A new synergistic approach for monitoring wetlands using Sentinels -1 and 2 data with object-based machine learning algorithms

In this work the synergistic use of Sentinel-1 and 2 combined with the System for Automated Geoscientific Analyses (SAGA) Wetness Index in the content of land use/cover (LULC) mapping with emphasis in wetlands is evaluated. A further objective has been to develop a new Object-based Image Analysis (O...

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Vydáno v:	Environmental modelling & software : with environment data news Ročník 104; s. 40 - 54
Hlavní autoři:	Whyte, Andrew, Ferentinos, Konstantinos P., Petropoulos, George P.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Oxford Elsevier Ltd 01.06.2018 Elsevier Science Ltd
Témata:	Algorithms Array processors Artificial intelligence automation Classification data collection Image analysis Image processing Image segmentation Land cover Land use land use and land cover maps Learning algorithms Machine learning Mapping Moisture content monitoring Object-based classification Random access memory Random Forests Sentinel-1 Sentinel-2 Statistical analysis Support Vector Machines Wetlands Random Forests Support Vector Machines Sentinel-1 Object-based classification Sentinel-2
ISSN:	1364-8152, 1873-6726
On-line přístup:	Získat plný text
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