A combination of Sentinel-1 RADAR and Sentinel-2 multispectral data improves classification of morphologically similar savanna woody plants

The co-existence of diverse plant forms in densely vegetated savanna environments presents a challenge when mapping species diversity using single remotely sensed data type that carries either optical or structural information. In the present study, Sentinel-1 RADAR and Sentinel-2 multispectral da...

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Veröffentlicht in:	European journal of remote sensing Jg. 55; H. 1; S. 372 - 387
Hauptverfasser:	Fundisi, Emmanuel, Tesfamichael, Solomon G., Ahmed, Fethi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Cagiari Taylor & Francis 31.12.2022 Taylor & Francis Ltd Taylor & Francis Group
Schlagworte:	Accuracy Artificial neural networks Biodiversity C band Classification data fusion Deep Neural Network algorithm Environmental management Flowers & plants Image classification Land cover Neural networks Plant species Plants (botany) Radar Radar data Rain Remote sensing Remote sensing systems Savanna Savannahs Sentinel-1 C-band Sentinel-2 Short wave radiation Species diversity Vegetation woody plant species diversity Woody plants
ISSN:	2279-7254, 2279-7254
Online-Zugang:	Volltext
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