Q-DAI: design and implementation of a QGIS plugin for disaggregation of soil moisture content at 30 m spatial resolution.
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| Title: | Q-DAI: design and implementation of a QGIS plugin for disaggregation of soil moisture content at 30 m spatial resolution. |
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| Authors: | Nawandar, Neha K., Sen, Shaunak1, Janardhanan, S.1 janas@ee.iitd.ac.in |
| Source: | Current Science (00113891). 8/25/2024, Vol. 127 Issue 4, p432-437. 6p. |
| Subjects: | Soil moisture, Plug-ins (Computer programs), Geographic information system software, Spatial resolution, Graphical user interfaces |
| Geographic Terms: | Ventura (Calif.), Delhi (India) |
| Abstract: | Soil moisture content (SMC) plays a significant role in land surface water and energy cycle and is essential in performing various field-related studies. It is a crucial parameter provided by passive L-band sensors on soil moisture active passive/soil moisture ocean salinity satellite missions at a resolution of ~36–40 km. To obtain inference from the SMC data and apply it to different applications, its study and analysis are required that is achievable using any geographic information systems software. Quantum Geographic Information System (QGIS) is an open-source software with a user-friendly graphical user interface (GUI) and a repository of application-specific plugins. However, no plugin provides SMC or downscales the SMC product for a required location. Q-Daily Arial Image (Q-DAI), the QGIS plugin proposed here, implements a downscaling algorithm to obtain the low-resolution SMC product from SMAP/SMOS at fine resolution using inputs from high-resolution satellite imagery. The plugin is developed by designing a GUI using Qt Creator and defining its functionality using Python. Q-DAI is tested on QGIS 3.16.16 on Windows 10, 8 GB RAM PC and QGIS 3.22 on a macOS Ventura laptop. Q-DAI can be used to obtain high-resolution SMC for any location, and in this article, sample results of Q-DAI implemented for Delhi region data have been shown. [ABSTRACT FROM AUTHOR] |
| Copyright of Current Science (00113891) is the property of Indian Academy of Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 179221621 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Q-DAI: design and implementation of a QGIS plugin for disaggregation of soil moisture content at 30 m spatial resolution. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Nawandar%2C+Neha+K%2E%22">Nawandar, Neha K.</searchLink><br /><searchLink fieldCode="AR" term="%22Sen%2C+Shaunak%22">Sen, Shaunak</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Janardhanan%2C+S%2E%22">Janardhanan, S.</searchLink><relatesTo>1</relatesTo><i> janas@ee.iitd.ac.in</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Current+Science+%2800113891%29%22">Current Science (00113891)</searchLink>. 8/25/2024, Vol. 127 Issue 4, p432-437. 6p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Soil+moisture%22">Soil moisture</searchLink><br /><searchLink fieldCode="DE" term="%22Plug-ins+%28Computer+programs%29%22">Plug-ins (Computer programs)</searchLink><br /><searchLink fieldCode="DE" term="%22Geographic+information+system+software%22">Geographic information system software</searchLink><br /><searchLink fieldCode="DE" term="%22Spatial+resolution%22">Spatial resolution</searchLink><br /><searchLink fieldCode="DE" term="%22Graphical+user+interfaces%22">Graphical user interfaces</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Ventura+%28Calif%2E%29%22">Ventura (Calif.)</searchLink><br /><searchLink fieldCode="DE" term="%22Delhi+%28India%29%22">Delhi (India)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Soil moisture content (SMC) plays a significant role in land surface water and energy cycle and is essential in performing various field-related studies. It is a crucial parameter provided by passive L-band sensors on soil moisture active passive/soil moisture ocean salinity satellite missions at a resolution of ~36–40 km. To obtain inference from the SMC data and apply it to different applications, its study and analysis are required that is achievable using any geographic information systems software. Quantum Geographic Information System (QGIS) is an open-source software with a user-friendly graphical user interface (GUI) and a repository of application-specific plugins. However, no plugin provides SMC or downscales the SMC product for a required location. Q-Daily Arial Image (Q-DAI), the QGIS plugin proposed here, implements a downscaling algorithm to obtain the low-resolution SMC product from SMAP/SMOS at fine resolution using inputs from high-resolution satellite imagery. The plugin is developed by designing a GUI using Qt Creator and defining its functionality using Python. Q-DAI is tested on QGIS 3.16.16 on Windows 10, 8 GB RAM PC and QGIS 3.22 on a macOS Ventura laptop. Q-DAI can be used to obtain high-resolution SMC for any location, and in this article, sample results of Q-DAI implemented for Delhi region data have been shown. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Current Science (00113891) is the property of Indian Academy of Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.18520/cs/v127/i4/432-437 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 6 StartPage: 432 Subjects: – SubjectFull: Soil moisture Type: general – SubjectFull: Plug-ins (Computer programs) Type: general – SubjectFull: Geographic information system software Type: general – SubjectFull: Spatial resolution Type: general – SubjectFull: Graphical user interfaces Type: general – SubjectFull: Ventura (Calif.) Type: general – SubjectFull: Delhi (India) Type: general Titles: – TitleFull: Q-DAI: design and implementation of a QGIS plugin for disaggregation of soil moisture content at 30 m spatial resolution. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Nawandar, Neha K. – PersonEntity: Name: NameFull: Sen, Shaunak – PersonEntity: Name: NameFull: Janardhanan, S. IsPartOfRelationships: – BibEntity: Dates: – D: 25 M: 08 Text: 8/25/2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 00113891 Numbering: – Type: volume Value: 127 – Type: issue Value: 4 Titles: – TitleFull: Current Science (00113891) Type: main |
| ResultId | 1 |
