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Social and Behavioral Sciences Commons™
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Full-Text Articles in Social and Behavioral Sciences
Accuracy Assessment Of Pictometry® Height Measurements Stratified By Cardinal Direction And Image Magnification Factor, Daniel Unger, David Kulhavy, I-Kuai Hung, Yanli Zhang
Accuracy Assessment Of Pictometry® Height Measurements Stratified By Cardinal Direction And Image Magnification Factor, Daniel Unger, David Kulhavy, I-Kuai Hung, Yanli Zhang
Faculty Publications
The aim of this project was to ascertain if Pictometry® estimated height could be used in lieu of field-based height estimation. Height of a light pole measured with a telescopic height pole was compared to Pictometry® hyperspatial 4-inch (10.2 centimeters) multispectral imagery estimated light pole height on the campus of Stephen F. Austin State University, Nacogdoches, Texas. Average percent agreement between light pole height and Pictometry® estimated light pole height summarized by Pictometry® image magnification factors at 100%, 125%, 150%, 200%, and 300% magnification were within 98% of light pole height with percent disagreement ranging from …
Incorporating Applied Undergraduate Research In Senior To Graduate Level Remote Sensing Courses, Richard Henley, Daniel Unger, David Kulhavy, I-Kuai Hung
Incorporating Applied Undergraduate Research In Senior To Graduate Level Remote Sensing Courses, Richard Henley, Daniel Unger, David Kulhavy, I-Kuai Hung
Faculty Publications
An Arthur Temple College of Forestry and Agriculture (ATCOFA) senior spatial science undergraduate student engaged in a multi-course undergraduate research project to expand his expertise in remote sensing and assess the applied instruction methodology employed within ATCOFA. The project consisted of performing a change detection land-use/land-cover classification for Nacogdoches and Angelina counties in Texas using satellite imagery. The dates for the imagery were spaced approximately ten years apart and consisted of four different acquisitions between 1984 and 2013. The classification procedure followed and expanded upon a series of concrete theoretical remote sensing principles, transforming the four remotely sensed raster images …
Accuracy Assessment Of Land Cover Maps Derived From Multiple Data Sources, Daniel Unger, Hillary Tribby, Hans Michael Williams, I-Kuai Hung
Accuracy Assessment Of Land Cover Maps Derived From Multiple Data Sources, Daniel Unger, Hillary Tribby, Hans Michael Williams, I-Kuai Hung
Faculty Publications
Maximum Likelihood (ML) and Artificial Neural Network (ANN) supervised classification methods were used to demarcate land cover types within IKONOS and Landsat ETM+ imagery. Three additional data sources were integrated into the classification process: Canopy Height Model (CHM), Digital Terrain Model (DTM) and Thermal data. Both the CHM and DTM were derived from multiple return small footprint LIDAR. Forty maps were created and assessed for overall map accuracy, user's accuracy, producer's accuracy, kappa statistic and Z statistic using classification schemes from U.S.G.S. 1976 levels 1 and 2 and T.G.l.C. 1999 levels 2 and 4. Results for overall accuracy of land …