SATELLITE AND UNMANNED AERIAL VEHICLE DATA FOR THE CLASSIFICATION OF SAND DUNE VEGETATION
| Autor: | N. Merloni, Maurizio Barbarella, Floriano Goffo, Marco Dubbini, Nicolas Greggio, M. De Giglio |
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| Přispěvatelé: | De Giglio, M., Goffo, F., Greggio, N., Merloni, N., Dubbini, M., Barbarella, M. |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
lcsh:Applied optics. Photonics
010504 meteorology & atmospheric sciences Vegetation classification Geography Planning and Development Multispectral image Image processing Information System 010502 geochemistry & geophysics 01 natural sciences lcsh:Technology Sand dune stabilization Object-based classification Pixel-based classification 0105 earth and related environmental sciences Remote sensing Sand dune Pixel lcsh:T Orthophoto lcsh:TA1501-1820 Unmanned aerial vehicle Coastal vegetation WorldView2 Habitat lcsh:TA1-2040 Threatened species lcsh:Engineering (General). Civil engineering (General) Geology |
| Zdroj: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-3-W2, Pp 43-50 (2017) |
| ISSN: | 2194-9034 1682-1750 |
| Popis: | Within coastal systems, sand dunes are the only natural barriers able to counteract erosive processes. Since their equilibrium is often threatened by human activities and high vulnerability of the coastal environment, dunes require increasing attention and specific monitoring. Located between the mainland and the sea, dunes are unique residue habitats for some plant and animal species. In particular, their vegetation is important because it has a consolidation function and promotes the vertical dune accretion. A georeferenced vegetation classification can be useful to define the advancements or erosion stage of the dune, usually based only on the geometric reconstruction. The proposed study aims to compare the classifications performed with some combinations of two of the last generation sensors and traditional image processing techniques. High spectral resolution satellite image (WorldView-2) and a multispectral orthophoto, obtained from data acquired by an unmanned aerial vehicle, were used. Objects and pixel algorithms were applied and the results were compared by a statistical test. Using the same bands, the findings show that both data are suitable for monitoring the evolutionary dune status. Specifically, the WorldView-2 pixel-based classification and UAV object-based classification provide the same accurate results. |
| Databáze: | OpenAIRE |
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