Authors
Martin Karlson, Madelene Ostwald, Heather Reese, Hugues Roméo Bazié, Boalidioa Tankoano
Publication date
2016/8/1
Journal
International Journal of Applied Earth Observation and Geoinformation
Volume
50
Pages
80-88
Publisher
Elsevier
Description
High resolution satellite systems enable efficient and detailed mapping of tree cover, with high potential to support both natural resource monitoring and ecological research. This study investigates the capability of multi-seasonal WorldView-2 imagery to map five dominant tree species at the individual tree crown level in a parkland landscape in central Burkina Faso. The Random Forest algorithm is used for object based tree species classification and for assessing the relative importance of WorldView-2 predictors. The classification accuracies from using wet season, dry season and multi-seasonal datasets are compared to gain insights about the optimal timing for image acquisition. The multi-seasonal dataset produced the most accurate classifications, with an overall accuracy (OA) of 83.4%. For classifications based on single date imagery, the dry season (OA = 78.4%) proved to be more suitable than the wet …
Total citations
20162017201820192020202120222023202414131523141393
Scholar articles
M Karlson, M Ostwald, H Reese, HR Bazié… - International Journal of Applied Earth Observation and …, 2016