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Articles 1 - 11 of 11
Full-Text Articles in Remote Sensing
Prediction Of Methane Gas By Using Hyperspectral Imageries And Remote Sensing Techniques, Aysha Ali Alharmasi Alhajeri
Prediction Of Methane Gas By Using Hyperspectral Imageries And Remote Sensing Techniques, Aysha Ali Alharmasi Alhajeri
Thesis/ Dissertation Defenses
Greenhouse gases is important for sustaining life on earth as well as in mitigating climate change. Methane (CH4) is considered as one of the most important critical gases for the global climate change and have significant influences on our life. Accordingly, the prediction of this greenhouse gas emissions is very important for avoiding the climate change effects and to maintain environmental sustainability. The objective of this study is to explore the potential applications for remote sensing to predict methane levels in the Earth’s atmosphere with a combination of local ground data and data from hyperspectral satellite imagery. By using hyperspectral …
Prediction Of Methane Gas By Using Hyperspectral Imageries And Remote Sensing Techniques, Aysha Ali Alhajeri
Prediction Of Methane Gas By Using Hyperspectral Imageries And Remote Sensing Techniques, Aysha Ali Alhajeri
Theses
Greenhouse gases is important for sustaining life on earth as well as in mitigating climate change. Methane (CH4) is considered as one of the most important critical gases for the global climate change and have significant influences on our life. Accordingly, the prediction of this greenhouse gas emissions is very important for avoiding the climate change effects and to maintain environmental sustainability. The objective of this study is to explore the potential applications for remote sensing to predict methane levels in the Earth’s atmosphere with a combination of local ground data and data from hyperspectral satellite imagery. By using hyperspectral …
Techniques For Tree Species Classification With Hyperspectral Imagery At Neon Science Sites, Anthony T. Albanese
Techniques For Tree Species Classification With Hyperspectral Imagery At Neon Science Sites, Anthony T. Albanese
Theses and Dissertations
Studies three sets of techniques for hyperspectral tree species classification at NEON science sites, aiming to work towards producing a general classification model.
Composite Style Pixel And Point Convolution-Based Deep Fusion Neural Network Architecture For The Semantic Segmentation Of Hyperspectral And Lidar Data, Kevin T. Decker, Brett J. Borghetti
Composite Style Pixel And Point Convolution-Based Deep Fusion Neural Network Architecture For The Semantic Segmentation Of Hyperspectral And Lidar Data, Kevin T. Decker, Brett J. Borghetti
Faculty Publications
Multimodal hyperspectral and lidar data sets provide complementary spectral and structural data. Joint processing and exploitation to produce semantically labeled pixel maps through semantic segmentation has proven useful for a variety of decision tasks. In this work, we identify two areas of improvement over previous approaches and present a proof of concept network implementing these improvements. First, rather than using a late fusion style architecture as in prior work, our approach implements a composite style fusion architecture to allow for the simultaneous generation of multimodal features and the learning of fused features during encoding. Second, our approach processes the higher …
Deep Learning For Land Cover Classification Using Only A Few Bands, Chiman Kwan, Bulent Ayhan, Bence Budavari, Yan Lu, Daniel Perez, Jiang Li, Sergio Bernabe, Antonio Plaza
Deep Learning For Land Cover Classification Using Only A Few Bands, Chiman Kwan, Bulent Ayhan, Bence Budavari, Yan Lu, Daniel Perez, Jiang Li, Sergio Bernabe, Antonio Plaza
Electrical & Computer Engineering Faculty Publications
There is an emerging interest in using hyperspectral data for land cover classification. The motivation behind using hyperspectral data is the notion that increasing the number of narrowband spectral channels would provide richer spectral information and thus help improve the land cover classification performance. Although hyperspectral data with hundreds of channels provide detailed spectral signatures, the curse of dimensionality might lead to degradation in the land cover classification performance. Moreover, in some practical applications, hyperspectral data may not be available due to cost, data storage, or bandwidth issues, and RGB and near infrared (NIR) could be the only image bands …
Determining Remote Sensing Spatial Resolution Requirements For The Monitoring Of Harmful Algal Blooms In The Great Lakes, John Lekki, Eric Deutsch, Michael Sayers, Karl Bosse, Robert Anderson, Roger Tokars, Reid W. Sawtell
Determining Remote Sensing Spatial Resolution Requirements For The Monitoring Of Harmful Algal Blooms In The Great Lakes, John Lekki, Eric Deutsch, Michael Sayers, Karl Bosse, Robert Anderson, Roger Tokars, Reid W. Sawtell
Michigan Tech Publications, Part 1
