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MAPPING ROBINIA PSEUDOACACIA FOREST HEALTH CONDITIONS BY USING COMBINED SPECTRAL, SPATIAL AND TEXTUREAL INFORMATION EXTRACTED FROM IKONOS IMAGERY
In this study grey-level co-occurrence matrix (GLCM) textures and a local statistical analysis Getis statistic (Gi), computed from IKONOS multispectral (MS) imagery acquired from the Yellow River Delta in China, along with a random forest (RF) classifier, were used to discriminate <i>Robina ps...
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| Главные авторы: | , , , |
|---|---|
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Copernicus Publications
2016-10-01
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| Серии: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online-ссылка: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B8/1425/2016/isprs-archives-XLI-B8-1425-2016.pdf |
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