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Wildfires play a fundamental role in Land Use/Land Cover (LULC) change dynamics by burning vegetation in forested and rural areas and by affecting human infrastructures. Conversely, LULC can disturb fire regime by altering vegetation cover, conditioning subsequent transitions, and acting on fuel loads and continuity. Though there is an evident mutual influence between wildfires and LULC changes, a rigorous quantification of their reciprocal effects in Europe has never been performed before. To fill this gap, in the present study we developed a methodology allowing the evaluation of different indicators for the quantitative assessment and a better understanding of the transitions among LULC classes and Burnt Areas (BA) that occurred in Europe within the last two decades (2000 – 2020).Our analyses revealed that the two LULC classes which had experienced major changes were Forests (44%), and Scrubs and/or herbaceous vegetation associations (32%). As a general trend, within the five European Mediterranean Countries more prone to wildfires (Portugal, Spain, France, Italy, and Greece) we found a decrease in the classes Forests and Arable land, and an increase in Scrubs and/or herbaceous vegetation associations, suggesting the impact of wildfires in shaping the natural and rural landscape. This assumption was better evaluated and confirmed by the following analyses, performed at both the European and national levels. Results showed that most of the BA have occurred in Forests (42% for the entire Europe), with a predominance in Coniferous forests; the subsequent transitions from BA were generally to Transitional woodland/shrub or again to BA. This last indicates a high frequency of wildfires in a given area, while the first transition can be partially due to the regeneration/recolonization of the vegetation after a wildfire event. Outcomes for the single countries followed almost the same trend.Overall, our results confirm the existence of a strong relationship between wildfires and LULC changes in Europe, which have been quantified in the present study. These findings are in line with previous research and provide a deep insight into the process at the global and local levels, paving the way for further analyses on fire intensity and frequency with coupled environmental elements of land cover and climate changes.

Obtaining Soil Moisture Content (SMC) over large scales is of key importance in several environmental and agricultural applications especially in the context of climate change and transition to digital farming. Remote sensing (RS) has a demonstrated capability in retrieving SMC over large areas with several operational products already available at different spatiotemporal resolutions. At the same time, cosmic-ray neutron sensing is a recently emerged approach in retrieving high temporal resolution SMC at intermediate spatial scales. The present study conducts an intercomparison between different RS-based soil moisture products, daily SMC retrievals from a cosmic-ray neutron sensor (CRNS) station and a network of in situ SoilNet wireless sensors installed at the Pinios Hydrologic Observatory ILTER site in central Greece for a time period of 2018-2019. The RS-based soil moisture products included herein are from NASA’s Soil Moisture Active Passive (SMAP) and Metop-A/B Advanced Scatterometer (ASCAT) satellite missions. The methodological workflow adopted includes standardized validation procedures employing a series of statistical measures to quantify the agreement between the different RS-based soil moisture products, CRNS-based SMC and the SoilNet ground truth data. Our study results contribute towards global efforts aiming at exploiting CRNS data in the context of soil moisture retrievals and their potential synergies with RS-based products. Furthermore, our findings provide valuable insights into assessing the capability of CRNS at retrieving more accurate SMC estimates at arid and semi-arid environments such as those found in the Mediterranean basin, while supporting also ongoing global validation efforts.Keywords: Cosmic Ray Neutron Sensors; SMAP; ASCAT; SoilNet; Soil Moisture Content

The present work aims at unveiling possible precursory signals of the devastating fire in North Evia island, during August 2021, that destroyed approximately 400 km2 of forest and cultivated land. Therefore, the time series of two environmental parameters known to be related to wild fire occurrence, i.e. soil moisture and Normalized Difference Vegetation Index (NDVI) were extracted and analyzed. Soil moisture in the top soil layer from 0 to 7cm was extracted from the ERA5-Land Monthly Averaged - ECMWF Climate Reanalysis data set at a spatial resolution of 9 km. The time series of remotely sensed NDVI was accessed through the Landsat 8 mission, at a spatial resolution of 30m, with a 32-day time step. Both time series covered the period from January 2015 to October 2021. Results indicated two specific patterns in the examined time series. Soil moisture time series in the affected areas demonstrated a shard declining trend since 2018, reaching its lowest value just prior the fire events in North Evia. The NDVI time series did not show any distinctive trend during the examined period in the affected sites, however comparing it to surrounding unaffected areas with the same extent, occupied from the same land cover types, an alarming finding was revealed; the NDVI time series in the affected sites demonstrated statistically significant lower variability compared to unaffected ones. This difference corresponds to a more homogeneous vegetation and possible absence of fire breaks in the burned areas compared to the ones that were not affected. Findings of the present work may help in highlighting areas with specific characteristics related to soil moisture and NDVI, that indicate a high risk of fire occurrence.

