Estimating the accuracy of vectors derived from open data

Nikolakopoulos, Konstantinos G.; Dimitropoulos, George

doi:10.1117/12.2278275

Cited by 4 publications

(5 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, Hu et al [46] proved that GE imagery provides similar classification results compared to the original Quickbird satellite images. In a recent study [47], it was proven that vectors derived from the GE images presented negligible differences in length derived from the orthorectified images. Characteristic examples are presented in Figure 2.…”

Section: Methodsmentioning

confidence: 97%

An Event-Based Inventory Approach in Landslide Hazard Assessment: The Case of the Skolis Mountain, Northwest Peloponnese, Greece

Litoseliti

Koukouvelas

Nikolakopoulos

et al. 2020

IJGI

Self Cite

View full text Add to dashboard Cite

Assessment of landslide hazard across mountains is imperative for public safety. Pre- and post-earthquake landslide mapping envisage that landslides show significant size changes during earthquake activity. One of the purposes of earthquake-induced landslide investigation is to determine the landslide state and geometry and draw conclusions on their mobility. This study was based on remote sensing data that covered 72 years, and focused on the west slopes of the Skolis Mountains, in the northwest Peloponnese. On 8 June 2008, during the strong Movri Mountain earthquake (Mw = 6.4), we mapped the extremely abundant landslide occurrence. Historical seismicity and remote sensing data indicate that the Skolis Mountain west slope is repeatedly affected by landslides. The impact of the earthquakes was based on the estimation of Arias intensity in the study area. We recognized that 89 landslides developed over the last 72 years. These landslides increased their width (W), called herein as inflation or their length (L), termed as enlargement. Length and width changes were used to describe their aspect ratio (L/W). Based on the aspect ratio, the 89 landslides were classified into three types: I, J, and Δ. Taluses, developed at the base of the slope and belonging to the J- and Δ-landslide types, are supplied by narrow or irregular channels. During the earthquakes, the landslide channels migrated upward and downward, outlining the mobility of the earthquake-induced landslides. Landslide mobility was defined by the reach angle. The reach angle is the arctangent of the landslide’s height to length ratio. Furthermore, we analyzed the present slope stability across the Skolis Mountain by using the landslide density (LD), landslide area percentage (LAP), and landslide frequency (LF). All these parameters were used to evaluate the spatial and temporal landslide distribution and evolution with the earthquake activity. These results can be considered as a powerful tool for earthquake-induced landslide disaster mitigation

show abstract

Section: Methodsmentioning

confidence: 97%

An Event-Based Inventory Approach in Landslide Hazard Assessment: The Case of the Skolis Mountain, Northwest Peloponnese, Greece

Litoseliti

Koukouvelas

Nikolakopoulos

et al. 2020

IJGI

Self Cite

View full text Add to dashboard Cite

show abstract

“…No data Ganasri and Ramesh (2016) Nethravathi/India 2009 17 Aiello et al (Antonello et al, 2015) Italy, CATENA 2001 77 Papakonstantinou et al (2016) Lesvos Island, Eressos beach Greece 2015 3 Chikhradze et al (Nino et al, 2015) Portugal 2015 No data Sekovski et al (Ivan et al, 2014) Ravenna Province Italy 2011 82 Nikolakopoulos et al (Nikolakopoulos Konstantinos & George, 2017) Rio, Patras, Greece 79 Nikolakopoulos et al (Konstantinos et al, 2007) Greece 2004 43 Drummond et al (Christopher et al, 2015) 2015 30 Elsner et al (Elsner Paul et al, 2015) Pevensey Bay, East Sussex, England 2014 No data Letortu et al (Pauline et al, 2018) Dieppe (Mitra et al, 2017) Mandarmani coast 2009 90 Turner et al (Ian et al, 2016) Narrabeen Liu & Trinder (2018) Gold Coast of Australia 1999No data Trebossen et al (2005 French Guiana 1992Guiana -2002Guiana 17 (2003 used aerial photographs to investigate the coastal evolution on a ten-year scale in the Pomeranian Bight in the Southernmost part of the Baltic Sea. Furthermore, many studies that have been carried out the last 20 years have combined aerial photographs and orthophotographs with remote sensing data.…”

Section: -2010mentioning

confidence: 99%

“…As well as the spatial resolution is very high, these data can be used by someone to execute on-screen digitizing of water bodies, hydrographic networks and other geological structures in GIS environment (Malarvizhi et al, 2016). In an older study by Nikolakopoulos and Dimitropoulos (Nikolakopoulos Konstantinos & George, 2017) has been evaluated the usage of Google Earth data for mapping. Accuracy measurements were performed through roads being digitized from GE images and overlapped them to those vectorized from Quickbird.…”

Section: -2010mentioning

confidence: 99%

See 1 more Smart Citation

A review and meta-analysis of remote sensing data, GIS methods, materials and indices used for monitoring the coastline evolution over the last twenty years

Apostolopoulos

Nikolakopoulos

2021

European Journal of Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Google Earth collected highresolution images from many satellite companies, which are combined into a blended image. In an older study [5] the usage of Google Earth data for mapping has been evaluated. Recently GE images were used in many different coastal studies.…”

Section: Introductionmentioning

confidence: 99%

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

Verrou,

Apostolopoulos,

Nikolakopoulos

2023

Earth Resources and Environmental Remote Sensing/Gis Applications XIV

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Estimating the accuracy of vectors derived from open data

Cited by 4 publications

References 16 publications

An Event-Based Inventory Approach in Landslide Hazard Assessment: The Case of the Skolis Mountain, Northwest Peloponnese, Greece

An Event-Based Inventory Approach in Landslide Hazard Assessment: The Case of the Skolis Mountain, Northwest Peloponnese, Greece

A review and meta-analysis of remote sensing data, GIS methods, materials and indices used for monitoring the coastline evolution over the last twenty years

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

Contact Info

Product

Resources

About