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Exploration Of The Mtsat2 Satellite Capabilities For Real Time Detection And Characterization Of Volcanic Emissions, Nicholas R. Stewart
Exploration Of The Mtsat2 Satellite Capabilities For Real Time Detection And Characterization Of Volcanic Emissions, Nicholas R. Stewart
Dissertations, Master's Theses and Master's Reports - Open
In this report, we attempt to define the capabilities of the infrared satellite remote sensor, Multifunctional Transport Satellite-2 (MTSAT-2) (i.e. a geosynchronous instrument), in characterizing volcanic eruptive behavior in the highly active region of Indonesia. Sulfur dioxide data from NASA's Ozone Monitoring Instrument (OMI) (i.e. a polar orbiting instrument) are presented here for validation of the processes interpreted using the thermal infrared datasets. Data provided from two case studies are analyzed specifically for eruptive products producing large thermal anomalies (i.e. lava flows, lava domes, etc.), volcanic ash and SO2 clouds; three distinctly characteristic and abundant volcanic emissions. Two primary …
Object-Based Classification Of Earthquake Damage From High-Resolution Optical Imagery Using Machine Learning, James Bialas
Object-Based Classification Of Earthquake Damage From High-Resolution Optical Imagery Using Machine Learning, James Bialas
Dissertations, Master's Theses and Master's Reports - Open
Object-based approaches to the segmentation and supervised classification of remotely-sensed images yield more promising results compared to traditional pixel-based approaches. However, the development of an object-based approach presents challenges in terms of algorithm selection and parameter tuning. Subjective methods and trial and error are often used, but time consuming and yield less than optimal results. Objective methods are warranted, especially for rapid deployment in time sensitive applications such as earthquake induced damage assessment.
Our research takes a systematic approach to evaluating object-based image segmentation and machine learning algorithms for the classification of earthquake damage in remotely-sensed imagery using Trimble’s eCognition …
Assessment Of Land Cover And Riparian Zones For The Ford Research Forest - Hickey Creek/Sturgeon River And Falls River Subwatersheds, Fay Dearing
Dissertations, Master's Theses and Master's Reports - Open
For landowners, knowing the contents of their land is always a primary concern. Traditional field based assessments can be challenging and expensive for large landholdings as well. However, by utilizing remote sensing and GIS models the land cover/land use and riparian areas can be more easily identified on a larger landscape level. To this end two remote sensing techniques were explored to create a land cover/land use map for the study area. The first, utilizing object-oriented techniques and high spatial resolution generated an overall accuracy of 71.97% which indicated a moderate agreement with the classified image and the field truthed …