Dr. Dionysios N. Apostolopoulos Profile

Dr. Dionysios N. Apostolopoulos

G.I.S & Remote Sensing Geologist

SPIE Involvement:

Author

Area of Expertise:

Shoreline , Coastal erosion , GIS , Remote Sensing

Dr. Dionysios Apostolopoulos works as a Geologist in the Technical Department of the Region of Western Greece and he is a Post Doctoral Researcher at the University of Patras since 2023. He has a degree in Geology from the University of Patras (1998) and he holds a MSc in environmental issues of the Hellenic Open University entitled: "Environmental Design of Infrastructure Projects" (2009).

His PhD aimed at the study, understanding and application of new technologies such as: Unmanned Aerial Vehicles, Global Navigation Satellite System, Terrestrial Laser Scanners, Geographic Information Systems etc, in the study of coastal erosion focusing on the coastal area of Ilia and Achaia prefectures.

He has been a member of the research team implementing the program entitled: “Integrated research of coastal vulnerability in Western Greece with remote sensing, engineering geology and in situ measurements (MIS 5047163)” which has been included in the Operational Program «Human Resources Development, Education and Lifelong Learning 2014-2020».

So far, he has 20 scientific publications in scientific journals and conference proceedings (2023).

Scopus profile: https://www.scopus.com/authid/detail.uri?authorId=57216331020

https://sciprofiles.com/profile/848543

Google Scholar profile:

https://scholar.google.gr/citations?hl=el&user=tqnefJwAAAAJ

Proceedings Article | 19 October 2023 Paper

Quantitative comparison of temporal changes in coastline utilizing Google Earth, Landsat and Sentinel-2 historical time series case study: the Mytikas coast, Aitoloakarnania Prefecture, Greece

Vasiliki Verrou, Dionysios Apostolopoulos, Konstantinos Nikolakopoulos

Proceedings Volume 12734, 1273417 (2023) https://doi.org/10.1117/12.2679499

KEYWORDS: Landsat, Satellites, Satellite imaging, Earth observing sensors, Remote sensing, Spatial resolution, Linear regression, Geographic information systems

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Google Earth (GE) is a useful, free of charge platform which provide images from the Earth’s surface during time. The present study investigates the usage of the GE integrated timeline module, to assess the shoreline temporal displacement. The results were compared to the respective results derived from Landsat and Sentinel-2 images. The littoral area of the bay of Mytika situated in the Prefecture of Aitoloakarnania’s, Greece, has been used as test site. Past shoreline positions for the 2003-2022 period have been demarcated, through on-screen digitizing method, from the GE images in a Geographic Information System (G.I.S.) environment, using the wetted boundaries that where visible on the images. Moreover, automatic indices such as NDWI, NDVI and MNDWI were used to delineate the land from the water from the satellite images respectively. The shoreline evolution was estimated based on the cross-shore transects method and compared for each dataset via the Linear Regression Rate (LRR). In addition, the future shoreline position (forecasted shoreline), in ten and 20 years from 2022, was estimated using the integrated forecasting function of the fifth version of the Digital Shoreline Analysis System (DSAS) tool of the ArcGIS software. The mean value of declination among the future shorelines emerged, were statistically compared via the Shoreline Change Envelope (SCE) rates. The satellite images have been orthorectified and georeferenced to the Hellenic Geodetic Reference System of 1987 (Greek Grid) using the Leica Photogrammetry Suite (LPS), while perpendicular to the coast lines (transects) were created every 30 meters spanning along the coastline and used for the measurements. The results revealed that the NDVI predicted shoreline based on the Sentinel-2 images, yielded the lower value of declination from the GE shores, for both time periods (ten - and 20- year), ranging from 4.45 m to 7.37 m respectively, while the Landsat datasets emerged high rates of declination.

