Location- and Time-Specific Hydrological Simulations with Multi-Resolution Remote Sensing Data in Urban Areas.
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| Title: | Location- and Time-Specific Hydrological Simulations with Multi-Resolution Remote Sensing Data in Urban Areas. |
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| Authors: | Wirion, Charlotte1 Charlotte.Wirion@vub.ac.be, Bauwens, Willy1 wbauwens@vub.ac.be, Verbeiren, Boud1 Boud.Verbeiren@vub.ac.be |
| Source: | Remote Sensing. Jul2017, Vol. 9 Issue 7, p645. 18p. |
| Subjects: | Remote sensing, Multiresolution time-domain method, Hydrologic models, Vegetation mapping, Water management |
| Abstract: | A major challenge in hydrologic modeling remains the mapping of vegetation dynamics in an urban landscape. The impact of vegetation on interception storage varies over time and needs to be quantified in order to enable proper management of water resources in urban areas. However, the heterogeneity and complexity of the urban landscape makes it challenging to monitor urban vegetation. A more detailed spatial and temporal scale is needed. To characterize surface cover at a high spatial resolution, a hyperspectral APEX image (2 m) is used, while a time series of Proba-V images (daily, 100 m) allows a detailed characterization of the seasonal variation of urban greenness. For this study, we use and validate the leaf area index (LAI) maps derived from APEX and Proba-V data for a selected pixel in the Watermaelbeek catchment in Brussels (Belgium). The ground-truthing of the Proba-V pixels includes a detailed mapping of land cover characteristics and more specifically vegetation cover throughout the seasons. LAI values calculated based on the APEX image agree with the LAI values measured from the ground (n = 106, R2 = 0.68). Further, the aggregated APEX pixels correlate with the Proba-V pixels (R2 = 0.79), and the Proba-V data can be used to monitor vegetation dynamics. As the seasonal LAI measurements correspond with the Proba-V dynamics, we conclude that Proba-V images allow the characterization of vegetation dynamics at a high spatial resolution in heterogeneous areas. We create a time series of LAI maps at a high resolution (2 m), which allows a location- and time-specific simulation of interception storage and thus contributes to managing water resources in urban areas. [ABSTRACT FROM AUTHOR] |
| Copyright of Remote Sensing is the property of MDPI 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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| Items | – Name: Title Label: Title Group: Ti Data: Location- and Time-Specific Hydrological Simulations with Multi-Resolution Remote Sensing Data in Urban Areas. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Wirion%2C+Charlotte%22">Wirion, Charlotte</searchLink><relatesTo>1</relatesTo><i> Charlotte.Wirion@vub.ac.be</i><br /><searchLink fieldCode="AR" term="%22Bauwens%2C+Willy%22">Bauwens, Willy</searchLink><relatesTo>1</relatesTo><i> wbauwens@vub.ac.be</i><br /><searchLink fieldCode="AR" term="%22Verbeiren%2C+Boud%22">Verbeiren, Boud</searchLink><relatesTo>1</relatesTo><i> Boud.Verbeiren@vub.ac.be</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Jul2017, Vol. 9 Issue 7, p645. 18p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Remote+sensing%22">Remote sensing</searchLink><br /><searchLink fieldCode="DE" term="%22Multiresolution+time-domain+method%22">Multiresolution time-domain method</searchLink><br /><searchLink fieldCode="DE" term="%22Hydrologic+models%22">Hydrologic models</searchLink><br /><searchLink fieldCode="DE" term="%22Vegetation+mapping%22">Vegetation mapping</searchLink><br /><searchLink fieldCode="DE" term="%22Water+management%22">Water management</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: A major challenge in hydrologic modeling remains the mapping of vegetation dynamics in an urban landscape. The impact of vegetation on interception storage varies over time and needs to be quantified in order to enable proper management of water resources in urban areas. However, the heterogeneity and complexity of the urban landscape makes it challenging to monitor urban vegetation. A more detailed spatial and temporal scale is needed. To characterize surface cover at a high spatial resolution, a hyperspectral APEX image (2 m) is used, while a time series of Proba-V images (daily, 100 m) allows a detailed characterization of the seasonal variation of urban greenness. For this study, we use and validate the leaf area index (LAI) maps derived from APEX and Proba-V data for a selected pixel in the Watermaelbeek catchment in Brussels (Belgium). The ground-truthing of the Proba-V pixels includes a detailed mapping of land cover characteristics and more specifically vegetation cover throughout the seasons. LAI values calculated based on the APEX image agree with the LAI values measured from the ground (n = 106, R2 = 0.68). Further, the aggregated APEX pixels correlate with the Proba-V pixels (R2 = 0.79), and the Proba-V data can be used to monitor vegetation dynamics. As the seasonal LAI measurements correspond with the Proba-V dynamics, we conclude that Proba-V images allow the characterization of vegetation dynamics at a high spatial resolution in heterogeneous areas. We create a time series of LAI maps at a high resolution (2 m), which allows a location- and time-specific simulation of interception storage and thus contributes to managing water resources in urban areas. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Remote Sensing is the property of MDPI 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: 10.3390/rs9070645 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 18 StartPage: 645 Subjects: – SubjectFull: Remote sensing Type: general – SubjectFull: Multiresolution time-domain method Type: general – SubjectFull: Hydrologic models Type: general – SubjectFull: Vegetation mapping Type: general – SubjectFull: Water management Type: general Titles: – TitleFull: Location- and Time-Specific Hydrological Simulations with Multi-Resolution Remote Sensing Data in Urban Areas. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Wirion, Charlotte – PersonEntity: Name: NameFull: Bauwens, Willy – PersonEntity: Name: NameFull: Verbeiren, Boud IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 07 Text: Jul2017 Type: published Y: 2017 Identifiers: – Type: issn-print Value: 20724292 Numbering: – Type: volume Value: 9 – Type: issue Value: 7 Titles: – TitleFull: Remote Sensing Type: main |
| ResultId | 1 |
