How Remote Sensing Works
. . . 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
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
0.5 µm 0.6 µm 0.7 µm 0.4 µm
The Electromagnetic Spectrum
Blue Band
0.4 – 0.5 µm
Green Band
0.5 – 0.6 µm
Red Band
0.6 – 0.7 µm
EM Band – Narrow range of wavelengths that can be measured by a sensor
The Electromagnetic Spectrum
Infrared Bands
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
0.4 µm 0.5 µm 0.6 µm 0.7 µm
NIR – CIR imagery; vegetation growth
SWIR/MIR – Moisture content; penetrate smoke/haze; minerals; man-made materials
TIR – Heat sources; radiant energy; crop monitoring (evapotranspiration)
NIR and SWIR Examples
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.
NASA image, Robert Simmon
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.
⍴ =𝑅
𝐼 * 100
What Happens to Energy When Strikes a Ground Target?
Spectral Reflectance = % of total energy for each λ that is reflected by the target.
⍴ =𝑅
𝐼 * 100
What do the sensors actually record?
Brightness Values Spatial Resolution – the smallest area that can be measured. One pixel.
What do the sensors actually record?
Spatial Resolution
(Pixel size)
Brightness Values
Satellite Sensor Characteristics
• What Level of Detail Spatial
Resolution
• What Colors or Bands Spectral
Resolution
• Revisit Time Temporal
Resolution
• Color Depth Radiometric 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).
Spatial Resolution
Aerial photo with 1m spatial resolution (pixel size) Satellite image with 10m 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
Spatial Resolution
Multispectral Scanner
(MSS)
Landsat 1-5
Thematic Mapper
(TM) Landsat 4 & 5
Enhanced Thematic
Mapper Plus (ETM+)
Landsat 7
Operational Land
Imager (OLI) / Thermal
Infrared Sensor (TIRS)
Landsat 8
Spectral
Resolution
(mm)
• 0.5-0.6 (green)
• 0.6-0.7 (red)
• 0.7-0.8 (NIR)
• 0.8-1.1 (NIR)
1. 0.45-0.52 (B)
2. 0.52-0.60 (G)
3. 0.63-0.69 (R)
4. 0.76-0.90 (NIR)
5. 1.55-1.75 (MIR)
6. 10.4-12.5 (TIR)
7. 2.08-2.35 (MIR)
1. 0.45-0.52
2. 0.52-0.60
3. 0.63-0.69
4. 0.77-0.90
5. 1.55-1.75
6. 10.4-12.5
7. 2.09-2.35
8. 0.52-0.90 (Pan)
1. 0.43-0.45
2. 0.45-0.51
3. 0.53-0.59
4. 0.64-0.67
5. 0.85-0.88
6. 1.57-1.65
7. 2.11-2.29
8. 0.50-0.68 (Pan)
9. 1.36-1.38
10. 10.60-11.19 (TIRS)
11. 11.50-12.51 (TIRS)
Spatial
Resolution
(meter)
79 x 79
30 x 30
120 x 120 (TIR)
15 x 15 (Pan)
30 x 30
60 x 60 (TIR)
15 x 15 (Pan)
30 x 30
100 x 100 (TIRS)
Temporal
Resolution
(revisit days)
18 (Landsat 1,2,3)
16
16
16
Comparison of Landsat Sensors
Satellite Sensor Characteristics
• What Level of Detail Spatial
Resolution
• What Colors or Bands Spectral
Resolution
• Revisit Time Temporal
Resolution
• Color Depth Radiometric 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
Sentinel 2-A, ESA Copernicus Programme
• Twin Satellite Constellation (2A – 2015 / 2B – 2017)
• 13 Band, Multi-resolution
• 290 Km FOV
Multispectral Scanner
(MSS)
Landsat 1-5
Thematic Mapper
(TM) Landsat 4 & 5
Enhanced Thematic
