remote sensing and hydrology. remote sensing: -measuring environmental variables without any direct...
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Remote sensing and Hydrology
Remote sensing:
-Measuring environmental variables without any direct contact with a target
-Measuring strength of electromagnetic radiation
-Extraction of valuable information from the remote sensing data uses mathematically and statistically based algorithms.
• Understand EM radiative transfer
•Understand sensor characteristics resolution, orbit, etc.
Electromagnetic energy:
EM wave travel through vacuum at speed of light (c = 3 x 108 m/s). There are two field – electric field and magnetic field – intersect at right angle. Both vectors are perpendicular to the direction of wave (wave model)
Wavelength and frequency:
Longer wavelength has higher frequency
λc
ν
Where c = speed of light (3.0 x 108 m/s) λ = wavelength
Frequency
Electromagnetic spectrum:The Sun, earth or any objects emit a continuous spectrum of energy from gamma rays to radio waves.
Satellite sensors measure EM radiation from visible through microwave range
Strength of energy emitted depends on physical body temperature (-> blackbody radiation curve).
• Stefan-Boltzmann law -> Determine total energy, f(T) • Wein’s displacement law -> Determine dominant λ
Measure of EM radiation
Radiant flux (Φλ) : energy per unit time, unit = [W]
Radiant flux density (Φλ/A) : unit = [W/m2]
Irradiance: incident radiant flux upon a unit area Exitance: radiant flux leaving from a unit area
Radiance (Lλ) : Irradiance from a certain direction (θ), unit = [W/m2/sr]
dtransmitteabsorbedreflectedi ΦΦΦΦ
the total amount of incident radiant flux in specific wavelengths incident (Φi) must be sum of radiant flux reflected from the surface (Φreflected), the amount of radiant flux absorbed by the surface (Φabsorbed), and the amount of radiant flux transmitted through the surface (Φtransmitted):
transmission
absorption
reflectionincident
Radiation budget equation
Hemispherical Reflectance, Absorptance, and Transmittance
dtransmitteabsorbedreflected ρρρ 1
i
dtransmittedtransmitteρ
ΦΦ
i
reflectedreflectedρ
ΦΦ
i
absorbedabsorbedρ
ΦΦ
Absorptance (emissivity)
Transmittance
Reflectance
Reflectance is often used for remote sensing analysisAll depend on wavelength and materials
Absorptance = emissivity (Kirchhoffs law)
Divide both side of radiation budget equation by incident radiance
Reflectance
Scattering
Mie scattering
Particle size roughly equal to wavelength
Scattering amount proportional to λ-1
Rayleigh scattering
Particle size is smaller than wavelength
Scattering amount proportional to λ-4
Nonselective scattering
Particle size is ~10 times larger than λ
Scattering amount not function of λ
Three types of scattering: Function of particle size (gas molecule, water vapor) relative to wavelength
Redirection of EM radiation by hitting small particles (typically in the atmosphere)
For atmosphere
Active
• EM Energy is emitted by a sensor toward target
• Measure energy reflected by a target
e.g. radar
Passive
• Measure EM energy emitted by earth or sun
e.g. satellite sensors
Active vs. Passive
Remote sensing sensor
Some terminologyInstantaneous field of view (IFOV):
The solid angle over which a measurement is made at any instance. Given the sensor altitude and IFOV, spatial resolutions (linear distance) is determined
Swath width
Width of the strip that can be scanned by the sensor.
Nadir
Point on the earth just underneath the sensor
Source: http://ccrs.nrcan.gc.ca/
nadir
swath
A= IFOV
B= pixel size
C= altitude
Satellite orbit
Polar orbit vs. Equatorial orbit
A polar orbit is 90 degree angle of inclination to the equator (passing north and south poles), whereas an equatorial orbit is zero degree angle of inclination to equator.
Sun-synchronous (polar orbit)
A special case of polar orbit. Platform pass the same location at the (roughly) same local time.
Geostationary orbit (equatorial orbit)
A special case of equatorial orbit. Satellite rotate at the same speed of earth rotation. A satellite appears to be still at the sky all the time. A satellite altitude is very high (35850 km)
More info -> http://www.rap.ucar.edu/~djohnson/satellite/coverage.html
Polar orbit satellite
One rotation
Advantage is daily global coverageThere are ascending path and descending path
Rotations per day
Geostationary
Top view Side view
Need several satellites to cover the entire earth
Geostationary vs. Polar Orbit
G P
Altitude High Low
Speed Slow fast
IFOV Small large
Sensor resolution
Spatial – the size of field of view (pixel size)
Spectral – range of EM spectrum each band of sensor detects
Temporal – frequency of measurements at a certain location
Radiometric – sensitivity of a sensor to difference in EM energy strength
(recording resolution of sensor)
Radiometric: a sensor records EM energy as brightness value (integer)
8-bit8-bit8-bit8-bit
9-bit9-bit9-bit9-bit
0
0
255
511
Conversion from binary to decimal for 2-bit00 = 0x21 +0x20 = 0 01 = 0x21 +1x20 = 110 = 1x21 +0x20 = 211 = 1x21 +1x20 = 3
2-bit2-bit2-bit2-bit 0 3
Sensor resolution
0
127
255
Brightness value range
(typically 8 bit)Associated gray-scale
10 15 17 20
15 16 18 21
17 18
20
22
18
20
22 24
1
2
3
4
1 5432Columns ( j)
Bands (k )
1
2
3
4
X axis Picture element (pixel) at location Line 4, Column 4, in Band 1 has a Brightness Value of 24, i.e., BV4,4,1 = 24 .
