eng remote sensing and image measurement
TRANSCRIPT
Remote Sensing;Geospatial Data Acquisition from Imagery
Digital Imaging Sensors!
What kinds of information can we extract from imagery data? In case of Camera
Color
Directional VectorOr Geometric information.
Principle of geometric measurement from Imagery
Vector of light or ray from an object( 3D directional vector )
Position and Attitude of Camera when taking a picture or an image
Principle of 3D measurement using Stereo Imagery
3D coordinates of an object can be determined as an intersection point of two light rays.
More robust and accurate measurementfrom a series of images.
Mathematical formulation
Sensor CRS( x,y,z )
O: Center of Projection (Focus p.) (X0,Y0,Z0) : Ground CRS
Rotating angle of this coor.sys. (ω,φ,κ) : 3 axis attitude(地上座標系からみたセンサ座標系の回転角(傾き))
Image plane (Film plane) parallel to xy plane of sensor CRS
f: focal length
Ai (Xa,Ya,-f): Image point of ABased on sensor CRSZ
YX Ground CRS
O, Ai, A are on the same ray (straight line) in 3D space
z
x
yφ
ω
κ
A
Ray
(X1, Y1,Z1)
i ) co-linearity equation
Co-linearity Equation (共線条件式)
CRS: Coordinate System
Co-linearity Equation (共線条件式)
X = fa11(X1-X0)+a21(Y1-Y0)+a31(Z1-Z0)a13(X1-X0)+a23(Y1-Y0)+a33(Z1-Z0)
Y = fa12(X1-X0)+a22(Y1-Y0)+a32(Z1-Z0)a13(X1-X0)+a23(Y1-Y0)+a33(Z1-Z0)
aij = aij(ω,φ,κ ) : Rotation Matrix
Ground coordinate of a target
Sensor positionImage coordinate of a target
Sensor attitude
Estimation of sensor position and attitude using GCP(External orientation)
Position and attitude of sensor cood.sys.(X0, Y0,Z0) : Position(ω,φ,κ): Attitude six unknown
parameters
GCP’s image coordinatesAi(xa, ya, -f)A(X1,Y1,Z1)
Given : f (focal length)
xa = f
ya = f
............................
..............
..............
Collinearity Eq.
Non-linear least squares method
Estimated
(X0, Y0, Z0)
(ω,φ,κ)
^ ^^
^ ^ ^
GCP: Ground Control Point
Imaging plane
(x,y,z)
3D measurement with stereo images
Image or sensor with given or estimated position/attitude
Image coordinates have to be measured
Image or sensor with given or estimated position/attitude
Ground
roof
Basic Concept for 3D Building Extraction
3D information is key to differentiate the roofs from the objects on the ground
Stabilizerデータ処理装置
画像表示装置
データ記録装置GPS
位置データ
Gyro
3 line CCD array
TLS ( Three Line Scanner ) ;Example of Digital Camera for 3D Mapping
■Specifications・ Resolution 10cm(x-y) 、 20cm(z)・ continuous strip of digital imagery・ B/W and color imaging
鉛直
前方
後方進行方向
Imaging mode of TLS
Fore image
Nadir image
Aft image
■Stereo (triplet) images can be acquired simultaneously
1404/12/2023
Images taken from different angles
Forward BackwardNadir
• It can acquire the images from three different view point.
• No distortion of altitude comparison in flight direction.
3 次元データを使った変化の自動検出例
3 方向画像から作成した 3 次元モデル
Laser Scanner or Profiler
Electric Wire
Electric Tower
Tree tops
国土交通省国土地理院提供
Urban Terrain with Laser Scanner
Microwave Sensors
range direction
azimuth direction
pulse length
return time
return signal intensity
a) Real Aperture Radar
To improve resolution of cross-track(range) direction in processing return signal
b) Synthetic Aperture Radar
- Applying pulse compression for along track (azimuth) direction
Ground resolution : 1m~
Improving ground resolution by using Doppler effect
b) Change in frequency of return signal due to Doppler effect c) Characteristic of matched filter
d) Output from matched-filter for receiving point target A
Geometry of Radar Image
Distortions of Radar Imagery
A
A'
B
B'
angle of incidenceincident wave
aspect angle surface
sensor
direction of flight
off-nadir angle
angle of incidence
azimuth directionrange direction
航空機搭載SAR画像の例
Atmosphere
Sensor
PlatformSun
Spectral reflectionRadiation
object
Principles of Remote SensingAcquiring information of objects through electromagnetic wave
reflected or radiated by the objects
Strengths:
Simultaneous observation of
wide areasHomogeneous data
Digital dataLimitations, problems:
Reference data is required for quantitative measurement
Only information reflected in electromagnetic wave
can be observed.
(Only "visible" objects!)
