WSU - ESRI ARCMAP CHECKLIST
Raster datasets represent geographic features by dividing the world into discrete square or rectangular cells laid out in a grid. Each cell has a value that is used to represent some characteristic of that location, such as temperature, elevation, or a spectral value. Raster datasets are commonly used for representing and managing imagery, digital elevation models, and numerous other phenomena. Often rasters are used as a way to represent point, line, and polygon features. In the example below, you can see how a series of polygons would be represented as a raster dataset. Rasters can be used to represent all geographic information (features, images, and surfaces), and they have a rich set of analytic geoprocessing operators. In addition to being a universal data type for holding imagery in GIS, rasters are also heavily used to represent features, enabling all geographic objects to be used in raster-based modeling and analysis. (Esri)
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Raster to Geodatabase
Extract Value to Point
Check Difference between RasterValue and Actual Value
Conversion - Raster to Geodatabase
This strategy is useful when you want to manage rasters, add behavior, and control the schema; want to manage a well-defined set of raster datasets as part of your DBMS; need to get high performance without loss of content and information (no compression); and want one data architecture for managing all your content. If this tool is used to load raster datasets into a raster catalog, then you need to run the Calculate Default Spatial Grid Index tool [Data Management (Feature Class)] after the loading is completed.
Saving rasters into the geodatabase: RasterSEEMPL.gdb
Raster Processing - Clipping
Cuts out a portion of a raster dataset, mosaic dataset, or image service layer.
Clipped SEemplIDWC2 raster via this tool under Data Management Toolbox/Raster/Raster Processing.
Raster Processing - Extract to Point
Extracts the cell values of a raster based on a set of point features and records the values in the attribute table of an output feature class.
SEempRastCal based on the average between IDW and EBK --> extracting raster data to store's point location as SEStoresEXTV2P.
Difference between RasterValue and Actual Value
Took various interpolation methods (IDW, EBK, Average between two), Extract Value to Point, connected back to SEStores, found the difference of RasterValue - Employees, and then symbolized based on standard deviation.