Akira MUKAIDA RESTEC Feb. 21 2012@UNESCAP Workshop on Flood Risk Reduction through Space Application in South‐East Asia Satellite‐based Digital Terrain Mapper
Jul 15, 2020
Akira MUKAIDA RESTECFeb. 21 2012@UNESCAPWorkshop on Flood Risk Reduction through Space Application in South‐East Asia
Satellite‐based Digital Terrain Mapper
Mar 14, 2011 Ishinomaki cityALOS/AVNIR-2
Mar 24, 2011 Rikuzentakata cityALOS/PRISM, AVNIR-2
Nov 19, 2011 Central BangkokBy Pi-SAR-L
Contents
• What remote sensing can provide?
• Terrain observation from space.– Basics of terrain observation.
– Observation by optical sensor.• Example of ALOS/PRISM
• Example of water resource management using remote sensing.
• Summary
What remote sensing can provide?
Satellite remote sensing can provide…• High frequent observation.• Wide coverage and high resolution.• Observation in equivalence quality (objective).
What remote sensing can provide?
The information from remote sensing data will help water resource management ,
• Nowcasting(i.e. inundation monitoring..)
• Forecasting
• Together with prediction model or assimilation.
Digital Terrain Modelfrom satellite remote sensing
Digital Elevation Model (DEM)– An array of elevation points without any attributes (i.e. may represent the
terrain surface. No buildings and trees.)
Digital Surface Model (DSM) <our target>– An array of elevation points representing the surface closest to the sensor
(may be same as a DEM)
Digital Terrain Model (DTM)– An array of points representing the terrain. Also called Digital Ground
Model.– Strictly speaking, the term DTM, Digital Terrain Model, should be reserved
for those models of reality which includes information relating to surface texture, etc., in addition to information regarding elevation.
Reference : Ian Dowman, “Generating Digital Elevation Models from Satellite Imagery”, presentation materials of the special seminar on DEM extractions in JAXA/EORC, Tokyo, 2002.
Basics
Height reference– Orthometric height = Height above the reference geoid level (mean sea
level) (i.e. EGM96)– Ellipsoidal height = Height above the reference ellipsoid model (i.e. GRS80
ellipsoid) <our target>– Geoidal height = Height of geoid surface above the reference ellipsoid
model (i.e. GRS80)
Generally…
ジオイド
準拠楕円体
地面
楕円体高
ジオイド高
標高
数値表層モデル(DSM )
数値地形モデル(DTM )
Digital Surface Model (DSM)
Digital Elevation Model (DEM)
Ground
Reference Geoid model(i.e. EGM96)
Reference Ellipsoid model (i.e. GRS80)
Geoidal height
Orthometric heightEllipsoidal height
Basics
Types and patterns– Generally corrected as pseudo random points (TIN)– Re-sampled to grid using interpolation <our target>– Breaklines added to define special features
Data sources– Ground survey– Aerial Photography– Satellite data
– Optical sensor <our target>– Interferometric SAR (InSAR)
– LIDAR– Existing data - maps
Basics
ALOS mission objectives are to;Provide and update maps for Japan and other countries including those in the Asian-Pacific region (Cartography),Perform regional observation for “sustainable development,” harmonization between earth environment and development (Regional Observation),Conduct disaster monitoring around the world (Disaster Monitoring),Survey natural resources (Resources Surveying), andDevelop technology necessary for future earth observing satellites (Technology Development).
