evaluating the rapideye, geoeye-1, cartosat-2 and kompsat ... · cartosat-2 and kompsat-2 imagery...

15th Conference 'Geomatics in support of the CAP" - Taormina (Sicily-Italy), 18-20 November 2009 1

Evaluating the RapidEye, GeoEye-1, Cartosat-2 and KOMPSAT-2 Imagery for use in the CAP CwRS programme

Joanna K. Nowak Da CostaPiotr A. Tokarczyk JRC, IPSC, MARS, CIDPär J. Åstrand


AcknowledgementsWe would like to thank:- the RapidEye personnel, and in particular Scott Douglass, who kindly provided us with a big

sample of the RapidEye test data and technical assistance.

- the SpotImage & Customer Relations Managers ~ KOMPSAT-2 personnel, and in particular Christelle Puech & Philomène Jacquier, Pierre Boubée, Bruno Montfort, who kindly provided us with the Kompsat-2 test data over the JRC Maussane test site.

- Mr. Usha and Mr. Kaveri from Indian National Remote Sensing Centre (NRSC) of Indian Space Research Organisation (ISRO), who kindly provided us with the Cartosat-2 scene over the JRC Maussane test site.

- the EFTAS company personnel, and in particular Jörn Brockmann and Robert Stein, who kindly provided us with their RapidEye 3A LPIS-based quality control results and the set of their check points over MFRA and WEIL German control zones.

- the GISAT company personnel, and in particular Lubos Kucera, who kindly provided us with their auxiliary data (aerial orthoimages) for the RE 1B test over CZ control zones.

- the TRAGSATEC personnel, and in particular Pedro Miguelsanz Munoz, for excellent cooperation.


Outline

• Methodology• RapidEye• GeoEye-1• Cartosat-2• Kompsat-2• Further Research Agenda• Key issues


Image Geometric Quality Analysis - Methodology

Do I have the right tools for the job?



Do I have the right tools for the job?



The planimetric accuracy of orthoimage is sensitive to various factors:

- number, distribution & accuracy of ground control points (GCPs)- number, distribution & accuracy of validation data (ICPs)- features selection for GCP/ICP locations- observer’s capacity to identify GCP/ICP on image data- accuracy of height data (DEM) for image correction- satellite incidence angles- mathematical model used for sensor orientation, i.e. RPC, Toutin’s- order of polynomial functions (if used)- implementation of sensor mathematical model into software- …



Change one factor at a time while keeping all other conditions the same


CAP CwRS Geometric Accuracy Requirements

The EU standard for the orthoimagery to be used for the purpose of the CAP CwRS requires the assessment of the final orthoimage.

The RMS error calculated for Independent Check Points (ICPs), measured on the final orthoimage, should not exceed a given value in each direction (either Easting or Northing).

The RMS_ICPs errors obtained during the sensor orientation (image geometric correction) phase are part of the orthoimage quality assurance process, HOWEVER they are NOT RECOMMENDEDto be used as the final orthoimage accuracy result.


CAP CwRS Geometric Accuracy Requirements

The difference between the RMSE values before (model) and after (actual) image orthorectification based on RPC method – for the same set of independent check points (RE 1B PEPR).

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RMSE_E [m] (after)

RMSE_N [m] (after)

RMSE_E [m] (before)

RMSE_N [m] (before)


RapidEye 1B Geometric Quality Analysis

RMSE based on the measurements of the 12 (MAUSS) or 14 (PEPR) ICPs on the final ortho• RMSE remains almost unchanged with increasing number of GCPs• RMSE of circa one RE pixel (5m) already reached based on one GCP

RMSE_ICP [m] as a function of the GCPs number used during the RPC-based sensor orientation

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RMSE_E (EQC) MAUSS

RMSE_N (EQC) MAUSS

RMSE_E (EQC) PEPR

RMSE_N (EQC) PEPR


RapidEye 1B Geometric Quality Analysis

RMSE based on the measurements of the 12 (MAUSS) or 14 (PEPR) ICPs on the final ortho• RMSE not sensitive to the sensor orientation method

RMSE_ICP [m] as a function of the GCPs number used during the RPC-based sensor orientation (MAUSS, PEPR_CZ) vs. Toutin’s rigorous model (MAUSS)

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RMSE_E (RPC) MAUSS

RMSE_N (RPC) MAUSS

RMSE_E (RPC) PEPR

RMSE_N (RPC) PEPR

RMSE_E (rigorous) MAUSS

RMSE_N (rigorous) MAUSS


RapidEye 3A Geometric Quality Analysis

RMSE based on the measurements of 20 well-distributed ICPs except for 2.7, 3.9 and 7.5° cases • RMSE is of an average value of 17m (= almost four RE pixels!)• RMSE of 8.5m (or better) achieved after systematic shift elimination (0-order polynomial)

based on minimum 6 well-distributed points• RMSE remains almost unchanged with increasing across track incidence angle

RMSE_ICP [m] as a function of the across track incidence angle (MAUSS and KARD_BG)

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RMSE_X [m] Easting

RMSE_Y [m] Northing

RMSE_X [m] Easting (0-order polynomial warping)

RMSE_Y [m] Northing (0-order polynomial warping)

not well distributed ICPs


RapidEye 3A Geometric Quality Analysis

Provision of more accurate auxiliary data - to substitute RE standard data - also leads to an improvement of the geometric quality of the final image product, e.g. the LPIS-based GCPs are of better accuracy than the Global Landsat Mosaic-based ones.

