An interactive tool for semi-automatic feature extraction of hyperspectral data
The spectral reflectance of the surface provides valuable information about the environment, which can be used to identify objects (e.g. land cover classification) or to estimate quantities of substances (e.g. biomass). We aimed to develop an MS Excel add-in – Hyperspectral Data Analyst (HypDA) – fo...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2016-09-01
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| Series: | Open Geosciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/geo-2016-0040 |
| _version_ | 1818649895941177344 |
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| author | Kovács Zoltán Szabó Szilárd |
| author_facet | Kovács Zoltán Szabó Szilárd |
| author_sort | Kovács Zoltán |
| collection | DOAJ |
| description | The spectral reflectance of the surface provides valuable information about the environment, which can be used to identify objects (e.g. land cover classification) or to estimate quantities of substances (e.g. biomass). We aimed to develop an MS Excel add-in – Hyperspectral Data Analyst (HypDA) – for a multipurpose quantitative analysis of spectral data in VBA programming language. HypDA was designed to calculate spectral indices from spectral data with user defined formulas (in all possible combinations involving a maximum of 4 bands) and to find the best correlations between the quantitative attribute data of the same object. Different types of regression models reveal the relationships, and the best results are saved in a worksheet. Qualitative variables can also be involved in the analysis carried out with separability and hypothesis testing; i.e. to find the wavelengths responsible for separating data into predefined groups. HypDA can be used both with hyperspectral imagery and spectrometer measurements. This bivariate approach requires significantly fewer observations than popular multivariate methods; it can therefore be applied to a wide range of research areas. |
| first_indexed | 2024-12-17T01:41:36Z |
| format | Article |
| id | doaj.art-c72ca2d00c0e419384246928c7932e91 |
| institution | Directory Open Access Journal |
| issn | 2391-5447 |
| language | English |
| last_indexed | 2024-12-17T01:41:36Z |
| publishDate | 2016-09-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Open Geosciences |
| spelling | doaj.art-c72ca2d00c0e419384246928c7932e912022-12-21T22:08:19ZengDe GruyterOpen Geosciences2391-54472016-09-018149350210.1515/geo-2016-0040geo-2016-0040An interactive tool for semi-automatic feature extraction of hyperspectral dataKovács Zoltán0Szabó Szilárd1Department of Physical Geography and Geoinformation Systems, University of Debrecen, Debrecen, HungaryDepartment of Physical Geography and Geoinformation Systems, University of Debrecen, Debrecen, HungaryThe spectral reflectance of the surface provides valuable information about the environment, which can be used to identify objects (e.g. land cover classification) or to estimate quantities of substances (e.g. biomass). We aimed to develop an MS Excel add-in – Hyperspectral Data Analyst (HypDA) – for a multipurpose quantitative analysis of spectral data in VBA programming language. HypDA was designed to calculate spectral indices from spectral data with user defined formulas (in all possible combinations involving a maximum of 4 bands) and to find the best correlations between the quantitative attribute data of the same object. Different types of regression models reveal the relationships, and the best results are saved in a worksheet. Qualitative variables can also be involved in the analysis carried out with separability and hypothesis testing; i.e. to find the wavelengths responsible for separating data into predefined groups. HypDA can be used both with hyperspectral imagery and spectrometer measurements. This bivariate approach requires significantly fewer observations than popular multivariate methods; it can therefore be applied to a wide range of research areas.https://doi.org/10.1515/geo-2016-0040hyperspectral dataspectral profilereflectanceregressionhypothesis testingseparability indices |
| spellingShingle | Kovács Zoltán Szabó Szilárd An interactive tool for semi-automatic feature extraction of hyperspectral data Open Geosciences hyperspectral data spectral profile reflectance regression hypothesis testing separability indices |
| title | An interactive tool for semi-automatic feature extraction of hyperspectral data |
| title_full | An interactive tool for semi-automatic feature extraction of hyperspectral data |
| title_fullStr | An interactive tool for semi-automatic feature extraction of hyperspectral data |
| title_full_unstemmed | An interactive tool for semi-automatic feature extraction of hyperspectral data |
| title_short | An interactive tool for semi-automatic feature extraction of hyperspectral data |
| title_sort | interactive tool for semi automatic feature extraction of hyperspectral data |
| topic | hyperspectral data spectral profile reflectance regression hypothesis testing separability indices |
| url | https://doi.org/10.1515/geo-2016-0040 |
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