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|Title:||Develop and Operate 'monitoring and early warning services on effective user demands'|
|Authors:||SMETS Bruno; PEKEL JEAN-FRANÇOIS; DEFOURNY Pierre; CRESMAN Keith; JACOBS Tim; COELST Frederik|
|Publisher:||Czech Technical University|
|Type:||Articles in periodicals and books|
|Abstract:||The Desert Locust is the most feared of all the locusts worldwide. With a great mobility (up to 1000km a week) and a vast invasion area (30 million km2), a single swarm can consume 20000 tons of vegetation daily and threaten the food security and human livelihoods. Currently available satellites cannot directly detect swarms, however provide relevant information about eco-logical conditions such as vegetation development which are important factors for monitoring the habits and forecasting locust development. This study aims at developing a user customized method to monitor these conditions in the breeding areas of the Desert Locust. The methodology uses a colorimetric approach to monitor land surface status from MODIS 250m to detect the green vegetation. Dynamic green vegetation maps are calculated every 10 days within an automated process since 2010 and are used directly by the Geographical Information System (GIS) at several national locust control centers as well as at the UN-FAO Desert Locust Information Service (DLIS). The maps show the spatial-temporal variations of the green vegetation and reduces the confusion between bare soils and vegetation. Due to the spatial resolution, not all vegetation can yet be detected in sparsely vegetated areas, the maps provide a major improvement in the early warning system and so allow to rapidly assess the situation and to estimate control measures to be taken. A wider use of the approach has been developed into an agriculture phenology prototype product.|
|JRC Directorate:||Sustainable Resources|
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