Fire is a major disturbance affecting Mediterranean ecosystems. Due to a lack of exhaustive fire registration, fire drivers in the Middle East have been hardly investigated. We propose here the analysis of a newly produced fire patch reconstruction from remote sensing over the 1984 – 2020 period in Lebanon and Syria. First, we will provide a description of the particular bimodal and late season fire regimes in the two neighboring countries. Then, taking into account their different socio-political conditions since the start of the Syrian civil war in 2011, we will disentangle climate and social drivers by analyzing the ICEWS conflict events data-base.

At local or regional scales, where Landsat has been extensively applied to monitor burned areas, semi- or fully-automated methods are not very common. Koutsias et al. (2013) developed and improved (2021) a semi-automatic method to map burned areas consisted of a set of rules that are valid especially when the post-fire image has been captured shortly after the fire. However, the rule-based approach is not free of errors that eventually create limitations to adopt this method for reconstructing the fire history in a fully automated mode. In this work, we improved the method by incorporating vegetation indices. The vegetation indices evaluated were the: (i) Normalized Difference Vegetation Index (NDVI), (ii) Ratio Vegetation Index (RVI), (iii) Normalized Burn Ratio (NBR), (iv) Normalized Difference Water Index (NDWI) and (v) Shortwave Infrared Water Stress Index (SIWSI).

Wood resources have been essential for human welfare throughout history. Also nowadays, the volume of growing stock (GS) is considered one of the most important forest attributes monitored by National Forest Inventories (NFIs) to inform policy decisions and forest management planning. The origins of forest inventories closely relate to times of early wood shortage in Europe causing the need to explore and plan the utilisation of GS in the catchment areas of mines, saltworks and settlements. Over time, forest surveys became more detailed and their scope turned to larger areas, although they were still conceived as stand-wise inventories. In the 1920s, the first sample-based NFIs were introduced in the northern European countries. Since the earliest beginnings, GS monitoring approaches have considerably evolved. Current NFI methods differ due to country-specific conditions, inventory traditions, and information needs. Consequently, GS estimates were lacking international comparability and were therefore subject to recent harmonisation efforts to meet the increasing demand for consistent forest resource information at European level. As primary large-area monitoring programmes in most European countries, NFIs assess a multitude of variables, describing various aspects of sustainable forest management, including for example wood supply, carbon sequestration, and biodiversity. Many of these contemporary subject matters involve considerations about GS and its changes, at different geographic levels and time frames from past to future developments according to scenario simulations. Due to its historical, continued and currently increasing importance, we provide an up-to-date review focussing on large-area GS monitoring where we i) describe the origins and historical development of European NFIs, ii) address the terminology and present GS definitions of NFIs, iii) summarise the current methods of 23 European NFIs including sampling methods, tree measurements, volume models, estimators, uncertainty components, and the use of air- and space-borne data sources, iv) present the recent progress in NFI harmonisation in Europe, and v) provide an outlook under changing climate and forest-based bioeconomy objectives.

Fire activity has significantly changed in Europe over the last decades (1980-2020s), with the emergence of summers attaining unprecedented fire prone weather conditions. Here we report a significant shift in the non-stationary relationship linking fire weather conditions and fire intensity measured in terms of CO

