High Resolution Satellite Images for Instantaneous Shoreline Extraction Using New Enhancement Algorithms

Abstract

Knowledge of a territory is an essential element in any future planning action and in appropriate territorial and environmental requalification action planning. The current large-scale availability of satellite data, thanks to very high resolution images, provides professional users in the environmental, urban planning, engineering, and territorial government sectors, in general, with large amounts of useful data with which to monitor the territory and cultural heritage. Italy is experiencing environmental emergencies, and coastal erosion is one of the greatest threats, not only to the Italian heritage and economy, but also to human life. The aim of this paper is to find a rapid way of identifying the instantaneous shoreline. This possibility could help government institutions such as regions, civil protection, etc., to analyze large areas of land quickly. The focus is on instantaneous shoreline extraction in Ortona (CH, Italy), without considering tides, using WorldView-2 satellite images (50-cm resolution in panchromatic and 2 m in multispectral). In particular, the main purpose of this paper is to compare commercial software and ACM filters to test their effectiveness.

Automatic Shoreline Detection from Eight-Band VHR Satellite Imagery

“…The availability of multispectral satellite images at very high resolution (VHR) allows, in fact, acquisition in a short time and simultaneously of long stretches of coast. The geometric accuracies of submetric to decimetric order are absolutely compatible with the specific application and the availability of different bands allows semi-automatic or automatic approaches [15][16][17] such as those proposed in this paper.…”

Shoreline Extraction Based on an Active Connection Matrix (ACM) Image Enhancement Strategy

“…An orthorectification was performed using ERDAS Imagine 2015 [33], and rational polynomial coefficients (RPCs) were used to correct the geometric distortions. In addition, 17 ground control points (GCPs) and 8 check points (CPs) were used to improve the process [10]. Finally, the original spatial resolution of the multi-spectral bands was improved with the panchromatic one by applying the HCS (hyperspherical color dpace) resolution merge algorithm, designed for WorldView-2 [34] and implemented in Erdas Imagine.…”

“…Several survey methodologies are used for the detection of shorelines: from traditional topographical and GNSS (Global Navigation Satellite System) surveys to remote sensing techniques (aerial and unmanned aerial vehicle (UAV) photogrammetry, video systems and satellite optical and SAR images [8,9]), as widely discussed in another recent work [10]. In the last few years, the use of optical and SAR satellite images for automatic and semi-automatic shoreline extraction has complemented the traditional approach based on surveying methods and air-photo processing [11].…”

“…In particular, water indices (WIs) and vegetation indices (VIs) have been developed, which are obtained by combining two or more spectral bands. Although VIs are mainly used for vegetation analysis, they have also been tested for shoreline mapping purposes [10,16]. WIs have been specifically developed for water body detection [17].…”

Small reservoirs for a sustainable water resources management

“…Both Sentinel-2 platforms are equipped with a multispectral sensor that acquires 13 spectral bands with 12 bit radiometric resolution and different geometric resolutions at 10 m (blue, green, red and NIR), 20 m (six bands including SWIR) and 60 m, as reported in Table 1. Remote sensed data are used for lake identification through water index (WI) evaluation by means of the NDWI (Normalized Difference Water Index) and the MNDWI (Modified Normalized Difference Water Index; Xiucheng et al, 2017;Gordana and Ugur, 2017;Yun et al, 2016;Dominici et al, 2019;Avisse et al, 2017;Gideon and Maurice, 2015;Mishra and Prasad, 2015).…”