AER 102: Remote Sensing and Mesospheric Modeling

AER 102: Remote Sensing and Mesospheric Modeling

AER 102 provides PoSSUM students a basic proficiency in programming and gain an understanding remote sensing techniques including light detection and ranging (lidar), radar, and computer vision in the context of emerging technologies such as autonomous navigation and terrain modelling as well as a review & extension of Project PoSSUM aeronomy collection & processing efforts.

6 STUDENTS ENROLLED

    Objective:

    AER 102 provides an introduction to multiple topics and concepts in remote sensing. Each topic is first presented generally, then through the lens of how it can be applied to the aeronomy goals of Project PoSSUM. The course will emphasize basic principles, interspersed with some Python code examples and discussion of implementation strategies.

    Prerequisites:

    • PoSSUM Academy or PoSSUM Scientist-Astronaut Candidate
    • AER 101 Space Environment
    • Familiarity with trigonometry, algebra, and differential & integral calculus
    • Knowledge of a programming language at an introductory/novice level (Python, R, MATLAB, IDL)

    Text:

    There is no specific textbook for the course. Readings will be provided to the students as necessary, except in cases where an assignment requests the student to select a work of their own choosing. However, there are several books that are excellent general resources that cover many of the course topics, and are recommended by the instructor. These include, but are not limited to:

    • Lillesand, T., Kiefer, R. W., & Chipman, J. (2015). Remote sensing and image interpretation. John Wiley & Sons.    
    • Schott, J. R. (2007). Remote sensing: the image chain approach. Oxford University Press on Demand.

    Syllabus:

    1. Introduction
      1. What is remote sensing, and why do we need it for aeronomy?
      2. Important Moments in Remote Sensing History
    2. “Traditional” Imaging: Cameras
      1. Apertures: Pinholes vs Lenses (example: PMCTurbo)
      2. Exposure
      3. Bayer patterns
      4. Spatial sampling theorem (Nyquist)
    3. Photogrammetry
      1. Mono techniques
      2. Stereo techniques
    4. Radiometry & Calibration
      1. Atmospheric absorption and transmittance
      2. Planck’s Law
      3. Radiometric Calibration
        1. Types of atmospheric models (i.e., MODTRAN & similar vs NRLMSISE-00)
        2. Exoplanetary atmospheric models
    5. Noise
      1. Sources (environmental, electronic, physical, etc.)
      2. Statistical representations
      3. Mitigation strategies
    6. Image Processing
      1. Data management
      2. File formatting
      3. Kernels & Band Math
    7. Spectroscopy & Polarimetry
      1. What are they, and why do we need them for aeronomy? 
    8. Active Systems: Radar
      1. Basic history & principles of radar
      2. System examples
      3. Radar and aeronomy
    9. Active Systems: Lidar
      1. Basic history & principles of lidar
      2. System examples
      3. Lidar and aeronomy
    10. Wrap-up

    Assignments:

    Homework for the course will consist of a mix of written summaries based on literature review and light mathematical derivations and computation. Potential homework assignments include:

    • Read an overview paper for a well-known remote sensing platform or satellite, and write a one to two page summary describing the remote     sensing principles by which at least one of the associated sensors operate. (This     assignment might be given 2-3 times, with a different platform/modality each time)    
    • Write a function to compute a blackbody curve based on Planck’s Law
    • Write a function to compute the height of a point observed from a stereo     image pair of known geometries
    • Write a function to iterate input parameters for an atmospheric model

    Course assignments also include a final project, which will consist of a student-selected topic in remote sensing and/or aeronomy in which the student will address a problem or explore nuances of processing remotely sensed data, whether through code or third party software (such as ENVI, ESA SNAP, or ImageJ). The student will complete a written one page proposal at some point during the course, with a final report approximately five pages in length turned in with source code (or a flowchart of steps taken in third party software) at the end of the course.

    2021 Course Schedule

    december

    07dec(dec 7)8:00 am11(dec 11)5:00 pmFeaturedBIO 103 Microgravity Research CampaignMicrogravity Research Campaign supporting the IIAS BIO 103 Program

    january

    15jan(jan 15)6:30 pm20(jan 20)5:00 pmPoSSUM Scientist-Astronaut Class 2001 and 2002

    18jan(jan 18)8:00 am22(jan 22)5:00 pm2020 PoSSUM Academy - Red Sprite Group

    22jan(jan 22)6:30 pm27(jan 27)5:00 pmPoSSUM Scientist-Astronaut Class 2003

    25jan(jan 25)8:00 am29(jan 29)5:00 pm2020 PoSSUM Academy - Blue Jet Group

    30jan(jan 30)8:00 am03feb(feb 3)5:00 pmOPS 102 Spacecraft Egress and Rescue Operations On-SiteOn-site compliment to OPS 102 course providing aircraft egress and sea survial training to complement post-landing human space flight system engineering instruction

    february

    04feb(feb 4)8:00 am08(feb 8)5:00 pmFeaturedBIO 104: Advanced Egress - Spacesuit Landing and Post-Landing Testing

    april

    24apr(apr 24)8:00 am27(apr 27)3:00 pmEVA 103 Planetary Field Geology Field CampaignEVA 103 course covers the requirements and design considerations for EVA systems and tools for conducting planetary field geology

    28apr(apr 28)8:00 am02may(may 2)5:00 pmEVA 102 Operational Space Medicine Field CampaignField component to cover wilderness medicine in extreme environments, culminating with a 4-day on-site lab portion devoted to triage, scenarios and skills pertaining to wilderness medicine

    may

    03may(may 3)8:00 am07(may 7)5:00 pmFeaturedEVA 104 Gravity-Offset EVA Space Suit Evaluation CampaignGravity-offset research campaign to evaluate the Final Frontier Design EVA space suit by applying the tools and techniques developed through EVA 102 and EVA 103 courses

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