GCOM-C/SGLI geometric correction algorithm
Junichi Takaku
RESTEC, Oct. 2018 (v1.000)

1. Overview
The GCOM-C/SGLI geometric correction algorithm processes the Level-1B images into theLevel-2 (LTOA) tiles on Sinusoidal (EQA) coordinates. The algorithm consists of1) the orientation process (G2A), which supports the precise correction by utilizing the groundcontrol points (GCPs),
2) the ortho/mosaic process (G2B/G2C), which mosaics the multiple Level-1B images
through the ortho-rectification by using the digital elevation model (DEM), and3) the GCP matching (G2D), which automatically measures the GCPs with an image matchingtechnique.
Figure 1 shows the geometric correction flow of GCOM-C/SGLI images (including the Level-1Bprocess).

GCP

DEM

Run by each scene
L1A
L1A
24 scenes/path (VNP/IRS)
L1A
L1A
Level-1A
1 half-path (POL)
Level 1B process(Radio)+(Geo)

L1A
L1A
L1A
Level-1B

GCP matching

GCP
GCP
GCP
GCP
Info.
Info.
Info.
Info.

Orientation

L1B
list
L1B
listforfor
L1B
for
L1Blistlist
foreachtile
eachtile
eacheachtile
tile

Run by each tile

Level-2 ortho/mosaic

Level
2LevelLevel22
Tile
Level-2
Tile
Tile
Tile

PGCP

Run by each pathAll 36x18(x2: day-night) tiles(250m/1km)

Daily (approx. 14 paths)

Figure 1.

Geometric correction flow from Level 1A to Level 2.

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2. Orientation
The orientation process (G2A) estimates the orientation parameters of geometric models in SGLI
sensors by using the collinearity equations defined from the GCPs. The algorithm is based on the oneused in the SGLI’s predecessor GLI, which utilizes the least-square fit of GCP errors in a manner ofthe traditional photogrammetry [1]. The initial orientation parameters to be estimated are set to theattitude errors of the satellite (including the sensor alignment errors), while they can be changed
depending on the on-orbit calibration. The linear dynamics of the errors, as well as the constant bias,
are compensated in a path-basis. The process inputs the Level-1B datasets as well as GCPs
(GCP_info) in a target path; and then, it output the estimated attitude errors as well as the residuals ofGCPs to the PGCP file. Figure 2 shows the processing flow of the orientation.

Including L1B list
Path no.

Read data

L1B(VNR/IRS)

Orientation process(path-basis)

GCP_Info

Write PGCP
Figure 2.

Processing flow of the orientation.

2PGCP

3. Level-2 (LTOA) ortho/mosaic
The Level-2 ortho/mosaic process (G2B/G2C) mosaics the multiple Level-1B images into theLevel-2 (LTOA) tiles on Sinusoidal coordinates through the ortho-rectification by using the digital
elevation model (DEM) as well as the precise correction by utilizing the orientation parameters(PGCP). In the Sinusoidal coordinates the global areas are divided into 36 x 18 tiles while each tile
has an area of approximately 1200 km x 1200 km (10° x 10° at the equator). Figure 3 shows the tile
frame structure of the LTOA products [2].

Figure 3.

Sinusoidal tiles for LTOA product [2]The tiles of two grid spacing, i.e., 250 m (LTOAQ/G2B) and 1 km (LTOAK/G2C), are separately
defined, so that the tiles of LTOAQ and LTOAK include 4800 x 4800 grids and 1200 x 1200 grids,respectively. Moreover, the descending (day time) and the ascending (night time) tiles are
independently defined in each of them. Namely, there are four tile frames, i.e., LAOTQ-day,
LTOAQ-night, LTOAK-day, and LTOAK-night. The mosaicking is daily-basis where approximately
14 paths are observed in each day. On overlapping areas of neighboring paths a pixel that has
smallest sensor zenith angle is preferentially assigned in the mosaicking. The ASTER/GDEM version
2 [3] is used as the global DEM input. In the LTOAK processing the 250 m images of LTOAQ are
preferentially set with 4 x 4 pixel averaging if it exists instead of setting the 1 km images of Level-1B.
Figure 4 shows the processing flow of the Level-2 ortho/mosaic.

