Innovative spectral library for identification common wild plants using hyperspectral technology in Northwestern Coast, Egypt
Many wild and medicinal plants today face extinction but the information is lacking in detail. For this mapping and identification of natural vegetation are main issues for biodiversity management. It could be concluded that hyperspectral remote sensing techniques is effective valuable in identifica...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2021-12-01
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| Series: | Egyptian Journal of Remote Sensing and Space Sciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110982320302015 |
| Summary: | Many wild and medicinal plants today face extinction but the information is lacking in detail. For this mapping and identification of natural vegetation are main issues for biodiversity management. It could be concluded that hyperspectral remote sensing techniques is effective valuable in identification and conservation of wild plants in northwest coast of Egypt. This current work aims to establish a spectral library for identification and studying spectral characteristics of common plants in northwestern coast of Egypt. Such library will support characterization of wild plants in study area, in addition to enhancing wild plants observation by remote sensing. A field spectroradiometer was used to measure the spectral reflectance pattern for 27 important plant species along the North West coast of Egypt. The spectral library was created; based on measured spectral reflectance values in order to identify common wild plant species spectrally. The optimal spectral zones and waveband/s to discriminate between the different species were identified. Numbers of vegetation indices have been extracted and calculated from spectrometric analysis to assess the vitality of canopy. The study produced an updated map for the spatial distribution of all investigated wild plants along the study area. The results of Tukey’s analyses showed that NIR and SWIRII spectral zones are the best zones for the discrimination between plants. It was found that Normalized Difference Vegetation Index (NDVI) high correlated with Red Edge Normalized Difference Vegetation Index (RENDVI). Results indicate that studying of spectral characteristics of the different plants in the study area were a necessary step to identify the locations of the important and economically valued plants. |
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| ISSN: | 1110-9823 |