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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Sensor-Based Soil Water Monitoring To More Effectively Manage Agricultural Water Resources In Coastal Plain Soils, Christopher Bellamy
Sensor-Based Soil Water Monitoring To More Effectively Manage Agricultural Water Resources In Coastal Plain Soils, Christopher Bellamy
All Theses
Cotton (Gossypium hirsutum L.) is widely grown in the United States with 5.7 million ha grown nationally and 1.2 million ha grown in the humid southeastern states in 2005. From 1969 to 2003, agricultural irrigated farmland acreage and total water applied increased by over 40% and 11% respectively to include a total of 55.3 million acres in 2002. Combined with recent and more frequent drought periods and legal water conflicts between states, there has been an increased interest in more effective southeastern water management, thus making the need to develop improved irrigation scheduling methods and enhanced water use efficiency of …
Using Multiple Robust Parameter Design Techniques To Improve Hyperspectral Anomaly Detection Algorithm Performance, Matthew T. Davis
Using Multiple Robust Parameter Design Techniques To Improve Hyperspectral Anomaly Detection Algorithm Performance, Matthew T. Davis
Theses and Dissertations
Detecting and identifying objects of interest is the goal of all remote sensing. New advances, specifically in hyperspectral imaging technology have provided the analyst with immense amounts of data requiring evaluation. Several filtering techniques or anomaly detection algorithms have been proposed. However, most new algorithms are insufficiently verified to be robust to the broad range of hyperspectral data being made available. One such algorithm, AutoGAD, is tested here via two separate robust parameter design techniques to determine optimal parameters for consistent performance on a range of data with large attribute variances. Additionally, the results of the two techniques are compared …
Exploitation Of Intra-Spectral Band Correlation For Rapid Feacture Selection And Target Identification In Hyperspectral Imagery, Michael K. Miller
Exploitation Of Intra-Spectral Band Correlation For Rapid Feacture Selection And Target Identification In Hyperspectral Imagery, Michael K. Miller
Theses and Dissertations
This research extends the work produced by Capt. Robert Johnson for detecting target pixels within hyperspectral imagery (HSI). The methodology replaces Principle Components Analysis for dimensionality reduction with a clustering algorithm which seeks to associate spectral rather than spatial dimensions. By seeking similar spectral dimensions, the assumption of no a priori knowledge of the relationship between clustered members can be eliminated and clusters are formed by seeking high correlated adjacent spectral bands. Following dimensionality reduction Independent Components Analysis (ICA) is used to perform feature extraction. Kurtosis and Potential Target Fraction are added to Maximum Component Score and Potential Target Signal …