Week 8.1

GEOGRAPHY 280: THINKING SPATIALLY IN A DIGITAL WORLD

Course Details

  • Course Code: W.8.1 EMR

Tutorial 4 Overview

  • Start Date: Will commence this week.

  • Objectives:

    • Create your own maps and perform analysis.

    • Important to watch tutorial videos even if you do not plan to use the highlighted techniques; videos can be sped up.

  • Use of Generative AI:

    • Allowed for analysis problem-solving or troubleshooting ArcGIS online/data issues.

    • NOT permitted for the written portion of the assignment, including analysis writing, descriptions, and questions.

Responsibilities

  • Students must manage their own analyses and troubleshoot their work independently. Resources include Google, ESRI documents, etc.

  • Tutorial Hours:

    • Attend to begin analysis and discuss solutions with peers or TAs.

  • TA Office Hours: Possible additional session offered.

  • Extra Drop-in Session:

    • Location: ES 342

    • Dates/Times:

    • Friday, Oct 24, 1:30 – 2:30

    • Friday, Oct 31, 1:30 – 2:30

Course Recap

  • Topics Covered: Historical development of imaging and technology, entwined with both scientific innovation and cultural influences.

  • Satellite Orbits:

    • Types of Orbits: Low Earth Orbit, Geostationary, Polar, Sun-synchronous.

Remote Sensing: Landsat Overview

  • Landsat Program:

    • Jointly operated by the United States Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA).

    • Inspired by imagery from Apollo Moon missions.

    • Initial satellite, Landsat 1, launched in July 1972.

    • Total of 9 satellites launched to date, providing over 50 years of continuous Earth imaging and uninterrupted data collection.

Remote Sensing Classification

  • Passive vs. Active Remote Sensing:

    • Passive Sensors:

    • Rely on naturally occurring energy; typically utilize solar energy.

    • Usually collect data during the day, includes examples like Landsat and Sentinel-2.

    • Active Sensors:

    • Generate their own energy directed toward targets.

    • Measure the energy reflected from those targets, allowing for data collection at any time.

    • Example includes LiDAR (Light Detection and Ranging).

Understanding Electromagnetic Radiation (EMR)

  • Nature of EMR:

    • EMR can be conceptualized as both a wave in motion and as discrete packets known as photons.

  • Source:

    • Generated in great quantities by the sun through thermonuclear fusion or by the acceleration of electrical charges.

  • Wave Model of EMR:

    • When EMR travels, it exhibits wave properties where electric and magnetic fields fluctuate perpendicularly to the direction of travel.

    • Speed of light: approximately 3 imes 10^8 ext{ m/s}, denoted as c.

  • Generation: EMR is emitted by any object exceeding absolute zero (−273 degrees Celsius).

EMR Properties

  • Wavelength (D) and Frequency (f):

    • Wavelength is measured crest-to-crest (or trough-to-trough).

    • Common units: Micrometers (μm) or nanometers (nm).

    • Frequency refers to the number of wave crests passing a point per second.

    • Measured in megahertz (MHz) or gigahertz (GHz).

    • Relationship formula: D = v/f where:

    • D = wavelength,

    • v = velocity,

    • f = frequency.

Wavelength and Frequency Characteristics

  • Types:

    • High wavelength corresponds to low frequency.

    • Low wavelength corresponds to high frequency.

  • Wavelength Examples:

    • Radio Waves: Length of a football field.

    • Microwaves: Width of a baseball.

    • Infrared: Thickness of paper.

    • X-Rays: Width of a water molecule.

    • Gamma Waves: Size of atomic nuclei.

    • Indicates the electromagnetic spectrum range from Radio Waves to Gamma Waves.

EMR-Environment Interactions

  • Types of Interactions:

    • Transmission: EMR passes through a target.

    • Reflectance: Fraction of reflected EMR compared to total incoming energy; calculated from radiance values.

    • Scattering: Similar to reflection but unpredictable in nature.

    • Absorption: EMR is absorbed and converted into different forms of energy.

  • Note: Reflectance values are critical in optical remote sensing; they are not directly measured but calculated.

Reflectance Curves

  • Different materials exhibit distinct reflection patterns as expressed within their spectral signature (pattern across wavelengths).

  • Sample Reflectance Curves for various materials required.

  • The USGS maintains a spectral library for reference.

  • Example Melting Conditions: Draw spectral reflectance curves for materials such as a small dark lake, astroturf, and snow.

Spectral Reflectance in Vegetation

  • Common spectral bands included are for blue, green, and infrared (near, middle, and far infrared) to analyze vegetation health and geology.

  • A critical range known as the 'Red Edge' in reflectance curves indicates vegetation health.

Landsat-8 Specifications

  • Landsat-8 Bands Characteristics:

    • Band 1 (Coastal/Aerosol): 0.435 - 0.451 μm

    • Band 2 (Blue): 0.452 - 0.512 μm

    • Band 3 (Green): 0.533 - 0.590 μm

    • Band 4 (Red): 0.636 - 0.673 μm

    • Band 5 (NIR): 0.851 - 0.879 μm

    • Bands 6, 10-11 serve TIR specifications, with varying resolutions and spectral ranges.

Color Representation in Remote Sensing

  • Channel Allocation: Each raster band displayed corresponds to a specific channel on the monitor.

  • True Color Images: Assign bands to red, green, and blue accordingly to achieve realistic imagery.

  • False Color Images: Different combinations can highlight specific features like geology, vegetation health, etc.

    • Example combination for highlighting vegetation:

    • Red channel: Near Infrared

    • Green channel: Red

    • Blue channel: Green