January 11, 2022

From Raster to Vector Data in Global Mapper

Written by: Mackenzie Mills

 

A picture is worth a thousand words; a mantra that can be applied in many situations, including the field of GIS. Raster data, most often used as a base map or reference layer, holds a lot of visual information that  forms the basis for numerous geospatial analysis procedures. Tools in Global Mapper Pro include options for editing, converting, and analyzing  raster data, keeping it in its native pixel-based format, or transitioning the data to vector features. 

Vectorizing Land Areas

Looking at a wide view of a coastal area, lower resolution satellite imagery can be used to extract land or water areas to vector polygons. Displayed as multiple layers in Global Mapper, bands of satellite data show how different wavelengths of electromagnetic radiation interact with different surfaces and land covers. Principles of remote sensing include the knowledge of how these different wavelengths of energy interact with surfaces allowing the use of multiband satellite data for enhanced visualization of an area. For more  information on loading and visualizing multiband satellite data in Global Mapper, refer to this previous blog post.  

Combining bands of data through a multiband export in Global Mapper and adjusting the layer display contrast, true and false-color images are generated, clearly showing land and water areas.

The clear and consistent depiction of water in this image creates the opportunity to vectorize this area based on color usingGlobal Mapper Pro’s Vectorize Raster tool. This will work well on the evenly colored water in the image, but differences in the color display of land areas make it difficult to directly extract these shapes. While this operation creates polygons representing the water instead of land, it is a good start. 

An area feature outlining water in an image
The extracted areas representing water can be used to create features for the land areas in the image.

A specialized option in Global Mapper’s Digitizer toolset can then be used to generate polygons representing land. After creating a larger bounding box polygon for the study area, the vector editing option to Cut Selected Area(s) from Another Area(s) can be used to cut the water areas from the bounding box, leaving only polygons bounding the land. 

Water is represented by complex polygons in this image
Starting with satellite collected raster data, complex polygons for land in this coastal area are created in Global Mapper and can be exported to any supported format.

Land Cover Change Detection

The United States’ National Land Cover Dataset (NLCD) is a palette raster image in which each pixel value corresponds to a different land cover type. This data, updated every few years, shows basic land cover and land use. In the example below covering the area surrounding the city of Austin, Texas, the red pixels indicate developed, or more urban areas. 

Screenshot displaying land cover data and legend
The NLCD data provides an overview of the land cover and land use across the United States.

Using Global Mapper’s Raster Reclassify tool, the developed areas are isolated and retain their original pixel values and color. Repeating this reclassification for the 2019 and 2016 NLCD data creates new layers displaying only developed areas, and can be used in a visual analysis to detect urban area change. 

Subtle changes in the developed land cover areas from 2016 to 2019 can be seen using the Image Swipe tool in Global Mapper.

To better understand and quantify the developed land change in this region, the Raster Calculator is used to subtract the 2016 developed area layer from the 2019 developed areas. This pixel based calculation creates a new layer depicting positive and negative change as well as areas of no change. Using a custom shader for visualization, the developed area land cover change is clearly visible throughout the region. 

A screenshot of measured change represented by color
With blue representing negative change and red showing positive change, the more intense colors represent a higher degree of change in development from 2016 to 2019.

Converting these detected change areas to vector format is simple in Global Mapper. The Create Area Features from Equal Values tool vectorizes any raster data based on matching pixel values. Now, instead of showing change with a shaded raster layer, each area of change is represented by a polygon. 

A screenshot of measured change index
Transitioning from raster format to vector data allows attributes to be calculated and created for the features, increasing the information and meaning they can hold.

The analysis and manipulation of raster data provide valuable insight into an area of interest. Taking that analysis a step further with the vectorization of pixel-based data and some simple vector editing and attribute creation, Global Mapper contains numerous opportunities for continued data analysis. If you would like to explore satellite data and other tools in Global Mapper, download a 14-day free trial today! If you have any questions, don’t hesitate to get in touch.

If you enjoyed this blog, you may also find these other resources useful:

From Raster To Vector Data In Global Mapper

Ask the Experts: Ability to Automatically Generate Vectorization from Imagery/Terrain

GeoTalks Express: Working with Raster Data in Global Mapper

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