Cindy Brewer’s research explores the automation of adaptive thinning of road features suitable for mapping scales ranging from 1:24,000 to 1:1,000,000. Thinning methods are applied to road features and labels for The National Map of the United States. Adaptive thinning removes features by feature hierarchy and network connectivity, and preserves many characteristic urban/rural local density patterns that can be lost through simple category elimination. Figure 7a shows the unclassified labels placed for all roads shown at 1000 m thinning. Figure 7b shows all the unplaced labels turned on as a reminder that many labels need to be removed to solve these road label problems, and it is wise to guide those omissions.
Cindy Brewer’s research explores the automation of adaptive thinning of road features suitable for mapping scales ranging from 1:24,000 to 1:1,000,000. Thinning methods are applied to road features and labels for The National Map of the United States. Adaptive thinning removes features by feature hierarchy and network connectivity, and preserves many characteristic urban/rural local density patterns that can be lost through simple category elimination. Figure 7a shows the unclassified labels placed for all roads shown at 1000 m thinning. Figure 7b shows all the unplaced labels turned on as a reminder that many labels need to be removed to solve these road label problems, and it is wise to guide those omissions. Photo provided
Cindy Brewer’s research explores the automation of adaptive thinning of road features suitable for mapping scales ranging from 1:24,000 to 1:1,000,000. Thinning methods are applied to road features and labels for The National Map of the United States. Adaptive thinning removes features by feature hierarchy and network connectivity, and preserves many characteristic urban/rural local density patterns that can be lost through simple category elimination. Figure 7a shows the unclassified labels placed for all roads shown at 1000 m thinning. Figure 7b shows all the unplaced labels turned on as a reminder that many labels need to be removed to solve these road label problems, and it is wise to guide those omissions. Photo provided

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