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited., Lightning is the major cause of the natural ignition of wildfires worldwide and produces the largest wildfires in some regions. Lightning strokes produce about 5% of forest fires in the Mediterranean Basin and are one of the most important precursors of the largest forest fires during the summer. Lightning-ignited wildfires produce significant emissions of aerosols, black carbon, and trace gases, such as CO, SO2, CH4, and O3, affecting air quality. Characterization of the meteorological and cloud conditions of lightning-ignited wildfires in the Mediterranean Basin can serve to improve fire forecasting models and to upgrade the implementation of fire emissions in atmospheric models. This study investigates the meteorological and cloud conditions of lightning-ignited wildfires (LIWs) and long continuing current (LCC) lightning flashes in the Iberian Peninsula and Greece. LCC lightning and lightning in dry thunderstorms with a low precipitation rate have been proposed to be the main precursors of the largest wildfires. We use lightning data provided by the World Wide Lightning Location Network (WWLLN), the Earth Networks Total Lightning Network (ENTLN), and the Lightning Imaging Sensor (LIS) on board the International Space Station (ISS), together with four databases of wildfires produced in Spain, Portugal, southern France, and Greece, respectively, in order to produce a climatology of LIWs and LCC lightning over the Mediterranean Basin. In addition, we use meteorological data provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis data set and by the Spanish State Meteorological Agency (AEMET), together with the Cloud Top Height product (CTHP) derived from Meteosat Second Generation (MSG) satellites measurements to investigate the meteorological conditions of LIWs and LCC lightning. According to our results, LIWs and a significant amount of LCC lightning flashes tend to occur in dry thunderstorms with weak updrafts. Our results suggest that LIWs tend to occur in clouds with a high base and with a vertical content of moisture lower than the climatological value, as well as with a higher temperature and a lower precipitation rate. Meteorological conditions of LIWs from the Iberian Peninsula and Greece are in agreement, although some differences possibly caused by the highly variable topography in Greece and a more humid environment are observed. These results show the possibility of using the typical meteorological and cloud conditions of LCC lightning flashes as proxy to parameterize the ignition of wildfires in atmospheric or forecasting models. © 2021 Copernicus GmbH. All rights reserved., This research has been supported by the Federal Ministry for Education and Research of Germany through the Alexander von Humboldt Foundation, the Spanish Ministry of Science and Innovation (grant nos. PID2019-109269RB-C43 and PID2019-109269RB-C42 and the FEDER program), and the Spanish MCIU through the “Center of Excellence Severo Ochoa” award for the Instituto de Astrofísica de Andalucía (grant no. SEV-2017-0709). The article processing charges for this open-access publication were covered by the German Aerospace Center (DLR).

Biomass burning is one of the most critical factors impacting vegetation and atmospheric trends, with important societal implications, particularly when extreme weather conditions occur. Trends and factors of burned area (BA) have been analysed at regional and global scales, but little effort has been dedicated to study the interannual variability. This paper aimed to better understand factors explaining this variation, under the assumption that the more human control of fires the more frequently they occur, as burnings will be less dependent of weather cycles. Interannual variability of BA was estimated from the coefficient of variation of the annual BA (BA_CV) estimated from satellite data at 250 m, covering the period from 2001 to 2018. These data and the explanatory variables were resampled at 0.25-degree resolution for global analysis. Relations between this variable and explanatory factors, including human and climate drivers, were estimated using Random Forest (RF) and generalized additive models (GAM). BA_CV was negatively related to BA_Mean, implying that areas with higher average BA have lower variability as well. Interannual BA variability decreased when maximum temperature (TMAX) and actual and potential evapotranspiration (AET, PET) increased, cropland and livestock density increased and the human development index (HDI) values decreased. GAM models indicated interesting links with AET, PET and precipitation, with negative relation with BA_CV for the lower ranges and positive for the higher ones, the former indicating fuel limitations of fire activity, and the latter climate constrains. For the global RF model, TMAX, AET and HDI were the main drivers of interannual variability. As originally hypothesised, BA_CV was more dependent on human factors (HDI) in those areas with medium to large BA occurrence, particularly in tropical Africa and Central Asia, while climatic factors were more important in boreal regions, but also in the tropical regions of Australia and South America.

This study presents an improvement of an old rule-based semi-automatic method to map burned areas by using multi-temporal Landsat and Seninel-2 images. The rule-based approach consists of a set of rules developed based on spectral properties of burned areas as compared to the pre-fire unburned vegetation and to the spectral signatures of other land cover types found in post-fire satellite scene. Actually, the spectral properties based on which the rules have been developed are presented in two graphs, one that corresponds to spectral signatures plots and the second that corresponds to the histogram data plots. The spectral patterns based on which the rule-based approach has been developed are not always the same. For example, depending on the type of the fire-affected vegetation (e.g. dry vegetation instead of green) the spectral pattern of the SWIR channel that correspond to channel 7 in Landsat 4-7 and 8 is not valid. Instead, there is a similar spectral behaviour but in the SWIR channel that correspond to channel 5 in Landsat 4-7, or channel 6 in Landsat 8. Additionally, the threshold value of 0.10-0.25 of the second rule seems not to be sufficient to cover all variability since there are cases that this value should be higher. Two characteristic examples of the insufficiencies found on the old-rules are concerned in the current analysis, one that presents limitations concerning the rule 5 (Serifos) and one that represents limitations concerning the rule 2 (Portugal). In this study we present a further improvement of the method and also its application to several cases spread out in Greek islands using both Landsat and Sentinel-2 images.

