OTB-Users-Day-2018.md

@@ -37,7 +37,8 @@ The morning session will be dedicated to short talks from users and contributors
 * SAR Sentinel-1 images pre-processing : a processing chain in Python, based upon OTB.
 * Deforestation map in French Guyana, using OTB through QGIS scripts.
 * Integration of OTB in remote platform
-* Automatic segmentation of Loire habitats: Example of the islands of the Mareaux-aux-Prés National Nature Reserve. [comment]: <> (Monitoring vegetation dynamics in nature reserves requires accurate mapping of habitats. In August 2017, we used a drone to acquire LAS images and high-resolution (2cm)orthophotos on islands of nature reserve of St-Mesmin along the Loire river. At the same time, we mapped habitats based on vegetation sampling every 15 m and the phytosociological nomenclature published by the Botanical Conservatory of the Paris Basin. The OTB workflow allowed us to map 9 vegetation types but with an overall kappa of 0.60 only. If the results were satisfactory for the differents ripparian forest types (min F-score = 0.70) , the various tools tested under OTB failed to correctly classify open areas as reed-bed (F-score = 0.31) and grassland (F-score = 0.18). Two hypotheses can explain this problem: the low accuracy of the field GPS data and some subjectivity in the interpretation of the phytosociological nomenclature.)
+* Automatic segmentation of Loire habitats: Example of the islands of the Mareaux-aux-Prés National Nature Reserve. 
+[comment]: <> (Monitoring vegetation dynamics in nature reserves requires accurate mapping of habitats. In August 2017, we used a drone to acquire LAS images and high-resolution (2cm)orthophotos on islands of nature reserve of St-Mesmin along the Loire river. At the same time, we mapped habitats based on vegetation sampling every 15 m and the phytosociological nomenclature published by the Botanical Conservatory of the Paris Basin. The OTB workflow allowed us to map 9 vegetation types but with an overall kappa of 0.60 only. If the results were satisfactory for the differents ripparian forest types (min F-score = 0.70) , the various tools tested under OTB failed to correctly classify open areas as reed-bed (F-score = 0.31) and grassland (F-score = 0.18). Two hypotheses can explain this problem: the low accuracy of the field GPS data and some subjectivity in the interpretation of the phytosociological nomenclature.)
 
 ## 10:30 - 10:50 : Coffee break