Abstract

The constellation of Landsat-8 and Sentinel-2 optical satellites offers opportunities for a wide range of Earth Observation (EO) applications and scientific studies in Earth sciences mainly related to geohazards. The multi-temporal co-registration accuracy of images provided by both missions is, however, currently not fully satisfactory for change detection, time-series analysis and in particular Earth surface motion measurements. The objective of this work is the development, implementation and test of an automatic processing chain for correcting co-registration artefacts targeting accurate alignment of Sentinel-2 and Landsat-8 imagery for time series analysis. The method relies on dense sub-pixel offset measurements and robust statistics to correct for systematic offsets and striping artefacts. Experimental evaluation at sites with diverse environmental settings is conducted to evaluate the efficiency of the processing chain in comparison with previously proposed routines. The experimental evaluation suggests lower residual offsets than existing methods ranging between R M S E x y = 2.30 and 2.91 m remaining stable for longer time series. A first case study demonstrates the utility of the processor for the monitoring of continuously active landslides. A second case study demonstrates the use of the processor for measuring co-seismic surface displacements indicating an accuracy of 1/5 th of a pixel after corrections and 1/10th of a pixel after calibration with ground measurements. The implemented processing chain is available as an open source tool to support a better exploitation of the growing archives of Sentinel-2 and Landsat-8.

Highlights

  • The constellation of Landsat-8 [1] and Sentinel-2 optical satellites [2] have a great potential to be used synergetically for a variety of Earth Observation (EO) applications due to their similar spectral and spatial properties and free and open data access

  • Given that even sub-pixel offsets have detrimental impact on the accuracy of time-series analyses [3,13,14,15] and in particular surface motion measurements [6,10,16,17], improved geometric pre-processing constitutes an essential step to exploit image time-series. While this applies in general for the analysis of images acquired by different satellite and aerial platforms this study focuses in particular on Sentinel-2 and Landsat-8 which are both freely and globally available with standardized formats and similar spatial and spectral characteristics

  • We propose the coregis processor which has been designed to address both highly accurate co-registration of Sentinel-2 and Landsat-8 data and surface motion measurements

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Summary

Introduction

The constellation of Landsat-8 [1] and Sentinel-2 optical satellites [2] have a great potential to be used synergetically for a variety of Earth Observation (EO) applications due to their similar spectral and spatial properties and free and open data access. Given that even sub-pixel offsets have detrimental impact on the accuracy of time-series analyses [3,13,14,15] and in particular surface motion measurements [6,10,16,17], improved geometric pre-processing constitutes an essential step to exploit image time-series While this applies in general for the analysis of images acquired by different satellite and aerial platforms this study focuses in particular on Sentinel-2 and Landsat-8 which are both freely and globally available with standardized formats and similar spatial and spectral characteristics

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