Nancy F. Glenn

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This study documents successful discrimination of hoary cress (Cardaria draba) in southwestern Idaho using hyperspectral imagery to a maximum producer’s accuracy of 82% for infestations with greater than 30% cover. Different hyperspectral processing parameters were evaluated and compared, including data transformations, endmember selection, classification(More)
In the summer of 2010, an Unmanned Aerial Vehicle (UAV) hyperspectral calibration and characterization experiment of the Resonon PIKA II imaging spectrometer was conducted at the US Department of Energy’s Idaho National Laboratory (INL) UAV Research Park. The purpose of the experiment was to validate the radiometric calibration of the spectrometer and(More)
Jeffery Pettingill Bonneville County Weed Department, Idaho Falls, ID 83402 Remote sensing technology is a tool for detecting invasive species affecting forest, rangeland, and pasture environments. This article provides a review of the technology, and algorithms used to process remotely sensed data when detecting weeds and a working example of the detection(More)
JESSICA J. MITCHELL*†, NANCY F. GLENN‡, TEMUULEN T. SANKEY‡, DEWAYNE R. DERRYBERRY§, MATTHEW O. ANDERSON¶ and RYAN C. HRUSKA¶ †Department of Geosciences, Idaho State University, Idaho Falls, ID 83402, USA ‡Department of Geosciences, Idaho State University, Boise, ID 83702, USA §Department of Mathematics, Idaho State University, Pocatello, ID 83209, USA(More)
With the progression of LiDAR (Light Detection and Ranging) towards a mainstream resource management tool, it has become necessary to understand how best to process and analyze the data. While most ground surface identification algorithms remain proprietary and have high purchase costs; a few are openly available, free to use, and are supported by published(More)
The Kootenai River floodplain in Idaho, USA, is nearly disconnected from its main channel due to levee construction and the operation of Libby Dam since 1972. The decreases in flood frequency and magnitude combined with the river modification have changed the physical processes and the dynamics of floodplain vegetation. This research describes the concept,(More)
Separating ground from nonground laser returns from airborne light detection and ranging (LiDAR) data is a key step in creating digital terrain models (DTMs). In this letter, bare-earth and forested surfaces are classified from LiDAR intensity data in a data set from central Idaho, U.S. Next, a Gaussian fitting (GF) method is applied to determine ground(More)
The height and shape of shrub canopies are critical measurements for characterizing shrub steppe rangelands. Remote sensing technologies might provide an efficient method to acquire these measurements across large areas. This study compared point-cloud and rasterized lidar data to field-measured sagebrush height and shape to quantify the correlation between(More)