An Inproved Up-scaling Algorithm Combined TSA and PSF
Taking the Guanzhong Plain of Shanxi Province as the research area, the combine method of trend surface analysis method (TSA) and point spread function (PSF) (TSA+PSF) were used to up-scale the vegetation temperature condition index (VTCI) retrieved from Landsat 8 images (Landsat-VTCI) from a finer...
Gespeichert in:
| Veröffentlicht in: | IOP conference series. Materials Science and Engineering 2019-07, Vol.569 (5), p.52003 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | 5 |
| container_start_page | 52003 |
| container_title | IOP conference series. Materials Science and Engineering |
| container_volume | 569 |
| creator | Bai, Xuejiao Sang, Lingzhi Bai, Guichen Kang, Hongxia Liu, Zhen |
| description | Taking the Guanzhong Plain of Shanxi Province as the research area, the combine method of trend surface analysis method (TSA) and point spread function (PSF) (TSA+PSF) were used to up-scale the vegetation temperature condition index (VTCI) retrieved from Landsat 8 images (Landsat-VTCI) from a finer resolution to a coarser resolution. The up-scaled results were compared with VTCI images retrieved from Aqua MODIS (MODIS-VTCI) to provide technical support for the comprehensive application of drought monitoring results on two spatial scales. Meanwhile, a range of indicators, such as the semivariogram function (SVF), the structural similarity (SSIM), the correlation coefficients (r), root mean square errors (RMSE) were used to systematically compared the up-scaled methods. The results show that TSA+PSF performed better than TSA in terms of SSIM, the correlation and RMSE, the up-scaling model TSA+PSF has the higher accuracy, and it is more effective and robust than TSA. The model that uses PSF to analyze trend surface constructed by TSA is an improvement for up-scaling Landsat- VTCI images from a finer resolutions to a coarser resolutions. |
| doi_str_mv | 10.1088/1757-899X/569/5/052003 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2561126276</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2561126276</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3083-c93ce42f1a872ff60a43c400a8d21aa4e00387d1bc640f57dcb6df156f6ce40b3</originalsourceid><addsrcrecordid>eNqFkE9Lw0AQxRdRsFa_ggS8eImZ3ey_HENptVBRaAvels1utqa0Sdy0Bb-9WyIVQfA0A_N7b2YeQrcYHjBImWDBRCyz7C1hPEtYAowApGdocBqcn3qJL9FV160BuKAUBojldTStW98cShst27gzelPVqyjfrBpf7d630ajZFlUdpot5HunaRq_zyTW6cHrTlTffdYiWk_Fi9BTPXh6no3wWmxRkGpssNSUlDmspiHMcNE0NBdDSEqw1LcOdUlhcGE7BMWFNwa3DjDsedFCkQ3TX-4YDP_Zlt1PrZu_rsFIRxjEmnAgeKN5Txjdd50unWl9ttf9UGNQxInX8Xh2TUCEixVQfURDe98KqaX-cn-fjX5hqrQso-QP9x_8L-MhziA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2561126276</pqid></control><display><type>article</type><title>An Inproved Up-scaling Algorithm Combined TSA and PSF</title><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Institute of Physics Open Access Journal Titles</source><source>IOPscience extra</source><source>Free Full-Text Journals in Chemistry</source><creator>Bai, Xuejiao ; Sang, Lingzhi ; Bai, Guichen ; Kang, Hongxia ; Liu, Zhen</creator><creatorcontrib>Bai, Xuejiao ; Sang, Lingzhi ; Bai, Guichen ; Kang, Hongxia ; Liu, Zhen</creatorcontrib><description>Taking the Guanzhong Plain of Shanxi Province as the research area, the combine method of trend surface analysis method (TSA) and point spread function (PSF) (TSA+PSF) were used to up-scale the vegetation temperature condition index (VTCI) retrieved from Landsat 8 images (Landsat-VTCI) from a finer resolution to a coarser resolution. The up-scaled results were compared with VTCI images retrieved from Aqua MODIS (MODIS-VTCI) to provide technical support for the comprehensive application of drought monitoring results on two spatial scales. Meanwhile, a range of indicators, such as the semivariogram function (SVF), the structural similarity (SSIM), the correlation coefficients (r), root mean square errors (RMSE) were used to systematically compared the up-scaled methods. The results show that TSA+PSF performed better than TSA in terms of SSIM, the correlation and RMSE, the up-scaling model TSA+PSF has the higher accuracy, and it is more effective and robust than TSA. The model that uses PSF to analyze trend surface constructed by TSA is an improvement for up-scaling Landsat- VTCI images from a finer resolutions to a coarser resolutions.