Physical Sciences and Mathematics Commons^™

Arithfusion: An Arithmetic Deep Model For Temporal Remote Sensing Image Fusion, Md Reshad Ul Hoque, Jian Wu, Chiman Kwan, Krzysztof Koperski, Jiang Li

Electrical & Computer Engineering Faculty Publications

Different satellite images may consist of variable numbers of channels which have different resolutions, and each satellite has a unique revisit period. For example, the Landsat-8 satellite images have 30 m resolution in their multispectral channels, the Sentinel-2 satellite images have 10 m resolution in the pan-sharp channel, and the National Agriculture Imagery Program (NAIP) aerial images have 1 m resolution. In this study, we propose a simple yet effective arithmetic deep model for multimodal temporal remote sensing image fusion. The proposed model takes both low- and high-resolution remote sensing images at t₁ together with low-resolution images at a …

Shipboard Lidar As A Tool For Remotely Measuring The Distribution And Bulk Characteristics Of Marine Particles, Brian Leigh Collister

OES Theses and Dissertations

Light detection and ranging (lidar) can provide remote estimates of the vertical distribution of optical properties in the ocean, potentially revolutionizing our ability to characterize the spatial structure of upper ocean ecosystems. However, challenges associated with quantifying the relationship between lidar measurements and biogeochemical properties of interest have prevented its adoption for routinely mapping the vertical structure of marine ecosystems. To address this, we developed a shipboard oceanographic lidar that measures attenuation (α) and linear depolarization (δ) at scales identical to those of in-water optical and biogeochemical measurements. The instrument’s ability to resolve the distribution of optical and biogeochemical properties …

Towards An Integrated Assessment Of Sea-Level Observations Along The U.S. Atlantic Coast, Brett A. Buzzanga

OES Theses and Dissertations

Sea levels are rising globally due to anthropogenic climate change. However, local sea levels that impact coastal ecosystems often differ from the global trend, sometimes by a factor of two or more. Improved understanding of this regional variability provides insights into geophysical processes and has implications for coastal communities developing resilience to ongoing sea-level rise. This dissertation conducts an investigation of sea level and its contributing processes at multiple spatial scales. Focusing on primarily interannual time-scales and data-driven approaches, new data sources and technologies are utilized to reduce current uncertainties.

First, sea-level trends are assessed over the global ocean and …

Examining Melt Pond Dynamics And Light Availability In The Arctic Ocean Via High Resolution Satellite Imagery, Austin Wesley Abbott

OES Theses and Dissertations

As the Arctic experiences consequences of climate change, a shift from thicker, multi-year ice to thinner, first-year ice has been observed. First-year ice is prone to extensive pools of meltwater (“melt ponds”) forming on its surface, which enhance light transmission to the ocean. Changes in the timing and distribution of melt pond formation and associated increases in under-ice light availability are the primary drivers for seasonal progression of water column primary production and warming. Observations of melt pond development and distribution require meter scale resolution and have traditionally been limited to airborne images. However, recent advances in high spatial resolution …

Deep Learning For Remote Sensing Image Processing, Yan Lu

Computational Modeling & Simulation Engineering Theses & Dissertations

Remote sensing images have many applications such as ground object detection, environmental change monitoring, urban growth monitoring and natural disaster damage assessment. As of 2019, there were roughly 700 satellites listing “earth observation” as their primary application. Both spatial and temporal resolutions of satellite images have improved consistently in recent years and provided opportunities in resolving fine details on the Earth's surface. In the past decade, deep learning techniques have revolutionized many applications in the field of computer vision but have not fully been explored in remote sensing image processing. In this dissertation, several state-of-the-art deep learning models have been …

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/l_q regularized multiclass logistic regression technique to reduce the size of the new representation. We integrated the method with a linear …

Sparse Coding For Hyperspectral Images Using Random Dictionary And Soft Thresholding, Ender Oguslu, Khan Iftekharuddin, Jiang Li, Mark Allen Neifeld (Ed.), Amit Ashok (Ed.)

Electrical & Computer Engineering Faculty Publications

Many techniques have been recently developed for classification of hyperspectral images (HSI) including support vector machines (SVMs), neural networks and graph-based methods. To achieve good performances for the classification, a good feature representation of the HSI is essential. A great deal of feature extraction algorithms have been developed such as principal component analysis (PCA) and independent component analysis (ICA). Sparse coding has recently shown state-of-the-art performances in many applications including image classification. In this paper, we present a feature extraction method for HSI data motivated by a recently developed sparse coding based image representation technique. Sparse coding consists of a …

Vegetation Identification Based On Satellite Imagery, Vamsi K.R. Mantena, Ramu Pedada, Srinivas Jakkula, Yuzhong Shen, Jiang Li, Hamid R. Arabnia (Ed.)