Proceedings Article | 19 October 2023 Presentation + Paper

UAV photogrammetry and in situ measurements for mass wasting monitoring in a steep cliff

Ioannis Koukouvelas, Georgios Pappas, Aggeliki Kyriou, Dionysios Apostolopoulos, Konstantinos Nikolakopoulos

Proceedings Volume 12734, 127340X (2023) https://doi.org/10.1117/12.2679403

KEYWORDS: Earthquakes, Unmanned aerial vehicles, Rain, Soil science, Climatology, Remote sensing, RGB color model, Landslides, Photogrammetry, Orthophoto maps

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SPIE Journal Paper | 24 November 2022

Identifying sandy sites under erosion regime along the Prefecture of Achaia, using remote sensing techniques

Dionysios Apostolopoulos, Konstantinos Nikolakopoulos

JARS, Vol. 17, Issue 02, 022206, (November 2022) https://doi.org/10.1117/12.10.1117/1.JRS.17.022206

KEYWORDS: Remote sensing, Image processing, Earth observing sensors, Satellites, Satellite imaging, Spatial resolution, Geodesy, Statistical analysis, Photography, Geographic information systems

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The application of remote sensing (RS) in the treatment of problems caused by natural phenomena, such as coastal erosion, has proven to be very effective. An attempt was made to reveal areas that are in a state of erosion along the coastline of the Prefecture of Achaia, elongated ∼185 km. The study area comprised the Gulf of Patras in the west and a part of the Corinth Gulf to the east, which are connected through the narrow and shallow Rion Straits. The system of the two Gulfs consists of a Plio-Quaternary asymmetric grabens trending northeast – southwest (NE-SW) and west-northwest (WNW) – east-southeast (ESE), respectively. The shoreline evolution is estimated for the 1945 to 2016 period with the usage of high-resolution data, using RS and geographic information system techniques. An extension of ArcGIS, the digital shoreline analysis system tool, version 5 beta, has been used for the analysis of shoreline changes, whereas the ERDAS Imagine 2014 was used for the image georeferencing and orthomosaicing process. Various statistical indices were computed including the end point rate and the linear regression rate. Although these tools did not take into concern any of the local geological parameters, the results are similar to the respective derived from conventional survey techniques. Eight sandy areas were revealed that are under erosion regime: the Araxos, Karnari, Kalamaki, Drepano, Loggos, Akoli, Diacopto, and Akrata, while the future shoreline position was estimated for each coast using the forecasting beta tool of the DSASv.5.0, after 10 and 20 years since 2016. We found that it is very likely all sites will show the same trend of change in the next 10 and 20 years, similar to those computed using the available data from 1945 to 2016. The tectonic behavior of the Gulf of Corinth seems that it mainly affects the area’s erosion/accretion regime, while changes in the areas adjacent to the Gulf of Patras are related to natural processes (waves, currents, coastal floods, extreme rainfalls, etc.) and anthropogenic interventions. Moreover, the Araxos and Karnari coasts are at 65.71% and 64.41% under moderate erosion regime with rates of change −0.62 and −1.10 m / year, respectively. Kalamaki, Akoli, and Loggos percentages of 82.35%, 86.67%, and 86.23% are under low erosion, with rates of change −0.28, −0.21, and −0.34 m / year, respectively. Drepano and Diacopto are under low erosion, with rates of change −0.26 and −0.16 m / year, corresponding to 54.55% and 38.67% of the coast, respectively. Finally, Akrata is a coast where erosion prevails at 60.42% with annual rate of change −0.16 m / year, whereas the 43.38% of the coast correspond to stable area.

Proceedings Article | 26 October 2022 Poster + Paper

Synergy of UAV data and in situ measurements for the shoreline mapping in Arkoudi beach, Western Greece

Dionysios Apostolopoulos, Konstantinos Nikolakopoulos

Proceedings Volume 12268, 1226810 (2022) https://doi.org/10.1117/12.2635874

KEYWORDS: Unmanned aerial vehicles, RGB color model, Satellite navigation systems, Multispectral imaging, Cameras, Orthophoto maps, Data processing, Photogrammetry

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Proceedings Article | 26 October 2022 Presentation + Paper

Comparison of the IRS and SPOT satellite data for shoreline mapping: the case of Katakolo bay, Ilia Prefecture, Greece

Dionysios Apostolopoulos, Konstantinos Nikolakopoulos

Proceedings Volume 12268, 122680O (2022) https://doi.org/10.1117/12.2635727

KEYWORDS: Satellites, Earth observing sensors, Satellite imaging, Spatial resolution, Statistical analysis

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The current study investigates the shoreline forecasting results combining the IRS and SPOT medium resolution satellite imagery with the high-resolution air-photos. The littoral area of the bay of Katakolo situated in the Prefecture of Ilia’s, Greece, has been used as a test site.

