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ESSD | Articles | Volume 12, issue 1
Earth Syst. Sci. Data, 12, 539–553, 2020
https://doi.org/10.5194/essd-12-539-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Earth Syst. Sci. Data, 12, 539–553, 2020
https://doi.org/10.5194/essd-12-539-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Data description paper 05 Mar 2020

Data description paper | 05 Mar 2020

Geometric accuracy assessment of coarse-resolution satellite datasets: a study based on AVHRR GAC data at the sub-pixel level

Xiaodan Wu et al.

Data sets

ESA Cloud Climate Change Initiative (ESA Cloud_cci) data: Cloud_cci AVHRR-AM L3C/L3U CLD_PRODUCTS v2.0 M. Stengel, O. Sus, S. Stapelberg, C. Schlundt, C. Poulsen, and R. Hollmann, https://doi.org/10.5676/DWD/ESA_Cloud_cci/AVHRR-AM/V002

MOD13A1 MODIS/Terra Vegetation Indices 16-Day L3 Global 500m SIN Grid V006 [Data set] K. Didan https://doi.org/10.5067/MODIS/MOD13A1.006

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Short summary
Based on the idea of the co-registration method, this study proposes a method named correlation-based patch matching method (CPMM), which is capable of quantifying the geometric accuracy of coarse-resolution satellite data. The assessment is conducted at the sub-pixel level and not affected by the mixed-pixel problem. It is not limited to a certain landmark such as a lake or sea shoreline and thus enables a more comprehensive assessment.
Based on the idea of the co-registration method, this study proposes a method named...
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