{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T15:20:30Z","timestamp":1771514430043,"version":"3.50.1"},"reference-count":53,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2018,10,27]],"date-time":"2018-10-27T00:00:00Z","timestamp":1540598400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key R&amp;D Program of China","award":["2016YFA0602302"],"award-info":[{"award-number":["2016YFA0602302"]}]},{"name":"the National Key R&amp;D Program of China","award":["2016YFB0502502"],"award-info":[{"award-number":["2016YFB0502502"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Discriminating between surface soil freeze\/thaw states with the use of passive microwave brightness temperature has been an effective approach so far. However, soil moisture has a direct impact on the brightness temperature of passive microwave remote sensing, which may result in uncertainties in the widely used dual-index algorithm (DIA). In this study, an improved algorithm is proposed to identify the surface soil freeze\/thaw states based on the original DIA in association with the AMSR-E and AMSR2 soil moisture products to avoid the impact of soil moisture on the brightness temperature derived from passive microwave remotely-sensed soil moisture products. The local variance of soil moisture (LVSM) with a 25-day interval was introduced into this algorithm as an effective indicator for selecting a threshold to update and modify the original DIA to identify surface soil freeze\/thaw states. The improved algorithm was validated against in-situ observations of the Soil Moisture\/Temperature Monitoring Network (SMTMN). The results suggest that the temporal and spatial variation characteristics of LVSM can significantly discriminate between surface soil freeze\/thaw states. The overall discrimination accuracy of the improved algorithm was approximately 89% over a remote area near the town of Naqu on the East-Central Tibetan Plateau, which demonstrated an obvious improvement compared with the accuracy of 82% derived with the original DIA. More importantly, the correct classification rate for the modified pixels was over 96%.<\/jats:p>","DOI":"10.3390\/rs10111697","type":"journal-article","created":{"date-parts":[[2018,10,29]],"date-time":"2018-10-29T11:10:41Z","timestamp":1540811441000},"page":"1697","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["An Improved Algorithm for Discriminating Soil Freezing and Thawing Using AMSR-E and AMSR2 Soil Moisture Products"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6437-7868","authenticated-orcid":false,"given":"Huiran","family":"Gao","sequence":"first","affiliation":[{"name":"Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Wanchang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1639-7845","authenticated-orcid":false,"given":"Hao","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]}],"member":"1968","published-online":{"date-parts":[[2018,10,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"689","DOI":"10.1126\/science.234.4777.689","article-title":"Changing Climate: Geothermal Evidence from Permafrost in the Alaskan Arctic","volume":"234","author":"Lachenbruch","year":"1986","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1029\/2000GL011952","article-title":"Soil freeze\/thaw cycles over snow-free land detected by passive microwave remote sensing","volume":"28","author":"Zhang","year":"2001","journal-title":"Geophys. Res. Lett."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"D12101","DOI":"10.1029\/2003JD004472","article-title":"Trends in high northern latitude soil freeze and thaw cycles from 1988 to 2002","volume":"109","author":"Smith","year":"2004","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"279","DOI":"10.3390\/cli2040279","article-title":"A Study of the Relations between Soil Moisture, Soil Temperatures and Surface Temperatures Using ARM Observations and Offline CLM4 Simulations","volume":"2","author":"Jin","year":"2014","journal-title":"Climate"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/0168-1923(90)90106-G","article-title":"Mapping freeze\/thaw boundaries with SMMR data","volume":"52","author":"Zuemdorfer","year":"1990","journal-title":"Agric. For. Meteorol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"827","DOI":"10.1109\/36.602525","article-title":"Freeze\/thaw classification for prairie soils using SSM\/I radiobrightnesses","volume":"35","author":"Judge","year":"1997","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1126\/science.279.5348.214","article-title":"Sensitivity of boreal forest carbon balance to soil thaw","volume":"279","author":"Goulden","year":"1998","journal-title":"Science"},{"key":"ref_8","first-page":"1","article-title":"Groundwater in the permafrost regions on the Qinghai-Tibet Plateau and it changes","volume":"40","author":"Cheng","year":"2013","journal-title":"Hydrogeol. Eng. Geol."},{"key":"ref_9","first-page":"179","article-title":"Cryospheric changes and their impacts on regional water cycle and ecological conditions in the Qinghai-Tibetan Plateau","volume":"35","author":"Yao","year":"2013","journal-title":"Chin. J. Nat."