Example of Remote Sensing Satellite
ALOS: Advanced Land Observation Satellite
Payloads
PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping)
AVNIR-2 (Advanced Visible and Near Infrared Radiometer type-2)
PALSAR (Phased Array type L-band Synthetic Aperture Radar)
DRC antenna
Solar battery panel
PRISMPanchromatic Remote-sensing Instrument for Stereo Mapping
Wavelength (um) 0.52 - 0.77 (nadir, forward, aftward) (B/H=1 for forward and aftward)S/N 70IFOV 2.5 mSwath Width 35 km (70km)Gimbal Angle +/- 1.5 deg
nadir
fore
aft
Specification
Triplet observation for stable generation of DEM with 3-5m elevation error
AVNIR-2Advanced Visible and Near Infrared Radiometer type-2
Wavelength (um) 0.42 - 0.50 0.52 - 0.60 0.61 - 0.69 0.76 - 0.89S/N 200 IFOV 10 m (nadir) Swath Width 70 km Gimbal Angle +/- 40 deg
Specification
PALSARPhased Array type L-band Synthetic Aperture Radar
Mode High Resolution SCANSARFrequency L-bandPolarization HH or VVResolution 10 m 100 m Number of Looks 2 10 Swath Width 70 kmIncidence Angle 20 - 55 degS/N 15 dBS/A 25 dB
Specification
Spectral reflectance of vegetation, soil and water:(By measuring reflectance of each spectrum, objects can be identified.)
Spectral reflectance of tree species:(By measuring reflectance of each spectrum, objects can be identified.)
Spectral reflectance of rocks and minerals:(By measuring reflectance of each spectrum, objects can be identified.)
Physical features that could be measured withelectromagnetic wave
Ozone hole
Vegetation (primary production)
Land cover/use
Ground surface temperature
Soil water content
Precipitation
Snow depth
Sea surface wind (direction, velocity)
Sea surface temperature
Wave height, direction
vegetation biomass(standing biomass)
0.1 micro meter(100nm)
1.0 micro meter
10.0 micro meter
100. micro meter
1mm
1cm
10cm
100cm
Visible
Wave length
Microwave
U.V.
I.R.
Characteristic of atmospheric spectral transmittance
For Active Microwave Sensors
Biomass Estimation by Microwave Scatterometer
Weaker
Stronger back scattering (surface + volume scattering)
Measurement model; how to associate sensor data with physical properties
Object model
Sensor model (sensitivity)
data
Electromagnetic wave model(propagation, absorption, scattering…)
Platform model( fluctuation in position/attitude)
Atmospheric model
Radiation/reflectionShape/geometrySeasonal change/movement etc.
affecting
affecting
affecting
Estimating “truth” with limited observation data with MLE or
Maximum Likelihood Estimation.(最尤推定)
Sun( Passive sensor )
affecting
The other environmental model affecting
Environmental model in a broader sense
Activesensor
Examples of Remote Sensors
1) Sensor Types for Remote Sensing
Sensors
Passive Active
- Photogrametric camera - Multispectral camera
Non Scanning Type....Cameras
Scanning Type... (Scanners)
CCD Image Sensors Multispectral Scanners
Microwave Radiometer -Sea surface temperature, Vapor content, Salt content of water etc.
E
X
A
M
P
L
E
S
Non Scanning Type..
- Total Station (Range Measurement)
- LIDAR
- Microwave altimeter - Geoid, Sea surface height etc.
Scanning Type...
Microwave scatterometer
- Velocity and direction of sea surface wind - Intensity of rainfall - Water content of soil etc.
Imaging radar - Synthetic Aperture Radar - Side Looking Radar (Real Aperture Radar)
Laser Range Imager
Multi-spectral scanners(MSS)mechanical scanner
Optical Sensors
An Example of Classical Scanner
folding mirrorscan mirror
detector
spectroscope
instantaneous field of view
Flight direction( v )
Linear Array Sensor(Linear CCD)
Flight direction
Optics
Scan Line
Schematic diagram of data acquisition by push broom scanner
Concept of Bands
Band 1Band 2
Band 3
NOAA AVHRR Data received at AIT-Data receiving started from Oct. 1997.-Improvement of Processing software is on-going (by Aug.).
-geometric correction(extending GCP files to SE Asia)-atmospheric correction
-Processed data delivery may start from Sept.(personal anticipation)
1997.Jan.
1997.Apr.
1997.Jul.
1997.Oct.
