Remote Sensing

Concepts and Applications

 

 

Ben Hickson

Geospatial Specialist

University of Arizona Libraries

Remote Sensing

"...the science and technology by which characteristics of object of interest can be identified without direct contact."

Sensors

  • Optical
    • Visible
    • Near Infrared (NIR)
    • Infrared (IR)
  • Microwave
    • Passive (scatterometer)
    • Active (SAR, altimeter)
  • Laser
    • Active

http://www.seos-project.eu/modules/classification/images/spectral_signatures_landsat.jpg

Process

Energy Source or Illumination

Radiation and   

the Atmosphere

Interaction with the Target

Reflected Energy Recorded by the Sensor

Landsat 8 Depiction

Transmission, Reception, and Processing

Space Network WSGT - Las Cruces, NM

Interpretation and Analysis

Hydrology - Patagonia, Argentina

Application

Scope Creek Watershed - Atlas Land Cover Classification

Capturing Energy

  • Visible light is radiation is energy
     
  • So are radio waves, heat (infrared), ultra-violet, and x-rays

Visible Light

Violet: 0.400-0.446 µm

 

Blue: 0.446-0.500 µm

 

Green: 0.500-0.578 µm

Yellow: 0.578-0.592 µm

Orange: 0.592-0.620 µm

Red: 0.620 - 0.700 µm

Infrared (IR)

0.700 - 100 µm

 

  • Reflected IR
  • Emitted IR (thermal)

Microwave

100 µm - 1m (1000000 µm)

 

Longest wavelength used in remote sensing

Reflectance

  • How a material absorbs, reflects, and transmits energy can betray it's composition

 

Graph of material reflectance

Passive Remote Sensing

Measures energy that is already available (i.e. Sun)

 

Optical, like your camera.  Or Eyeballs

Active Remote Sensing

Emitted energy directed toward a subject

Reflected energy is measured

 

Advantage:

Control and Precision

Disadvantage:

Inefficient

Spatial Resolution

The area a pixel in an image represents at full resolution

 

Landsat 8 OLI: 30m x 30m

NAIP: 1m

Digital Globe Worldview-3: 0.30m

 

More info:

https://platform.digitalglobe.com/earth-imaging-basics-spatial-resolution/

Tradeoffs

Data Storage

30m x 30m is 900x the number of pixels of 1m x 1m

 

Frequency

MODIS: 250m+, every 1-2 days

Landsat: ~30m, every 16 days

 

Spectral Resolution

Differing materials require differing spectral resolutions

 

Water and Vegetation can be determined across broad wavelengths

 

Differing between different rock types requires finer separation of wavelengths

Spectral Resolution

MODIS (Moderate-resolution imaging spectroradiometer)

Multi vs Hyper

Multi: Several wavelengths at a single or several resolutions

 

Hyper: tens or hundreds of very narrow spectral bands

Radiometric Resolution

The sensor sensitivity to slight differences in energy

 

Data is represented in positive digital numbers from 0 to 1 less than a selected power of 2

 

4 bit = 2  = four possible values from 0 to 3

8 bit = 2  = 256 possible values from 0 to 255

2

8

Satellite, Aerial, & LiDAR

Common Satellite Sensors

LiDAR

Light Detection and Ranging

 

  • Active Remote Sensing
  • Often used for high accuracy and terrestrial mapping
  • Typically have a system mounted on a plane or truck
  • Creates "clouds" of XYZ points

LiDAR Process

  1. Pulses of light emitted (active) and time recorded (typically NIR)
  2. Reflection of the pulse is detected and time recorded
  3. Use delay in return and speed of light to calculate distance ("slant range")
  4. Use of position and orientation of sensor to calculate XYZ of reflected point

 

LiDAR Components

  • Laser scanner
  • Clock (very precise)
  • Global Positioning System (GPS)
  • Inertial Measurement Unit (IMU)
  • Data Storage and management station
  • GPS ground station

http://www.yellowscan.fr/wp-content/uploads/archeology-3d-terrain-mapping.jpg

https://www.wired.com/wp-content/uploads/2015/11/Screen-Shot-2015-11-13-at-4.02.07-PM.jpg

Applications

Get a lot of detail of large areas

  • Remote
  • Often revisited (orbits)

Vegetation

  • Composition and Health
  • Vegetation Indicies
     

Vegetation Indicies

  • Built around the "red edge"
  • Cholorophyll absorbs most of the red wavelengths while vegetation cell structure reflect the infrared
     
  • Unique relationship allows us to easily differentiate vegetation structures from other materials (soil, plastics, roof tops, etc)

Red Shift

Vegetation Indicies

NDVI

SAVI

MSAVI
EVI

GARI

WDRVI

NDVI =  (NIR - Red) / (NIR + Red)

Land Cover

Ecosystems and Ecological Units

Land cover types

Terrain

Change Detection

Ecosystems and Ecological Units

Land cover types

 

http://www.globalforestwatch.org/map

Resources

Credits

http://www.isprs.org/caravan/documents/Lao_Basic_RS.pdf

 

https://www.thoughtco.com/an-overview-of-remote-sensing-1434624

 

http://web.pdx.edu/~jduh/courses/geog493f12/Week04.pdf

THANKS

Introduction to Remote Sensing

By Benjamin Hickson

Introduction to Remote Sensing

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