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Seasonal separation of African savanna components using Worldview-2 imagery: a comparison of pixel- and object-based approaches and selected classification algorithms

Abstract:

Separation of savanna land cover components is challenging due to the high heterogeneity of this landscape and spectral similarity of compositionally different vegetation types. In this study, we tested the usability of very high spatial and spectral resolution WorldView-2 (WV-2) imagery to classify land cover components of African savanna in wet and dry season. We compared the performance of Object-Based Image Analysis (OBIA) and pixel-based approach with several algorithms: k-nearest neighb...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.3390/rs8090763

Authors


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Institution:
University of Oxford
Division:
MPLS Division
Department:
Zoology
Role:
Author
ORCID:
0000-0002-9361-0224
Publisher:
MDPI
Journal:
Remote Sensing More from this journal
Volume:
8
Issue:
9
Article number:
763
Publication date:
2016-09-16
Acceptance date:
2016-09-08
DOI:
EISSN:
2072-4292
ISSN:
2072-4292
Language:
English
Keywords:
Pubs id:
pubs:709185
UUID:
uuid:9b949254-633a-457d-86f7-cf67365c2576
Local pid:
pubs:709185
Source identifiers:
709185
Deposit date:
2019-10-10

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