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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...

Täydet tiedot

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Bibliografiset tiedot
Päätekijät: H. Wang, Y. Zhao, R. Pu, Z. Zhang
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: Copernicus Publications 2016-10-01
Sarja:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Linkit: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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