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Articles 1 - 5 of 5
Full-Text Articles in Social and Behavioral Sciences
Moving Fluid Mud Sondes, Optical And Acoustic Sensing Methods In Support Of Coastal Waterway Dredging, Charles R. Bostater, Tyler A. Rotkiske
Moving Fluid Mud Sondes, Optical And Acoustic Sensing Methods In Support Of Coastal Waterway Dredging, Charles R. Bostater, Tyler A. Rotkiske
Ocean Engineering and Marine Sciences Faculty Publications
Airborne, Satellite and In-Situ optical and acoustical imaging provides a means to characterize surface and subsurface water conditions in shallow marine systems. An important research topic to be studied during dredging operations in harbors and navigable waterways is the movement of fluidized muds before, during and after dredging operations. The fluid movement of the surficial sediments in the form of flocs, muck and mud is important to estimate in order to model the transport of solids material during dredging operations. Movement of highly turbid bottom material creates a lutocline or near bottom nephelometric layers, reduces the penetration of light reaching …
A Cautionary Tale.Pdf, Chris Laingen
A Cautionary Tale.Pdf, Chris Laingen
Faculty Research and Creative Activity
Remotely sensed imagery has been used for decades to quantify the area, rates, and types of land use and land cover change (LULCC) from local to global scales. Common platforms used to capture data include satellite- and aerial-based sensors and cameras. Inseparable from those data are errors—misclassified pixels in sensor-based data or incorrect observations in aerial photographs—created by spectral confusion on the part of the sensor or by misclassifying the raw data during interpretation. Such errors, if not sufficiently explained or taken into consideration when reporting LULCC results, could lead to dubious conclusions. For this article, four commonly used and …
Preface: Climate Extremes And Biogeochemical Cycles In The Terrestrial Biosphere: Impacts And Feedbacks Across Scales, M. Bahn, M. Reichstein, K. Guan, J. M. Moreno, Christopher A. Williams
Preface: Climate Extremes And Biogeochemical Cycles In The Terrestrial Biosphere: Impacts And Feedbacks Across Scales, M. Bahn, M. Reichstein, K. Guan, J. M. Moreno, Christopher A. Williams
Geography
No abstract provided.
Remote Sensing And Modeling Of Atmospheric Dust And Studying Its Impact On Environment, Weather, And Climate, Hesham El-Askary, Seon K. Park, Slobodan Nickovic, Mian Chin
Remote Sensing And Modeling Of Atmospheric Dust And Studying Its Impact On Environment, Weather, And Climate, Hesham El-Askary, Seon K. Park, Slobodan Nickovic, Mian Chin
Mathematics, Physics, and Computer Science Faculty Articles and Research
An overview of the 2015 volume of Advances in Meteorology, which was co-edited by Chapman faculty member Dr. Hesham El-Askary.
Sparse Coding Based Dense Feature Representation Model For Hyperspectral Image Classification, Ender Oguslu, Guoqing Zhou, Zezhong Zheng, Khan Iftekharuddin, Jiang Li
Sparse Coding Based Dense Feature Representation Model For Hyperspectral Image Classification, Ender Oguslu, Guoqing Zhou, Zezhong Zheng, Khan Iftekharuddin, Jiang Li
Electrical & Computer Engineering Faculty Publications
We present a sparse coding based dense feature representation model (a preliminary version of the paper was presented at the SPIE Remote Sensing Conference, Dresden, Germany, 2013) for hyperspectral image (HSI) classification. The proposed method learns a new representation for each pixel in HSI through the following four steps: sub-band construction, dictionary learning, encoding, and feature selection. The new representation usually has a very high dimensionality requiring a large amount of computational resources. We applied the l1/lq regularized multiclass logistic regression technique to reduce the size of the new representation. We integrated the method with a linear …