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