IGAC: Studying Flooding and Droughts as baseline in Agroclimatic Risks

Structure model developed for Landsat TM
Structure model developed for Landsat TM
CAIN, Automatic classification of flood areas using normalized water index
CAIN, Automatic classification of flood areas using normalized water index (MNDWI)
Images: CIAF/IGAC

CIAF, the “Research and Investigation Centre Remote Sensing Group and Geographic Applications” of UN-SPIDER's Colombia Regional Support Office IGAC, has developed a model to correct and process satellite images for automatic extraction of flood areas using image processing algorithms, called "CAIN" (Atmospheric Correction and Indexes of flooding). This project is being implemented within the framework of the technical assistance to the Colombian Corporation of Agricultural Research (CORPOICA, 2014).

The processing platform CAIN was developed under the PCI Geomatica Software 2013. This initiative is part of CIAF's efforts to improve geospatial information management and disaster and emergency response associated with agro-climatic risks by studying flood- and drought-related climatic events of the La Niña and El Niño phenomena.

Download the full study (in Spanish; 1.29 MB).