black
gray
white21
23
22
25
Lines or rows (i)
0
127
255
Brightness value range
(typically 8 bit)Associated gray-scale
10 15 17 20
15 16 18 21
17 18
20
22
18
20
22 24
1
2
3
4
1 5432Columns ( j)
Bands (k )
1
2
3
4
X axis Picture element (pixel) at location Line 4, Column 4, in Band 1 has a Brightness Value of 24, i.e., BV4,4,1 = 24 .
black
gray
white21
23
22
25
Lines or rows (i)
spatial
spectral
spatial
radiometric
Remote sensing – sensor (visible-thermal)
Band No. Wavelength range (μm) Ground IFOV (m)
1 0.45–0.53 (visible-blue) 30
2 0.52–0.60 (visible-green) 30
3 0.63–0.69 (visible-red) 30
4 0.76–0.90 (Near infrared) 30
5 1.55–1.75 (Near infrared) 30
6 10.40–12.50 (Thermal) 120
7 2.08–2.35 (Mid infrared) 30
Landsat TM (Thematic Mapper )
Platform = Landsat 4, 5 (sun-synchronous orbit)Swath width = 185 km16 day repeat cycle
More info -> http://landsat.usgs.gov/index.php
Remote sensing - sensor (visible-thermal)
Landsat ETM+ (Enhanced Thematic Mapper )
Band No. Wavelength range (μm) Ground IFOV (m)
1 0.45–0.515 (visible-blue) 30
2 0.525–0.605 (visible-green) 30
3 0.63–0.69 (visible-red) 30
4 0.75–0.90 (Near Infrared) 30
5 1.55–1.75 (Near Infrared) 30
6 10.40–12.50 (Thermal) 60
7 2.09–2.35 (Mid Infrared) 30
8 0.52–0.90 (panchromatic) 15
Platform = Landsat 7 (sun-synchronous orbit)Swath width = 185 km16 day repeat cycle
More info -> http://landsat.usgs.gov/index.php
Remote sensing - sensor (visible-thermal)
AVHRR (Advanced Very High Resolution Radiometer)
Band No. Wavelength range (μm) Ground IFOV (km)
1 0.58–0.68 1.09
2 0.725–1.00 1.09
3A 1.58–1.64 1.09
3B 3.55–3.93 1.09
4 10.30–11.30 1.09
5 11.50–12.50 1.09
Platform = NOAA Polar orbiting Environment satelliteSwath width = 2400 kmLong history since 1979Daily global coverage (morning and afternoon acquisition)
More info -> http://edcsns17.cr.usgs.gov/1KM/avhrr_sensor.html
Remote sensing - sensor (visible-thermal) MODIS (Moderate resolution Imaging Spectroradiometer)
Bands used for land surface
Band No. Wavelength range (μm) Ground IFOV (m)
1 0.620–0.670 250
2 0.841–0.876 250
3 0.459–0.479 500
4 0.545–0.565 500
5 1.230–1.250 500
6 1.628–1.652 500
7 2.105–2.155 500
Platform = EOS Terra and Aqua (Sun-synchronous orbit)Terra (morning equator-crossing) and Aqua (morning equator-crossing)Swath width = 2330 km
There are 36 bands (0.4 - 14.385 μm) visible to thermal
More info -> http://modis.gsfc.nasa.gov/about/specifications.php
Remote sensing – sensor (passive microwave)
PolarizationElectric field component (or magnetic field) of EM energy can vibrate in any directions perpendicular to the direction of travel. This vibration direction can also evolve with time
Can measure precipitation, soil moisture, snowpack volume (SWE, depth), Sea Surface temperature (SST)
Not affected by cloud (visible sensor is affected by cloud)
Coarse spatial resolution
vertical horizontal
Fixed vibration plane Rotating Vibration plane
Viewed along the travel direction
Brightness temperature (Tb)
Tb value is usually given for passive mircowave data.
Terrestrial matters are not perfect blackbody (graybody).
