{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T18:50:33Z","timestamp":1784141433907,"version":"3.55.0"},"reference-count":83,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2018,12,14]],"date-time":"2018-12-14T00:00:00Z","timestamp":1544745600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41771453"],"award-info":[{"award-number":["41771453"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41601448"],"award-info":[{"award-number":["41601448"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key Technology R&amp;D Program of China","award":["2016YFC0500106"],"award-info":[{"award-number":["2016YFC0500106"]}]},{"name":"Special Project of Science and Technology Basic Work","award":["2014FY210800-5"],"award-info":[{"award-number":["2014FY210800-5"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Land surface temperature (LST) is an important parameter to evaluate environmental changes. In this paper, time series analysis was conducted to estimate the interannual variations in global LST from 2001 to 2016 based on moderate resolution imaging spectroradiometer (MODIS) LST, and normalized difference vegetation index (NDVI) products and fine particulate matter (PM2.5) data from the Atmospheric Composition Analysis Group. The results showed that LST, seasonally integrated normalized difference vegetation index (SINDVI), and PM2.5 increased by 0.17 K, 0.04, and 1.02 \u03bcg\/m3 in the period of 2001\u20132016, respectively. During the past 16 years, LST showed an increasing trend in most areas, with two peaks of 1.58 K and 1.85 K at 72\u00b0N and 48\u00b0S, respectively. Marked warming also appeared in the Arctic. On the contrary, remarkable decrease in LST occurred in Antarctic. In most parts of the world, LST was affected by the variation in vegetation cover and air pollutant, which can be detected by the satellite. In the Northern Hemisphere, positive relations between SINDVI and LST were found; however, in the Southern Hemisphere, negative correlations were detected. The impact of PM2.5 on LST was more complex. On the whole, LST increased with a small increase in PM2.5 concentrations but decreased with a marked increase in PM2.5. The study provides insights on the complex relationship between vegetation cover, air pollution, and land surface temperature.<\/jats:p>","DOI":"10.3390\/rs10122034","type":"journal-article","created":{"date-parts":[[2018,12,14]],"date-time":"2018-12-14T12:11:08Z","timestamp":1544789468000},"page":"2034","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":71,"title":["Global Land Surface Temperature Influenced by Vegetation Cover and PM2.5 from 2001 to 2016"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2345-9741","authenticated-orcid":false,"given":"Zengjing","family":"Song","sequence":"first","affiliation":[{"name":"Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"Research Base of Karst Eco-environments at Nanchuan in Chongqing, Ministry of Nature Resources, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"Chongqing Jinfo Mountain Field Scientific Observation and Research Station for Karst Ecosystem, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"Chongqing Key Laboratory of Karst Environment, School of Geographical Sciences, Southwest University, Chongqing 400715, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruihai","family":"Li","sequence":"additional","affiliation":[{"name":"High School Affiliated to Southwest University, Chongqing 400700, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruiyang","family":"Qiu","sequence":"additional","affiliation":[{"name":"High School Affiliated to Southwest University, Chongqing 400700, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siyao","family":"Liu","sequence":"additional","affiliation":[{"name":"High School Affiliated to Southwest University, Chongqing 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Chang. R"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"462","DOI":"10.1038\/nclimate2223","article-title":"Evolution of land surface air temperature trend","volume":"4","author":"Ji","year":"2014","journal-title":"Nat. Clim. Chang."},{"key":"ref_4","first-page":"225","article-title":"Estimating evapotranspiration using improved fractinal vegetation cover and land surface temperatur space","volume":"2","author":"Sun","year":"2011","journal-title":"J. Resour. Ecol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2850","DOI":"10.3390\/rs70302850","article-title":"A new global climatology of annual land surface temperature","volume":"7","author":"Bechtel","year":"2015","journal-title":"Remote Sens."},{"key":"ref_6","unstructured":"Kerr, Y.H., Lagouarde, J.P., Nerry, F., Ottl\u00e9, C., Quattrochi, D.A., and Luvall, J.C. (2000). Land surface temperature retrieval techniques and applications. Therm. Remote Sens. LSP, 33\u2013109."