{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T19:56:21Z","timestamp":1775850981807,"version":"3.50.1"},"reference-count":39,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2021,5,19]],"date-time":"2021-05-19T00:00:00Z","timestamp":1621382400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Korea Environmental Industry &amp; Technology Institute","award":["2016000200009"],"award-info":[{"award-number":["2016000200009"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Rapid urbanization has led to several severe environmental problems, including so-called heat island effects, which can be mitigated by creating more urban green spaces. However, the temperature of various surfaces differs and precise measurement and analyses are required to determine the \u201ccoolest\u201d of these. Therefore, we evaluated the accuracy of surface temperature data based on thermal infrared (TIR) cameras mounted on unmanned aerial vehicles (UAVs), which have recently been utilized for the spatial analysis of surface temperatures. Accordingly, we investigated land surface temperatures (LSTs) in green spaces, specifically those of different land cover types in an urban park in Korea. We compared and analyzed LST data generated by a thermal infrared (TIR) camera mounted on an unmanned aerial vehicle (UAV) and LST data from the Landsat 8 satellite for seven specific periods. For comparison and evaluation, we measured in situ LSTs using contact thermometers. The UAV TIR LST showed higher accuracy (R2 0.912, root mean square error (RMSE) 3.502 \u00b0C) than Landsat TIR LST accuracy (R2 value lower than 0.3 and RMSE of 7.246 \u00b0C) in all periods. The Landsat TIR LST did not show distinct LST characteristics by period and land cover type; however, grassland, the largest land cover type in the study area, showed the highest accuracy. With regard to the accuracy of the UAV TIR LST by season, the accuracy was higher in summer and spring (R2 0.868\u20130.915, RMSE 2.523\u20133.499 \u00b0C) than in autumn and winter (R2 0.766\u20130.79, RMSE 3.834\u20135.398 \u00b0C). Some land cover types (concrete bike path, wooden deck) were overestimated, showing relatively high total RMSEs of 4.439 \u00b0C and 3.897 \u00b0C, respectively, whereas grassland, which has lower LST, was underestimated\u2014showing a total RMSE of 3.316 \u00b0C. Our results showed that the UAV TIR LST could be measured with sufficient reliability for each season and land cover type in an urban park with complex land cover types. Accordingly, our results could contribute to decision-making for urban spaces and environmental planning in consideration of the thermal environment.<\/jats:p>","DOI":"10.3390\/rs13101977","type":"journal-article","created":{"date-parts":[[2021,5,19]],"date-time":"2021-05-19T21:49:21Z","timestamp":1621460961000},"page":"1977","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["Comparison of Accuracy of Surface Temperature Images from Unmanned Aerial Vehicle and Satellite for Precise Thermal Environment Monitoring of Urban Parks Using In Situ Data"],"prefix":"10.3390","volume":"13","author":[{"given":"Dongwoo","family":"Kim","sequence":"first","affiliation":[{"name":"Korea Environment Institute, Bldg. B, 370 Sicheong-daero, Sejong 30147, Korea"},{"name":"Division of Environmental Science &amp; Ecological Engineering, Korea University, 02841 145 Anam-ro, Seongbuk-gu, Seoul 02841, Korea"}]},{"given":"Jaejin","family":"Yu","sequence":"additional","affiliation":[{"name":"Korea Environment Institute, Bldg. B, 370 Sicheong-daero, Sejong 30147, Korea"}]},{"given":"Jeongho","family":"Yoon","sequence":"additional","affiliation":[{"name":"Korea Environment Institute, Bldg. B, 370 Sicheong-daero, Sejong 30147, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5928-8510","authenticated-orcid":false,"given":"Seongwoo","family":"Jeon","sequence":"additional","affiliation":[{"name":"Division of Environmental Science &amp; Ecological Engineering, Korea University, 02841 145 Anam-ro, Seongbuk-gu, Seoul 02841, Korea"}]},{"given":"Seungwoo","family":"Son","sequence":"additional","affiliation":[{"name":"Korea Environment Institute, Bldg. B, 370 Sicheong-daero, Sejong 30147, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,19]]},"reference":[{"key":"ref_1","unstructured":"United Nations, Department of Economic and Social Affairs (2019). Population Division. World Urbanization Prospects: The 2018 Revision (ST\/ESA\/SER.A\/420), United Nations."},{"key":"ref_2","unstructured":"(2020, January 10). The World Bank Group. Available online: https:\/\/data.worldbank.org\/indicator\/sp.urb.totl.in.zs."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1038\/nature13945","article-title":"Implications of agricultural transitions and urbanization for ecosystem services","volume":"515","author":"Cumming","year":"2014","journal-title":"Nature"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"101864","DOI":"10.1016\/j.scs.2019.101864","article-title":"The roles of landscape both inside the park and the surroundings in park cooling effect","volume":"52","author":"Qiu","year":"2020","journal-title":"Sustain. Cities Soc."