# Characterisation of Coastal Sediment Properties from Spectral Reflectance Data
## 1 Introduction  
Sediment properties of sandy beaches and sand dunes, including grain size, carbonate content, moisture content, organic content, magnetic susceptibility and grain mineralogy, are most commonly measured and quantified based on field observations or field sampling, and then laboratory analysis of these samples using different analytical equipment [1, 2, 3, 4]. Following this, a range of statistical techniques (e.g., calculation of moment measures, multivariate analyses) can be used on the grain size data in particular, in order to characterise sediment properties and to interpret depositional processes and environments and their changes over time and space, e.g., [5, 6, 7, 8, 9, 10, 11]. This standard methodology has been undertaken on many beaches and dunes worldwide, resulting in an understanding of spatial patterns of different sediment properties (based mainly on grain size) across different coastal depositional environments, e.g., [12, 13, 14, 15]. The main problem of such a field-based approach is that it provides only a limited view of local-scale coastal sediment properties and dynamics, which is often strongly affected by the specific spatial and temporal context of field sampling at individual sites. In addition, studies also use different sampling strategies and methods of data analysis, which means that results from these individual studies may not be comparable. By contrast, remote sensing methods using a variety of platforms have potential to consistently map and quantify spatial patterns of sediments and landforms across beach-dune systems, and this has been undertaken in several studies e.g., [16, 17, 18, 19, 20, 21]. Thereare fewer studies, however, that have examined spectral data on sediment properties and stratigraphy. Sediment cores have been examined using different hyperspectral imaging techniques, mainly in the shortwave infrared (SWIR) wavebands, in order to identify stratigraphic variations in sediment grain size and mineralogy [22; 23; 24]. These studies have been used to produce spectral time series maps that represent variations in sediment properties through the cores, rather than identify individual spectra that represent certain sediment endmembers. There are only a few studies that have examined the spectral properties of sediments in coastal environments, and these have considered the role of variations in water content and mineralogy as key factors influencing their spectral signatures [18; 25]. Mineral compositions can then be used to derive endmembers for spatial modelling. Most work on spectral signatures of sediment has been done on river depositional environments [26; 27], and work on coastal sediments can be informed by these previous studies. For example, river and coastal sediment samples in NE Italy were evaluated by [PERSON] et al. [28] using an analytical spectral device (ASD) in order to derive a spectral library representing sample grain size and mineralogy, which was then compared to laboratory results. Principal component analysis was then used to identify sediment provenance endmembers. The same research approach was used by [PERSON] et al. [19] along the Belgian coast. Grain size properties along beaches were examined using Landsat visible, near infrared (VNIR) and thermal infrared bands in SE India [29], but these bands may have been influenced by a high concentration of heavy minerals (50-80%) at this site. Using IKONOS imagery, [PERSON] et al. [30] showed that all spectral bands have a good correlation (>0.8) with grain size, and [PERSON] and [PERSON] [31] showed that different spectral bands from synthetic aperture radar imagery are affected by surface moisture. Thus, there are several studies that have analysed the spectral properties of beach sand but these have tended to focus on the role of local environmental factors rather than the application of different techniques or methodologies.