Remote‐sensing applications for desert‐locust monitoring and forecasting

Successful implementation of a preventive desert-locust control strategy implies early and reliable detection of areas where rainfall and vegetation conditions are suitable for egg laying and hatching and for development. Satellite data provides high-frequency information on these parameters and data is operationally available through the FAO ARTEMIS system as standard products, such as cold cloud duration and vegetation index maps covering the recession area. A calibration study was undertaken to assess the reliability of vegetation index data, and to evaluate the level of detection of areas with sparse vegetation. Through a field study in the Tamesna area in Niger, factors were derived for soil and plant species-based calibration. In a GIS (Geographic Information System) environment, the use of a detailed land-unit map allows calibration of the standard vegetation index. This data, together with rainfall information, can be introduced into a CIS system to be synthesized, through a simple model, as a map delimiting potential desert-locust breeding areas.