Electrical & Computer Engineering Faculty Publications

Automatic vegetation identification plays an important role in many applications including remote sensing and high performance flight simulations. This paper presents a method to automatically identify vegetation based upon satellite imagery. First, we utilize the ISODATA algorithm to cluster pixels in the images where the number of clusters is determined by the algorithm. We then apply morphological operations to the clustered images to smooth the boundaries between clusters and to fill holes inside clusters. After that, we compute six features for each cluster. These six features then go through a feature selection algorithm and three of them are determined to …

New Evidence For Enhanced Ocean Primary Production Triggered By Tropical Cyclone, I. Lin, W. Timothy Liu, Chun-Chieh Wu, George T. F. Wong, Chuanmin Hu, Zhiqiang Chen, Wen-Der Liang, Yih Yang, Kon-Kee Liu

OES Faculty Publications

[1] New evidence based on recent satellite data is presented to provide a rare opportunity in quantifying the long-speculated contribution of tropical cyclones to enhance ocean primary production. In July 2000, moderate cyclone Kai-Tak passed over the South China Sea (SCS). During its short 3-day stay, Kai-Tak triggered an average 30-fold increase in surface chlorophyll-a concentration. The estimated carbon fixation resulting from this event alone is 0.8 Mt, or 2-4% of SCS's annual new production. Given an average of 14 cyclones passing over the SCS annually, we suggest the long-neglected contribution of tropical cyclones to SCS's annual new production may …

Trichodesmium Spp.: Numerical Studies Of Resource Competition, Carbohydrate Ballasting, And Remote-Sensing Reflectance, Tonya Denise Clayton

OES Theses and Dissertations

In recent years, a new appreciation for the role of diazotrophy in the oceans has emerged. This dissertation reports on three modeling studies designed to investigate ecological processes associated with Trichodesmium spp., the most conspicuous marine diazotroph: (1) characterization of a generalized model Trichodesmium and issues of macronutrient resource competition; (2) carbohydrate ballasting by Trchodesmium and implications for the formation of surface accumulations; and (3) the vertical distribution of Trichodesmium and implications for detection from space.

The first study focuses on issues of nitrogen and phosphorus competition and ecosystem structure. It utilizes a simple ecosystem model that includes dissolved nitrogen …

Observation Of Shelfwater Overrunning The Southern Slope Sea, Ajoy Kumar

OES Theses and Dissertations

Analyses of two years (1992 and 1993) of high resolution (1.47 km²) sea surface temperature satellite images of the southern Mid-Atlantic Bight (MAB), showed that unusually extensive overhang of shelf water occurs episodically, and coherently over along shelf distances of several hundred kilometers. These episodes are dubbed overrunning of the Slope Sea by shelf water. The overrunning volume has a "face" and a "back" (southern and northern limit). It transports substantial quantities of shelf water southward, and does not retreat onto the shelf, but eventually joins the western edge of the Gulf Stream in the vicinity of Chesapeake …

Autonomous Robot Navigation In Unknown Terrains Using Parallel Numerical Artificial Potential Fields, John C. Schneider

Computer Science Theses & Dissertations

We present a new artificial potential field formulation for resolution complete robot navigation that unifies the purely geometric path planning problem with the lower level force control problem. Our formulation is designed for numerical computation over a massively parallel mesh of processors and is responsive to newly discovered terrain features. It does not suffer from many of the problems commonly associated with potential fields and with adequate resolution provides provably correct, collision free convergence to the goal. In addition, our formulation supports many desirable, practical features required for implementation, such as bounded actuator torques, attainable incremental constructability, realizable computation and …

Flow Kinematics And Dynamics Of The Gulf Stream From Composite Imagery, Caitlin Patrice Mullen

OES Theses and Dissertations

A unique set of contemporaneous satellite-tracked drifters and five-day composite satellite images of the North Atlantic is studied in order to infer the near-surface flow kinematics and dynamics of the Gulf Stream. Using fractal and spectral analyses, two kinematic models, and a potential vorticity model, detailed comparisons are made between these data sets.

Fractal and spectral analyses show that the data set is not fractal, there is no geographic variability, and there is not a strong fractal scaling link between the drifter trajectories and composite temperature fronts as had been postulated by several investigators. These results indicate considerably more work …