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Qiao, Z., Liu, L., Qin, Y., Xu, X., Wang, B., and Liu, Z. (2020). The impact of urban renewal on land surface temperature changes: A case study in the main city of Guangzhou, China. Remote Sens., 12.","DOI":"10.3390\/rs12050794"},{"key":"ref_6","unstructured":"Howard, L. (1820). The Climate of London: Deduced from Meteorological Observations, Made at Different Places in the Neighbourhood of the Metropolis, W. Phillips."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"126630","DOI":"10.1016\/j.ufug.2020.126630","article-title":"Critical review on the cooling effect of urban blue-green space: A threshold-size perspective","volume":"49","author":"Yu","year":"2020","journal-title":"Urban For. Urban Green."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.uclim.2016.11.005","article-title":"Urban resilience to future urban heat waves under a climate change scenario: A case study for Porto urban area (Portugal)","volume":"19","author":"Carvalho","year":"2017","journal-title":"Urban Clim."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"134","DOI":"10.2134\/jeq2015.01.0062","article-title":"The bigger, the better? The influence of urban green space design on cooling effects for residential areas","volume":"45","author":"Jaganmohan","year":"2016","journal-title":"J. Environ. Qual."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Yang, C., He, X., Yu, L., Yang, J., Yan, F., Bu, K., Chang, L., and Zhang, S. (2017). The cooling effect of urban parks and its monthly variations in a snow climate city. Remote Sens., 9.","DOI":"10.3390\/rs9101066"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/j.apenergy.2017.01.079","article-title":"Numerical simulation of cooling effect of vegetation enhancement in a subtropical urban park","volume":"192","author":"Yang","year":"2017","journal-title":"Appl. Energy"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1016\/j.scitotenv.2011.10.043","article-title":"A study of urban heat island and its association with particulate matter during winter months over Delhi","volume":"414","author":"Pandey","year":"2012","journal-title":"Sci. Total Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1016\/j.rse.2012.11.007","article-title":"Temperature-land cover interactions: The inversion of urban heat island phenomenon in desert city areas","volume":"130","author":"Lazzarini","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Naughton, J., and McDonald, W. (2019). Evaluating the variability of urban land surface temperatures using drone observations. Remote Sens., 11.","DOI":"10.3390\/rs11141722"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"835","DOI":"10.1016\/j.rse.2017.09.033","article-title":"Three-dimensional thermal characterization of forest canopies using UAV photogrammetry","volume":"209","author":"Webster","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.marpetgeo.2017.10.025","article-title":"Drone high resolution infrared imaging of the Lusi mud eruption","volume":"90","author":"Mazzini","year":"2018","journal-title":"Mar. Pet. Geol."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Kelly, J., Kljun, N., Olsson, P.O., Mihai, L., Liljeblad, B., Weslien, P., Klemedtsson, L., and Eklundh, L. (2019). Challenges and best practices for deriving temperature data from an uncalibrated UAV thermal infrared camera. Remote Sens., 11.","DOI":"10.3390\/rs11050567"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Song, B., and Park, K. (2020). Verification of Accuracy of Unmanned Aerial Vehicle (UAV) Land Surface Temperature Images Using In-Situ Data. Remote Sens., 12.","DOI":"10.3390\/rs12020288"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Acorsi, M.G., Gimenez, L.M., and Martello, M. (2020). Assessing the Performance of a Low-Cost Thermal Camera in Proximal and Aerial Conditions. Remote Sens., 12.","DOI":"10.3390\/rs12213591"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.ufug.2018.05.009","article-title":"Spatio temporal non-uniformity of urban park greenness and thermal characteristics in a semi-arid region","volume":"34","author":"Dronova","year":"2018","journal-title":"Urban For. Urban Green."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.ufug.2009.02.003","article-title":"Benefits and well-being perceived by people visiting green spaces in periods of heat stress","volume":"8","author":"Lafortezza","year":"2009","journal-title":"Urban For. Urban Green."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.ufug.2018.01.008","article-title":"Urban heat islands in relation to green land use in European cities","volume":"37","author":"Nastran","year":"2019","journal-title":"Urban For. Urban Green."