Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/93525
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Land Surveying and Geo-Informatics | en_US |
dc.contributor | Research Institute for Sustainable Urban Development | en_US |
dc.creator | He, J | en_US |
dc.creator | Liu, Z | en_US |
dc.date.accessioned | 2022-07-08T01:02:56Z | - |
dc.date.available | 2022-07-08T01:02:56Z | - |
dc.identifier.issn | 0196-2892 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/93525 | - |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers | en_US |
dc.rights | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en_US |
dc.rights | The following publication He, J., & Liu, Z. (2020). Refining MODIS NIR atmospheric water vapor retrieval algorithm using GPS-derived water vapor data. IEEE Transactions on Geoscience and Remote Sensing, 59(5), 3682-3694 is available at https://doi.org/10.1109/TGRS.2020.3016655 | en_US |
dc.subject | Global positioning system (GPS) | en_US |
dc.subject | Land cover | en_US |
dc.subject | Moderate resolution imaging spectroradiometer (MODIS) | en_US |
dc.subject | Precipitable water vapor (PWV) | en_US |
dc.title | Refining MODIS NIR atmospheric water vapor retrieval algorithm using GPS-derived water vapor data | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 3682 | en_US |
dc.identifier.epage | 3694 | en_US |
dc.identifier.volume | 59 | en_US |
dc.identifier.issue | 5 | en_US |
dc.identifier.doi | 10.1109/TGRS.2020.3016655 | en_US |
dcterms.abstract | A new algorithm of retrieving atmospheric water vapor from MODIS near-infrared (IR) (NIR) data by using a regression fitting method based on Global Positioning System (GPS)-derived water vapor is developed in this work. The algorithm has been used to retrieve total column water vapor from Moderate Resolution Imaging Spectroradiometer (MODIS) satellites both Terra and Aqua under cloud-free conditions from solar radiation in the NIR channels. Water vapor data estimated from GPS observations recorded from 2003 to 2017 by the SuomiNet GPS network over the western North America are used as ground truth references. The GPS stations were classified into six subsets based on the surface types adopted from MCD12Q1 IGBP legend. The differences in surface types are considered in the regression fitting procedure, thus different regression functions are trained for different surface types. Thus, the wet bias in the operational MODIS water vapor products has been significantly reduced. Water vapor retrieved from each of the three absorption channels and the weighted water vapor of combined three absorption channels are analyzed. Validation shows that the weighted water vapor performs better than the single-channel results. Compared to the MODIS/Terra water vapor products, the RMSE has been reduced by 50.78% to 2.229 mm using the two-channel ratio transmittance method and has been reduced by 53.06% to 2.126 mm using the three-channel ratio transmittance method. Compared to the MODIS/Aqua water vapor products, the RMSE has been reduced by 45.54% to 2.423 mm using the two-channel ratio transmittance method and has been reduced by 45.34% to 2.432 mm using the three-channel ratio transmittance method. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | IEEE transactions on geoscience and remote sensing, May 2021, v. 59, no. 5, p. 3682-3694 | en_US |
dcterms.isPartOf | IEEE transactions on geoscience and remote sensing | en_US |
dcterms.issued | 2021-05 | - |
dc.identifier.scopus | 2-s2.0-85102062936 | - |
dc.identifier.eissn | 1558-0644 | en_US |
dc.description.validate | 202207 bcfc | en_US |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | LSGI-0037 | - |
dc.description.fundingSource | RGC | en_US |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | Key Program of the National Natural Science Foundation of China; the Emerging Frontier Area (EFA) Scheme of Research Institute for Sustainable Urban Development (RISUD) of the Hong Kong Polytechnic University | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 56135724 | - |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
He_Refining_MODIS_NIR.pdf | Pre-Published version | 1.24 MB | Adobe PDF | View/Open |
Page views
54
Last Week
0
0
Last month
Citations as of May 12, 2024
Downloads
73
Citations as of May 12, 2024
SCOPUSTM
Citations
12
Citations as of May 16, 2024
WEB OF SCIENCETM
Citations
11
Citations as of May 16, 2024
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.