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.rse.2012.12.008","article-title":"Satellite-derived land surface temperature: Current status and perspectives","volume":"131","author":"Li","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.rse.2018.10.002","article-title":"Monitoring and validating spatially and temporally continuous daily evaporation and transpiration at river basin scale","volume":"219","author":"Song","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1016\/j.scitotenv.2018.04.105","article-title":"Spatial-temporal change of land surface temperature across 285 cities in China: An urban-rural contrast perspective","volume":"635","author":"Peng","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2431","DOI":"10.1175\/JHM-D-15-0218.1","article-title":"Global soil moisture estimation by assimilating AMSR-E brightness temperatures in a coupled CLM4\u2013RTM\u2013DART system","volume":"17","author":"Zhao","year":"2016","journal-title":"J. Hydrometeorol."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Anastasios, P., Theleia, M., and Constantinos, C. (2018). Quantifying the trends in land surface temperature and surface urban heat island intensity in mediterranean cities in view of smart urbanization. Urban Sci., 2.","DOI":"10.3390\/urbansci2010016"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"892","DOI":"10.1109\/36.508406","article-title":"A generalized split-window algorithm for retrieving land-surface temperature from space","volume":"34","author":"Wan","year":"1996","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"3613","DOI":"10.5194\/amt-6-3613-2013","article-title":"Kalman filter physical retrieval of surface emissivity and temperature from geostationary infrared radiances","volume":"6","author":"Masiello","year":"2013","journal-title":"Atmos. Meas. Tech."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Yu, W., Ma, M., Li, Z., Tan, J., and Wu, A. (2017). New Scheme for validating remote-sensing land surface temperature products with station observations. Remote Sens., 9.","DOI":"10.3390\/rs9121210"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2981","DOI":"10.5194\/amt-8-2981-2015","article-title":"Kalman filter physical retrieval of surface emissivity and temperature from SEVIRI infrared channels: A validation and intercomparison study","volume":"8","author":"Masiello","year":"2015","journal-title":"Atmos. Meas. Tech."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Masiello, G., Serio, C., Venafra, S., Liuzzi, G., Poutier, L., and G\u00f6ttsche, F.-M. (2018). Physical retrieval of land surface emissivity spectra from hyper-spectral infrared observations and validation with in situ measurements. Remote Sens., 10.","DOI":"10.3390\/rs10060976"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"9185","DOI":"10.1002\/2017JD026880","article-title":"A spatio-temporal 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":"Ghent","year":"2017","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1038\/s41598-017-19088-x","article-title":"Relationship among land surface temperature and LUCC, NDVI in typical karst area","volume":"8","author":"Deng","year":"2018","journal-title":"Sci. Rep."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1659\/MRD-JOURNAL-D-12-00090.1","article-title":"Spatial and temporal variations of land surface temperature over the Tibetan Plateau Based on Harmonic analysis","volume":"33","author":"Xu","year":"2013","journal-title":"Mt. Res. Dev."},{"key":"ref_20","first-page":"161","article-title":"A method to make use of thermal infrared temperature and NDVI measurements to infer surface soil water content and fractional vegetation cover","volume":"9","author":"Carlson","year":"1994","journal-title":"Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"6136","DOI":"10.3390\/rs6076136","article-title":"Analysis of the relationship between land surface temperature and wildfire severity in a series of Landsat images","volume":"6","author":"Vlassova","year":"2014","journal-title":"Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"464","DOI":"10.1007\/s10661-015-4691-3","article-title":"Temporal change and its spatial variety on land surface temperature and land use changes in the Red River Delta, Vietnam, using MODIS time-series imagery","volume":"187","author":"Kawamura","year":"2015","journal-title":"Environ. Monit. Assess."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1016\/j.tree.2005.05.011","article-title":"Using the satellite-derived NDVI to assess ecological responses to environmental change","volume":"20","author":"Pettorelli","year":"2005","journal-title":"Trends Ecol. Evol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"432","DOI":"10.2747\/1548-1603.48.3.432","article-title":"Assessment of vegetation response to drought in Nebraska using Terra-MODIS land surface temperature and normalized difference vegetation index","volume":"48","author":"Swain","year":"2013","journal-title":"GISci. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1002","DOI":"10.1007\/BF02915523","article-title":"The influence of vegetation cover on summer precipitation in China: A statistical analysis of NDVI and climate data","volume":"20","author":"Jingyong","year":"2003","journal-title":"Adv. Atmos. