Desert locusts (Schistocerca gregaria, Forskl) are known to be one of the dreaded insects since time immemorial for agricultural production. More than 60 countries are affected at varying degrees during plague development caused by several consecutive generation of successful breeding triggered by a favourable sequence of heavy and widespread rainfall. Normally in solitary phase density remains low and poses no economic threat but under favourable bio-climatic condition population increases very fast over space and time and forms gregarious swarms which can devastate agricultural lands. It is during this period that locusts can cause enormous damage to standing crops even

Satellite Remote Sensing and GIS Applications in Agricultural Meteorology pp. 401-423

several hundred kilometers away from their origin. However, early detection of locust growth and breeding sites are two key issues for efficient surveillance and control of desert locusts (DL). Locating high frequency breeding areas over temporal and spatial scale warrants analysis of large number of biophysical and bio-climatic variables in relation to locust physiology. Nevertheless the most difficult part of forecasting is migration of adult winged locusts, which is influenced by large number of weather parameters at synoptic scale.

To manage the locust devastation and its timely warning there is a need for structured geospatial database in GIS environment and interfacing with other analytical and modeling tools to form sophisticated spatial Decision Support System (Healy et al., 1996). This paper describes one such system and the approach to meet forecasting need using ARC/INFO GIS and a host of digital data especially from optical and microwave satellites sensors. GIS and Remote Sensing technology dramatically improves the ability of forecasting through effective manipulation of large volume and variety of spatially referenced and descriptive data. The logical aspects of database design employs integration of all application requirements in a database structure that supports the view and processing needs of these applications. The physical aspects refers to evalusation of alternative implementations and choosing storage structure, query mechanism and access methods (Navathe and Schkolnik, 1978).

The major plague of 1985-89 prompted the world acridologists to improve the forecasting tools and methodologies in order to maximize the effectiveness of pesticides and reduce the toxicity in aquatic environment. The highest priority was assigned to modeling and validating the spread of infestations over space and time in relation to concurrent changes in weather and vegetation (FAO, 1989).

In the present study effort has been made to provide interface to handle population dynamics, physiological development, habitat suitability as well as climate suitability for breeding and migration. The locusts biology in relation to weather and other environmental factors have been used in forecasting process. The DSS essentially adheres with norms of database design standard, customization, validation, integration before actual query mechanism and performing modeling operations.

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