</description><identifier>ISSN: 1757-8981</identifier><identifier>EISSN: 1757-899X</identifier><identifier>DOI: 10.1088/1757-899X/569/5/052003</identifier><language>eng</language><publisher>Bristol: IOP Publishing</publisher><subject>Algorithms ; Correlation coefficients ; Environmental monitoring ; Landsat satellites ; MODIS ; Point spread functions ; Satellite imagery ; Scaling ; Surface analysis (chemical) ; Technical services</subject><ispartof>IOP conference series. Materials Science and Engineering, 2019-07, Vol.569 (5), p.52003</ispartof><rights>Published under licence by IOP Publishing Ltd</rights><rights>2019. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c3083-c93ce42f1a872ff60a43c400a8d21aa4e00387d1bc640f57dcb6df156f6ce40b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://iopscience.iop.org/article/10.1088/1757-899X/569/5/052003/pdf$$EPDF$$P50$$Giop$$Hfree_for_read</linktopdf><link.rule.ids>315,782,786,27931,27932,38875,38897,53847,53874</link.rule.ids></links><search><creatorcontrib>Bai, Xuejiao</creatorcontrib><creatorcontrib>Sang, Lingzhi</creatorcontrib><creatorcontrib>Bai, Guichen</creatorcontrib><creatorcontrib>Kang, Hongxia</creatorcontrib><creatorcontrib>Liu, Zhen</creatorcontrib><title>An Inproved Up-scaling Algorithm Combined TSA and PSF</title><title>IOP conference series. Materials Science and Engineering</title><addtitle>IOP Conf. Ser.: Mater. Sci. Eng</addtitle><description>Taking the Guanzhong Plain of Shanxi Province as the research area, the combine method of trend surface analysis method (TSA) and point spread function (PSF) (TSA+PSF) were used to up-scale the vegetation temperature condition index (VTCI) retrieved from Landsat 8 images (Landsat-VTCI) from a finer resolution to a coarser resolution. The up-scaled results were compared with VTCI images retrieved from Aqua MODIS (MODIS-VTCI) to provide technical support for the comprehensive application of drought monitoring results on two spatial scales. Meanwhile, a range of indicators, such as the semivariogram function (SVF), the structural similarity (SSIM), the correlation coefficients (r), root mean square errors (RMSE) were used to systematically compared the up-scaled methods. The results show that TSA+PSF performed better than TSA in terms of SSIM, the correlation and RMSE, the up-scaling model TSA+PSF has the higher accuracy, and it is more effective and robust than TSA. The model that uses PSF to analyze trend surface constructed by TSA is an improvement for up-scaling Landsat- VTCI images from a finer resolutions to a coarser resolutions.</description><subject>Algorithms</subject><subject>Correlation coefficients</subject><subject>Environmental monitoring</subject><subject>Landsat satellites</subject><subject>MODIS</subject><subject>Point spread functions</subject><subject>Satellite imagery</subject><subject>Scaling</subject><subject>Surface analysis (chemical)</subject><subject>Technical services</subject><issn>1757-8981</issn><issn>1757-899X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>O3W</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNqFkE9Lw0AQxRdRsFa_ggS8eImZ3ey_HENptVBRaAvels1utqa0Sdy0Bb-9WyIVQfA0A_N7b2YeQrcYHjBImWDBRCyz7C1hPEtYAowApGdocBqcn3qJL9FV160BuKAUBojldTStW98cShst27gzelPVqyjfrBpf7d630ajZFlUdpot5HunaRq_zyTW6cHrTlTffdYiWk_Fi9BTPXh6no3wWmxRkGpssNSUlDmspiHMcNE0NBdDSEqw1LcOdUlhcGE7BMWFNwa3DjDsedFCkQ3TX-4YDP_Zlt1PrZu_rsFIRxjEmnAgeKN5Txjdd50unWl9ttf9UGNQxInX8Xh2TUCEixVQfURDe98KqaX-cn-fjX5hqrQso-QP9x_8L-MhziA</recordid><startdate>20190701</startdate><enddate>20190701</enddate><creator>Bai, Xuejiao</creator><creator>Sang, Lingzhi</creator><creator>Bai, Guichen</creator><creator>Kang, Hongxia</creator><creator>Liu, Zhen</creator><general>IOP Publishing</general><scope>O3W</scope><scope>TSCCA</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>KB.