Resilience is the actions that state and local governments can take now to minimize the inevitable impact of shocks and stresses for the community, and accelerate the response for when those stresses occur. A geographic information system (GIS) is a critical part of building resilience.
Review our technical sessions and check out the presentations on resilience.
Machine learning is a form of artificial intelligence, and deep learning is the most popular form of machine learning. Analysis techniques such as prediction, classification, and regression are forms of machine learning, and they have been driving geographic information systems (GIS) and other business intelligence technologies for years.
Review our technical sessions and check out the presentations on Geo AI.
Imagery that is used in GIS can include aerial photos, satellite images, thermal images, digital elevation models (DEMs), scanned maps, land classification maps and surfaces created from a previous analysis that are saved as an image (Managing Imagery with ArcGIS 10). Hyperspectral, multispectral and panchromatic are general terms that describe imagery types. Hyperspectral imagery is imagery that is used for classifying different land types on the Earth (Dempsey, 2011). It is mostly used for agriculture, forestry management and other projects that examine the Earth’s physical landscape. Multispectral imagery is imagery that is made up of two or more images that are taken at the same type but in different portions of the electromagnetic spectrum.
Review our technical sessions and check out the presentations on Imagery.
Review our technical sessions and check out the Round Table Discussions.
While SHRUG is widely considered a grass roots organization of GIS users, it is important to note that without the generosity of our sponsors, we could not host an event like this. Please show your appreciation by visiting our sponsors at their booths and be sure to let them know just how much you appreciate their efforts to be here and support GIS users in our region.