Raster Data Processing

Share

Summary

This video introduces raster data, its characteristics, different types of raster data (continuous and thematic), common file formats, and important operations performed on raster datasets in hydrology, such as mosaicing, resampling, clipping, reclassification, raster calculations, and extracting values.

Highlights

Introduction to Raster Data
00:00:00

Raster data is presented as a matrix of cells organized in rows and columns, defined by its cell size (horizontal spatial resolution). Cells are typically square but can vary. Key information defining a raster includes the number of rows and columns, cell size (or grid size), and spatial resolution (e.g., 30 meters).

Types of Raster Data: Continuous vs. Thematic
00:01:33

Raster datasets can be continuous (e.g., elevation data, temperature, precipitation, where values change smoothly) or discrete/thematic (e.g., land use, where values represent distinct categories). Different symbologies (stretched for continuous, unique values for thematic) are used to represent these data types.

Raster Data File Formats
00:03:20

Common raster file formats include IMG (proprietary, image-based), ASC (ASCII, non-proprietary text file), TIFF (non-proprietary), and GRID (Esri/ArcGIS proprietary). Other formats like BIL, BIP, and BSQ are used for remotely sensed images.

Raster Operations in Hydrology: Mosaicing
00:04:43

Mosaicing involves combining multiple raster tiles into a single, larger raster. This is useful for processing multiple datasets efficiently. Tools like 'Mosaic To New Raster' in ArcGIS can handle overlapping areas by averaging values or prioritizing specific rasters.

Raster Operations in Hydrology: Resampling and Pyramids
00:06:05

Resampling creates a new raster with a different cell size or spatial resolution, often to reduce computational time for very high-resolution data. Building raster pyramids, a common practice in ArcGIS, resamples the original raster at different resolutions to improve visualization speed, memory usage, and processing efficiency by displaying the appropriate resolution based on the zoom level.

Raster Operations in Hydrology: Clipping
00:08:28

Clipping extracts a portion of a raster to a specific area of interest. This can be done using a vector dataset (like a polygon) or another raster dataset that defines the study area. ArcGIS tools like 'Clip', 'Extract by Polygon', or 'Mask' are used for this purpose.

Raster Operations in Hydrology: Reclassification
00:09:24

Reclassification changes the values of input raster cells to new values, often used with thematic datasets to group similar categories. For instance, different types of impervious surfaces can be reclassified into a single 'impervious' category, which can improve computational speed. The 'Reclassify' tool in ArcGIS performs this operation.

Raster Operations in Hydrology: Raster Calculator
00:10:50

The raster calculator performs mathematical operations on raster datasets, including addition, subtraction, and conditional operations. An example shows identifying streams in a DEM by querying cells with elevation values below a certain threshold. This is a powerful tool for hydrologic applications.

Raster Operations in Hydrology: Extracting Values
00:12:14

Values can be extracted from a raster for specific geometries. This includes extracting values at point locations ('Extract Values to Points'), along a line to create a profile (e.g., river cross-section using 'Interpolate Shape'), or within a polygon to calculate statistics like mean, maximum, minimum, and standard deviation ('Zonal Statistics').

Recently Summarized Articles

Loading...