Coastal Management Using UAS and High-Resolution Satellite Images for Touristic Areas

Παπακωνσταντίνου, Απόστολος; Doukari, Michaela; Stamatis, Panagiotis J.; Topouzelis, Konstantinos

doi:10.4018/ijagr.2019010103

Cited by 7 publications

(10 citation statements)

References 35 publications

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“…UAS as aerial platforms for the acquisition of detailed spatial information is ideal for such applications. UAS-derived data have been used for the detection and classification of marine habitats, underwater 3D modeling [4][5][6][7][8][9][10][11][12][13], monitoring and mapping of marine litter in the coastal zone [14,15], coastline erosion monitoring [16], coastal management [17], reconstruction of topography on coastal environments [18,19]. The availability of sub-decimeter datasets in combination with field measurements and observations can be used as validation data for satellite imagery.…”

Section: Introductionmentioning

confidence: 99%

A Protocol for Aerial Survey in Coastal Areas Using UAS

et al. 2019

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Aerial surveys in coastal areas using Unmanned Aerial Vehicles (UAVs) present many limitations. However, the need for detailed and accurate information in a marine environment has made UAVs very popular. The aim of this paper is to present a protocol which summarizes the parameters that affect the reliability of the data acquisition process over the marine environment using Unmanned Aerial Systems (UAS). The proposed UAS Data Acquisition Protocol consists of three main categories: (i) Morphology of the study area, (ii) Environmental conditions, (iii) Flight parameters. These categories include the parameters prevailing in the study area during a UAV mission and affect the quality of marine data. Furthermore, a UAS toolbox, which combines forecast weather data values with predefined thresholds and calculates the optimal flight window times in a day, was developed. The UAS toolbox was tested in two case studies with data acquisition over a coastal study area. The first UAS survey was operated under optimal conditions while the second was realized under non-optimal conditions. The acquired images and the produced orthophoto maps from both surveys present significant differences in quality. Moreover, a comparison between the classified maps of the case studies showed the underestimation of some habitats in the area at the non-optimal survey day. The UAS toolbox is expected to contribute to proper flight planning in marine applications. The UAS protocol can provide valuable information for mapping, monitoring, and management of the coastal and marine environment, which can be used globally in research and a variety of marine applications.

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Section: Introductionmentioning

confidence: 99%

A Protocol for Aerial Survey in Coastal Areas Using UAS

et al. 2019

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“…Traditionally, a variety of remote-sensing data including low-, medium-and high-resolution images (e.g., MODIS; Landsat; QuickBird), as well as ready satellite products (e.g., ASTER Global Digital Elevation Model, ASTER GDEM) were used to extract valuable information regarding natural and anthropogenic hazards as well as to assess the overall risk for CH sites and monuments [8]. Although the spatial resolution of satellite imagery has significantly improved in the last decade (tens of centimeters), the data collected is still not sufficient to map medium to small characteristics in CH, as centimeter-level accuracy is needed [9]. Furthermore, traditional remote-sensing data are not capable of monitoring small-scale changes due to inherent limitations such as spatial resolution and data volume.…”

Section: Introductionmentioning

confidence: 99%

Mapping Cultural Heritage in Coastal Areas with UAS: The Case Study of Lesvos Island

et al. 2019

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Dynamic processes in coastal zones and human activities in the coastal environment produce pressure on cultural heritage, especially in touristic places. Unmanned aerial systems (UAS) are used as an additional tool for monitoring cultural heritage sites in sensitive coastal areas. UASs provide low-cost accurate spatial data and high-resolution imagery products in various spatial and temporal scales. The use of UAS for mapping cultural heritage sites in the coastal zone is of increasing interest among scientists and archaeologists in terms of monitoring, documentation, mapping, and restoration. This study outlines the integration of UAS data acquisition and structure from motion (SfM) pipeline for the visualization of selected cultural heritage areas (ancient harbors) in the coastal zone. The UAS-SfM methodology produces very detailed orthophoto maps for mapping and detecting cultural heritage sites. Additionally, a metadata cataloging system has been developed in order to facilitate online searching operations for all products of the data acquisition, SfM pipeline, and cartographic processes. For this reason, a specific metadata profile was implemented, based on the European INSPIRE framework. As a result, datasets reusability and catalogs interoperability are promoted.

