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4. Focal Analysis 4.1 Definition of focal analysis
___________________________________________________________ Advanced GIS UNT Geography 4. Focal Analysis 4.1 Definition of focal analysis 4.2 Shape and size of neighborhood 4.3 Focal statistics 4.4 Point statistics 4.5 Line statistics
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4.1 Definition of focal analysis
___________________________________________________________ Advanced GIS UNT Geography 4.1 Definition of focal analysis Focal analysis is also known as “neighborhood analysis” or “per-neighborhood analysis”. The output is a function of the input cells in the specified neighborhood of each location.
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4.2 Shape and size of neighborhood
___________________________________________________________ Advanced GIS UNT Geography 4.2 Shape and size of neighborhood Shapes - Annulus (Ring) - Circle - Rectangle - Wedge Sizes: 2, 3, 4, 5, … 3 x 3 Square (Default) Circle: Radius = 2 Wedge: 45°, Radius = 3
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4.2 Shape and size of neighborhood (cont.)
___________________________________________________________ Advanced GIS UNT Geography 4.2 Shape and size of neighborhood (cont.) Output cell center: x = (w + 1)/2 = 2 y = (h + 1)/2 = 2 (Truncate to integer) Output cell center: x = (w + 1)/2 = 3 y = (h + 1)/2 = 3 Odd neighborhood size Even neighborhood size w – width of the neighborhood; h – height of the neighborhood.
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Advanced GIS UNT Geography 4.3 Focal statistics ArcToolbox Spatial Analyst Tools Neighborhood Focal Statistics ArcToolbox Spatial Analyst Tools Neighborhood Focal Statistics
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4.3 Focal statistics (cont.)
___________________________________________________________ Advanced GIS UNT Geography 4.3 Focal statistics (cont.) Example 1: Raster data smoothing Human Footprint Grid, South Ghana (Data from CIESIN, Columbia University) Smoothed Data (mean) Raw Data (color) Raw Data (B/W)
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4.3 Focal statistics (cont.)
___________________________________________________________ Advanced GIS UNT Geography 4.3 Focal statistics (cont.)
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4.3 Focal statistics (cont.)
___________________________________________________________ Advanced GIS UNT Geography 4.3 Focal statistics (cont.)
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4.3 Focal statistics (cont.)
___________________________________________________________ Advanced GIS UNT Geography 4.3 Focal statistics (cont.)
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Advanced GIS UNT Geography 4.4 Point statistics ArcToolbox Spatial Analyst Tools Neighborhood Point Statistics
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4.4 Point statistics (cont.)
___________________________________________________________ Advanced GIS UNT Geography 4.4 Point statistics (cont.) Example 2: Median rent of U.S. cities in 1990 Cities Shapefile Point Statistics: Mean of Median Rent High $823 Low $148
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4.4 Point statistics (cont.)
___________________________________________________________ Advanced GIS UNT Geography 4.4 Point statistics (cont.) Example 3: Median housing value of U.S. cities in 1990 Cities Shapefile Point Statistics: Mean of Median Rent High $314,955 Low $27,400
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4.4 Point statistics (cont.)
___________________________________________________________ Advanced GIS UNT Geography 4.4 Point statistics (cont.) Median Rent (1990) High $823 Low $148 Median Value (1990) Question: What are the white areas in the output? High $314,955 Low $27,400
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4.4 Point statistics (cont.)
___________________________________________________________ Advanced GIS UNT Geography 4.4 Point statistics (cont.) Challenge Question 1: Given a point shapefile for cities of the Contiguous United States, create a new field in the shapefile attribute table, so that the values in the field represent the number of cities within 100 km of each city. (Answers will be provided after Module 7) Dallas 34 Denton 28 …
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4.4 Point statistics (cont.)
___________________________________________________________ Advanced GIS UNT Geography 4.4 Point statistics (cont.) Challenge Question 2: Density of TB cases The left maps shows real TB cases in an area, and A, B, and C are squares with equal size. It appears that C has the highest density of TB cases, but point statistics in the squares show that A has the highest density of TB cases (right). What would be the possible reasons? A A B B C C
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4.4 Point statistics (cont.)
___________________________________________________________ Advanced GIS UNT Geography 4.4 Point statistics (cont.) Example 4: Intensity of LiDAR points in a forest The map shows 10 million LiDAR points for a 1 km by 1 km study area (about 10 points per sq. meter) in the Soquel Demonstration State Forest in California. Objective: calculate average intensity (return strength of the laser pulses) in a 3 x 3 window (cell size = 0.5 m). • • • • • • • • • • • • • • • • • • • • • • • •
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4.4 Point statistics (cont.)
___________________________________________________________ Advanced GIS UNT Geography 4.4 Point statistics (cont.) Example 4: Intensity of LiDAR points in a forest (cont.) Point statistics results: Different intensity values from ground objects, e.g. low intensity from dense forests and asphalt pavements, and high intensity from open areas. • • • • • • • • • • • • • • • • • • • • • • • •
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Advanced GIS UNT Geography 4.5 Line statistics
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4.5 Line statistics (cont.)
___________________________________________________________ Advanced GIS UNT Geography 4.5 Line statistics (cont.)
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Review 4.1 Definition of focal analysis
___________________________________________________________ Advanced GIS UNT Geography Review 4.1 Definition of focal analysis 4.2 Shape and size of neighborhood 4.3 Focal statistics 4.4 Point statistics 4.5 Line statistics
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