How Remote Sensing Works, 1

. . . the process of collecting information related to the electromagnetic energy reflected or emitted by an object on the ground using a device some distance away from the target.

Credit: NASA The Remote Sensing Process

Energy radiating from the sun interacts with the atmosphere and objects on the ground before a portion is reflected back to the sensor The Electromagnetic Spectrum

0.4 µm 0.5 µm 0.6 µm 0.7 µm

Units for measuring wavelengths will be listed either in micrometers (µm, µ ) or nanometers (nm) The visible spectrum is: 0.4 – 0.7 µm Or 400 – 700 nm The Electromagnetic Spectrum EM Band – Narrow range of wavelengths that can be measured by a sensor

Blue Green Red Band Band Band 0.4 – 0.5 µm 0.5 – 0.6 µm 0.6 – 0.7 µm

The Electromagnetic Spectrum Infrared Bands

NIR – CIR imagery; vegetation growth SWIR/MIR – Moisture content; penetrate smoke/haze; minerals; man-made materials TIR – Heat sources; radiant energy; crop monitoring (evapotranspiration)

0.4 µm 0.5 µm 0.6 µm 0.7 µm

Near infrared (NIR): 0.7 - 1.3µm Shortwave or middle infrared (SWIR/MIR): 1.3 – 3.0 µm Thermal infrared (TIR): 3.0 – 14.0 µm NIR and SWIR Examples

NASA image, Robert Simmon NIR image displaying variations in mineral content, vegetation, and water cause patterns of light and dark in this near infrared view of the Piqiang Fault in northwestern China. NIR and SWIR Examples

NASA image, Robert Simmon SWIR color composite utilizes the differences between 3 shortwave infrared bands to highlight the mineral geology surrounding China’s Piqiang Fault. What Happens to Energy When Strikes a Ground Target?

Transmission – Energy simply passes through to act on something else. i.e. greenhouse. Absorption – Energy is trapped and held rather than being reflected or transmitted. The reason we see colors. Reflection – Energy bounces off target to be recorded by a sensor.

What Happens to Energy When Strikes a Ground Target?

Incident Energy (I) = Transmission (T) + Absorption (A) + Reflection (R)

Spectral Reflectance = % of total energy for each λ that is reflected by the target.

푅 ⍴ = * 100 퐼 What Happens to Energy When Strikes a Ground Target?

Spectral Reflectance = % of 푅 total energy for each λ that ⍴ = * 100 퐼 is reflected by the target. What do the sensors actually record?

Spatial Resolution – the smallest area that can be measured. One pixel. Brightness Values What do the sensors actually record? Brightness Values

Spatial Resolution (Pixel size) Satellite Sensor Characteristics

Spatial • What Level of Detail Resolution

Spectral • What Colors or Bands Resolution

Temporal • Revisit Time Resolution

Radiometric • Color Depth Resolution Spatial Resolution

Spatial Resolution describes how much detail in an image is visible to the human eye.

The ability to "resolve," or separate, small details is one way of describing what we call spatial resolution.

Higher spatial resolution = larger file sizes; increased processing time; and higher cost (if purchasing from a commercial vendor).

Aerial photo with 1m spatial resolution (pixel size) Satellite image with 10m spatial resolution Spatial Resolution Planimetric data – roads, buildings, driveways Spatial Resolution 80 meter Landsat MSS w/ planimetric overlay Spatial Resolution 30 meter Landsat TM w/ planimetric overlay Spatial Resolution 10 meter SPOT w/ planimetric overlay Spatial Resolution 1 meter DOQ w/ planimetric overlay Spatial Resolution Sub-meter data w/ planimetric overlay Comparison of Landsat Sensors