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“…Thus, habitat mapping is a prime necessity for environmental planning and management [4,5]. The continued provision of updated habitat maps has a decisive contribution to the design and coordination of relevant actions, the conservation of natural resources, and the monitoring of changes caused by natural disasters or anthropogenic effects [6]. Habitat maps are in critical demand, raising increasing interest among scientists monitoring sensitive coastal areas.…”

Section: Introductionmentioning

confidence: 99%

“…These processes require multitemporal data, either from satellites or from unmanned aerial systems (UAS). The availability of very high-resolution orthomosaics presents increasing interest, as it provides to scientists and relevant stakeholders detailed information for understanding coastal dynamics and implementing environmental policies [6,[10][11][12][13]. However, the use of high-resolution orthomosaics created from UAS data is expected to improve mapping accuracy.…”

Section: Introductionmentioning

confidence: 99%

“…The increasing demand of detailed maps for monitoring the coastal areas requires automatic algorithms and techniques. Object-based image analysis (OBIA) is an object-based analysis of remote sensing imagery that uses automated methods to partition imagery into meaningful image-objects and generate geographic information in a GIS-ready format, from which new knowledge can be obtained [6,14,15].…”

Section: Introductionmentioning

confidence: 99%

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Comparison of True-Color and Multispectral Unmanned Aerial Systems Imagery for Marine Habitat Mapping Using Object-Based Image Analysis

Παπακωνσταντίνου¹,

Stamati²,

Topouzelis³

2020

Remote Sensing

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The use of unmanned aerial systems (UAS) over the past years has exploded due to their agility and ability to image an area with high-end products. UAS are a low-cost method for close remote sensing, giving scientists high-resolution data with limited deployment time, accessing even the most inaccessible areas. This study aims to produce marine habitat mapping by comparing the results produced from true-color RGB (tc-RGB) and multispectral high-resolution orthomosaics derived from UAS geodata using object-based image analysis (OBIA). The aerial data was acquired using two different types of sensors-one true-color RGB and one multispectral-both attached to a UAS, capturing images simultaneously. Additionally, divers' underwater images and echo sounder measurements were collected as in situ data. The produced orthomosaics were processed using three scenarios by applying different classifiers for the marine habitat classification. In the first and second scenario, the k-nearest neighbor (k-NN) and fuzzy rules were applied as classifiers, respectively. In the third scenario, fuzzy rules were applied in the echo sounder data to create samples for the classification process, and then the k-NN algorithm was used as the classifier. The in situ data collected were used as reference and training data. Additionally, these data were used for the calculation of the overall accuracy of the OBIA process in all scenarios. The classification results of the three scenarios were compared. Using tc-RGB instead of multispectral data provides better accuracy in detecting and classifying marine habitats when applying the k-NN as the classifier. In this case, the overall accuracy was 79%, and the Kappa index of agreement (KIA) was equal to 0.71, which illustrates the effectiveness of the proposed approach. The results showed that sub-decimeter resolution UAS data revealed the sub-bottom complexity to a large extent in relatively shallow areas as they provide accurate information that permits the habitat mapping in extreme detail. The produced habitat datasets are ideal as reference data for studying complex coastal environments using satellite imagery.

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Coastal Management Using UAS and High-Resolution Satellite Images for Touristic Areas

Cited by 7 publications

References 35 publications

A Protocol for Aerial Survey in Coastal Areas Using UAS

A Protocol for Aerial Survey in Coastal Areas Using UAS

Mapping Cultural Heritage in Coastal Areas with UAS: The Case Study of Lesvos Island

Comparison of True-Color and Multispectral Unmanned Aerial Systems Imagery for Marine Habitat Mapping Using Object-Based Image Analysis

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