OTB-Users-Day-2018.md

@@ -62,6 +62,9 @@ This open source tool box is mainly based on Orfeo ToolBox for Sentinel-1 pre-pr
 > For 5 years now, CEREMA's satellite team is engaged in designing a large scale land cover map by supervised classification coupled with specific database processing. In order to follow public policy in territorial planning, these maps over several acquisition dates are compared to detect land change and monitor the landscape. Because of uncertainty of each measurement, the comparison introduces a lot of over-detection. These differences have to be filtered to identify relevant ground change.
 > Since OTB's latest version offers a function to produce confidence map linked to classification, it has been tested to characterize difference areas. This experimentation shows how this map, representing classification algorithm capability, cannot directly be used as a quality layer and must be upgraded to become suitable for thematic users.
 
+* **[CONFIRMED]** Classification of tree species from MODIS temporal series (Jean-Philippe Denux, DYNAFOR)
+
+> Time series of remote sensing images can be used to produce homogeneous and up-to-date landcover maps. We used Orfeo ToolBox to test whether MODIS time series can be classified using a detailed nomenclature alike national forest inventories nomenclatures. To identify best practices for classifying time series, three algorithms were compared: Maximum Likelihood, Support Vector Machine and Random Forest. For each algorithm, we optimized training, temporal compositing and selection of input features. Our results showed a clear improvement in classification accuracy when spectral bands were used instead of vegetation indices alone. Temporal compositing had a major impact when the whole phenological cycle was used for three consecutive years. Random Forest produced the best classification.
 * **[CONFIRMED]** Differential SAR Interferometry in OTB (Usseglio Gaelle - THALES SERVICES)
 
 > The differential SAR interferometry (DInSAR) technique relies on the processing of two SAR images of the same portion of the Earth's surface taken at different time. The aim is to analyze potential events (earthquake, destruction, ...) by highlighting differences between SAR images. DInSAR involves a set of tools such as creation of deformation grids , coregistration or building of interferograms. An Orfeo Toolbox remote module (DiapOTB) contains all necessary steps and allows to launch a complete DInSAR chain. The DiapOTB module were used with Sentinel-1 data with satisfactory results.