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Simoni Alexiou
Laboratory of Mineralogy-Geology, Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 75, Iera Odos Str., 11855 Athens, Greece

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Journal article
Published: 29 May 2021 in ISPRS International Journal of Geo-Information
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Analysis of two small semi-mountainous catchments in central Evia island, Greece, highlights the advantages of Unmanned Aerial Vehicle (UAV) and Terrestrial Laser Scanning (TLS) based change detection methods. We use point clouds derived by both methods in two sites (S1 & S2), to analyse the effects of a recent wildfire on soil erosion. Results indicate that topsoil’s movements in the order of a few centimetres, occurring within a few months, can be estimated. Erosion at S2 is precisely delineated by both methods, yielding a mean value of 1.5 cm within four months. At S1, UAV-derived point clouds’ comparison quantifies annual soil erosion more accurately, showing a maximum annual erosion rate of 48 cm. UAV-derived point clouds appear to be more accurate for channel erosion display and measurement, while the slope wash is more precisely estimated using TLS. Analysis of Point Cloud time series is a reliable and fast process for soil erosion assessment, especially in rapidly changing environments with difficult access for direct measurement methods. This study will contribute to proper georesource management by defining the best-suited methodology for soil erosion assessment after a wildfire in Mediterranean environments.

ACS Style

Simoni Alexiou; Georgios Deligiannakis; Aggelos Pallikarakis; Ioannis Papanikolaou; Emmanouil Psomiadis; Klaus Reicherter. Comparing High Accuracy t-LiDAR and UAV-SfM Derived Point Clouds for Geomorphological Change Detection. ISPRS International Journal of Geo-Information 2021, 10, 367 .

AMA Style

Simoni Alexiou, Georgios Deligiannakis, Aggelos Pallikarakis, Ioannis Papanikolaou, Emmanouil Psomiadis, Klaus Reicherter. Comparing High Accuracy t-LiDAR and UAV-SfM Derived Point Clouds for Geomorphological Change Detection. ISPRS International Journal of Geo-Information. 2021; 10 (6):367.

Chicago/Turabian Style

Simoni Alexiou; Georgios Deligiannakis; Aggelos Pallikarakis; Ioannis Papanikolaou; Emmanouil Psomiadis; Klaus Reicherter. 2021. "Comparing High Accuracy t-LiDAR and UAV-SfM Derived Point Clouds for Geomorphological Change Detection." ISPRS International Journal of Geo-Information 10, no. 6: 367.

Journal article
Published: 28 April 2020 in Land
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The western part of Crete Island has undergone serious landslide events in the past. The intense rainfalls that took place in the September 2018 to February 2019 period provoked extensive landslide events at the northern part of Chania prefecture, along the motorway A90. Geospatial analysis methods and earth observation data were utilized to investigate the impact of the various physical and anthropogenic factors on landslides and to evaluate landslide susceptibility. The landslide inventory map was created based on literature, aerial photo analysis, satellite images, and field surveys. A very high-resolution Digital Elevation Model (DEM) and land cover map was produced from a dense point cloud and Earth Observation data (Landsat 8), accordingly. Sentinel-2 data were used for the detection of the recent landslide events and offered suitable information for two of them. Eight triggering factors were selected and manipulated in a GIS-based environment. A semi-quantitative method of Analytical Hierarchy Process (AHP) and Weighted Linear Combination (WLC) was applied to evaluate the landslide susceptibility index (LSI) both for Chania prefecture and the motorway A90 in Chania. The validation of the two LSI maps provided accurate results and, in addition, several susceptible points with high landslide hazards along the motorway A90 were detected.

ACS Style

Emmanouil Psomiadis; Andreas Papazachariou; Konstantinos X. Soulis; Despoina-Simoni Alexiou; Ioannis Charalampopoulos. Landslide Mapping and Susceptibility Assessment Using Geospatial Analysis and Earth Observation Data. Land 2020, 9, 133 .

AMA Style

Emmanouil Psomiadis, Andreas Papazachariou, Konstantinos X. Soulis, Despoina-Simoni Alexiou, Ioannis Charalampopoulos. Landslide Mapping and Susceptibility Assessment Using Geospatial Analysis and Earth Observation Data. Land. 2020; 9 (5):133.

Chicago/Turabian Style

Emmanouil Psomiadis; Andreas Papazachariou; Konstantinos X. Soulis; Despoina-Simoni Alexiou; Ioannis Charalampopoulos. 2020. "Landslide Mapping and Susceptibility Assessment Using Geospatial Analysis and Earth Observation Data." Land 9, no. 5: 133.