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"87","DOI":"10.2480\/agrmet.D-17-00011","article-title":"Satellite-based assessment of rapid mega-urban development on agricultural land","volume":"74","author":"Hong","year":"2018","journal-title":"J. Agric. Meteorol."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Yang, Y., and Lee, X. (2019). Four-band thermal mosaicking: A new method to process infrared thermal imagery of urban landscapes from UAV flights. Remote Sens., 11.","DOI":"10.3390\/rs11111365"},{"key":"ref_25","unstructured":"Lillesand, T., Kiefer, R.W., and Chipman, J. (2015). Remote Sensing and Image Interpretation, John Wiley & Sons. [6th ed.]."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Ortiz-Sanz, J., Gil-Docampo, M., Arza-Garc\u00eda, M., and Ca\u00f1as-Guerrero, I. (2019). IR Thermography from UAVs to Monitor Thermal Anomalies in the Envelopes of Traditional Wine Cellars: Field Test. Remote Sens., 11.","DOI":"10.3390\/rs11121424"},{"key":"ref_27","unstructured":"USGS (2018). Landsat 8 (L8) Data Users Handbook (LSDS-1574, Version 3.0)."},{"key":"ref_28","first-page":"339","article-title":"Revision of the single-channel algorithm for land surface temperature retrieval from Landsat thermal-infrared data","volume":"47","author":"Sobrino","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"3719","DOI":"10.1080\/01431160010006971","article-title":"A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region","volume":"22","author":"Qin","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Sekertekin, A., and Bonafoni, S. (2020). Sensitivity Analysis and Validation of Daytime and Nighttime Land Surface Temperature Retrievals from Landsat 8 Using Different Algorithms and Emissivity Models. Remote Sens., 12.","DOI":"10.3390\/rs12172776"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"316","DOI":"10.1109\/TGRS.2007.904834","article-title":"Land surface emissivity retrieval from different VNIR and TIR sensors","volume":"46","author":"Sobrino","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Masina, M., Lambertini, A., Dapr\u00e0, I., Mandanici, E., and Lamberti, A. (2020). Remote Sensing Analysis of Surface Temperature from Heterogeneous Data in a Maize Field and Related Water Stress. Remote Sens., 12.","DOI":"10.3390\/rs12152506"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Malb\u00e9teau, Y., Parkes, S., Aragon, B., Rosas, J., and McCabe, M.F. (2018). Capturing the diurnal cycle of land surface temperature using an unmanned aerial vehicle. Remote Sens., 10.","DOI":"10.3390\/rs10091407"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"64","DOI":"10.3389\/feart.2018.00064","article-title":"Mapping surface temperatures on a debris-covered glacier with an unmanned aerial vehicle","volume":"6","author":"Kraaijenbrink","year":"2018","journal-title":"Front. Earth Sci."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Smigaj, M., Gaulton, R., Suarez, J.C., and Barr, S.L. (2017). Use of miniature thermal cameras for detection of physiological stress in conifers. Remote Sens., 9.","DOI":"10.3390\/rs9090957"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Sheng, H., Chao, H., Coopmans, C., Han, J., McKee, M., and Chen, Y. (2010, January 15\u201317). Low-cost UAV-based thermal infrared remote sensing: Platform, calibration and applications. Proceedings of the 2010 IEEE\/ASME International Conference on Mechatronic and Embedded Systems and Applications, QingDao, China.","DOI":"10.1109\/MESA.2010.5552031"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1080\/22797254.2018.1564888","article-title":"Airborne thermal remote sensing: The case of the city of Olomouc, Czech Republic","volume":"52","author":"Pour","year":"2019","journal-title":"Eur. J. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Ribeiro-Gomes, K., Hern\u00e1ndez-L\u00f3pez, D., Ortega, J.F., Ballesteros, R., Poblete, T., and Moreno, M.A. (2017). Uncooled thermal camera calibration and optimization of the photogrammetry process for UAV applications in agriculture. Sensors, 17.","DOI":"10.3390\/s17102173"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.ufug.2009.10.002","article-title":"Seasonal variations in the cooling effect of urban green areas on surrounding urban areas","volume":"9","author":"Hamada","year":"2010","journal-title":"Urban For. Urban Green."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/10\/1977\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:04:01Z","timestamp":1760162641000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/10\/1977"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,19]]},"references-count":39,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2021,5]]}},"alternative-id":["rs13101977"],"URL":"https:\/\/doi.org\/10.3390\/rs13101977","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,19]]}}}