Multispectral Scanner Thematic Mapper Enhanced Thematic Operational Land (MSS) (TM) Landsat 4 & 5 Mapper Plus (ETM+) Imager (OLI) / Thermal Landsat 1-5 Landsat 7 Infrared Sensor (TIRS) Landsat 8 • 0.5-0.6 (green) 1. 0.45-0.52 (B) 1. 0.45-0.52 1. 0.43-0.45 • 0.6-0.7 (red) 2. 0.52-0.60 (G) 2. 0.52-0.60 2. 0.45-0.51 • 0.7-0.8 (NIR) 3. 0.63-0.69 (R) 3. 0.63-0.69 3. 0.53-0.59 • 0.8-1.1 (NIR) 4. 0.76-0.90 (NIR) 4. 0.77-0.90 4. 0.64-0.67 Spectral 5. 1.55-1.75 (MIR) 5. 1.55-1.75 5. 0.85-0.88 Resolution 6. 10.4-12.5 (TIR) 6. 10.4-12.5 6. 1.57-1.65 (mm) 7. 2.08-2.35 (MIR) 7. 2.09-2.35 7. 2.11-2.29 8. 0.52-0.90 (Pan) 8. 0.50-0.68 (Pan) 9. 1.36-1.38 10. 10.60-11.19 (TIRS) 11. 11.50-12.51 (TIRS)

Spatial 30 x 30 15 x 15 (Pan) 15 x 15 (Pan) Resolution 79 x 79 120 x 120 (TIR) 30 x 30 30 x 30 (meter) 60 x 60 (TIR) 100 x 100 (TIRS)

Temporal Resolution 18 (Landsat 1,2,3) 16 16 16 (revisit days) Satellite Sensor Characteristics

Spatial • What Level of Detail Resolution

Spectral • What Colors or Bands Resolution

Temporal • Revisit Time Resolution

Radiometric • Color Depth Resolution Spectral Resolution

• Number of spectral bands (red, green, blue, NIR, Mid-IR, thermal, etc.) • Width of each spectral band • Certain spectral bands (or combinations) are good for identifying specific ground features

• Panchromatic – 1 spectral band (B&W) • Color – 3 spectral bands (RGB) • Multispectral – 4+ discrete spectral bands (e.g. RGBNIR) Spectral Resolution: Sentinel-2

• Twin Satellite Constellation (2A – 2015 / 2B – 2017) • 13 Band, Multi-resolution • 290 Km FOV Sentinel 2-A, ESA Copernicus Programme Comparison of Landsat Sensors Multispectral Scanner Thematic Mapper Enhanced Thematic Operational Land (MSS) (TM) Landsat 4 & 5 Mapper Plus (ETM+) Imager (OLI) / Thermal Landsat 1-5 Landsat 7 Infrared Sensor (TIRS) Landsat 8 • 0.5-0.6 (green) 1. 0.45-0.52 (B) 1. 0.45-0.52 1. 0.43-0.45 • 0.6-0.7 (red) 2. 0.52-0.60 (G) 2. 0.52-0.60 2. 0.45-0.51 • 0.7-0.8 (NIR) 3. 0.63-0.69 (R) 3. 0.63-0.69 3. 0.53-0.59 • 0.8-1.1 (NIR) 4. 0.76-0.90 (NIR) 4. 0.77-0.90 4. 0.64-0.67 Spectral 5. 1.55-1.75 (MIR) 5. 1.55-1.75 5. 0.85-0.88 Resolution 6. 10.4-12.5 (TIR) 6. 10.4-12.5 6. 1.57-1.65 (mm) 7. 2.08-2.35 (MIR) 7. 2.09-2.35 7. 2.11-2.29 8. 0.52-0.90 (Pan) 8. 0.50-0.68 (Pan) 9. 1.36-1.38 Discrete Spectral Coverage 10. 10.60-11.19 (TIRS) 11. 11.50-12.51 (TIRS)

Spatial 30 x 30 15 x 15 (Pan) 15 x 15 (Pan) Resolution 79 x 79 120 x 120 (TIR) 30 x 30 30 x 30 (meter) 60 x 60 (TIR) 100 x 100 (TIRS)

Temporal Resolution 18 (Landsat 1,2,3) 16 16 16 (revisit days) Unique Spectral Properties / Spectral Response Curve Spectral Response Curve

Spectral reflectance curves, or spectral signatures, of different types of ground targets provide the knowledge base for information extraction. Spectral Response Curve

Spectral responses (brightness values) from ground targets are recorded in separate spectral bands by sensors. Spectral Response Curves

April and May Spectra for P. australis P. australis (Phragmites) and S. patens S. patens (Spartina)

Blue Green Red NIR 0.6 April P. australis May P. australis 0.5 April S. patens May S. patens

