Publications by Year: 2018

Antoniou V, Mavroulis S, Theocharis D, Skourtsos E, Vassilakis E, Lekkas E. Post-fire landslide susceptibility mapping in the 2016 fire-affected areas of Chios Island (Northeastern Aegean Sea, Greece). EGU2018-7452. 2018;19.Abstract
n July 25 and August 26 2016 wildfires broke out in the southwestern and central-western part of Chios Island(NE Aegean Sea, Greece), respectively. The first affected an area of approximately 47km2 and burned throughalmost 90% of olive groves and mastic trees, while the second broke out in a forested area and affected approximately6.6km2 of forest and farmland.A research aiming at the post-fire landslide susceptibility (LS) mapping of both areas was conducted. Morphologicaldata (slope, aspect, curvature, drainage network) derived from a 5m-DEM model of the areas was used.Lithological and geological data (lithology, tectonic structures) were digitized from previous field work maps.Land cover was derived from Worldview-2 satellite images before and after the fire events. Soil thickness was derivedfrom field survey observations within the fire-affected areas, road network from OpenStreetMap and rainfalldata resulted from related measurements derived from Chios meteorological station. Post-fire landslide inventorywas created after an extensive field survey of both areas before the beginning of the rainfall period (October 2016)and before the end of winter season (February 2017).Data classification of each factor according to their estimated LS followed, by using the reverse ranking method,where 1 is the least susceptible and 10 is the most one. Each category was normalized to 100% and the final rasterthematic maps of landslide controlling factors were produced. Finally, using numerical weight for each factor,which was assigned by the Analytic Hierarchy Process using Pairwise Comparison Method and according to theweighted linear combination, a map was generated where each cell has a certain post-fire LS index (LSI) value.The higher the LSI value, the higher the LS, whereas lower LSI value means lower LS.This procedure was repeated twice, first using pre-fire land cover and secondly using the severity of the fire events.The resulted maps, classified with natural breaks method, constitute the final pre- and post-fire LS maps of theaffected areas with five LS categories: very low, low, moderate, high and very high.Comparison of these two final maps showed, more or less, the same LS areas, but with LSI value enhanced. Thevalidated results showed good agreement between post-fire landslide occurrence and the produced post-fire LS maps.
Diakakis M, Nikolopoulos E, Mavroulis S, Vassilakis E, Korakaki E. The role of wildfires in inducing hydrogeomorphological disasters in the Mediterranean. A case from Greece. EGU2018-7452. 2018;19.Abstract
Although forest fires are an integral part of Mediterranean forest ecosystems, they constitute one of the most devastating natural hazards in the region. Apart from the direct consequences, fires induce well-documented longer term effects in the geomorphological and hydrological processes, influencing environmental factors that in turn can affect the occurrence of other natural hazards, such as floods and mass movement phenomena.This work focuses on the forest fire of 2007 in Peloponnese, Greece that burnt 1773 km2, causing 78 fatalities and very significant damages in property and infrastructure and went down as the largest fire in the country’s record. It examines the occurrence of flood and mass movement phenomena, before and after this mega-fire and studies different influencing factors to investigate the degree to which the 2007 fire and/or other parameters have affected their frequency.Observational evidence based on several data sources collected during the period 1989-2016 show that the 2007 fire has contributed to an increase of average flood and mass movement events frequency by approximately 3.3 and 5.6 times respectively.Fire affected areas record a substantial increase in the occurrence of both phenomena, presenting a noticeably stronger increase compared to neighbouring areas that have not been affected. Examination of the monthly occurrence of events showed an increase even in months of the year were rainfall intensity presented decreasing trends.Although no major land use changes has been identified and chlorophyll is shown to recover 2 years after the fire incident, differences on the type of vegetation as tall forest has been substituted with lower vegetation are considered significant drivers for the observed changes in hydrogeomorphic response of the fire affected basins.The findings of this work are strong indications that future climatic change, with more frequent and severe droughts and storms will be a disastrous combination for the Mediterranean region.
Chrysafis I, Christopoulou A, Kazanis D, Farangitakis G-P, Mallinis G, Mitsopoulos I, Arianoutsou M, Emm. V, Antoniou V, Theofanous N, et al.

Post-fire vegetation recovery mapping using multi-temporal Sentinel-2A imagery in Chios island, Greece

. EGU 2018-7452. 2018.Abstract
Remote sensing techniques offer the opportunity to study fire effects and vegetation recovery dynamics across large areas, providing essential information for effective management strategies development over fire-prone landscapes. Chios, the fifth largest of the Greek islands, has experienced recurring forest fires during the recent years, resulting to significant risk of environmental degradation. During the summer of 2016, the island experienced two severe wildfires, with the biggest one recorded in the southern part of the island. The affected area was mostly covered by maquis and phrygana (formations of low shrubs) (40.9%), while pine forests (Pinus brutia) represented 15.5% of the burned area. The aim of this study was to estimate and analyze the state of post-fire vegetation recovery in the island of Chios following major fire events occurred during the summer of 2016. A post-fire 8-band WorldView-2 image was used for burned area mapping by employing a geographic object-based classification approach, followed by field campaign for assessing post fire vegetation recovery, which was conducted during summer 2017 by establishing reference plots in the main pre-fire vegetation types (maquis, shrublands and pine forest areas) within the fire-affected area. A series of single and multi-temporal spectral indices including Normalized Burn Ratio, Normalized Difference Vegetation Index, Enhanced Vegetation Index and Soil Adjusted Vegetation Index, were derived from multi-temporal Sentinel-2 images. A random forest modelling procedure was performed for estimating post fire vegetation recovery within the burned area, as well as the areas of high risk erosion. We identified dNDVI, EVI and the second red edge band of Sentinel-2 as the most important spectral variables for predicting vegetation recovery within pre-fire areas. In the case of pre-fire areas with maquis, post-fire NBR, EVI and NDVI were selected as best predictors. Finally, the results revealed that vegetation recovery is more pronounced within the pre-fire pine forest areas, while topographic and geological sub-strata factors were also found significant in defining post-fire vegetation recovery.
Tsokos Α, Kotsi Ε, Petrakis S, Vassilakis E.

Combining series of multi-source high spatial resolution remote sensing datasets for the detection of shoreline displacement rates and the effectiveness of coastal zone protection measures

. Journal of Coastal Conservation [Internet]. 2018. pdfAbstract
The long-term change of the shoreline location is a phenomenon, which is highly factored in the design of construction projects along the coastal zone. Especially, beach erosion is characterized as one of the major problems at coastal areas and it is of high importance as a quite significant percentage of social development is concentrated in a relatively narrow zone not far from the waterfront. This study presents a methodology that aims to quantify the shoreline displacement rate by involving the processing of different types of remote sensing datasets such as aerial photographs, satellite images and unmanned aerial system data coupled with in-situ observations and measurements. Several photogrammetric techniques were used in order to orthorectify and homogenize a time series of remotely sensed data acquired from 1945 to 2017, representing a rapidly relocating coastal zone at the southern part of Corinth Gulf (Greece), as a case study. All images were digitally processed and optically optimized in order to produce a highly accurate representation of the shoreline at the time period of each acquisition. The data were imported in a Geographic Information System platform, where they were subjected to comparison and geostatistical analysis. High erosion rates were calculated, reaching the order of 0.18 m/year on average whilst extreme rates of 0.70 m/year were also observed in specific locations leading to the segmentation of the coastal zone according to its vulnerability and consequently the risk for further development as well as the effectiveness of measures already taken by the authorities.