{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T21:57:21Z","timestamp":1764194241601,"version":"build-2065373602"},"reference-count":26,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2017,6,14]],"date-time":"2017-06-14T00:00:00Z","timestamp":1497398400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Special Foundation for Young Scientists of the State Laboratory of Remote Sensing Science","award":["15RC-07"],"award-info":[{"award-number":["15RC-07"]}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41501398"],"award-info":[{"award-number":["41501398"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the National Key Basic Research Program of China","award":["2015CB953701"],"award-info":[{"award-number":["2015CB953701"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Microwave vegetation index (MVI) is a vegetation index defined in microwave bands. It has been developed based on observations from AMSR-E and widely used to monitor global vegetation. Recently, our study found that MVI was influenced by the atmosphere, although it was calculated from microwave bands. Ignoring the atmospheric influence might bring obvious uncertainty to the study of global vegetation. In this study, an atmospheric effect sensitivity analysis for MVI was carried out, and an atmospheric correction algorithm was developed to reduce the influence of the atmosphere. The sensitivity analysis showed that water vapor, clouds and precipitation were main parameters that had an influence on MVI. The result of the atmospheric correction on MVI was validated at both temporal and spatial scales. The validation showed that the atmospheric correction algorithm developed in this study could obviously improve the underestimation of MVI on most land surfaces. Seasonal patterns in the uncorrected MVI were obviously related to atmospheric water content besides vegetation changes. In addition, global maps of MVI showed significant differences before and after atmospheric correction in the northern hemisphere in the northern summer. The atmospheric correction will make the MVI more reliable and improve its performance in calculating vegetation biomass.<\/jats:p>","DOI":"10.3390\/rs9060606","type":"journal-article","created":{"date-parts":[[2017,6,14]],"date-time":"2017-06-14T10:49:53Z","timestamp":1497437393000},"page":"606","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Atmospheric Effect Analysis and Correction of the Microwave Vegetation Index"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6388-2555","authenticated-orcid":false,"given":"Da-Bin","family":"Ji","sequence":"first","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 20 Datun Road, Chaoyang District, Beijing 100101, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6163-2912","authenticated-orcid":false,"given":"Jian-Cheng","family":"Shi","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 20 Datun Road, Chaoyang District, Beijing 100101, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7336-8872","authenticated-orcid":false,"given":"Husi","family":"Letu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 20 Datun Road, Chaoyang District, Beijing 100101, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8997-7197","authenticated-orcid":false,"given":"Tian-Xing","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 20 Datun Road, Chaoyang District, Beijing 100101, China"}]},{"given":"Tian-Jie","family":"Zhao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 20 Datun Road, Chaoyang District, Beijing 100101, China"}]}],"member":"1968","published-online":{"date-parts":[[2017,6,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/0034-4257(95)00195-6","article-title":"Retrieving leaf area index of boreal conifer forests using Landsat TM images","volume":"55","author":"Chen","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/S0034-4257(99)00057-7","article-title":"Relationships between leaf area index and Landsat TM spectral vegetation indices across three temperate zone sites","volume":"70","author":"Turner","year":"1999","journal-title":"Remote Sens. Environ."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1016\/j.rse.2014.08.032","article-title":"Indirect measurement of leaf area index on the basis of path length distribution","volume":"155","author":"Hu","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/0034-4257(79)90013-0","article-title":"Red and photographic infrared linear combinations for monitoring vegetation","volume":"8","author":"Tucker","year":"1979","journal-title":"Remote Sens. Environ."},{"key":"ref_5","unstructured":"Huete, A.R., Didan, K., Leeuwen, W.V., Jacobson, A., Solanos, R., and Laing, T. (1999). MODIS Vegetation Index (MOD 13) Algorithm Theoretical Basis Document Version 3.1, The University of Arizona. Available online: https:\/\/vip.arizona.edu\/documents\/MODIS\/MODIS_VI_ATBD.pdf."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"4285","DOI":"10.1016\/j.rse.2008.07.015","article-title":"Microwave vegetation indices for short vegetation covers from satellite passive microwave sensor AMSR-E","volume":"112","author":"Shi","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1080\/01431168708948660","article-title":"Monitoring vegetation using Nimbus-7 scanning multichannel microwave radiometer\u2019s data","volume":"8","author":"Choudhury","year":"1987","journal-title":"Int. J. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1085","DOI":"10.1080\/01431168708954754","article-title":"Monitoring global vegetation using Nimbus-7 37 GHz Data Some empirical relations","volume":"8","author":"Choudhury","year":"1987","journal-title":"Int. J. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1016\/0034-4257(88)90031-4","article-title":"Relative sensitivity of normalized difference vegetation index (NDVI) and microwave polarization difference index (MPDI) for vegetation and desertification monitoring","volume":"24","author":"Becker","year":"1988","journal-title":"Remote Sens. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1016\/j.rse.2005.10.020","article-title":"Remote sensing of evapotranspiration and carbon uptake at Harvard Forest","volume":"100","author":"Min","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"4379","DOI":"10.1109\/JSTARS.2015.2423153","article-title":"The development of microwave vegetation indices from WindSat data","volume":"8","author":"Li","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"096003","DOI":"10.1117\/1.JRS.9.096003","article-title":"Effective vegetation optical depth retrieval using microwave vegetation indices from WindSat data for short vegetation","volume":"9","author":"Li","year":"2015","journal-title":"J. Appl. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.1175\/1520-0450(2001)040<1145:AMLMFP>2.0.CO;2","article-title":"A melting-layer model for passive\/active microwave remote sensing applications. Part I: Model formulation and comparison with observations","volume":"40","author":"Olson","year":"2001","journal-title":"J. Appl. Meteorol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1164","DOI":"10.1175\/1520-0450(2001)040<1164:AMLMFP>2.0.CO;2","article-title":"A melting-layer model for passive\/active microwave remote sensing applications. Part II: Simulation of TRMM observations","volume":"40","author":"Olson","year":"2001","journal-title":"J. Appl. Meteorol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"16673","DOI":"10.1029\/JD095iD10p16673","article-title":"Passive microwave remote sensing of cloud liquid water over land regions","volume":"95","author":"Jones","year":"1990","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_16","unstructured":"Liou, K.N. (2004). An Introduction to Atmospheric Radiation, China Meteorological Press. [2nd ed.]."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1016\/j.rse.2017.01.028","article-title":"A total precipitable water retrieval method over land using the combination of passive microwave and optical remote sensing","volume":"191","author":"Ji","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_18","unstructured":"Jarvis, A., Reuter, H.I., Nelson, A., and Guevara, E. (2016, December 01). Hole-Filled Seamless SRTM Data V4. Available online: http:\/\/www.cgiar-csi.org\/data\/srtm-90m-digital-elevation-database-v4-1."},{"key":"ref_19","unstructured":"King, M.D., Tsay, S.C., Platnick, S.E., Wang, M., and Liou, K.N. (2016, December 01). Cloud Retrieval Algorithms for MODIS: Optical Thickness, Effective Particle Radius, and Thermodynamic Phase. Available online: https:\/\/cimss.ssec.wisc.edu\/dbs\/China2011\/Day2\/Lectures\/MOD06OD_Algorithm_Theoretical_Basis_Document.pdf."},{"key":"ref_20","unstructured":"Menzel, W.P., Baum, B.A., Strabala, K.I., and Frey, R.A. (2002). Cloud Top Properties and Cloud Phase Algorithm Theoretical Basis Document Version 6, Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"5798","DOI":"10.1016\/j.atmosenv.2006.05.025","article-title":"Improved retrievals of cloud boundaries from modis for use in air quality modeling","volume":"40","author":"Hutchison","year":"2006","journal-title":"Atmos. Environ."},{"key":"ref_22","unstructured":"Wan, Z. (1999). MODIS Land-Surface Temperature Algorithm Theoretical Basis Document (LST ATBD), Institute for Computational Earth System Science."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Holmes, T.R.H., De Jeu, R.A.M., Owe, M., and Dolman, A.J. (2009). Land surface temperature from Ka band (37 GHz) passive microwave observations. J. Geophys. Res. Atmos., 114.","DOI":"10.1029\/2008JD010257"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Seethala, C., and Horv\u00e1th, \u00c1. (2010). Global assessment of AMSR-E and MODIS cloud liquid water path retrievals in warm oceanic clouds. J. Geophys. Res. Atmos., 115.","DOI":"10.1029\/2009JD012662"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"249","DOI":"10.14358\/PERS.72.3.249","article-title":"A global assessment of the SRTM performance","volume":"72","author":"Rodriguez","year":"2006","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_26","unstructured":"Nishihama, M., Wolfe, R., Solomon, D., Patt, F., Blanchette, J., Fleig, A., and Masuoka, E. (2016, December 01). MODIS Level 1A Earth Location: Algorithm Theoretical Basis Document Version 3.0, Available online: https:\/\/modis.gsfc.nasa.gov\/data\/atbd\/atbd_mod28.pdf."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/6\/606\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:39:05Z","timestamp":1760207945000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/6\/606"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,6,14]]},"references-count":26,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2017,6]]}},"alternative-id":["rs9060606"],"URL":"https:\/\/doi.org\/10.3390\/rs9060606","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2017,6,14]]}}}