Past shoreline positions have been demarcated, through on-screen digitizing method, for the years of 1945, 1960, 1965, 1968, 1975, 1987, and 1996, based on the respective high-resolution images. The shoreline evolution for the 1945-1996 period was estimated for each dataset via the Linear Regression Rate (LRR) using for the 1996 the shorelines derived from the High Resolution (HR), SPOT, and IRS datasets respectively. The results were cross-validated using the R-squared, the Root Mean Square Error (RMSE), and the Mean Annual Error (MAE) coefficient methods. In addition, future position of the shoreline (forecasted shoreline) was estimated for 10 years (2006) by alternating the reference shoreline of the 1996 with the relative shoreline derived from the IRS and SPOT-3 satellite images respectively. The integrated forecasting function of the fifth version of the Digital Shoreline Analysis System (DSAS) tool of the ArcGIS software was used for the computations. The End Point Rate (EPR) was calculated for the 1996 - 2006 period, using the 1996 actual and the 2006 forecasted shorelines based on the SPOT and the IRS data, and compared to the respective rates derived from the high-resolution actual shorelines. Moreover, the Shoreline Change Envelope (SCE) rates were computed in order to estimate the mean rate of distance between the 2006 actual and forecasted shoreline of each dataset.

The images have been orthorectified and georeferenced to Hellenic Geodetic Reference System of 1987 (Greek Grid) using Leica Photogrammetry Suite (LPS), while transects every 30 meters along the coastline were created and used for the measurements.

It was proved that although both datasets provide similar results, the SPOT (Pan) images seem to have an advantage, while the comparison based on the forecasting models should be avoided in sites where infrastructures have taken place as they distort the results.

SPIE Journal Paper | 22 March 2022

Assessment of the shoreline evolution using the CORONA declassified images. A case study in the north of Ilia prefecture, Peloponnese, Greece

Dionysios N. Apostolopoulos, Konstantinos G. Nikolakopoulos

JARS, Vol. 16, Issue 02, 022205, (March 2022) https://doi.org/10.1117/12.10.1117/1.JRS.16.022205

KEYWORDS: Coastal modeling, Satellites, Earth observing sensors, Statistical analysis, Satellite imaging, Data modeling, Spatial resolution, Photography, Lawrencium, Image processing

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Proceedings Article | 12 September 2021 Presentation + Paper

Comparison of two open-source tools for diachronic shoreline monitoring: a case study from northwestern Peloponnese

Dionysios Apostolopoulos, Konstantinos Nikolakopoulos

Proceedings Volume 11863, 118630T (2021) https://doi.org/10.1117/12.2597700

KEYWORDS: Statistical analysis, Geographic information systems, Geodesy, Analytical research, Spatial resolution, Coastal modeling, Statistical modeling, Photogrammetry, Water, Remote sensing

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Coastal environments are under successive physical and morphodynamical pressure. Nowadays, it is crucial to have a reliable and simple tool in order to measure the changes occurred diachronically. Among the research community there have been developed and applied many relative statistical models which are quite reliable. In this study we try to compare in statistical terms the results of the most famous free extension, suited for commercial software for shoreline monitoring: The Digital Shoreline Analysis System (DSAS) and the Analyzing Moving Boundaries Using R (AMBUR). Both software are free open-source tools for shoreline analysis in Geographic Information System environment. The test site is located in the northwestern Peloponnese, Greece, between two littoral villages named Rogitika and Kaminia situated in the Gulf of Patras. The shoreline length is more than 6 kilometers. High-resolution images (air-photos mosaic and very high-resolution satellite data) for the years 1987, 1996, 2008, and 2018 were used. The images have been orthorectified and georeferenced to Hellenic Geodetic Reference System of 1987 (Greek Grid) using Leica Photogrammetry Suite (LPS). The data spatial resolution ranges from 0.25 m to 1.00 m. Transects every 50 meters were created and used for the measurements. We digitized the relative shorelines and we computed and compared the End Point Rate (EPR) rates calculated from both tools for three periods such as 1987-2018, 1996-2018, and 2008-2018 respectively. EPR calculates the annual rate of erosion or accretion computed in a specific transect. The rates between -0.10 and + 0.10 m were considered that correspond to a “stable” area. The tide height rates were considered negligible (0.00 m ± 10.00 cm) and so did not affect the computations. Moreover, a Linear Regression statistical process applied for correlation of EPR calculated rates from AMBUR and DSAS seaward and landward models. Finally, the results are presented and discussed in the current paper.

