Journal
REMOTE SENSING
Volume 12, Issue 3, Pages -Publisher
MDPI
DOI: 10.3390/rs12030387
Keywords
unmanned aircraft vehicle; remote sensing; vegetation index; aquatic plants; GIS; multi-spectral
Categories
Funding
- National Research Foundation of Korea (NRF) - Ministry of Education [NRF-2019R1I1A1A01063568]
- Korea Ministry of Environment as Waste to Energy-Recycling Human Resource Development Project [YL-WE-19-001]
- National Research Foundation of Korea [31Z20130012924] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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In this study, aquatic plants in a small reservoir were detected using multispectral UAV (Unmanned Aerial Vehicle) imagery and various vegetation indices. A Firefly UAV, which has both fixed-wing and rotary-wing flight modes, was flown over the study site four times. A RedEdge camera was mounted on the UAV to acquire multispectral images. These images were used to analyze the NDVI (Normalized Difference Vegetation Index), ENDVI (Enhance Normalized Difference Vegetation Index), NDREI (Normalized Difference RedEdge Index), NGRDI (Normalized Green-Red Difference Index), and GNDVI (Green Normalized Difference Vegetation Index). As for multispectral characteristics, waterside plants showed the highest reflectance in R-nir, while floating plants had a higher reflectance in R-re. During the hottest season (on 25 June), the vegetation indices were the highest, and the habitat expanded near the edge of the reservoir. Among the vegetation indices, NDVI was the highest and NGRDI was the lowest. In particular, NGRDI had a higher value on the water surface and was not useful for detecting aquatic plants. NDVI and GNDVI, which showed the clearest difference between aquatic plants and water surface, were determined to be the most effective vegetation indices for detecting aquatic plants. Accordingly, the vegetation indices using multispectral UAV imagery turned out to be effective for detecting aquatic plants. A further study will be accompanied by a field survey in order to acquire and analyze more accurate imagery information.
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