{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:17:13Z","timestamp":1760217433651,"version":"build-2065373602"},"reference-count":31,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2015,5,22]],"date-time":"2015-05-22T00:00:00Z","timestamp":1432252800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This study analyzed the scaling problem of land surface temperature (LST) data retrieved with the Temperature Emissivity Separation (TES) algorithm. We compiled a remotely sensed dataset that included Thermal Airborne Hyperspectral Imager (TASI) and satellite-based Advanced Spaceborne Thermal Emission Reflection (ASTER) data, which were acquired simultaneously. This dataset provided the range of spatial heterogeneities of land surface necessary for the study, which was quantified by the dispersion variance. The LST scaling problem was studied by comparing the remotely sensed LST products in two ways. First, the LST products calculated in the distributed method and the lumped method were compared. Second, the airborne and satellite-based LST products derived from the TES algorithm were compared. Four upscaling methods of LST were used in the process. A scaling correction methodology was developed based on the comparisons. The results showed that the scaling effect could be as large as 0.8                                                   when the spatial resolution of the TASI LST data was coarse. The scaling effect increases quickly with the spatial resolution until it reaches the characteristic scale of the landscape and is positively correlated with the spatial heterogeneity. The first two upscaling methods denoted as Methods 1\u20132 can upscale the LST more effectively when compared with the other two scaling methods (Methods 3\u20134). The scaling effect for the ASTER data is not notable. The comparison between the TASI and ASTER data showed that they were highly consistent, with a root mean square error (RMSE) of approximately 0.88 K, when the pixels were relatively homogeneous. When the spatial heterogeneity was significant, the RMSE was as large as 2.68 K    The scaling correction methodology provided resolution-invariant results with scaling effects of less than 0.5 K.<\/jats:p>","DOI":"10.3390\/rs70506489","type":"journal-article","created":{"date-parts":[[2015,5,26]],"date-time":"2015-05-26T04:16:36Z","timestamp":1432613796000},"page":"6489-6509","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Analysis of the Land Surface Temperature Scaling Problem: A Case Study of Airborne and Satellite Data over the Heihe Basin"],"prefix":"10.3390","volume":"7","author":[{"given":"Tian","family":"Hu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"Joint Center for Global Change Studies (JCGCS), Beijing 100875, China"},{"name":"College of Resources and Environment, University of Chinese Academy of Sciences,  Beijing 100049, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3713-9511","authenticated-orcid":false,"given":"Qinhuo","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"Joint Center for Global Change Studies (JCGCS), Beijing 100875, China"}]},{"given":"Yongming","family":"Du","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"Joint Center for Global Change Studies (JCGCS), Beijing 100875, China"}]},{"given":"Hua","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Heshun","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Biao","family":"Cao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China"}]}],"member":"1968","published-online":{"date-parts":[[2015,5,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/0034-4257(92)90008-8","article-title":"Change of scale in models of remote sensing: A general method for spatialization of models","volume":"40","author":"Raffy","year":"1992","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"747","DOI":"10.1109\/36.581996","article-title":"A framework for analyzing and designing scale invariant remote sensing algorithms","volume":"35","author":"Zhenglin","year":"1997","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1016\/j.rse.2006.07.013","article-title":"Influence of landscape spatial heterogeneity on the non-linear estimation of leaf area index from moderate spatial resolution remote sensing data","volume":"105","author":"Garrigues","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"4879","DOI":"10.5194\/bg-10-4879-2013","article-title":"Effects of vegetation heterogeneity and surface topography on spatial scaling of net primary productivity","volume":"10","author":"Chen","year":"2013","journal-title":"Biogeosciences"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1016\/S0022-1694(96)03133-2","article-title":"The scaling characteristics of remotely-sensed variables for sparsely-vegetated heterogeneous landscapes","volume":"190","author":"Moran","year":"1997","journal-title":"J. Hydrol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1304","DOI":"10.1109\/TGRS.2010.2063034","article-title":"Generating consistent land surface temperature and emissivity products between aster and modis data for earth science research","volume":"49","author":"Hulley","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1109\/LGRS.2014.2341925","article-title":"Improving leaf area index retrieval over heterogeneous surface by integrating textural and contextual information: A case study in the heihe river basin","volume":"12","author":"Gaofei","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"3503","DOI":"10.1080\/01431161.2012.716537","article-title":"Impact of nonlinearity and discontinuity on the spatial scaling effects of the leaf area index retrieved from remotely sensed data","volume":"34","author":"Wu","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1768","DOI":"10.3390\/s90301768","article-title":"Scale issues in