SPIE Journal Paper | 2 September 2021

Statistical methods to estimate the accuracy of diachronic low-resolution satellite instruments for shoreline monitoring

Dionysios Apostolopoulos, Konstantinos Nikolakopoulos

JARS, Vol. 16, Issue 01, 012007, (September 2021) https://doi.org/10.1117/12.10.1117/1.JRS.16.012007

KEYWORDS: Earth observing sensors, Landsat, Statistical analysis, Statistical methods, Satellites, Spatial resolution, Sensors, Lawrencium, Geodesy, Data acquisition

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Proceedings Article | 20 September 2020 Presentation + Paper

GIS-based analysis and accuracy assessment of low-resolution satellite imagery for coastline monitoring

Dionysios Apostolopoulos, Konstantinos Nikolakopoulos, Vassilios Boumpoulis, Nikolaos Depountis

Proceedings Volume 11534, 115340B (2020) https://doi.org/10.1117/12.2573440

KEYWORDS: Earth observing sensors, Satellites, Satellite imaging, Geographic information systems, Accuracy assessment, Image resolution, Landsat, Spatial resolution, Multispectral imaging, Image processing

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It is well known that in order to study the shoreline evolution in an accurate way, successive time series of high-resolution images are needed. However, the availability of historical high-resolution data is limited to analogue air photos while the more recent high-resolution satellite images are quite expensive. Thus, many researchers have based their coastal evolution studies on low-resolution images like Sentinel and Landsat data. As a result, a main question is raised about the accuracy of the results of such studies. As the Landsat program has started in 1972, there is archival data spanning almost 50 years. This is a great tool for longterm shoreline change monitoring in researchers’ hands. Another advantage of the specific data set is the existence of diverse multispectral bands and the opportunity to extract band ratios sensitive to existence or not of water. The biggest challenge for using this archive for shoreline monitoring is its limited spatial resolution (30m). In the current study, the accuracy of low-resolution satellite data such as Sentinel-2 MSI and Landsat ΤΜ, ΕΤΜ+ and 8 OLI for coastal monitoring is under control. Many low-resolution images were digitally processed, and Normalized Difference Vegetation Index (NDVI) as well as on-screen digitizing are used in order to automatically and manually separate the sea from the land respectively and extract the coastline in different periods. Then, the shoreline vectors derived from the Landsat and Sentinel-2 data were compared to the respective shorelines derived from high resolution satellite data such as Worldview-2 (0.5 m resolution) and orthomosaics created from digital airphotos with 1m spatial resolution. The study area is located in the Gulf of Patras in the North Peloponnese, Greece. The accuracy control covered three different periods from 1996 to 2018 and in every case, shorelines extracted from low resolution data sets were compared to shorelines created from high resolution data sets. Statistical analysis was performed, and the results are presented and discussed in the current paper.

Proceedings Article | 26 August 2020 Paper

Mapping the Panagopoula landslide extent fifty years after the event

Konstantinos Nikolakopoulos, Dionysios Apostolopoulos

Proceedings Volume 11524, 115241E (2020) https://doi.org/10.1117/12.2570813

KEYWORDS: Landslide (networking), Satellites, Orthophoto maps, Earth observing sensors, Satellite imaging, Spatial resolution, Image processing, Photogrammetry, Remote sensing

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