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"7423","DOI":"10.1029\/91JD00045","article-title":"Classification of snow cover and precipitation using the special sensor microwave imager","volume":"96","author":"Grody","year":"1991","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1109\/TGRS.1986.289643","article-title":"Textural Information in SAR Images","volume":"24","author":"Ulaby","year":"1986","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"464","DOI":"10.1109\/TGRS.1990.572923","article-title":"Radio brightness of diurnally heated, freezing soil","volume":"28","author":"England","year":"1990","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/S0034-4257(00)00160-7","article-title":"Application of the NASA Scatterometer (NSCAT) for Determining the Daily Frozen and Nonfrozen Landscape of Alaska","volume":"75","author":"Kimball","year":"2001","journal-title":"Remote Sens. Environ."},{"key":"ref_14","first-page":"370","article-title":"A Review on the Algorithms of Frozen\/Thaw Boundary Detection by Using Passive Microwave Remote Sensing","volume":"17","author":"Jin","year":"2002","journal-title":"Remote Sens. Technol. Appl."},{"key":"ref_15","first-page":"542","article-title":"Classification of Alaska Spring Thaw Characteristics Using Satellite L-Band Radar Remote Sensing","volume":"53","author":"Du","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Mcdonald, K.C., Kimball, J.S., Njoku, E., Zimmermann, R., and Zhao, M. (2004). Variability in springtime thaw in the terrestrial high latitudes: Monitoring a major control on the biospheric assimilation of atmospheric CO2 with space borne microwave remote sensing. Earth Interact., 8.","DOI":"10.1175\/1087-3562(2004)8<1:VISTIT>2.0.CO;2"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1804","DOI":"10.1109\/36.851764","article-title":"Monitoring of seasonal thawing in Siberia with ERS scatterometer data","volume":"38","author":"Wismann","year":"2000","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Mcdonald, K.C., and Kimball, J.S. (2006). Estimation of surface freeze\u2013thaw states using microwave sensors. Encyclopedia of Hydrological Sciences, John Wiley & Sons, Ltd.","DOI":"10.1002\/0470848944.hsa059a"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"7631","DOI":"10.1080\/01431161.2014.975376","article-title":"Comparison of the classification accuracy of three soil freeze\u2013thaw discrimination algorithms in China using SSMIS and AMSR-E passive microwave imagery","volume":"35","author":"Chai","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2775","DOI":"10.1109\/TGRS.2014.2364823","article-title":"An Algorithm Based on the Standard Deviation of Passive Microwave Brightness Temperatures for Monitoring Soil Surface Freeze\/Thaw State on the Tibetan Plateau","volume":"53","author":"Han","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1109\/36.124219","article-title":"Radio brightness decision criteria for freeze\/thaw boundaries","volume":"30","author":"Zuemdorfer","year":"1992","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/0034-4257(90)90038-N","article-title":"The effect of freezing and thawing on the microwave signatures of bare soil","volume":"33","year":"1990","journal-title":"Remote Sens. Environ."},{"key":"ref_23","unstructured":"Zuemdorfer, B., England, A.W., and Wakefield, G.H. (1989, January 10\u201314). The radio brightness of freezing terrain. Proceedings of the 12th Canadian Symposium on Remote Sensing International Conference, Vancouver, BC, Canada."},{"key":"ref_24","first-page":"139","article-title":"Monitoring terrain soil freeze\/ thaw condition on Qinghai plateau in spring and autumn using microwave remote sensing","volume":"1","author":"Cao","year":"1997","journal-title":"J. Remote Sens."},{"key":"ref_25","first-page":"1073","article-title":"Overview of the Satellite Remote Sensing of Frozen Ground: Passive Microwave Sensors","volume":"24","author":"Zhang","year":"2009","journal-title":"Adv. Earth Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2651","DOI":"10.1016\/j.rse.2009.08.003","article-title":"A decision tree algorithm for surface soil freeze\/thaw classification over China using SSM\/I brightness temperature","volume":"113","author":"Jin","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1704","DOI":"10.1002\/hyp.7930","article-title":"A new soil freeze\/thaw discriminant algorithm using AMSR-E passive microwave imagery","volume":"25","author":"Zhao","year":"2011","journal-title":"Hydrol. Processes"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1016\/j.rse.2017.06.035","article-title":"Detection of land surface freeze-thaw status on the Tibetan Plateau using passive microwave and thermal infrared remote sensing data","volume":"199","author":"Kou","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"949","DOI":"10.1109\/TGRS.2010.2070515","article-title":"Developing a Global Data Record of Daily Landscape Freeze\/Thaw Status Using Satellite Passive Microwave Remote Sensing","volume":"49","author":"Kim","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"3457","DOI":"10.1016\/j.rse.2011.08.009","article-title":"Monitoring freeze\/thaw cycles using ENVISAT ASAR Global Mode","volume":"115","author":"Park","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"206","DOI":"10.1016\/j.rse.2014.03.007","article-title":"Detection of soil freezing from L-band passive microwave observations","volume":"147","author":"Rautiainen","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"4442","DOI":"10.1109\/JSTARS.2015.2476358","article-title":"Evaluation of Spaceborne L-Band Radiometer Measurements for Terrestrial Freeze\/Thaw Retrievals in Canada","volume":"8","author":"Roy","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Rautiainen, K., Parkkinen, T., Lemmetyinen, J., Schwank, M., Wiesmann, A., Ikonen, J., Derksen, C., Davydov, S., Davydova, A., and