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/j.rse.2018.05.018","article-title":"Increasing global vegetation browning hidden in overall vegetation greening: Insights from time-varying trends","volume":"214","author":"Pan","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1033","DOI":"10.1007\/s13157-015-0692-9","article-title":"Influences of climate extremes on NDVI (Normalized Difference Vegetation Index) in the Poyang Lake Basin, China","volume":"35","author":"Tan","year":"2015","journal-title":"Wetlands"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1088\/1748-9326\/3\/4\/044008","article-title":"Spatio-temporal variability of NDVI\u2013precipitation over southernmost South America: Possible linkages between climate signals and epidemics","volume":"3","author":"Tourre","year":"2008","journal-title":"Environ. Res. Lett."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.gloplacha.2013.06.012","article-title":"NDVI-based vegetation changes and their responses to climate change from 1982 to 2011: A case study in the Koshi River Basin in the middle Himalayas","volume":"108","author":"Zhang","year":"2013","journal-title":"Glob. Planet. Chang."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/j.jafrearsci.2017.06.007","article-title":"The investigation of spatiotemporal variations of land surface temperature based on land use changes using NDVI in southwest of Iran","volume":"134","author":"Fathizad","year":"2017","journal-title":"J. Afr. Earth Sci."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.rse.2006.03.011","article-title":"Changes in land surface temperatures and NDVI values over Europe between 1982 and 1999","volume":"103","author":"Julien","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1111","DOI":"10.1029\/2007GL031485","article-title":"Note on the NDVI-LST relationship and the use of temperature-related drought indices over North America","volume":"34","author":"Sun","year":"2007","journal-title":"Geophys. Res. Lett."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1240","DOI":"10.1073\/pnas.1014425108","article-title":"Spring temperature change and its implication in the change of vegetation growth in North America from 1982 to 2006","volume":"108","author":"Wang","year":"2011","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"17473","DOI":"10.1038\/s41598-017-17810-3","article-title":"Spatial-temporal variation of drought in China from 1982 to 2010 based on a modified Temperature Vegetation Drought Index (mTVDI)","volume":"7","author":"Zhao","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"843","DOI":"10.1007\/s11356-015-5321-x","article-title":"The impact of PM2.5 on asthma emergency department visits: A systematic review and meta-analysis","volume":"23","author":"Fan","year":"2016","journal-title":"Environ. Sci. Pollut. Res."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Lin, Y., Zou, J., Yang, W., and Li, C.Q. (2018). A review of recent advances in research on PM2.5 in China. Int. J. Environ. Res. Public Health, 15.","DOI":"10.3390\/ijerph15030438"},{"key":"ref_37","first-page":"1","article-title":"Impact assessment of meteorological and environmental parameters on PM2.5 concentrations using remote sensing data and GWR analysis (case study of Tehran)","volume":"3","author":"Hajiloo","year":"2018","journal-title":"Environ. Sci. Pollut. Res. Int."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.atmosenv.2007.09.003","article-title":"Air pollution in mega cities in China","volume":"42","author":"Chan","year":"2008","journal-title":"Atmos. Environ."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1016\/j.habitatint.2016.12.012","article-title":"Convergence of carbon intensity in the Yangtze River Delta, China","volume":"60","author":"Li","year":"2017","journal-title":"Habitat Int."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"362","DOI":"10.1016\/j.envpol.2007.06.012","article-title":"Human health effects of air pollution","volume":"151","author":"Kampa","year":"2008","journal-title":"Environ. Pollut."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/S1001-0742(08)60019-4","article-title":"A review on the generation, determination and mitigation of Urban Heat Island","volume":"20","author":"Rizwan","year":"2008","journal-title":"J. Environ. Sci."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"5439","DOI":"10.5194\/acp-17-5439-2017","article-title":"Urbanization-induced urban heat island and aerosol effects on climate extremes in the Yangtze River Delta region of China","volume":"17","author":"Zhong","year":"2017","journal-title":"Atmos. Chem. Phys."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"818","DOI":"10.1016\/j.scitotenv.2018.04.254","article-title":"Interaction between urban heat island and urban pollution island during summer in Berlin","volume":"636","author":"Li","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"681587","DOI":"10.1155\/2010\/681587","article-title":"Urban surface temperature reduction via the urban aerosol direct effect: A remote sensing and WRF model sensitivity study","volume":"2010","author":"Jin","year":"2010","journal-title":"Adv. Meteorol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2011JD016816","article-title":"Aerosol direct, indirect, semidirect, and surface albedo effects from sector contributions based on the IPCC AR5 emissions for preindustrial and present-day conditions","volume":"117","author":"Bauer","year":"2012","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2005GL024586","article-title":"More frequent cloud-free sky and less surface solar radiation in China from 1955 to 2000","volume":"33","author":"Qian","year":"2006","journal-title":"Geophys. Res. Lett."