Thursday, February 24, 2011
Better mapping of human settlements supports disaster management
Terra Daily: When a major disaster strikes in remote parts of the world, knowing if the area is populated, and how densely, is crucial for the effective organisation of humanitarian operations. The Global Human Settlements Layer (GHSL), developed by the European Commission's Joint Research Centre (JRC), will soon provide this detailed information for the first time on a global scale. The breakthrough is new advanced algorithms, developed by the JRC, that allow automatic analysis of medium resolution data provided by European satellites. The first test results confirm that the combined use of ICT technologies permit fast and precise mapping of built-up areas, anywhere in the world.
In addition, the algorithms allow massive datasets to be processed more efficiently and rapidly, making it possible to monitor the changes in human settlements regularly and equally importantly, to collect the same information from heterogeneous satellite data. This can help to reduce risks in areas that experience recurrent disasters and to focus post-disaster humanitarian interventions on the most likely populated places in disaster affected countries and regions.
The European Commission's Joint Research Centre, in collaboration with the European Space Agency's (ESA) Earth Observation Ground Segment Department (EOP-G) has produced the first prototype of a new Global Human Settlement Layer (GHSL) using European radar satellite (ENVISAT) capacity and advanced automatic pattern recognition algorithms.
One of the major problems in disaster-struck areas in less developed countries is the lack of relevant and up to date pre-disaster information that can help to quickly locate and assess the type and extent of damage, especially in populated places. The GHSL will help to focus damage analysis very quickly over populated places, leading to improvements in emergency rescue and humanitarian relief operations.
The GHSL will help to improve the quantification of the building stock which is valuable information both for risk assessment activities and for emergency rescue operations. As the building stock is an indicator of human presence, this critical piece of information on population (often lacking in remote areas) can help the first responder communities to focus their efforts in a particular area…
An 18th century map of an African village. From Antoine-François Prevost d'Exiles: Histoire generale des voyages ou nouvelle collection de toutes les relations de voyages par met et par terre..., Paris: Didot 1749–1758.
In addition, the algorithms allow massive datasets to be processed more efficiently and rapidly, making it possible to monitor the changes in human settlements regularly and equally importantly, to collect the same information from heterogeneous satellite data. This can help to reduce risks in areas that experience recurrent disasters and to focus post-disaster humanitarian interventions on the most likely populated places in disaster affected countries and regions.
The European Commission's Joint Research Centre, in collaboration with the European Space Agency's (ESA) Earth Observation Ground Segment Department (EOP-G) has produced the first prototype of a new Global Human Settlement Layer (GHSL) using European radar satellite (ENVISAT) capacity and advanced automatic pattern recognition algorithms.
One of the major problems in disaster-struck areas in less developed countries is the lack of relevant and up to date pre-disaster information that can help to quickly locate and assess the type and extent of damage, especially in populated places. The GHSL will help to focus damage analysis very quickly over populated places, leading to improvements in emergency rescue and humanitarian relief operations.
The GHSL will help to improve the quantification of the building stock which is valuable information both for risk assessment activities and for emergency rescue operations. As the building stock is an indicator of human presence, this critical piece of information on population (often lacking in remote areas) can help the first responder communities to focus their efforts in a particular area…
An 18th century map of an African village. From Antoine-François Prevost d'Exiles: Histoire generale des voyages ou nouvelle collection de toutes les relations de voyages par met et par terre..., Paris: Didot 1749–1758.
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