RMSE of circa one RE pixel (5m) can be reached (left chart) BUT one can obtain similar or even better value through RE 1B orthorectification based on one GCP (right)

RMSE_ICP [m] of enhanced RE 3A product as a function of the across track incidence angle

(MAUSS, MFRA_DE, WEIL_DE)

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RMSE_X [m] (higher number and accuracy of GCPs)

RMSE_Y [m] (higher number and accuracy of GCPs)

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RMSE_E (EQC) MAUSS

RMSE_N (EQC) MAUSS

RMSE_E (EQC) PEPR

RMSE_N (EQC) PEPR

RMSE_ICP [m] of RE 1B as a function of GCPs number used for RPC-based sensor orientation

and orthorectification (MAUSS, PEPR_CZ)


GeoEye-1 Geometric Image Quality Analysis

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RMSE_ICP_X Tragsatec, PCIRMSE_ICP_X JRC CID, ERDAS LPSRMSE_ICP_Y Tragsatec, PCIRMSE_ICP_Y JRC CID, ERDAS LPS

RMSE based on the measurements of the 13 well-distributed ICPs on the final orthoimages • RMSE remains almost unchanged with increasing number of GCPs• RMSE of 2.5m already reached based on 3 GCPs

RMSE [m] of ICPs as a function of the number of the GCPs used for RPC-based sensor orientation

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RMSE_ICP_X Tragsatec, PCIRMSE_ICP_X JRC CID, ERDAS LPSRMSE_ICP_Y Tragsatec, PCIRMSE_ICP_Y JRC CID, ERDAS LPS


Cartosat-2 Geometric Quality Analysis

RMSE based on the measurements of the SINGLE orthoimage over MAUSS (13 constant ICPs)• RMSE of 2.5m already reached based on 3 GCPs (4 GCPs recommended)• RMSE decreases with increasing number of GCPs (negligible for more than 6)

RMSE_ICP [m] as a function of the GCPs number used during RPC-based sensor orientation

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RMSE_East [m]

RMSE_North [m]

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Kompsat-2 Geometric Quality Analysis

RMSE based on the measurements of the SINGLE orthoimage over MAUSS (13 constant ICPs)• RMSE of 2.5m reached based on 3 and 12 GCPs (RPC and rigorous, respectively) but• Questionable RMSE convergency with increasing number of GCPs

RMSE_ICP [m] as a function of the GCPs number used during the RPC-based sensor orientation (1st polynomial order) vs. Toutin’s rigorous model (MAUSS image)

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RMSE_E (rigorous)

RMSE_N (rigorous)

RMSE_E (RPC)

RMSE_N (RPC)


Kompsat-2 Geometric Quality Analysis

RMSE based on the measurements of the 13 or 9 well-distributed ICPs (FR or BG, respectively)• RMSE of 2.5m reached for 9 GCPs for BG site (ReSAC company analysis of 2008)• Questionable RMSE convergency with increasing number of GCPs for MAUSS!

RMSE_ICP [m] as a function of the GCPs number used during the single scene correction by RPC-based method (1st polynomial order) over French (Maussane) and Bulgarian test site

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RMSE_E (RPC) MAUSS

RMSE_N (RPC) MAUSS

RMSE_E (RPC) BG

RMSE_N (RPC) BG


Further Research Agenda

NEW:• WorldView-2• UK-DMC2• Theos

Continuation (more sample images needed):• Kompsat-2• Cartosat-2• EROS-B

- RMSE convergency with increasing number of GCPs - Influence of the across track incidence angle - Block adjustment


Key IssuesBased on the limited RE, GE1, C2, K2 sample images that were made available to us:- the RapidEye 1B orthoimage accuracy is 5.5m provided that one ground control point (GCP)

is introduced during the sensor orientation phase when using the Rational Functions mathematical model. The addition of one more GCP allows to achieve a 1-D RMSE of <4m

- the RapidEye 3A product can reach 8.5m accuracy (or more) provided that systematic shift is eliminated (e.g. 0-order polynomial warping) based on at least 6 well-distributed GCPs. The original product RMSE is 17m on average.

- the GeoEye-1 orthoimage accuracy meets the geometric specification of 2.5m (1D) RMSE corresponding to EU technical requirements for at least three well-distributed ground control points

- the Cartosat-2 orthoimage accuracy meets the geometric specification of 2.5m (1D) RMSE corresponding to EU technical requirements for at least three well-distributed ground control points (4-6 GCPs recommended)

- the Kompsat-2 orthoimage accuracy meets the geometric specification of 2.5m (1D) RMSE corresponding to EU technical requirements for at least nine well-distributed ground control points (12 GCPs recommended)

Satellite Image Quality Research Cooperation – VERY WELCOME


Thank you!

[email protected]

http://cidportal.jrc.ec.europa.eu/

http://mars.jrc.ec.europa.eu/

evaluating the rapideye, geoeye-1, cartosat-2 and kompsat ... · cartosat-2 and kompsat-2 imagery...

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