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"83","DOI":"10.3390\/rs3010083","article-title":"Satellite-observed urbanization characters in Shanghai, China: Aerosols, urban heat island effect, and land\u2013atmosphere interactions","volume":"3","author":"Jin","year":"2011","journal-title":"Remote Sens."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"12509","DOI":"10.1038\/ncomms12509","article-title":"Urban heat islands in China enhanced by haze pollution","volume":"7","author":"Cao","year":"2016","journal-title":"Nat. Commun."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"5187","DOI":"10.3390\/rs70505187","article-title":"A Prototype network for remote sensing validation in China","volume":"7","author":"Ma","year":"2015","journal-title":"Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1649","DOI":"10.1109\/LGRS.2014.2314134","article-title":"Validation of the MODIS NDVI products in different land-use types using in situ measurements in the Heihe River Basin","volume":"11","author":"Geng","year":"2014","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"e1601063","DOI":"10.1126\/sciadv.1601063","article-title":"Carbon emissions from land-use change and management in China between 1990 and 2010","volume":"2","author":"Lai","year":"2016","journal-title":"Sci. Adv."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Mao, D., Wang, Z., Yang, H., Li, H., Thompson, J., Li, L., Song, K., Chen, B., Gao, H., and Wu, J. (2018). Impacts of climate change on Tibetan Lakes: Patterns and processes. Remote Sens., 10.","DOI":"10.3390\/rs10030358"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.rse.2013.08.027","article-title":"New refinements and validation of the collection-6 MODIS land-surface temperature\/emissivity product","volume":"140","author":"Wan","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.agwat.2018.07.030","article-title":"Differences in ecosystem water-use efficiency among the typical croplands","volume":"209","author":"Wang","year":"2018","journal-title":"Agric. Water Manag."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"835","DOI":"10.1016\/j.asr.2005.08.037","article-title":"Reconstructing pathfinder AVHRR land NDVI time-series data for the Northwest of China","volume":"37","author":"Ma","year":"2006","journal-title":"Adv. Space Res."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1111","DOI":"10.1080\/0143116021000020144","article-title":"Variability of the seasonally integrated normalized difference vegetation index across the north slope of Alaska in the 1990s","volume":"24","author":"Stow","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1002\/2017JD027010","article-title":"Snow cover and vegetation-induced decrease in global albedo from 2002 to 2016","volume":"123","author":"Li","year":"2018","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"3413","DOI":"10.1080\/0143116021000021170","article-title":"Interannual growth dynamics of vegetation in the Kuparuk River watershed, Alaska based on the normalized difference vegetation index","volume":"24","author":"Hope","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/j.ecoinf.2010.10.002","article-title":"Evaluation of ecological restoration through vegetation patterns in the lower Tarim River, China with MODIS NDVI data","volume":"6","author":"Sun","year":"2011","journal-title":"Ecol. Inform."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"3762","DOI":"10.1021\/acs.est.5b05833","article-title":"Global estimates of fine particulate matter using a combined geophysical-statistical method with information from satellites, models, and monitors","volume":"50","author":"Martin","year":"2016","journal-title":"Environ. Sci. Technol."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Tan, C., Guo, B., Kuang, H., Yang, H., and Ma, M. (2018). Lake area changes and their influence on factors in arid and semi-arid regions along the Silk Road. Remote Sens., 10.","DOI":"10.3390\/rs10040595"},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Tan, C., Ma, M., and Kuang, H. (2017). Spatial-Temporal characteristics and climatic responses of water level fluctuations of global major lakes from 2002 to 2010. Remote Sens., 9.","DOI":"10.3390\/rs9020150"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1146\/annurev.earth.35.031306.140120","article-title":"The Aral Sea Disaster","volume":"35","author":"Micklin","year":"2007","journal-title":"Annu. Rev. Earth Planet. Sci."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1029\/2008EO190001","article-title":"The Arctic and Antarctic: Two faces of climate change","volume":"89","author":"Overland","year":"2008","journal-title":"Eos"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"646","DOI":"10.1126\/science.aar5443","article-title":"Transport expansion threatens the Arctic","volume":"359","author":"Yang","year":"2018","journal-title":"Science"},{"key":"ref_66","unstructured":"Hulley, G.C., Hall, D.K., and Hook, S.J. (2013, January 9\u201313). In monitoring snow melt characteristics on the Greenland ice sheet using a new MODIS land surface temperature and emissivity product (MOD21). Proceedings of the AGU Fall Meeting, San Francisco, CA, USA."