Mapper Plus (ETM+)
Landsat 7
Operational Land
Imager (OLI) / Thermal
Infrared Sensor (TIRS)
Landsat 8
Spectral
Resolution
(mm)
• 0.5-0.6 (green)
• 0.6-0.7 (red)
• 0.7-0.8 (NIR)
• 0.8-1.1 (NIR)
1. 0.45-0.52 (B)
2. 0.52-0.60 (G)
3. 0.63-0.69 (R)
4. 0.76-0.90 (NIR)
5. 1.55-1.75 (MIR)
6. 10.4-12.5 (TIR)
7. 2.08-2.35 (MIR)
1. 0.45-0.52
2. 0.52-0.60
3. 0.63-0.69
4. 0.77-0.90
5. 1.55-1.75
6. 10.4-12.5
7. 2.09-2.35
8. 0.52-0.90 (Pan)
1. 0.43-0.45
2. 0.45-0.51
3. 0.53-0.59
4. 0.64-0.67
5. 0.85-0.88
6. 1.57-1.65
7. 2.11-2.29
8. 0.50-0.68 (Pan)
9. 1.36-1.38
10. 10.60-11.19 (TIRS)
11. 11.50-12.51 (TIRS)
Spatial
Resolution
(meter)
79 x 79
30 x 30
120 x 120 (TIR)
15 x 15 (Pan)
30 x 30
60 x 60 (TIR)
15 x 15 (Pan)
30 x 30
100 x 100 (TIRS)
Temporal
Resolution
(revisit days)
18 (Landsat 1,2,3)
16
16
16
Comparison of Landsat Sensors
Discrete Spectral Coverage
Unique Spectral Properties / 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 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
and S. patens
0
0.1
0.2
0.3
0.4
0.5
0.6
350 450 550 650 750 850 950
Wavelength (nm)
Re
fle
cta
nc
e (
%)
April P. australis
May P. australis
April S. patens
May S. patens
Blue Green Red NIR
Discrete
Spectral
Coverage
P. australis (Phragmites) S. patens (Spartina)
Spectral Response Curves
April and May Spectra for P. australis
and S. patens
0
0.1
0.2
0.3
0.4
0.5
0.6
350 450 550 650 750 850 950
Wavelength (nm)
Re
fle
cta
nc
e (
%)
April P. australis
May P. australis
April S. patens
May S. patens
Blue Green Red NIR Mid-IR Violet
Discrete
Spectral
Coverage
P. australis (Phragmites) S. patens (Spartina)
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
• sensor was capable of resolving over 220 continuous spectral bands at 10 nm interval (from 0.4 to 2.5 µm)
• 30 meter spatial resolution.
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
(Jordan) that are uniformly dark in natural color (top) are variegated in false-color (lower),
signifying different rock types. Credit: NASA, Robert Simmon, using Hyperion data.
JORDAN
SAUDI
ARABIA
SYRIA
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 Channel Green Channel Blue Channel
Red Band BV Green Band BV Blue Band BV
+ +
=
True Color Composite
Color Composites – Brightness Values to Colorized Renditions
Red Channel Green Channel Blue Channel
NIR Band Red Band Green Band
+ +
=
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
12
a
3
4
0
5
10
15
20
25
30
35
Blue
(0.45 - 0.52 mm)
Per
cen
t R
efle
ctan
ce
Green leaf
Yellow
Red/orange
Brown 4
2
1
3
45
40
Green
(0.52 - 0.60 mm)Red
(0.63 - 0.69 mm)
Near-Infrared
(0.70 - 0.92 mm)
a.
b.
c.
d.
Spectral Indices – Normalized Difference Vegetation Index (NDVI)
NDVI =(𝑁𝐼𝑅 −𝑅𝑒𝑑)
(𝑁𝐼𝑅+𝑅𝑒𝑑)
• 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)
NDVI =(𝑁𝐼𝑅 −𝑅𝑒𝑑)
(𝑁𝐼𝑅+𝑅𝑒𝑑)
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
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)
A few examples:
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