NDVI Seasonal Changes
Red: High NDVI values Yellow: Low NDVI values
Hyper-spectral Sensors
Asphalt (Hongo street)
Sanshiro pond
Gotenshita field
Yasuda Halltrees
(単位: nm (ナノメータ))
greenblue Near Infrared
Wav
e len
gth
(東京大学生産技術研究所 安岡研究室提供)
0
1000
2000
3000
4000
5000
6000
400 500 600 700 800 900 1000
Vegetation
Asphalt
Athletic Field
Hall
Pond
Ground/Sea Surface Temperature measured by the radiation in far infrared wave length (1999/3/1, 21:00pm)
y = 0.0839x + 9.7174R² = 0.812
10.0
12.0
14.0
16.0
18.0
20.0
22.0
20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 110.0 120.0
Sur
face
Tem
p.(1
℃)
Air Temp.(0.1℃)Relationship between Surface Temp and Air Temp
補正後平均値
線形 (補正後平均値)
Microwave Scatterometer
- Active Microwave Sensor- By emitting microwave to an object, information can be extracted
from scattered or return microwave
Basic idea underlying Surface Wind Measurement using Microwave scatterometer
Surface Wind
Sea Surface
Surface Wind
Weak Scattering (Reflectance)
Observation (Emission of Microwaves)
Strong Scattering (Reflectance)
Wind Velocity 2m/s(rms) : 3-20m/s10% : 20-30m/s
Wind Direction 20deg.(rms): 3-30m/s
Spatial Resolution
25km : 0deg. Cell50km : Wind Cells
Location Accuracy
25km(rms) : Absolute 10km(rms) : Relative
Coverage 90% of ocean every 2days
Mass 300kg Power 275W
Data Rate 2.9kbps
NSCAT_ant_imsk http://www.ee.byu.edu/ee/mers/NSCAT-1.html
Biomass Estimation by Microwave Scatterometer
Weaker
Stronger back scattering (surface + volume scattering)
Microwave Radiometer- Passive Microwave Sensor
Measuring radiated microwave from an object
AMSR-E Instrument DescriptionThe PM-1 AMSR is a twelve channel, six frequency total power passive microwave radiometer system. It measures brightness temperatures at 6.925, 10.65, 18.7, 23.8, 36.5, and 89.0 GHzhttp://www.ghcc.msfc.nasa.gov/AMSR/html/amsr_products.html
http://www.eoc.nasda.go.jp/guide/satellite/sendata/tmi_e.html
AMSR-E Level 2 EOS Standard Data Products
PARAMETER ACCURACY SPATIAL
RESOLUTION
Brightness Temperature 0.2 - 0.7 K 6 - 76 km
Ocean Wind Speed 1.5 m/s 12 km
Water VaporOver Ocean 0.2 g/cm2 23 km
Cloud Liquid WaterOver Ocean
3 mg/cm2 23 km
Sea Surface Temperature 0.5 K 76 km
Surface Soil Moisture0.06 g/cm3
where vegetation is lessthan 1.5 kg/m2
25 km(Equal Area Earth
Grid)
Global Rainfall Ocean: 1 mm/hr or 20%
(whichever is greater)10 km
Land: 2 mm/hr or 40%(whichever is greater)Global Rain Type
(Convection fraction) N/A
10 km
Satellite Missions
For Details: https://
directory.eoportal.org/web/eoportal/satellite-missions (English)
http://www.restec.or.jp/knowledge/satellite_term.html (Japanese)
内閣官房・宇宙戦略本部事務局作成http://www.kantei.go.jp/jp/singi/utyuu/RSSkentou/dai1/siryou2.pdf
内閣官房・宇宙戦略本部事務局作成http://www.kantei.go.jp/jp/singi/utyuu/RSSkentou/dai1/siryou2.pdf
内閣官房・宇宙戦略本部事務局作成http://www.kantei.go.jp/jp/singi/utyuu/RSSkentou/dai1/siryou2.pdf
Landsat 1 to 8
(1972 – present)
Satellite Launch Date Period of Operation
Landsat 1 23 July 1972Decommissioned 6 January 1978
Landsat 2 22 January 1975Decommissioned 25 February 1982
Landsat 3 5 March 1978Decommissioned 31 March 1983
Landsat 4 16 July 1982Decommissioned June 2001
Landsat 5 1 March 1984
Thematic Mapper stopped acquiring data 18 November 2011
Landsat 6 October 1993 Failed on Launch
Landsat 7 15 April 1999Operating in SLC-Off Mode after May 2003
Landsat 8 February 2013Due to be launched February 2013
http://www.ga.gov.au/ausgeonews/ausgeonews201209/landsat.jsp
Landsat TM Image (spatial resolution: 30m)
SPOT 1 to 6
SPOT-5 sample image of Naples (Italy) in 2002 (image credit: CNES) the spatial resolution of the imagery to < 3 m in the panchromatic band and to 10 m in the multispectral mode
https://directory.eoportal.org/web/eoportal/satellite-missions/s/spot-5
MOS-1Main Characteristics of the MOS-1
------------------------------------------- Scape : Box type with expanding type
solar cell paddle (one wing) Bus unit 1.26mx2.4mx1.48m
Solar cell paddle, total length 5.28mx2m Weight : Approx. 740kg Attitude control : Three axes control Design life : 2 years
------------------------------------------- Launch vehicle : H-I
Launch site : Tanegashima Space Center, Kagoshima
Launch date : February 7, 1990 -------------------------------------------
Orbit Type : Sun synchronous subrecurrent orbit Altitude : Approx. 909km Inclination : Approx. 99deg. Period : Approx. 103min.
