Quantitative geometric calibration &amp;#x00026; validation of the Rapideye constellation

Robertson, B.C.; Beckett, Keith; Rampersad, Chris; Putih, Rony

doi:10.1109/igarss.2009.5417700

Cited by 6 publications

(8 citation statements)

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“…The RapidEye constellation was launched in 2008 and consists of five identical satellites that allow an up to daily acquisition of multispectral images (5 bands in the visible to near infrared) with a spatial resolution of 6.5 m. Basic preprocessing had already been applied to the purchased L3A data, including radiometric, sensor and geometric corrections, as well as on-board spacecraft corrections [58]. Both RapidEye and Landsat TM data were geometrically resampled to a common 20 m grid used in the simulations.…”

Section: Parameter Retrieval From Earth Observation Datamentioning

confidence: 99%

Using a Remote Sensing-Supported Hydro-Agroecological Model for Field-Scale Simulation of Heterogeneous Crop Growth and Yield: Application for Wheat in Central Europe

2015

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Abstract:The challenge of converting global agricultural food, fiber and energy crop cultivation into an ecologically and economically sustainable production process requires the most efficient agricultural management strategies. Development, control and maintenance of these strategies are highly dependent on temporally and spatially continuous information on crop status at the field scale. This paper introduces the application of a process-based, coupled hydro-agroecological model (PROMET) for the simulation of temporally and spatially dynamic crop growth on agriculturally managed fields. By assimilating optical remote sensing data into the model, the simulation of spatial crop dynamics is improved to a point where site-specific farming measures can be supported. Radiative transfer modeling (SLC) is used to provide maps of leaf area index from Earth Observation (EO). These maps are used in an assimilation scheme that selects closest matches between EO and PROMET ensemble runs. Validation is provided for winter wheat (years 2004, 2010 and 2011). Field samples validate the temporal dynamics of the simulations (avg. R² = 0.93) and > 700 ha of calibrated combine harvester data are used for accuracy assessment of the spatial yield simulations (avg. RMSE = 1.15 t·ha −1). The study shows that precise simulation of field-scale crop growth and yield is possible, if spatial remotely sensed information is combined with temporal dynamics provided by land surface process models. The presented methodology represents a technical solution to make the best

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Section: Parameter Retrieval From Earth Observation Datamentioning

confidence: 99%

Using a Remote Sensing-Supported Hydro-Agroecological Model for Field-Scale Simulation of Heterogeneous Crop Growth and Yield: Application for Wheat in Central Europe

2015

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“…As the external angle element and line element are strongly correlated, we only take the attitude measurement error into account and treat the orbit measurement error as a part of the attitude measurement error.) In a single scene of image the attitude measurement error can be considered as a constant, whereas there is a degree of random deviation between different scenes of images acquired at different times [2]. Meanwhile, it is noteworthy that, as a scene-dependent random error, it is impossible to distinguish the attitude measurement error from the camera installation angle error using a single scene of an image.…”

Section: Attitude Measurement Errormentioning

confidence: 99%

On-Orbit Geometric Calibration Model and Its Applications for High-Resolution Optical Satellite Imagery

Wang

Yang

et al. 2014

Remote Sensing

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On-orbit geometric calibration is a key technology to guarantee the geometric quality of high-resolution optical satellite imagery. In this paper, we present an approach for the on-orbit geometric calibration of high-resolution optical satellite imagery, focusing on two core problems: constructing an on-orbit geometric calibration model and proposing a robust calculation method. First, a rigorous geometric imaging model is constructed based on the analysis of the major error sources. Second, we construct an on-orbit geometric calibration model through performing reasonable optimizing and parameter selection of the rigorous geometric imaging model. On this basis, the calibration parameters are partially calculated with a stepwise iterative method by dividing them into two groups: external and internal calibration parameters. Furthermore, to verify the effectiveness of the proposed calibration model and methodology, on-orbit geometric calibration experiments for ZY1-02C panchromatic camera and ZY-3 three-line array camera are conducted using the reference data of the Songshan calibration test site located in the Henan Province, China. The experimental results demonstrate a certain deviation of the on-orbit calibration result from the initial design values of the calibration parameters. Therefore, on-orbit geometric calibration is necessary for optical satellite imagery. On the other hand, by choosing multiple images, which cover different areas and are acquired at different points in time to verify their geometric accuracy before and after calibration, we find that after on-orbit geometric calibration, the geometric accuracy of these images without ground control points is significantly OPEN ACCESS

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“…Therefore, it is common for earth-observation satellite programs to calibrate the alignment during the initial commissioning period [2,3,[6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. However, it is difficult to obtain an accurate alignment because the alignment error is measured as the sum of various error sources [6].…”

Section: Introductionmentioning

confidence: 99%

“…Some researchers tried an automatic GCP extraction technique using reference ortho-photos and image-based feature matching to get a much higher number of GCPs [12][13][14]21,22]. Robertson et al even included the automated GCP extraction step to RapidEye's ground processing chain for alignment calibration [14].…”

Section: Introductionmentioning

confidence: 99%

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On-Orbit Camera Misalignment Estimation Framework and Its Application to Earth Observation Satellite

Lee

Shin

2015

Remote Sensing

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Despite the efforts for precise alignment of imaging sensors and attitude sensors before launch, the accuracy of pre-launch alignment is limited. The misalignment between attitude frame and camera frame is especially important as it is related to the localization error of the spacecraft, which is one of the essential factors of satellite image quality. In this paper, a framework for camera misalignment estimation is presented with its application to a high-resolution earth-observation satellite-Deimos-2. The framework intends to provide a solution for estimation and correction of the camera misalignment of a spacecraft, covering image acquisition planning to mathematical solution of camera misalignment. Considerations for effective image acquisition planning to obtain reliable results are discussed, followed by a detailed description on a practical method for extracting many GCPs automatically using reference ortho-photos. Patterns of localization errors that commonly occur due to the camera misalignment are also investigated. A mathematical model for camera misalignment estimation is described comprehensively. The results of simulation experiments showing the validity and accuracy of the misalignment estimation model are provided. The proposed framework was applied to Deimos-2. The real-world data and results from Deimos-2 are presented.

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Quantitative geometric calibration & validation of the Rapideye constellation

Cited by 6 publications

References 0 publications

Using a Remote Sensing-Supported Hydro-Agroecological Model for Field-Scale Simulation of Heterogeneous Crop Growth and Yield: Application for Wheat in Central Europe

Using a Remote Sensing-Supported Hydro-Agroecological Model for Field-Scale Simulation of Heterogeneous Crop Growth and Yield: Application for Wheat in Central Europe

On-Orbit Geometric Calibration Model and Its Applications for High-Resolution Optical Satellite Imagery

On-Orbit Camera Misalignment Estimation Framework and Its Application to Earth Observation Satellite

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