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Param. (tile id, etc.)
Including L1B list

Read param.&L1B list
Read DEM

DEM(GDEM)LTOAQ -> LTOAK*
LTOAQ**) in case of LTOAK process

Ortho-projection
address calc.
Mosaicking(scene/path)

PGCP

Set. flag, ancillary, etc.

L1B(VNR/IRS/POL)
250m/1km

LTOAQ/LTOAK

Write LTOA
Figure 4.

Processing flow of the Level-2 ortho/mosaic.

The LTOAQ tile includes not only 250 m images but also other images as follows:
1) LTOAQ includes IRS 1km images of SW01, SW02, and SW04, whereas it does not include
the IRS 1km images of SW03, TI01, and TI02.
2) LTOAQ includes the POL 1 km images only if it includes 250 m images of VNR or IRS.
3) The IRS 500 m images of TI01 and TI02 are up-sampled to 250 m with NN resampling andare set to LTOAQThe geometric ancillary data i.e., the azimuth/zenith angles of the sensor/solar, observing time,and relevant flags are mosaicked to LTOA tiles as well as the image data.

44. GCP matching
The GCP matching automatically measures the GCPs for VNR/IRS Level-1B images with animage matching techniques. The GCP is derived from the ortho-rectified ALOS/AVNIR-2 images(only nadir pointing) that have a geometric accuracy of 21.9 m (RMS) in its 10 m ground resolution[4]. The AVNIR-2 images, which have the size of 70 km x 70 km each, are automatically selected fortarget SGLI Level-1B images from the GCP database. Both of the SGLI and AVNIR-2 images areresampled on a common image coordinates in 50 m grid spacing for the image matching. Featurepoints are automatically extracted from the SGLI images with their local statistics as well as edge
analysis so that outlier areas e.g., water, cloud, snow, or ice can be excluded before the matchingprocess. The matching algorithm is based on the conventional normalized cross correlation and ismeasuring the tie-points between the feature points of SGLI images and the AVNIR-2 images. The
blunders of the image matching are filtered with the correlation threshold of 0.9. The results of themeasurement are finally output as the GCPs (GCP_info) with the latitude/longitude and height thatwere derived from the AVNIR-2 geometric information and the ASTER/GDEM, respectively. In theimage matching only 250 m images of VN11 (868.5 nm) and SW03 (1630 nm) are used in VNR andIRS respectively whereas only band-4 (760~890 nm) is used in AVNIR-2. Figure 5 shows theprocessing flow of the GCP matching.

L1B (VNR/IRS)
250m

Read L1B
Search AVNIR-2 (GCP)

AVNIR-2(GCP)

Read AVNIR-2 (GCP)
Matching proc.
Read DEM

DEM(GDEM)

Write GCP_info

Figure 5.

Processing flow of the GCP matching.

5GCP_info

References[1] T.

Hashimoto,“GeometricCorrectionofADEOS-II/GLI,”International

Archivesof

Photogrammetry and Remote Sensing, Vol. XXXIII, Part B1, pp.141-147, Amsterdam, 2000.
[2] R. E. Wolfe, D. P. Roy, and E. Vermote, “MODIS Land Data Storage, Gridding, and Compositing
Methodology: Level 2 Grid,” IEEE Transactions on Geoscience and Remote Sensing, Vol. 36, no. 4,
pp.1324-1358, 1998.
[3] T. Tachikawa, M. Hato, M. Kaku, and A. Iwasaki, “Characteristics of ASTER GDEM version 2,”
Proc. IEEE IGARSS 2011, pp.3657-3660, 2011.
[4] JAXA/EORC, “Calibration Result of JAXA standard products (As of Sep. 6, 2011),” [Online].
Available: https://www.eorc.jaxa.jp/en/hatoyama/satellite/data_tekyo_setsumei/alos_hyouka_e.html.
[Accessed Nov. 1, 2018].

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