JERS-1
Band 1 2 3 4 *
Frequency (µm) .55 - .60 .63 - .69 .76 - .86 .76 - .86
GSD (M) 18.3 x 24.2
Scene size (km) 75 x 75
Revisit interval (days) 44 at equator
* Viewing 15.3° forward, provides stereoscopic capability when used with band 3
Optical System (OPS)
Synthetic Aperture Radar (SAR)
Spectral Bands
Frequency
Polarisation
Incidence Angle
Spatial Resolution
Swath (Km)
L-Band
1.275 GHz HH
35.21° off nadir
18 m 75
-Commercial satellite-Launched by Canada
-Only SAR (C band)-fine resolution. mode - scan SAR mode
ADEOSSensors in ADEOS
1. OCTS - Ocean Color and Temperature Scanner
2. AVNIR - Advanced Visible and Near Inrared Radiometer
3. NSCAT - NASA Scatterometer
4. TOMS - Total Ozone Mapping Spectrometer
5. IMG - Interferometric Monitor for Greenhouse Gases
6. POLDER - Polarization and Directionality of the Earthe's Reflectance
7. ILAS - Improved Limb Atmospheric Scatterometer
TRMM
EOS-AM and PM
AQUA(EOS-PM)
TERRA (EOS-AM)http://terra.nasa.gov/
http://aqua.nasa.gov
ENVISAT
MERIS ASAR AATSR RA-2 MWR DORIS GOMOS MIPAS SCIAMACHY LRR
http://envisat.esa.int/
内閣官房・宇宙戦略本部事務局作成http://www.kantei.go.jp/jp/singi/utyuu/RSSkentou/dai1/siryou2.pdf
High Resolution Satellites
Geo-Eye
http://www.spaceimaging.co.jp
http://news.satimagingcorp.com/2008/09/geoeye-1_satellite_sensor_launched_successfully_from_vandenberg_air_force_base_in_california_.html
ALOS(Advanced Land Observation Satellite)
ForeAft
Nadir
flight direction
ForeAft
Nadir
flight direction
Fore
Aft
Nadir
ASTER G-DEM International joint project between METI and NASA Earth observing sensor developed by Japan (METI) flying on Terra Launched in December 1999, in stable operation for more than 7 years
ASTER provides:
1) Surface condition The earth surface is observed in visible to thermal infrared (invisible to human eyes) spectral regions to obtain detailed information on the condition and distribution of the surface (vegetation, geology, etc.).
2) Surface temperature The distribution of surface temperature is observed by the thermal infrared sensor to study the urban heat island effect and other phenomenon in detail.
3) DEMDEM is derived from a stereo-pair of images over a single area acquired in nadir and backward viewing angles.
Backward Nadir
satellite TerraFlight direction
Features of ASTER G-DEM Joint project between METI and NASA Generation of global land DEM based on the ASTER coverage Enhanced accuracy due to the use of multiple ASTER data over one region User friendly with the capability for selective cropping
Red-colored area: ASTER coverage (1.1 million scenes)Deeper red indicates more frequent observations, thus providing higher accuracy.
applied to all land area
Easy to use, allowing for selective cropping
Generation of seamless DEM using all ASTER data ever acquired over the target area
Automated processing
A seamless wide-coverage
ASTER scene (60km x 60km)
ASTER G-DEM
DEM
Comparison with other DEMsASTER G-DEM SRTM3
Shuttle Radar Topography Mission Data at 3 Arc-Seconds
GTOPO30Global 30 Arc-Second Elevation Data Set
Data source ASTER Space shuttle radar From organizations around the world that have DEM data
Generation and distribution
METI of Japan / NASA NASA/NGA/USGS USGS
Release year 2009 ~ (planned) 2003 ~ 1996 ~Data acquisition period
2000 ~ ongoing 11 days ( in 2000 )
DEM resolution 30m 90m 1000m
DEM accuracy (stdev.)
±7m ±10m ±30m
DEM coverage 83 degrees north ~ 83 degrees south
60 degrees north ~ 56 degrees south
Global
Area of missing data Areas with no ASTER data due to constant cloud cover
Topographically steep area (due to radar characteristics)
None
The ASTER G-DEM is the only sophisticated global coverage DEM, which will be widely used as the global standard.
NGA : National Geospatial-intelligence
Agency
USGS : United States Geological Survey