Comparison of two Satellite Imaging Platforms for Evaluating Sand Dune Migration in the Ubari Sand Sea (Libyan Fazzan)

Abstract

ABSTRACT:Sand dunes can change location, form or dimensions depending on wind direction and strength. Sand dune movements can be effectively monitored through the comparison of multi-temporal satellite images. However, not all remote sensing platforms are suitable to study sand dunes. This study compares coarse (Landsat) and fine (Worldview) resolution platforms, specifically focussing on sand dunes within the Ubari Sand Sea (Libya). Sand dune features (crest line, dune ridge basal outlines) were extracted from Landsat and Worldview 2 imagery in order to construct geomorphic maps. These geomorphic maps were then compared using image overlay and differencing, and the Root Mean Squared Error (RMSE) was used to determine if the mapped dune patterns were significantly different. It was found that Landsat is a sufficient data source when studying dune patterns within a regional sand sea, but smaller dunes identified from Worldview data were not capable of being extracted in the data sourced from Landsat. This means that for studies concerned with the dune patterns and movements within sand seas, Landsat is sufficient. But in studies where the specific dynamics of specific dunes are required, a finer resolution is required; platforms such as Worldview are needed in order to gain more detailed insight and to link the past and present day climate and environmental change.

Comparison of CBERS-04, GF-1, and GF-2 Satellite Panchromatic Images for Mapping Quasi-Circular Vegetation Patches in the Yellow River Delta, China

“…However, the cost of acquiring fine-resolution remote sensing data and the associated data processing time over large land areas is prohibitive. Therefore, ongoing research is devoted to the comparison of the mapping and detection capabilities of various sensors to determine the optimal scale for monitoring vegetation, burn severity, land surface water, gross primary productivity, soil information, sand dune features, and archaeological crop marks, amongst others [ 22 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 ]. The overall success rate for mapping the six invasive plants using full resolution Advanced Visible Infrared Imaging Spectrometer (AVIRIS, 174 bands, 4 m spatial resolution) was 17% more than that of the spatially degraded AVIRIS (174 bands, 30 m) [ 22 ].…”

Mapping dune dynamics by InSAR coherence

“…Early studies relied mainly on passive optical systems, such as Landsat 1 (ERTS), to map and classify dunes McKee, 1979). More recent studies have exploited improvements in the spectral and spatial resolution of remote sensing technologies (Maman et al, 2011;Hugenholtz et al, 2012;Hereher, 2014;Els et al, 2015;Martone et al, 2016;Paillou et al, 2016) for quantitative investigations of dune features, forms and pattern development, which were not possible with the earlier types of imagery (Ewing and Kocurek, 2010;Hugenholtz and Barchyn, 2010;Yang et al, 2011;Hermas et al, 2012;Livingstone, 2013).…”

Detecting Areas Vulnerable to Sand Encroachment Using Remote Sensing and GIS Techniques in Nouakchott, Mauritania

“…In Nouakchott, the most vulnerable area is the eastern and northern part of the city, with vulnerability values ranging from medium to high (23 to 27) ( Figure 7, bottom-right). The center and south of the city evidence lower vulnerability, with values from medium to low (17)(18)(19)(20)(21)(22). It should be noted that a small area in the western part of Nouakchott is missing due to a lack of information for some of the factors, such that it was not possible to calculate the SDEVI.…”

“…However, we also included other parameters that derive from geology, land cover/land use and remotely sensed soil moisture information. This new index is called the Sand Dune Encroachment Vulnerability Index (SDEVI), and aims to improve on previous efforts [18][19][20] carried out to assess vulnerability to the advance of sand as well as to help local authorities and decision-makers to devise predictive and mitigation measures. We considered adding remote sensing data in order to boost the adaptability of the assessment to our local conditions, as described in Equation 1.…”

“…In addition, Lancaster et al [17] suggest that validation methods are often difficult because field measures are short and not available on a multi-year basis. Some studies have focused on reducing the vulnerability of affected areas [18,19] and on monitoring the mobility of sand dunes [20]. In order to ensure the success of this type of project, satellite remote sensing approaches have been used to efficiently monitor large and difficult to access areas [21][22][23].…”