Boike, J. (2016). SMOS prototype algorithm for detecting autumn soil freezing. Remote Sens. Environ., 180.","DOI":"10.1016\/j.rse.2016.01.012"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"3390","DOI":"10.1016\/j.rse.2011.08.003","article-title":"Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across Europe","volume":"115","author":"Brocca","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2718","DOI":"10.1016\/j.rse.2011.06.012","article-title":"A first assessment of the SMOS data in southwestern France using in situ, airborne and model soil moisture estimates","volume":"115","author":"Albergel","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_36","unstructured":"Yaari, A., Wigneron, J.P., Ducharne, A., Kerrc, Y., Wagnere, W., Reichled, R., Lannoyd, G.D., Bitarc, A.A., Dorigoe, W., and Parrensc, M. (2014, January 13\u201318). Compared performances of microwave passive soil moisture retrievals (SMOS) and active soil moisture retrievals (ASCAT) using land surface model estimates (MERRA-LAND). Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS), Quebec City, QC, Canada."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1080\/01431161.2017.1378456","article-title":"Downscaling of passive microwave soil moisture retrievals based on spectral analysis","volume":"39","author":"Zhong","year":"2018","journal-title":"Int. J. Remote Sens."},{"key":"ref_38","unstructured":"Gonzalez, R.C., and Woods, R.E. (1992). Digital Image Process, Addison-Wesley Longman Publishing Co., Inc."},{"key":"ref_39","unstructured":"Ajafernandez, S., Estepar, R.S., Alberolalopez, C., and Westin, C. (September, January 30). Image Quality Assessment based on Local Variance. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, New York City, NY, USA."},{"key":"ref_40","first-page":"1546","article-title":"Image quality assessment based on local variance and structure similarity","volume":"19","author":"Wang","year":"2008","journal-title":"J. Optoelectron. Laser"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1907","DOI":"10.1175\/BAMS-D-12-00203.1","article-title":"A Multi-Scale Soil Moisture and Freeze-Thaw Monitoring Network on the Third Pole","volume":"94","author":"Yang","year":"2013","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2013.07.003","article-title":"Spatial upscaling of in-situ soil moisture measurements based on MODIS-derived apparent thermal inertia","volume":"138","author":"Qin","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_43","first-page":"19","article-title":"Evaluation of the AMSR-E Data Calibration Over Land","volume":"29","author":"Njoku","year":"2004","journal-title":"Ital. J. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.rse.2016.10.050","article-title":"Does AMSR2 produce better soil moisture retrievals than AMSR-E over Australia?","volume":"188","author":"Cho","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1109\/TGRS.2002.808243","article-title":"Soil moisture retrieval from AMSR-E","volume":"41","author":"Njoku","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_46","first-page":"102","article-title":"Relation of vegetation coverage to meteorological conditions in the Naqu area of Tibet","volume":"17","author":"Yang","year":"2008","journal-title":"Acta Pratacult. Sin."},{"key":"ref_47","first-page":"282","article-title":"Improvement of the AMSR-E algorithm for soil moisture estimation by introducing a fractional vegetation coverage dataset derived from MODIS data","volume":"29","author":"Fujii","year":"2009","journal-title":"J. Remote Sens. Soc. Japan"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/j.rse.2015.03.008","article-title":"Evaluation of remotely sensed and reanalysis soil moisture products over the Tibetan Plateau using in-situ observations","volume":"163","author":"Zeng","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.earscirev.2010.02.004","article-title":"Investigating soil moisture\u2013climate interactions in a changing climate: A review","volume":"99","author":"Seneviratne","year":"2010","journal-title":"Earth Sci. Rev."},{"key":"ref_50","first-page":"1199","article-title":"Soil moisture dynamics of apple orchard in Loess Plateau dryland","volume":"26","author":"Zhao","year":"2015","journal-title":"J. Appl. Ecol."},{"key":"ref_51","first-page":"221","article-title":"DisPATCh as a tool to evaluate coarse-scale remotely sensed soil moisture using localized in situ measurements: Application to SMOS and AMSR-E data in Southeastern Australia","volume":"45","author":"Merlin","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_52","unstructured":"Aja-Fern\u00e1ndez, S., Est\u00e9par, R.S., Alberola-L\u00f3pez, C., and Westin, C.F. (September, January 30). Image Quality Assessment based on Local Variance. Proceedings of the 28th IEEE EMBS Annual International Conference, New York City, NY, USA."},{"key":"ref_53","unstructured":"Zhou, Y.W., Guo, D.X., Qiu, G.Q., Cheng, G.D., and Li, S.D. (2000). Geocryology in China Beijing, Science Press in Chinese."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/11\/1697\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:26:36Z","timestamp":1760196396000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/11\/1697"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,10,27]]},"references-count":53,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2018,11]]}},"alternative-id":["rs10111697"],"URL":"https:\/\/doi.org\/10.3390\/rs10111697","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,10,27]]}}}