</scope><scope>L6V</scope><scope>M7S</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20190701</creationdate><title>An Inproved Up-scaling Algorithm Combined TSA and PSF</title><author>Bai, Xuejiao ; Sang, Lingzhi ; Bai, Guichen ; Kang, Hongxia ; Liu, Zhen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3083-c93ce42f1a872ff60a43c400a8d21aa4e00387d1bc640f57dcb6df156f6ce40b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Algorithms</topic><topic>Correlation coefficients</topic><topic>Environmental monitoring</topic><topic>Landsat satellites</topic><topic>MODIS</topic><topic>Point spread functions</topic><topic>Satellite imagery</topic><topic>Scaling</topic><topic>Surface analysis (chemical)</topic><topic>Technical services</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bai, Xuejiao</creatorcontrib><creatorcontrib>Sang, Lingzhi</creatorcontrib><creatorcontrib>Bai, Guichen</creatorcontrib><creatorcontrib>Kang, Hongxia</creatorcontrib><creatorcontrib>Liu, Zhen</creatorcontrib><collection>Institute of Physics Open Access Journal Titles</collection><collection>IOPscience (Open Access)</collection><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>Materials Science Database</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Materials Science Collection</collection><collection>Access via ProQuest (Open Access)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><jtitle>IOP conference series. Materials Science and Engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bai, Xuejiao</au><au>Sang, Lingzhi</au><au>Bai, Guichen</au><au>Kang, Hongxia</au><au>Liu, Zhen</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An Inproved Up-scaling Algorithm Combined TSA and PSF</atitle><jtitle>IOP conference series. Materials Science and Engineering</jtitle><addtitle>IOP Conf. Ser.: Mater. Sci. Eng</addtitle><date>2019-07-01</date><risdate>2019</risdate><volume>569</volume><issue>5</issue><spage>52003</spage><pages>52003-</pages><issn>1757-8981</issn><eissn>1757-899X</eissn><abstract>Taking the Guanzhong Plain of Shanxi Province as the research area, the combine method of trend surface analysis method (TSA) and point spread function (PSF) (TSA+PSF) were used to up-scale the vegetation temperature condition index (VTCI) retrieved from Landsat 8 images (Landsat-VTCI) from a finer resolution to a coarser resolution. The up-scaled results were compared with VTCI images retrieved from Aqua MODIS (MODIS-VTCI) to provide technical support for the comprehensive application of drought monitoring results on two spatial scales. Meanwhile, a range of indicators, such as the semivariogram function (SVF), the structural similarity (SSIM), the correlation coefficients (r), root mean square errors (RMSE) were used to systematically compared the up-scaled methods. The results show that TSA+PSF performed better than TSA in terms of SSIM, the correlation and RMSE, the up-scaling model TSA+PSF has the higher accuracy, and it is more effective and robust than TSA. The model that uses PSF to analyze trend surface constructed by TSA is an improvement for up-scaling Landsat- VTCI images from a finer resolutions to a coarser resolutions.</abstract><cop>Bristol</cop><pub>IOP Publishing</pub><doi>10.1088/1757-899X/569/5/052003</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1757-8981 |
| ispartof | IOP conference series. Materials Science and Engineering, 2019-07, Vol.569 (5), p.52003 |
| issn | 1757-8981 1757-899X |
| language | eng |
| recordid | cdi_proquest_journals_2561126276 |
| source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Institute of Physics Open Access Journal Titles; IOPscience extra; Free Full-Text Journals in Chemistry |
| subjects | Algorithms Correlation coefficients Environmental monitoring Landsat satellites MODIS Point spread functions Satellite imagery Scaling Surface analysis (chemical) Technical services |
| title | An Inproved Up-scaling Algorithm Combined TSA and PSF |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-04T16%3A40%3A38IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=An%20Inproved%20Up-scaling%20Algorithm%20Combined%20TSA%20and%20PSF&rft.jtitle=IOP%20conference%20series.%20Materials%20Science%20and%20Engineering&rft.au=Bai,%20Xuejiao&rft.date=2019-07-01&rft.volume=569&rft.issue=5&rft.spage=52003&rft.pages=52003-&rft.issn=1757-8981&rft.eissn=1757-899X&rft_id=info:doi/10.1088/1757-899X/569/5/052003&rft_dat=%3Cproquest_cross%3E2561126276%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2561126276&rft_id=info:pmid/&rfr_iscdi=true |