Monitoring of risk areas in the central Andes using SIG and satellites data

Several areas in the central Andes are historically affected by natural hazards occurring in glacial environments. As glaciers are very sensitive to temperature changes, we expect an intensification of glacier processes as response to the atmospheric warming detected in the Andes, possibly reducing...

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Autores:
Tipo de recurso:
http://purl.org/coar/resource_type/c_6641
Fecha de publicación:
2009
Institución:
Universidad Pedagógica y Tecnológica de Colombia
Repositorio:
RiUPTC: Repositorio Institucional UPTC
Idioma:
spa
OAI Identifier:
oai:repositorio.uptc.edu.co:001/12175
Acceso en línea:
https://revistas.uptc.edu.co/index.php/ingenieria_sogamoso/article/view/901
https://repositorio.uptc.edu.co/handle/001/12175
Palabra clave:
CBERS 2B
areas of risk
natural disasters
natural dangers
CBERS2B
áreas de riesgo
desastres naturales
peligros naturales
Rights
License
Derechos de autor 2009 Ingeniería Investigación y Desarrollo
Description
Summary:Several areas in the central Andes are historically affected by natural hazards occurring in glacial environments. As glaciers are very sensitive to temperature changes, we expect an intensification of glacier processes as response to the atmospheric warming detected in the Andes, possibly reducing the intervals of glacier-related disasters and hazards. In this context, the present study aims to test the potential of CBERS-2B data to be used for the identification of risk areas in the Andes. For that, semi-automatic routines for image processing and integration with a digital elevation models (DEM) were implemented in a Geographical Information Systems (GIS). CBERS-2B CCD (20-meters spatial resolution) and HRS (2,5-meters resolution) data are used for classification of ice, snow, waters, rocks and shadows, while a 15-meters DEM derived from ASTER imagery was used for the generation of slope and aspect information, and automatic delimitation of the catchment areas. Then, using the products of image classification and the data generated from the DEM, a tree classification algorithm was built with rules defined to select smooth areas just downward the glaciers. In order to validate the developed method, a comparison was done with the risk area delimited in the Jacha Pakuni Mountain (Tree Cruces mountain range, Bolivia) and the area affected by a glacier hazard occurred in 2007 at Pakuni mine. Hereby, the area affected by the debris flow was totally included within the risk zone delimited by the developed approach, showing the good potential of the method.