Pattern Recognition of Forest Vegetation from Hyperspectral Airborne and Multichannel Satellite Data of High Spatial Resolution: Comparison of Results and Estimation of Their Accuracy
| Autor: | V. D. Egorov, V. V. Kozoderov |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Atmospheric Science
010504 meteorology & atmospheric sciences business.industry Hyperspectral imaging Pattern recognition Oceanography 01 natural sciences Remote sensing (archaeology) Satellite data 0103 physical sciences Pattern recognition (psychology) Recognition system High spatial resolution Range (statistics) Forest vegetation Environmental science Artificial intelligence business 010303 astronomy & astrophysics 0105 earth and related environmental sciences |
| Zdroj: | Izvestiya, Atmospheric and Oceanic Physics. 56:1146-1158 |
| ISSN: | 1555-628X 0001-4338 |
| Popis: | The pattern recognition of a forest surface from remote sensing data (both airborne hyperspectral data and WorldView-2 multichannel satellite data of high spatial resolution) is investigated. Calculations have been performed using both the method developed earlier by the authors and the standard statistical approach. For three fragments of the forest surface, the range of changes in the accuracy of recognition calculations has been estimated for both airborne and satellite data, depending on the use of different databases developed for the recognition system. Some features of the pattern recognition of the underlying surface are discussed on the basis of both hyperspectral airborne data and multichannel satellite data of high spatial resolution. |
| Databáze: | OpenAIRE |
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