Launch DateSpacecraft MassGenerated PowerDesign LifeOrbitAltitudeInclinationPeriodRecurrent Cycle
: 2006.01.24: Approx. 4 tons: Approx. 7 kW (at End of Life): 3‐5 years: Sun‐Synchronous Sub‐Recurrent: 691.65 km (at Equator): 98.16 deg.: 98.7 min.: 46 days (Sub Cycle : 2 days)
ALOS Specification
Panchromatic Remote-sensing Instrument for Stereo Mapping
Observing Geometry of triplet mode
Wavelength : 0.52 ~ 0.77 μmNumber of Optics : 3 (Nadir; Forward; Backward)at +/‐23.8 deg. inclinationBase‐to‐Height ratio : 1.0 (Forward‐Backward)Spatial Resolution : 2.5mSwath Width : 35km (Triplet mode)S/N : >70MTF : >0.2Pointing Angle : ‐1.5 to +1.5 deg. (Cross Track)Quantization : 8 bits
PRISM configuration
PRISM Specification
13
Forward lookingBackward looking Nadir looking N
©JAXA
©JAXA©JAXA
Satellite path
PRISM Triplet observation
14
ForwardNadirBackward
約24°約24°
Nadir:red, Forward:blue
Backward:red, Forward:blue
©JAXA
©JAXA
2006.05.05
2006.05.05
Anaglyph image by PRISM
At least two looking images are required to generate Stereo looking image (ex. DSM).
Difference of terrain image looking from each angle.©RESTEC included JAXA
©RESTEC included JAXA
Stereo Viewing by PRISM
Conditions– Sensor geometries of input stereo products (Level 1B1) should be fixed with
orientation process• Relative geometry for generating epipolar images of stereo matching• Absolute geometry for calculating XYZ coordinates in object space if necessary
Strategies of stereo matching– Area based grid matching with cross-correlations– Exclusive triplet stereo matching algorithm on triplet epipolar images– Coarse To Fine (CTF) ortho-image base parallax search (Ortho-image pyramid)– Automatically optimizing the cross-correlation patch size depending on image
characteristics (i.e. textures, contrast, terrain, etc.)
DSM Generation of PRISM
Triplet stereo matching on epipolar images– Resample forward, nadir and backward images on UTM epipolar frame– Search forward and backward parallaxes against nadir simultaneously
FWD
NDR
BWD
sum
yx
N
i ii yyxxN
σσρ
∑ =−−
=1
))((1
Cross correlation
yx
N
i ii yyxxN
σσρ
∑ =−−
=1
))((1
Cross correlation
Parallax direction
DSM Generation of PRISM
Epipolar image (forward)
Par
alla
x di
rect
ion
DSM Generation of PRISM
Epipolar image (nadir)
Par
alla
x di
rect
ion
DSM Generation of PRISM
Epipolar image (backward)
Par
alla
x di
rect
ion
DSM Generation of PRISM
Full Ortho‐Image
Coarse To Fine (Image pyramid)– 3~5 stages (default=3)
1/4 Averaged Ortho‐Image
Calculated DSM Grid Matching Image ( Ortho‐rectified image )
Existing DEM(optional)
1/20 Averaged Ortho‐Image
1st Coarse DSM
2nd Coarse DSM
Fine DSM
Matching Point
Search Range
DSM Generation of PRISM
DSM of CTF loop 1Matching image resolution = 50m
DSM Generation of PRISM
DSM of CTF loop 2Matching image resolution = 10m
DSM Generation of PRISM
DSM of CTF loop 3Matching image resolution = 2.5m
DSM Generation of PRISM
DSM evaluation– Compare with existing DEM/DSM
• SRTM• LiDAR-DSM• Photogrammetry DSM• Etc…
PRISM-DSM
Height difference image
Difference histogram
Evaluation of PRISM/DSM
DSM evaluation– Compare height profiles
Evaluation of PRISM/DSM