Harmful algal blooms (HABs) have become a major health and environmental concern in the Great Lakes. In 2014, severe HABs prompted the State of Ohio to request NASA Glenn Research Center (GRC) to assist with monitoring algal blooms in Lake Erie. The most notable species of HAB is Microcystis aeruginosa, a hepatotoxin producing cyanobacteria that is responsible for liver complications for humans and other fauna that come in contact with these blooms. NASA GRC conducts semiweekly flights in order to gather up-to-date imagery regarding the blooms' spatial extents and concentrations. Airborne hyperspectral imagery is collected using two hyperspectral imagers, HSI-2 …
Real Time Habs Mapping Using Nasa Glenn Hyperspectral Imager, Reid W. Sawtell, Robert Anderson, Roger Tokars, John D. Lekki, Robert Shuchman, Karl Bosse, Michael Sayers
Real Time Habs Mapping Using Nasa Glenn Hyperspectral Imager, Reid W. Sawtell, Robert Anderson, Roger Tokars, John D. Lekki, Robert Shuchman, Karl Bosse, Michael Sayers
Michigan Tech Publications, Part 1
The hyperspectral imaging system (HSI) developed by the NASA Glenn Research Center was used from 2015 to 2017 to collect high spatial resolution data over Lake Erie and the Ohio River. Paired with a vicarious correction approach implemented by the Michigan Tech Research Institute, radiance data collected by the HSI system can be converted to high quality reflectance data which can be used to generate near-real time (within 24 h) products for the monitoring of harmful algal blooms using existing algorithms. The vicarious correction method relies on imaging a spectrally constant target to normalize HSI data for atmospheric and instrument …
Classification Of North Africa For Use As An Extended Pseudo Invariant Calibration Sites (Epics) For Radiometric Calibration And Stability Monitoring Of Optical Satellite Sensors, Mahesh Shrestha
Electronic Theses and Dissertations
An increasing number of Earth-observing satellite sensors are being launched to meet the insatiable demand for timely and accurate data to help the understanding of the Earth’s complex systems and to monitor significant changes to them. The quality of data recorded by these sensors is a primary concern, as it critically depends on accurate radiometric calibration for each sensor. Pseudo Invariant Calibration Sites (PICS) have been extensively used for radiometric calibration and temporal stability monitoring of optical satellite sensors. Due to limited knowledge about the radiometric stability of North Africa, only a limited number of sites in the region are …
A New Multispectral Imaging Instrument For In-Situ Characterization Of Flocs And Colloidal Aggregates In Natural Waters, Charles R. Bostater
A New Multispectral Imaging Instrument For In-Situ Characterization Of Flocs And Colloidal Aggregates In Natural Waters, Charles R. Bostater
Ocean Engineering and Marine Sciences Faculty Publications
No abstract provided.
Resolution Enhancement Optimizations For Hyperspectral And Multispectral Synthetic Image Fusion, Charles R. Bostater
Resolution Enhancement Optimizations For Hyperspectral And Multispectral Synthetic Image Fusion, Charles R. Bostater
Ocean Engineering and Marine Sciences Faculty Publications
Many sensor systems are available for sensing the earth surface from satellites as well as airborne and mobile platforms. Thus, fusing data from multiple sensors is becoming a common theme in earth remote sensing. A major goal of remote sensing image fusion is resolution enhancement. In this paper, optimization techniques are presented and discussed in order to help make an image fusion process a practical method for not only spectral signature based image analysis but also for algorithm development in remote sensing of water. The technique described and explored in this paper includes the identification of feature areas, stratified random …
Implementation Of A Ground Truth Process For Development Of A Submerged Aquatic Vegetation (Sav) Mapping Protocol Using Hyperspectral Imagery, Carlton R. Hall, Charles R. Bostater, Robert W. Virnstein
Implementation Of A Ground Truth Process For Development Of A Submerged Aquatic Vegetation (Sav) Mapping Protocol Using Hyperspectral Imagery, Carlton R. Hall, Charles R. Bostater, Robert W. Virnstein
Ocean Engineering and Marine Sciences Faculty Publications
Protocol development for science based mapping of submerged aquatic vegetation (SAV) requires comprehensive ground truth data describing the full range of variability observed in the target. The Indian River Lagoon, Florida, extends along 250 km of the east central Florida coast adjacent to the Atlantic Ocean. The lagoon crosses the transition zone between the Caribbean and Carolinian zoogeographic provinces making it highly diverse. For large scale mapping and management of SAV four common and three uncommon species of seagrass (Tracheophyta) and three broad groups of macroalgae; red algae (Rhodophyta), green algae (Chlorophyta), and brown algae (Phaeophyta) are recognized. Based on …