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June 26, 2012

Better Crop Management Through Geospatial Technology

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Use of remotely-sensed data in agriculture analysis enables making critical decisions to correct issues with the seasonal crop.  Crop analysis such as characteristic definition, health and stress detection, change detection and understanding the effects of environmental factors can all be used to make efficient and valuable decisions in a timely manner.

But, agriculture is a budget-conscious business and the high cost of remotely sensed data was previously a barrier to entry.    Now, however, the price of remotely sensed data is barreling downwards, and organizations can now afford purchasing imagery of their fields two or even three times in a season.  This broadens the range of analysis opportunities, at the same time increasing the organization’s need for a data management solution.

During this webinar, we will present a web solution based on Intergraph software and RapidEye satellite imagery.  The solution relies on OGC standards to provide online data delivery and processing as a tool for management of agricultural areas. Using the Model Maker tool in ERDAS IMAGINE,  algorithms for monitoring and change detection were developed and implemented and subsequently supplied as server-side geoprocesses using ERDAS APOLLO.  A RapidEye temporal dataset (i.e. repetitive coverages) is incorporated in the algorithms to generate change detection during sugar cane crop season in Brazil.   Ultimately, Intergraph software used in conjunction with RapidEye images demonstrate an efficient solution, assuring better environmental management on these areas and adding significant value to agricultural management on a sustainable basis.


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