PRISM-DSM validation test sites– Six sample scenes (including 9 DSM sites)
No. Ref. DSM Sites Obs. Date No. of GCPs No. of TPs
1 Mt.Tukuba/Chiriin 03/01/07 42 9
2 Okazaki 03/23/07 17 9
3 Fukuoka 04/29/07 24 9
4 Saitama 05/03/07 213 9
5 Thun /SW/ Bern 06/24/07 54 9
6 Mt.Ibuki 09/11/07 13 9
Site Terrain Source Size HeightRange
GroundResolution
HeightAccuracy
Source Year
Saitama*1) Flat & Urban LiDAR 14.0x12.0km 100m 1m <1m 2002
Okazaki*1) Mountainous Aerial Photo 6.0x6.0km 400m 10m ~10m 2005
Thun *2) Various Aerial Photo 7.5x14.5km 500m 2.5m 0.5~2.5m 2004
SW *2) Steep Aerial Photo 7.5x14.5km 1000m 2.5m 0.5~2.5m 2004
Bern *2) Various Aerial Photo 11.0x11.5km 400m 2.5m 0.5~2.5m 2004
Fukuoka*1) Various LiDAR 12.0x9.0km 500m 1m <1m 2002
Mt.Tukuba Mountainous LiDAR 1.5x1.5km 200m 1m 0.8m 2004
Chiriin Flat LiDAR 1.5x1.5km 50m 1m 0.8m 2004
Mt.Ibuki Steep LiDAR 1.2x1.9km 700m 1m 0.8m 2005
Test scenes (Triplet stereo)
EORC/JAXA Reference DSM sites
*1) provided by GSI*2) provided by ETH
Thun/SW/Bern
SaitamaOkazak
i
Saitama
OkazakiFukuoka
Chiriin/Mt.Tsukuba
Mt.Ibuki
Evaluation of PRISM/DSM
Scene 1 : Tsukuba / JapanDate = 03/01/2007
35km NDR image in UTM frame
Reference DSM site(Mt.Tsukuba)
PRISM-DSM in 0.3 arc-sec Lat-Lon frame
Reference DSM site(Chiriin)
Evaluation of PRISM/DSM
Mt.Tsukuba 03/01/2007
PRISM-DSM (1.8x2.2km) Height difference from Reference-DSM
500m0 250
Evaluation of PRISM/DSM
SRTM-3 DEM GSI50m DEM PRISM-DSM LiDAR-DSM
Height scale [m]
Various DSM/DEM visual comparison(Fukuoka: 4km x 4km)
90m 50m 10m 1m
All world land area in N60~S56
All Japan PRISM observation areas except for
clouds
N/A
InSAR from STS-99 mission
Measured from contour lines of 1/25,000 map
Triangulation with satellite stereo
images
Airborne LiDAR
Mesh size
Data area
Sources
Evaluation of PRISM/DSM
DSM from PRISM first light image on Mt. Fuji (Feb. 14, 2006)
First light image of PRISM/DSM
PRISM DSM with Pan-sharpen image of PRISM & AVNIR-2Contributing to the research on “Great Sichuan Earthquake” in China 2008
Disaster monitoring by PRISM/DSM
Fly-thru movie (Mt. Everest)
33Gray-scaled height image on 124 tiles with mask data
: Cloud/Snow mask (01)
: Land‐water mask (02): Sea mask (03)
2000m
0m
height
Valid (00) 5,436,770,700
Mask (01) 98,921,718
Mask (02) 40,784,118
Mask (03) 12,279,523,464
Number of data
Rate of land‐data completed =((00)+(02))/((00)+(01)+(02))*100= 98.2%
Maintained PRISM/DSM on Japan
DSM mosaic
Kanto3x3 deg. Tile@10m reso.Kyusyu3x3 deg. Tile@10m reso.
• Experiment on Mekon delta.
Water resource management using remote sensing
DMC@HNI
internet
JapanVietnam
SIWRP@HCM
Image & InformationDisplay
Image analysis &communication
Terminal
Image & InformationDisplay
Distribute toSMS/FAX
ALOS
A typical End‐User
Summary
• Satellite remote sensing data can provide,– High frequent, widely covered and objectively
observed data.– Terrain information which essential input for
inundation model.• With satellite derived terrain model,
– Expect improvement of prediction by inundation model.
• It will improve both nowcast and forecast of flood situation.
Thank you so much.
Akira [email protected]://www.restec.or.jp/