Abstract

Abstract. Detection of changes occurring on Earth surface has become an established practice in remote sensing science since the availability of high-resolution, global coverage, and multitemporal satellite imagery that has constantly increased during the last decades. Meanwhile, the open data policies embraced by some of the principal Earth Observation programs have boosted the spread of such analyses. This asset has attracted also the interest of the private sector which is developing strategies to exploit the potential of these data. In view of the above, we present an experimental procedure to investigate land cover displacements through an application on open multispectral imagery from the Landsat 8 and Sentinel-2 missions for desert sand dunes movements analysis. While most of the change detection techniques focus on locating changes and describing them by means of variation in the pixel spectral responses, the proposed technique aims at describing spatial and temporal patterns of displacements (i.e. directions and magnitude) applying cross-correlation analysis on a multitemporal images stack. Results of the proposed analysis are critical to a number of construction engineering operations that require sand mitigation planning and continuous site monitoring to prevent windblown sand interactions with infrastructures in the desert environment. An overview of the preliminary results is presented together with an extensive discussion on further improvements requested by the procedure. Computational steps leverage exclusively open data and free and open source GIS software thus providing large rooms to empower, replicate and improve thereof.

Highlights

  • The emerging availability of high-resolution, global coverage, and multitemporal imagery - captured by the modern satellite missions - has empowered a number of studies focusing on the detection of changes occurring on the Earth’s surface

  • The increased interest in multitemporal imagery analysis is mainly triggered by the rising number of satellites with short revisiting time that enables the acquisition of either long time series or frequent bi-temporal images (Ghamisi et al, 2019)

  • The use of shorter time steps and a moving master should be preferred when the dynamic of periodical displacements is the focus of the analysis

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Summary

Introduction

The emerging availability of high-resolution, global coverage, and multitemporal imagery - captured by the modern satellite missions - has empowered a number of studies focusing on the detection of changes occurring on the Earth’s surface. The open distribution policies of both archive data as well as new observations - adopted by some of the principal Earth Observation programs - enable outstanding opportunities for the user community to grow and, in turn, facilitate the spread of case studies exploiting multitemporal imagery (Belward, Skøien, 2015). The high spatial and spectral resolution - nowadays provided by the open multispectral satellite imagery – allows for applications at a finer scale. These assets are further attracting the interest of

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