MTU Grad Students

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Research from MTU’s Integrated Geospatial Technology MS Program mtu.edu/technology/graduate/igt/ Research described in this presentation was carried out in part at the Jet Propulsion Laboratory under a Research and Technology Development Grant, under contract with the National Aeronautics and Space Administration. Copyright 2015 California Institute of Technology. All Rights Reserved. US Government Support Acknowledged

Transcript of MTU Grad Students

Page 1: MTU Grad Students

Research fromMTU’s Integrated

Geospatial Technology MS Program

mtu.edu/technology/graduate/igt/Research described in this presentation was carried out in part at the Jet Propulsion Laboratory under a Research and Technology Development Grant, under contract with the National Aeronautics and Space Administration. Copyright 2015 California Institute of Technology. All Rights Reserved. US Government Support Acknowledged

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Contributors ❏ Yushin Ahn, Assistant Professor, School of Technology, MTU❏ Jorge Garcia, Visiting Scholar, School of Technology, MTU ❏ Eugene Levin, Associate Professor, School of Technology, MTU❏ Jessica McCarty, Research Scientist, MTRI and Adjunct Assistant

Professor, School of Technology, MTU❏ Thomas Oommen, Assistant Professor, Geologic and Mining

Engineering and Sciences, MTU❏ Umaa Rebbapragada, Jet Propulsion Laboratory, California Institute of

Technology

❏ Sam Aden, MS Graduate, IGT, MTU❏ James Bialas, MS Student, IGT, MTU❏ Zach Champion, MS Student, IGT, MTU❏ Joseph Grocholski, Undergraduate, Geospatial Engineering, MTU❏ Jeremiah Harrington, MS Student, IGT, MTU❏ Greg Martin, MS Student, IGT, MTU ❏ Krishna Murthy, MS Graduate, IGT, MTU

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Unmanned Aerial Vehicles (UAVs)

● Fixed Wing and Multirotor ● Pixhawk and ArduPilot controls● RGB, NIR, and thermal infrared sensors ● 3-D printed fixed wing

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Infrared Thermal Sensing

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Near Infrared Imagery

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Aerial Imagery

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Quincy Smelter Mapping

● Working in conjunction with Keweenaw National Historical Park

● Terrestrial LiDAR● Terrestrial close range photogrammetry ● Aerial Imagery from UAV

Image from nps.gov

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Quincy Smelter Slag Pile

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LiDAR Scanning of Quincy Smelter

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1938 aerial imagery from USGS

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Social Media Data Mining

● Twitter, Instagram, Strava ● Earthquakes, wildfires, pollution, bicycle

routes● Classification, visualization, natural

language processing, decision support.

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Identifying and classifying bicycle routes from social media

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Image Classification

● Object and Pixel Based● Supervised classification using machine

learning methods● Satellite and aerial imagery ● Earthquake damage identification● Long term land cover change analysis at

Philmont Scout Ranch in New Mexico

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Object and pixel based classifications of 2011 Christchurch, New Zealand Earthquake Damage

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Acknowledgements● Image Classification material is based upon work supported by the

National Science Foundation under Grant No. 1300720