Remote Sensing Commons^™

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

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 …

Evaluating Tree Height Using Pictometry® Hyperspatial Imagery, Daniel Unger, David Kulhavy, Matthew A. Wade

Faculty Publications

This study evaluated the use of Pictometry® hyperspatial 4-inch (10.2 centimeters) multispectral imagery to estimate height of baldcypress trees on the campus of Stephen F. Austin State University (SFASU), Nacogdoches, Texas. Actual tree heights of 60 baldcypress trees measured with a telescopic height pole were compared to Pictometry® estimated tree height. Linear correlation coefficients (r) and coefficient of determinations (R2) between actual tree height and Pictometry® estimated tree height for all 60 tress, and the shortest 30 and tallest 30 trees, were calculated. A paired t-test (alpha = 0.05) was calculated for all 60 tress, and the shortest 30 and …

Sub-Pixel Classification Of Forest Cover Types In East Texas, Joey Westbrook, I-Kuai Hung, Daniel Unger, Yanli Zhang

Faculty Publications

Sub-pixel classification is the extraction of information about the proportion of individual materials of interest within a pixel. Landcover classification at the sub-pixel scale provides more discrimination than traditional per-pixel multispectral classifiers for pixels where the material of interest is mixed with other materials. It allows for the un-mixing of pixels to show the proportion of each material of interest. The materials of interest for this study are pine, hardwood, mixed forest and non-forest. The goal of this project was to perform a sub-pixel classification, which allows a pixel to have multiple labels, and compare the result to a traditional …

Identifying Well Pads In The Haynesville Shale Region, Louisiana And Texas, With Digital Imagery, Darinda Dans, Daniel Unger, Kenneth W. Farrish, I-Kuai Hung

Faculty Publications

The Haynesville Shale is an underlying rock formation in northwest Louisiana and northeast Texas that contains vast quantities of natural gas. With new technology has come the ability to extract more natural gas from one of the largest gas deposits in the United States. With increased production, increased change in the local ecosystem will occur. It is necessary to examine oil and gas exploration effects on the local ecosystem due to changes in land cover, such as habitat loss and increased soil erosion. Remotely sensed imagery were utilized to ascertain the use of various digital image processing techniques to determine …

Assessing The Efficacy Of Modis Satellite-Derived Start Of Growing Season For Jurisdictional Determination Of East Texas Bottomland Hardwood Wetlands, Karen Malone, Hans Michael Williams, I-Kuai Hung, Daniel Unger

Faculty Publications

Introduction: Crucial to the determination of a jurisdictional wetland is the definition of “growing season”. Satellite imagery is being utilized in other ecological applications, but is lagging in wetland growing season determination. Both cost and temporal limitations historically have restrained use of satellite imagery in assessing the start up of the growing season. Multiple commercial satellites are available that provide high resolution imagery, but the cost are prohibitive for most studies. The National Aeronautics and Space Administration (NASA) and the U.S. Geological Survey (USGS) jointly manage the Landsat and the Moderate-resolution Imaging Spectroradiometer (MODIS) satellite programs. Landsat Enhanced Thematic Mapper …

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 …

Remotely Sensed Data To Map Forest Age Class By Cover Type In East Texas, Daniel Unger, I-Kuai Hung, Jeffrey M. Williams, James Kroll, Dean W. Coble, Jason Grogan

Faculty Publications

• Remote sensing in conjunction with ground truthing, can accurately quantify forest composition and age distributions in East Texas.
• Method uses standardized and readily available data available to the general public.
• Method was shown to be effective in terms of time and cost.