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What is Point Density Analysis

Chapter 21
Advanced Methodologies and Technologies in Engineering and Environmental Science
A tool of GIS mapping that can calculate the density of point features around each output raster cell. A neighborhood is defined around each raster cell center, and the number of points that fall within the neighborhood is totaled and divided by the area of the neighborhood. Possible uses include finding density of disease cases, crime cases, or firms clustering. For example, one address might actually represent a crime case, or some crime cases might be weighted more heavily than others in determining crime rates. Increasing the radius will not greatly change the calculated density values. Although more points will fall inside the larger neighborhood, this number will be divided by a larger area when calculating density. The main effect of a larger radius is that density is calculated considering a larger number of points, which can be outside from the raster cell.
Published in Chapter:
Exploring Tourism Cluster in the Peripheral Mountain Area Based on GIS Mapping
Ya-Hui Hsueh (National Taichung University of Education, Taiwan), Huey-Wen Chuang (National Taichung University of Education, Taiwan), and Wan-Chiang Hsieh (National Taichung Girls' Senior High School, Taiwan)
Copyright: © 2019 |Pages: 16
DOI: 10.4018/978-1-5225-7359-3.ch021
Abstract
This chapter locates a set of points of tourist spots distributed on a peripheral mountain area by GIS mapping, illustrates that accessibility and neighbor to community are the influencing factors of tourism cluster in a peripheral mountain area, and further analyzes the benefits of tourism cluster of establishing cooperation network by tourism associations. This research investigates the linkages and local impacts between tourism and agriculture of a well-known organic agricultural area of fruits in Taiwan. This research aims to demonstrate the increased tourism development due to the tourist attractions of organic agriculture and religious spots in a peripheral region through a tourism clustering process. By collecting a set of points of tourist spots specified to GIS slope raster and point density surface, tourism-agriculture linkages and their local impacts are demonstrated.
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Chapter 299
Exploring Tourism Cluster in the Peripheral Mountain Area Based on GIS Mapping
A tool of GIS mapping that can calculate the density of point features around each output raster cell. A neighborhood is defined around each raster cell center, and the number of points that fall within the neighborhood is totaled and divided by the area of the neighborhood. Possible uses include finding density of disease cases, crime cases, or firms clustering. For example, one address might actually represent a crime case, or some crime cases might be weighted more heavily than others in determining crime rates. Increasing the radius will not greatly change the calculated density values. Although more points will fall inside the larger neighborhood, this number will be divided by a larger area when calculating density. The main effect of a larger radius is that density is calculated considering a larger number of points, which can be outside from the raster cell.
Published in Chapter: Exploring Tourism Cluster in the Peripheral Mountain Area Based on GIS Mapping; From: Encyclopedia of Information Science and Technology, Fourth Edition
Full Text Chapter Download: US $37.50 Add to Cart
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