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Our environment is constantly changing due to weather, natural disasters, deforestation, urbanization, farming, politics, and many other factors. The ability to identify and understand recent changes and predict potential future changes is critical to many state, local and national government organizations. Hexagon US Federal provides an application that handles these requirements: the Land Cover Mapping (LCM) tool. Built on the ERDAS IMAGINE platform and incorporating a machine learning Classification and Regression Tree (CART) algorithm, the LCM tool is easy to use and provides powerful analysis of land cover datasets. This analysis supports numerous activities, such as monitoring changes of census tracts to verify farm subsidy eligibility among others. Attend this hands-on class to learn how to use the ERDAS IMAGINE platform, the built-in spatial modeler, and the LCM tool for land cover mapping applications. Students will learn (a) how to easily and accurately classify imagery such as the National Agriculture Imagery Program (NAIP) imagery available through the Hexagon Imagery Program, (b) how to properly train the machine learning algorithm for optimal results, and (c) the best techniques for choosing independent variable inputs, such as normalized difference vegetation index (NDVI), slope, moisture content, and elevation models. In addition to learning how to use the key features of the application, participants will also learn about using the spatial modeler to extend the LCM tool capabilities and workflows for publishing results as cloud services. Once these processes and resulting data sets become available as web services, they can be incorporated into autonomous connected ecosystems (ACE). These ACE may be used to control automated collections of new land cover imagery and integration of other sensor feeds important to understanding the dynamic environment. They may also be used for reporting and alerting based on specific land cover changes.
Hands-on (Complimentary - Walk-in)
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