0.4

0.3 Discrete Spectral 0.2 Reflectance(%) Coverage

0.1

0 350 450 550 650 750 850 950 Wavelength (nm) Spectral Response Curves

April and May Spectra for P. australis P. australis (Phragmites) and S. patens S. patens (Spartina)

Violet Blue Green Red NIR Mid-IR 0.6 April P. australis May P. australis 0.5 April S. patens May S. patens

0.4

0.3 Discrete Spectral 0.2 Reflectance(%) Coverage

0.1

0 350 450 550 650 750 850 950 Wavelength (nm) Earth Observing-1: Hyperion – Hyperspectral sensor (2000-2017) An imaging spectrometer having a 30 meter ground sample distance over a 7.5 kilometer swath and providing 10nm (sampling interval) contiguous bands of the solar reflected spectrum from 400-2500nm. Hyperion Hyperspectral Data

SYRIA

JORDAN

SAUDI ARABIA

• sensor was capable of resolving over 220 continuous spectral bands at 10 nm interval (from 0.4 to 2.5 µm) • 30 meter The hundreds of bands in hyperspectral imagery enable researchers to differentiate minerals and rocks that appear similar in visible light. Outcrops near Kirbhat en-Nahas spatial (Jordan) that are uniformly dark in natural color (top) are variegated in false-color (lower), resolution. signifying different rock types. Credit: NASA, Robert Simmon, using Hyperion data. Color Composites – Brightness Values to Colorized Renditions Color composite images require 3 channels of information – Red, Blue, Green (RGB) Color Composites – Brightness Values to Colorized Renditions

Red Band BV Green Band BV Blue Band BV + + =

Red Channel Green Channel Blue Channel

True Color Composite Color Composites – Brightness Values to Colorized Renditions

NIR Band Red Band Green Band + + =

Red Channel Green Channel Blue Channel

False Color Composite

Combination NIR, R, G is referred to as a color infrared image. This combination is also known as the Standard False Color Composite. Landsat ETM+ Spectral Resolution Spectral Indices

Relationship between spectral bands can provide an increased level of understanding beyond what standard 3-band composites can show

1 2 a

c. 45 1 40 Green leaf Yellow 35 Red/orange 2 30 Brown 3 4 25

15 Percent Reflectance Percent 10

d. 0 Blue Green Red Near-Infrared (0.45 - 0.52 mm) (0.52 - 0.60 mm) (0.63 - 0.69 mm) (0.70 - 0.92 mm) Spectral Indices – Normalized Difference Vegetation Index (NDVI)

(푁퐼푅 −푅푒푑) NDVI = (푁퐼푅+푅푒푑)

• Common in agriculture for assessing vegetation health and crop monitoring • Requires the presence of both NIR and Red bands

Spectral Indices – Normalized Difference Vegetation Index (NDVI)

(푁퐼푅 −푅푒푑) NDVI = (푁퐼푅+푅푒푑)

NDVI values range from -1 to +1 • Higher values indicate better health • Low or negative values highlight areas where nothing is growing Spectral Indices – Many Available Based on Needs A few examples:

Green Normalized Difference Vegetation Index (GNDVI) - more sensitive to the variation of chlorophyll content • GNDVI = (NIR-GREEN) /(NIR+GREEN)

Enhanced Vegetation Index (EVI) - corrects for some atmospheric conditions and canopy background noise and is more sensitive in areas with dense vegetation • EVI = G * ((NIR – R) / (NIR + C1 * R – C2 * B + L))

Moisture Stress Index (MSI) - canopy stress analysis, productivity prediction and biophysical modeling • MSI = MidIR / NIR

Normalized Burned Ratio Index (NBRI) - takes advantage of the near infrared and short wave infrared spectral bands, which are sensitive in vegetation changes, to detect burned areas and monitor the recovery of the ecosystem • NBR = (NIR – SWIR) / (NIR+ SWIR) Spectral Index Database

https://www.indexdatabase.de/

Partial listing of indices for Landsat 8 Lecture Resources

Required Reading – NASA Earth Observatory, Interpreting False Color Satellite Images https://earthobservatory.nasa.gov/features/FalseColor/page1.php