},{"key":"ref_67","first-page":"1","article-title":"Land surface temperature as potential indicator of burn severity in forest Mediterranean ecosystems","volume":"36","author":"Quintano","year":"2015","journal-title":"Int. J. Appl. Earth Obs."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"6485","DOI":"10.1029\/2018GL078283","article-title":"Increases in land surface temperature in response to fire in Siberian Boreal Forests and their attribution to biophysical processes","volume":"45","author":"Liu","year":"2018","journal-title":"Geophys. Res. Lett."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1038\/d41586-018-05879-3","article-title":"Identify and punish ozone depleters","volume":"560","author":"Yang","year":"2018","journal-title":"Nature"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1017\/S0032247413000296","article-title":"Antarctic climate change and the environment: An update","volume":"50","author":"Turner","year":"2013","journal-title":"Polar Rec."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3724\/SP.J.1084.2013.00001","article-title":"Evidence of Arctic and Antarcitc changes and their regulation of global climate change (further findings since the fourth IPCC assessment report released)","volume":"25","author":"Chen","year":"2013","journal-title":"Chin. J. Polar Res."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"963","DOI":"10.1016\/j.jaridenv.2009.04.022","article-title":"Climate and environmental change in arid Central Asia: Impacts, vulnerability, and adaptations","volume":"73","author":"Lioubimtseva","year":"2009","journal-title":"J. Arid Environ."},{"key":"ref_73","first-page":"11670","article-title":"Global sources of fine particulate matter: Interpretation of PM2.5 chemical composition observed by SPARTAN using a global chemical transport model","volume":"52","author":"Weagle","year":"2018","journal-title":"Environ. Sci. Technol."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Li, X., Li, S., Xiong, Q., Yang, X., Qi, M., Zhao, W., and Wang, X. (2018). Characteristics of PM2.5 chemical compositions and their effect on atmospheric visibility in urban Beijing, China during the heating season. Int. J. Environ. Res. Public Health, 15.","DOI":"10.3390\/ijerph15091924"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"14304","DOI":"10.1038\/s41598-017-14639-8","article-title":"India is overtaking China as the world\u2019s largest emitter of anthropogenic sulfur dioxide","volume":"7","author":"Li","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_76","first-page":"1","article-title":"Emissions of black carbon, organic, and inorganic aerosols from biomass burning in North America and Asia in 2008","volume":"116","author":"Kondo","year":"2011","journal-title":"J. Geophys. Res."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1016\/j.rse.2006.09.003","article-title":"Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery","volume":"106","author":"Yuan","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"698","DOI":"10.1038\/386698a0","article-title":"Increased plant growth in the northern high latitudes from 1981 to 1991","volume":"386","author":"Myneni","year":"1997","journal-title":"Nature"},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1111\/gcb.13920","article-title":"Differentiating drought legacy effects on vegetation growth over the temperate Northern Hemisphere","volume":"24","author":"Wu","year":"2018","journal-title":"Glob. Chang. Biol."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1007\/s10546-018-0362-6","article-title":"Relationship between fine-particle pollution and the urban heat island in Beijing, China: Observational evidence","volume":"169","author":"Zheng","year":"2018","journal-title":"Bound. Lay Meteorol."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"1057","DOI":"10.1007\/s00376-016-6259-8","article-title":"Observation-based estimation of aerosol-induced reduction of planetary boundary layer height","volume":"34","author":"Zou","year":"2017","journal-title":"Adv. Atmos. Sci."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"8728","DOI":"10.3390\/rs70708728","article-title":"Mapping of daily mean air temperature in agricultural regions using daytime and nighttime land surface temperatures derived from TERRA and AQUA MODIS data","volume":"7","author":"Huang","year":"2015","journal-title":"Remote Sens."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"6026","DOI":"10.3390\/rs70506026","article-title":"MODIS EVI and LST temporal response for discrimination of tropical land covers","volume":"7","author":"Phompila","year":"2015","journal-title":"Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/12\/2034\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:33:58Z","timestamp":1760196838000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/12\/2034"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,12,14]]},"references-count":83,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2018,12]]}},"alternative-id":["rs10122034"],"URL":"https:\/\/doi.org\/10.3390\/rs10122034","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,12,14]]}}}