Short Course

Remote Sensing Images Processing for Disasters Response – Use of CBERS-4 and Sentinel images and INPE's and ESA's Tools.

Description: The course will present digital image processing techniques for identifying damages and producing maps in support of disaster response, as well as, the use of Sentinel data and ESA tools for Disaster mapping. TerraView and SPRING, INPE's free and open source tools, and ESA's SNAP (Sentinel Application Platform) toolbox will be used during hands-on activities.

Learning Outcomes: By the end of the course, the participants will be able to: select and obtain appropriate images for disaster applications; perform some skills in image processing: registration and geometric correction, image mosaic, enhancement and export (KML/ShapeFile).

Level: Intermediate (previous experience in remote sensing and geoprocessing is desirable).

Length: 4 hours (split over two days - 5h and 6th).

Methods: Participants may get involved in hands-on activities or as a listener.

System Requirements: For the practical activities, participants must use their own laptop with 8GB RAM and must install the following software tools: SPRING, TerraView and SNAP.

Download links:
TerraView - latest release 5.4.0 - Win64, MacOS, Linux (Ubuntu): http://www.dpi.inpe.br/terralib5/wiki/doku.php?id=wiki:downloads
SPRING - Windows 64 bits (5.5.4), MacOS (5.5.3), Linux 64 (5.5.4) http://www.dpi.inpe.br/spring/
SNAP (Sentinel Application Platform) - Sentinel Toolboxes: http://step.esa.int/main/download/
Course Resources

Instructor: Dr. Laércio Namikawa
Image Processing Division, DPI - National Institute for Space Research, INPE, Brazil.

Bachelor's degree in Electronic Engineering from Universidade do Vale do Paraíba (1988), Master in Computer Science from Brazilian Institute for Space Research - INPE (1995) and Ph.D in Geography from State University of New York at Buffalo (2006). Current position is with Brazilian Institute for Space Research - INPE, at the Image Processing Division, with expertise in Computer Science, Image Processing and Geographic Information Science. Interests include Digital Terrain Modeling, Triangulated Irregular Networks, Spatially Explicit Dynamic Models of Geographic Processes, Hydrological Models, Natural Disasters Early Warning Systems, Color and Fusion in Remote Sensing.