Total energy emitted by graybody = blackbody radiation (given by plank law) times emissivity (0<ε<1)
Tb is given using emissivity (Tb = ε*T where T: actual physical temperature [K])
Emissivity is function of polarization, frequency, and materials
Tλkhcx
xλ
hcTEλ
1
125
2
exp
Rayleigh-Jeans approximation -> exp(x) ~ 1+x for longer λ
4
2
λ
TkcTEλ
44
22
λ
Tkc
λ
TkcεTEεTI b
λλ
Rayleigh-Jeans approximation
Plank’s law
Radiation of graybody is given by
Remote sensing – sensor (passive microwave)
SSM/I (Special Sensor Microwave Imager)
Platform = Defense Meteorological Satellite Program (DMSP) sun-synchronous orbitSwath width = 1394 kmDaily global coverage (morning and afternoon acquisition)
More info -> http://nsidc.org/data/docs/daac/nsidc0032_ssmi_ease_tbs.gd.html
Frequency (GHz) Polarization Ground IFOV (km)
19 λ=15.8 mm Horizontal 25
19 Vertical 25
22 λ=13.6 mm Vertical 25
37 λ= 8.8 mm Horizontal 25
37 Vertical 25
85 λ= 3.5 mm Horizontal 12.5
85 Vertical 12.5
Remote sensing – sensor (passive microwave)
AMSR (Advanced Microwave Scanning Radiometer)
Frequency (GHz) Polarization Ground IFOV (km)
6.925 λ=43.3 mm H / V 56
10.65 λ=28.2 mm H / V 38
18.7 λ=16.0 mm H / V 21
23.8 λ=12.6 mm H / V 24
36.5 λ= 8.2 mm H / V 12
89.0 λ= 3.4 mm H / V 5.4
Platform = EOS (Earth Observing System) AquaSwath width = 1445 kmDaily global coverage (morning and afternoon acquisition)
More info -> http://www.ghcc.msfc.nasa.gov/AMSR/index.html
Application for snow measurement
•Snow cover area (SCA)
Pixel level (Snow / no snow per pixel)
Subpixel level (percentage of SCA over pixel)
•Physical properties of snowpack
Albedo
Grain size
Depth (SWE)
Use visible – infrared sensors, passive microwave sensor, depending on what needs to be measured
Only estimate of depth (SWE) requires passive microwave data
SCA algorithm (Normalized difference snow index)
Snow if NDSI > 0.4 & Reflectance (band 2) > 11%
No snow, otherwise
52
52
bandband
bandband
TMTMTMTM
NDSI
64
64
bandband
bandband
MODISMODISMODISMODIS
NDSI
For Landsat TM
Snow if NDSI >0.4
No snow, otherwise
For MODIS
Use reflectance
To discriminate between Snow and cloud
TM band2
MODIS band4
TM band5
MODIS band6
Source: NOAA NOHRSC
SCA algorithm (subpixel level SCA mapping)
Linear spectral mixture analysis
λiλM
iiλ εRFR
,
1
Reflectance measured at each band is a linear combination of reflectance from individual surface (endmembers) such as snow, rock, or vege
Rλ: reflectance measured at band of wavelength λ
Rλ,i: reflectance of endmember, i, for band of wavelength λ
Fi : the fraction of endmember, i, over the pixel
M: the number of endmenber
ελ : residual error at wavelength λ
Find F for each endmember with numerical scheme that minimizes the sum of error
Use multispectral sensors (MODIS, AVHRR, Landsat TM) or hyperspectral sensors (better because of more bands)
Subpixel level SCA mapping
Binary SCA mapping
Source: Dozier, J., and T. H. Painter, Multispectral and hyperspectral remote sensing of
alpine snow properties, Annual Review of Earth and Planetary Sciences, 32, 465-494
SWE (or snow depth) algorithmRequire passive microwave data because EM radiation from shorter wavelength (visible – infrared sensors) cannot penetrate full depth of snowpack, but microwave does.
Tb measured over the snow cover is “cold” compared to bare ground because snow grains scatters microwave radiation (Mie scattering)
Algorithm to extract SWE from Tb data set is under development
Text for remote sensing and useful online
NASA remote sensing tutorial: http://rst.gsfc.nasa.gov/
John R. Jensen, Remote Sensing of the Environment: http://www.cas.sc.edu/geog/rsbook/Lectures/Rse/index.html
Engman, T, E. Recent advances in remote sensing in hydrology, Reviews of Geophysics, VOL. 33, NO. S1, 967-976, 1995.- general overview of remote sensing application to hydrology, no math, a little oldhttp://www.agu.org/revgeophys/engman00/engman00.html
Natural resources Canada, Earth Sciences Sectors:http://ccrs.nrcan.gc.ca/resource/tutor/fundam/index_e.php
Article for remote sensing for hydrology