25051","DOI":"10.3402\/gha.v7.25051","article-title":"The spatial distribution of health vulnerability to heat waves in Guangdong Province, China","volume":"7","author":"Zhu","year":"2014","journal-title":"Glob. Health Action"},{"key":"ref_115","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1016\/j.apgeog.2014.04.004","article-title":"A framework for the development of the SERV model: A Spatially Explicit Resilience-Vulnerability model","volume":"51","author":"Frazier","year":"2014","journal-title":"Appl. Geogr."},{"key":"ref_116","doi-asserted-by":"crossref","first-page":"678","DOI":"10.1016\/j.scitotenv.2017.08.062","article-title":"Assessing urban population vulnerability and environmental risks across an urban area during heatwaves\u2014Implications for health protection","volume":"610","author":"Macintyre","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_117","doi-asserted-by":"crossref","first-page":"1498","DOI":"10.1021\/acs.est.6b04355","article-title":"Spatially Explicit Mapping of Heat Health Risk Utilizing Environmental and Socioeconomic Data","volume":"51","author":"Hu","year":"2017","journal-title":"Environ. Sci. Technol."},{"key":"ref_118","doi-asserted-by":"crossref","first-page":"120529","DOI":"10.1016\/j.jclepro.2020.120529","article-title":"Spatiotemporal patterns of summer urban heat island in Beijing, China using an improved land surface temperature","volume":"257","author":"Liu","year":"2020","journal-title":"J. Clean. Prod."},{"key":"ref_119","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/j.puhe.2017.09.006","article-title":"Development of a heat vulnerability index for New York State","volume":"161","author":"Nayak","year":"2018","journal-title":"Public Health"},{"key":"ref_120","doi-asserted-by":"crossref","first-page":"715","DOI":"10.1289\/ehp.1103766","article-title":"Evaluation of a Heat Vulnerability Index on Abnormally Hot Days: An Environmental Public Health Tracking Study","volume":"120","author":"Reid","year":"2012","journal-title":"Environ. Health Perspect."},{"key":"ref_121","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1175\/WCAS-D-13-00014.1","article-title":"Performance Assessment of a Heat Wave Vulnerability Index for Greater London, United Kingdom","volume":"6","author":"Wolf","year":"2014","journal-title":"Weather. Clim. Soc."},{"key":"ref_122","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1175\/WCAS-D-13-00037.1","article-title":"Assessing the Performance of a Vulnerability Index during Oppressive Heat across Georgia, United States","volume":"6","author":"Maier","year":"2014","journal-title":"Weather. Clim. Soc."},{"key":"ref_123","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s00484-018-1631-2","article-title":"Quantification and evaluation of intra-urban heat-stress variability in Seoul, Korea","volume":"63","author":"Janicke","year":"2019","journal-title":"Int. J. Biometeorol."},{"key":"ref_124","doi-asserted-by":"crossref","first-page":"106742","DOI":"10.1016\/j.envint.2021.106742","article-title":"The relationship between population heat vulnerability and urbanization levels: A county-level modeling study across China","volume":"156","author":"Wang","year":"2021","journal-title":"Environ. Int."},{"key":"ref_125","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1108\/IJES-10-2012-0044","article-title":"Can a spatial index of heat-related vulnerability predict emergency service demand in Australian capital cities?","volume":"3","author":"Tapper","year":"2014","journal-title":"Int. J. Emerg. Serv."},{"key":"ref_126","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1007\/s10584-023-03592-3","article-title":"What is a heat(wave)? An interdisciplinary perspective","volume":"176","author":"Boni","year":"2023","journal-title":"Clim. Change"},{"key":"ref_127","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.scib.2022.12.014","article-title":"SDGSAT-1: The world\u2019s first scientific satellite for sustainable development goals","volume":"68","author":"Guo","year":"2023","journal-title":"Sci. Bull."},{"key":"ref_128","doi-asserted-by":"crossref","first-page":"e2022AV000729","DOI":"10.1029\/2022AV000729","article-title":"Lower Urban Humidity Moderates Outdoor Heat Stress","volume":"3","author":"Chakraborty","year":"2022","journal-title":"AGU Adv."},{"key":"ref_129","doi-asserted-by":"crossref","first-page":"eaay3452","DOI":"10.1126\/sciadv.aay3452","article-title":"Population dynamics modify urban residents\u2019 exposure to extreme temperatures across the United States","volume":"5","author":"Yang","year":"2019","journal-title":"Sci. Adv."},{"key":"ref_130","doi-asserted-by":"crossref","first-page":"101522","DOI":"10.1016\/j.uclim.2023.101522","article-title":"Quantifying urban heat exposure at fine scale-modeling outdoor and indoor temperatures using citizen science and VHR remote sensing","volume":"49","author":"Leichtle","year":"2023","journal-title":"Urban Clim."},{"key":"ref_131","doi-asserted-by":"crossref","first-page":"e2021EF002488","DOI":"10.1029\/2021EF002488","article-title":"Increasing Heat-Stress Inequality in a Warming Climate","volume":"10","author":"Alizadeh","year":"2022","journal-title":"Earths Future"},{"key":"ref_132","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_133","doi-asserted-by":"crossref","first-page":"111791","DOI":"10.1016\/j.rse.2020.111791","article-title":"Hyperlocal mapping of urban air temperature using remote sensing and crowdsourced weather data","volume":"242","author":"Venter","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_134","doi-asserted-by":"crossref","first-page":"157283","DOI":"10.1016\/j.scitotenv.2022.157283","article-title":"Mapping the gaps between cooling benefits of urban greenspace and population heat vulnerability","volume":"845","author":"Tieskens","year":"2022","journal-title":"Sci. Total Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/23\/4500\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:43:29Z","timestamp":1760114609000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/23\/4500"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,30]]},"references-count":134,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["rs16234500"],"URL":"https:\/\/doi.org\/10.3390\/rs16234500","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,30]]}}}