Please use this identifier to cite or link to this item:
|Title:||Monitoring African Surface Water Dynamic Using Medium Resolution Daily Data Allows Anomalies Detection in Nearly Real Time|
|Authors:||D'ANDRIMONT Raphael; PEKEL JEAN-FRANÇOIS; DEFOURNY Pierre|
|Citation:||2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp) p. 241-244|
|Type:||Contributions to Conferences|
|Abstract:||This paper proposes to use a water detection methodology based on a colorimetric approach to develop a near real time system allowing to monitor and to detect anomalies at a fine time resolution and in a systematic way The algorithm was calibrated over Africa using daily reflectance MODIS data from 2003 to 2011. The proposed approach has 3 major outputs updatable in near real time: (1) a permanent water mask (2) a every 10-days surface water map consolidated with time series and (3) an anomalies detection using 10 years of detection reanalysis. Three validation approaches are developed to deal with the large coverage and the high temporal resolution. The methodology is generic and could be applied to other extent and sensors.|
|JRC Institute:||Institute for Environment and Sustainability|
Files in This Item:
There are no files associated with this item.
Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.