Detection of Natural and Anthropic Features on Small Islands

Cappucci, Sergio; Valentini, Emiliana; Monte, Maurizio Del; Paci, Marida; Filipponi, Federico; Taramelli, Andrea

doi:10.2112/si77-008.1

Cited by 17 publications

(13 citation statements)

References 45 publications

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“…Vegetation and sand cover were detected by selecting a spectral subset of specific hyperspectral ranges (20 bands between 0.43 and 0.83 µm, and 8 bands between 1.15 and 1.55 µm) in order to capture most of the beach-dune targets, as was done in [37,38,54,55].…”

Section: Hyperspectral Airborne Imagerymentioning

confidence: 99%

“…These validation areas were appositely selected for the visual estimation of cover percentage and a quick classification of the main vegetation typologies like sand-partially vegetated, shrub and herbaceous vegetation, shrubs, and trees. The field observations dataset was integrated by in situ spectral measurements ( Figure 3) with a ViewSpecPRO ® ASD (Boulder, CO, USA) instrument [31,[35][36][37].…”

Section: Field Measurementsmentioning

confidence: 99%

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Exploring the Dunes: The Correlations between Vegetation Cover Pattern and Morphology for Sediment Retention Assessment Using Airborne Multisensor Acquisition

et al. 2020

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Coastal sand dunes are highly dynamic aeolian landforms where different spatial patterns can be observed due to the complex interactions and relationships between landforms and land cover. Sediment distribution related to vegetation types is explored here on a single ridge dune system by using an airborne hyperspectral and light detection and ranging (LiDAR) remote sensing dataset. A correlation model is applied to describe the continuum of dune cover typologies, determine the class metrics from landscape ecology and the morphology parameters, and extract the relationship intensity among them. As a main result, the mixture of different vegetation types such as herbaceous, shrubs, and trees classes shows to be a key element for the sediment distribution pattern and a proxy for dune sediment retention capacity, and the anthropic fingerprints can play an even major role influencing both ecological and morphological features. The novelty of the approach is mostly based on the synergistic use of LiDAR with hyperspectral that allowed (i) the benefit from already existing processing methods to simplify the way to obtain thematic maps and coastal metrics and (ii) an improved detection of natural and anthropic landscape.

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Section: Hyperspectral Airborne Imagerymentioning

confidence: 99%

Section: Field Measurementsmentioning

confidence: 99%

Exploring the Dunes: The Correlations between Vegetation Cover Pattern and Morphology for Sediment Retention Assessment Using Airborne Multisensor Acquisition

et al. 2020

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“…Infrastructure development and urbanization in coastal areas are the main factors linked to the modern dynamics [50]. Discerning between natural and anthropic changes in the Rodas system, as in other zones, is very complicated, because these factors are interrelated in the time and space [51]. Thus, all suppositions about coastal analysis should understand this problem and make an effort to improve the analytical techniques, for example, determining, in detail, the effect of tourists in a determinate zone in relation to the loss of sand.…”

Section: Discussionmentioning

confidence: 99%

Recent Evolution (1956–2017) of Rodas Beach on the Cíes Islands, Galicia, NW Spain

Gómez‐Pazo

Pérez‐Alberti

Pérez

2019

JMSE

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Sedimentary coastal areas change rapidly and are economically and environmentally important. This research focuses on determining the extent to which natural dynamics and human activity have contributed to visible changes on Rodas, Cíes Islands in southwestern Galicia (NW Spain). The number of visitors to the islands has increased in recent years, and the port infrastructure has therefore been expanded. Previously, this zone experimented with important sand extraction phases. These changes have influenced the ecosystem directly by modifying the sedimentary behavior and indirectly by promoting even greater numbers of visitors to the area. Aerial images and orthophotographs of the study zone were examined to identify changes that have taken place over the last sixty-one years (1956–2017). Changes in the position of the shoreline, defined as the boundary of the dune vegetation, were mapped at different times between 1956 and 2017. Changes in the shoreline were quantified using GIS (Geographic Information System) technology and Digital Shoreline Analysis System (DSAS) software. The findings revealed that the system regressed by more than 30 m between 1956 and 1981, in part as a result of sand extraction. We also identified different erosion/accretion phases that occurred before the reformation of the Rodas dock in 2010. The system is currently undergoing important changes, especially in the northern area, with a regression of 14.14 m in the last seven years. In this context, LiDAR analysis from 2010 and 2015 using Geomorphic Change Detection (GCD) tools allowed variations in the dune system to be verified. The elevation in the study zone increased in 83% of the area, mainly in the frontal dune and close to the winter inlet (north sector). However, the variations were very small.

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“…Besides morphometric analysis, other approaches, based on the use of Geomatics techniques, can provide important support for the study of vulnerability status of coastal systems [27][28][29]. Multispectral and hyperspectral remote sensing provide data sets that allow to map the seabed and habitat heterogeneity [30,31], to study the cover of vegetation in wetlands [32,33] and to map plant species in submerged shallow water areas [34][35][36][37][38].…”

Section: Introductionmentioning

confidence: 99%

Nearshore Sandbar Classification of Sabaudia (Italy) with LiDAR Data: The FHyL Approach

et al. 2020

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An application of the FHyL (field spectral libraries, airborne hyperspectral images and topographic LiDAR) method is presented. It is aimed to map and classify bedforms in submerged beach systems and has been applied to Sabaudia coast (Tirrenyan Sea, Central Italy). The FHyl method allows the integration of geomorphological observations into detailed maps by the multisensory data fusion process from hyperspectral, LiDAR, and in-situ radiometric data. The analysis of the sandy beach classification provides an identification of the variable bedforms by using LiDAR bathymetric Digital Surface Model (DSM) and Bathymetric Position Index (BPI) along the coastal stretch. The nearshore sand bars classification and analysis of the bed form parameters (e.g., depth, slope and convexity/concavity properties) provide excellent results in very shallow waters zones. Thanks to well-established LiDAR and spectroscopic techniques developed under the FHyL approach, remote sensing has the potential to deliver significant quantitative products in coastal areas. The developed method has become the standard for the systematic definition of the operational coastal airborne dataset that must be provided by coastal operational services as input to national downstream services. The methodology is also driving the harmonization procedure of coastal morphological dataset definition at the national scale and results have been used by the authorities to adopt a novel beach management technique.

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Detection of Natural and Anthropic Features on Small Islands

Cited by 17 publications

References 45 publications

Exploring the Dunes: The Correlations between Vegetation Cover Pattern and Morphology for Sediment Retention Assessment Using Airborne Multisensor Acquisition

Exploring the Dunes: The Correlations between Vegetation Cover Pattern and Morphology for Sediment Retention Assessment Using Airborne Multisensor Acquisition

Recent Evolution (1956–2017) of Rodas Beach on the Cíes Islands, Galicia, NW Spain

Nearshore Sandbar Classification of Sabaudia (Italy) with LiDAR Data: The FHyL Approach

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