Mapping an invasive goldenrod of Solidago altissima in urban landscape of Japan using multi-scale remote sensing and knowledge-based classification
An invasive goldenrod, Solidago altissima, is abundant in urban environment of Japan and a threat to native biodiversity. Aerial remote sensing approach would be useful for effective monitoring and management of the species. However, it is challenging for remote sensing technique to detect a specifi...
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| Format: | Article |
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Elsevier B. V.
2020
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| _version_ | 1796864394911547392 |
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| author | Mahmud, Mohd. Rizaludin Shinya, Numata Tetsuro, Hosaka |
| author_facet | Mahmud, Mohd. Rizaludin Shinya, Numata Tetsuro, Hosaka |
| author_sort | Mahmud, Mohd. Rizaludin |
| collection | ePrints |
| description | An invasive goldenrod, Solidago altissima, is abundant in urban environment of Japan and a threat to native biodiversity. Aerial remote sensing approach would be useful for effective monitoring and management of the species. However, it is challenging for remote sensing technique to detect a specific single plant species with a small crown and population size in highly heterogeneous urban environments. This study investigated the ability to upscale the in-situ hyperspectral reflectance signature obtained at crown level for landscape scale detection. Field hyperspectral sensors were used to obtain the spectral signatures of Solidago altissima and its surrounding features at crown scale (5 cm × 5 cm, instantaneous field of view (IFOV)). By using the first derivative analysis, the hyperspectral indices namely SAFI (S. altissima flower index) was developed based on the sensitive and peak reflectance of full blooming flower. This index was subsequently applied to identify the blooming S. altissima at population scale (1 m × 1 m) and landscape scale (5 m × 5 m) using field hyperspectral sensor and satellite data respectively. The results at crown scale showed that SAFI was able to discriminate S. altissima from their surrounding features with average probability of 72%. At the population scale with (1 m plot), SAFI can discriminate plot with different S. altissima flower distribution starting from 45%dominance. At landscape scale, effective detection was found at SAFI value over 0.3 to 0.5. The sites which hadhigh SAFI values but no actual presence of S. altissima were often under intensive land management such as frequent mowing. We conclude that the detection of S. altissima distribution at landscape scale by direct upscaling crown scale hyperspectral signature was possible using high resolution satellite image with availability of green(~480 nm) and yellow (~600 nm) spectrum bands at fine resolution (~5 m). The detection, however, were influenced by the phenology state of the flowering stages, community size and adjacent plant that possesses similar carotenoid characteristics. |
| first_indexed | 2024-03-05T20:41:13Z |
| format | Article |
| id | utm.eprints-87202 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T20:41:13Z |
| publishDate | 2020 |
| publisher | Elsevier B. V. |
| record_format | dspace |
| spelling | utm.eprints-872022020-10-31T12:26:41Z http://eprints.utm.my/87202/ Mapping an invasive goldenrod of Solidago altissima in urban landscape of Japan using multi-scale remote sensing and knowledge-based classification Mahmud, Mohd. Rizaludin Shinya, Numata Tetsuro, Hosaka G70.39-70.6 Remote sensing An invasive goldenrod, Solidago altissima, is abundant in urban environment of Japan and a threat to native biodiversity. Aerial remote sensing approach would be useful for effective monitoring and management of the species. However, it is challenging for remote sensing technique to detect a specific single plant species with a small crown and population size in highly heterogeneous urban environments. This study investigated the ability to upscale the in-situ hyperspectral reflectance signature obtained at crown level for landscape scale detection. Field hyperspectral sensors were used to obtain the spectral signatures of Solidago altissima and its surrounding features at crown scale (5 cm × 5 cm, instantaneous field of view (IFOV)). By using the first derivative analysis, the hyperspectral indices namely SAFI (S. altissima flower index) was developed based on the sensitive and peak reflectance of full blooming flower. This index was subsequently applied to identify the blooming S. altissima at population scale (1 m × 1 m) and landscape scale (5 m × 5 m) using field hyperspectral sensor and satellite data respectively. The results at crown scale showed that SAFI was able to discriminate S. altissima from their surrounding features with average probability of 72%. At the population scale with (1 m plot), SAFI can discriminate plot with different S. altissima flower distribution starting from 45%dominance. At landscape scale, effective detection was found at SAFI value over 0.3 to 0.5. The sites which hadhigh SAFI values but no actual presence of S. altissima were often under intensive land management such as frequent mowing. We conclude that the detection of S. altissima distribution at landscape scale by direct upscaling crown scale hyperspectral signature was possible using high resolution satellite image with availability of green(~480 nm) and yellow (~600 nm) spectrum bands at fine resolution (~5 m). The detection, however, were influenced by the phenology state of the flowering stages, community size and adjacent plant that possesses similar carotenoid characteristics. Elsevier B. V. 2020 Article PeerReviewed Mahmud, Mohd. Rizaludin and Shinya, Numata and Tetsuro, Hosaka (2020) Mapping an invasive goldenrod of Solidago altissima in urban landscape of Japan using multi-scale remote sensing and knowledge-based classification. Ecological Indicators, 111 . p. 105975. ISSN 1470-160X http://dx.doi.org/10.1016/j.ecolind.2019.105975 |
| spellingShingle | G70.39-70.6 Remote sensing Mahmud, Mohd. Rizaludin Shinya, Numata Tetsuro, Hosaka Mapping an invasive goldenrod of Solidago altissima in urban landscape of Japan using multi-scale remote sensing and knowledge-based classification |
| title | Mapping an invasive goldenrod of Solidago altissima in urban landscape of Japan using multi-scale remote sensing and knowledge-based classification |
| title_full | Mapping an invasive goldenrod of Solidago altissima in urban landscape of Japan using multi-scale remote sensing and knowledge-based classification |
| title_fullStr | Mapping an invasive goldenrod of Solidago altissima in urban landscape of Japan using multi-scale remote sensing and knowledge-based classification |
| title_full_unstemmed | Mapping an invasive goldenrod of Solidago altissima in urban landscape of Japan using multi-scale remote sensing and knowledge-based classification |
| title_short | Mapping an invasive goldenrod of Solidago altissima in urban landscape of Japan using multi-scale remote sensing and knowledge-based classification |
| title_sort | mapping an invasive goldenrod of solidago altissima in urban landscape of japan using multi scale remote sensing and knowledge based classification |
| topic | G70.39-70.6 Remote sensing |
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