remote sensing: A review on analysis, processing and modeling","volume":"9","author":"Wu","year":"2009","journal-title":"Sensors"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/S0034-4257(02)00102-5","article-title":"Radiative transfer based scaling of LAI retrievals from reflectance data of different resolutions","volume":"84","author":"Tian","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.rse.2006.06.012","article-title":"Scaling of land surface temperature using satellite data: A case examination on ASTER and MODIS products over a heterogeneous terrain area","volume":"105","author":"Liu","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1016\/j.rse.2014.03.027","article-title":"Minimum configuration of thermal infrared bands for land surface temperature and emissivity estimation in the context of potential future missions","volume":"148","author":"Sobrino","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"4913","DOI":"10.1109\/TGRS.2013.2285924","article-title":"Angular normalization of land surface temperature and emissivity using multiangular middle and thermal infrared data","volume":"52","author":"Huazhong","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_14","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_15","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1080\/02757259509532286","article-title":"Surface temperature and emissivity at various scales: Definition, measurement and related problems","volume":"12","author":"Becker","year":"1995","journal-title":"Remote Sens. Rev."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2636","DOI":"10.1109\/TGRS.2002.805069","article-title":"Normalization and comparison of surface temperatures across a range of scales","volume":"40","author":"Lakshmi","year":"2002","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.rse.2003.11.015","article-title":"Comparison of land surface emissivity and radiometric temperature derived from MODIS and ASTER sensors","volume":"90","author":"Jacob","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.rse.2006.03.013","article-title":"Quantifying spatial heterogeneity at the landscape scale using variogram models","volume":"103","author":"Garrigues","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.rse.2013.11.014","article-title":"Evaluation of the VIIRS and MODIS LST products in an arid area of northwest China","volume":"142","author":"Li","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.1175\/BAMS-D-12-00154.1","article-title":"Heihe watershed allied telemetry experimental research (HiWATER): Scientific objectives and experimental design","volume":"94","author":"Li","year":"2013","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1790","DOI":"10.1007\/s11430-014-4877-5","article-title":"Land cover mapping using time series HJ-1\/CCD data","volume":"57","author":"Zhong","year":"2014","journal-title":"Sci. China Earth Sci."},{"key":"ref_22","unstructured":"Zhong, B., Nie, A., Yang, A., Zhang, H., Ma, P., and Liu, Q. (2014). Heihe Plan Science Data Center, Heihe Plan Science Data Center."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1113","DOI":"10.1109\/36.700995","article-title":"A temperature and emissivity separation algorithm for advanced spaceborne thermal emission and reflection radiometer (ASTER) images","volume":"36","author":"Gillespie","year":"1998","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2778","DOI":"10.1109\/TGRS.2005.857886","article-title":"Accurate atmospheric correction of aster thermal infrared imagery using the WVS method","volume":"43","author":"Tonooka","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_25","unstructured":"Wang, H. (2014). Thermal Infrared Emissivity Extraction from Remote Sensing Data and Soil Emissivity Modeling. [Ph.D. Thesis, University of Chinese Academy of Sciences]."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Young, S.J., Johnson, B.R., and Hackwell, J.A. (2002). An in-scene method for atmospheric compensation of thermal hyperspectral data. J. Geophys. Res. Atmos., 107.","DOI":"10.1029\/2001JD001266"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1109\/LGRS.2012.2206367","article-title":"Estimating the optimal broadband emissivity spectral range for calculating surface longwave net radiation","volume":"10","author":"Cheng","year":"2013","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1080\/0143116031000115184","article-title":"Study of emissivity scaling and relativity of homogeneity of surface temperature","volume":"25","author":"Zhang","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1080\/02757259509532284","article-title":"Terminology in thermal infrared remote sensing of natural surfaces","volume":"12","author":"Norman","year":"1995","journal-title":"Remote Sens. Rev."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Hu, T., Liu, Q., Du, Y., Li, H., and Huang, H. (2015, January 26\u201331). Analysis of land surface temperature spatial heterogeneity using variogram model. Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, Italy.","DOI":"10.1109\/IGARSS.2015.7325716"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1109\/LGRS.2014.2336912","article-title":"Investigating the impact of soil moisture on thermal infrared emissivity using ASTER data","volume":"12","author":"Heshun","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/5\/6489\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:46:50Z","timestamp":1760215610000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/5\/6489"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,5,22]]},"references-count":31,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2015,5]]}},"alternative-id":["rs70506489"],"URL":"https:\/\/doi.org\/10.3390\/rs70506489","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2015,5,22]]}}}