Wildfire (WF) has the potential to occur in more than 30% of the worldwide land area, in many different biomes/ecosystems/land cover types, where it is controlled mainly by the environmental drivers such as vegetation structure, meteorological/climate conditions, and human activities. On the other hand, land use/land cover changes (LULCC) are one of the most important global alterations of the environment. In the last decades, Europe registered significant-high fire incidence and LULCC between all land cover classes. In the 2000 – 2018 period, according to the European Forest Fire Information System (EFFIS), Europe was affected by 18 882 WFs which burned 6 887,713 ha. According to CORINE land cover maps, the observed LULCC area in Europe for the same period was of 23,510,075 ha. Recent studies suggested that regional LULCC in the last decades promoted the occurrence of more and larger WF, in some European regions. Therefore, the main objectives of this study were to assessed the LULCC in and around burnt areas (BAs) during the 2000–2018 period. This study benefits from the use of reliable CORINE inventories and EFFIS BA product. A geospatial methodological approach was implemented to identify and quantify LULCC and to characterize the relationship between LULCC and WFs in Europe. This research provides a detailed characterization of the LULCC in and around BAs in Europe, and attempts to contribute to a better management of the landscape, urbanization and wildland-urban interface to reduce related losses in the natural and human system including losses of life, property and assets.

Vegetation phenology is an important element of vegetation characteristics that can be useful in vegetation monitoring especially when satellite remote sensing observations are used. In that sense temporal profiles extracted from spectral signal of time series MODIS satellite images can be used to characterize vegetation phenology and thus to be helpful for monitoring vegetation recovery in fire-affected areas. The aim of this study is to explore the phenology patterns and the vegetation recovery pattern of various wildfires occurred in Greece during the period 2000-2020. Satellite remote sensing data from MODIS satellites in the period from 2000 to 2020 were acquired and processed to extract the temporal profiles of the spectral signal for selected areas inside and outside the fire-affected areas. This dataset and time period analyzed together with the time that these fires occurred gave the opportunity to create temporal profiles for some years before and some years after the fire. Different metrics linked to key phenological events have been created and used to assess vegetation recovery in the fire-affected areas. Apart of the use of the original spectral data we estimated and used vegetation indices commonly found in vegetation studies as well as in burned area mapping studies. In this study we explore the strength and the use of these time series satellite data to characterize vegetation phenology as an aid to assess the fire-affected areas and to monitor their vegetation recovery.

A statistical analysis on the wildfire events, that have taken place in Greece during the period 1985-2007, for the assessment of the extremes has been performed. The total burned area of each fire was considered here as a key variable to express the significance of a given event. The data have been analyzed through the extreme value theory, which has been in general proved a powerful tool for the accurate assessment of the return period of extreme events. Both frequentist and Bayesian approaches have been used for comparison and evaluation purposes. Precisely, the Generalized Extreme Value (GEV) distribution along with Peaks over Threshold (POT) have been compared with the Bayesian Extreme Value modelling. Furthermore, the correlation of the burned area with the potential extreme values for other key parameters (e.g. wind, temperature, humidity, etc.) has been also investigated.

Accurate estimates of forest inventory parameters are essential to assess the potential hazards of wildfire and obtain above-ground biomass and carbon sequestration data that help develop strategies for the sustainable management of forests. This study aims to assess the accuracy of estimation of forest inventory parameters, such as diameter at breast height (DBH) and tree height, obtained using a Terrestrial Laser Scanner (TLS) in a Mediterranean coniferous stand in western Greece. DBH values measured in the field were compared with those derived from a TLS using the Computree algorithm for automatic DBH detection, and resulted in a coefficient of determination ( $$R^{2})$$ that ranged from 0.75 to 0.96 at the plot level. The average $$R^{2}$$ and RMSE values of 0.80 and 1.07 m, respectively, were obtained when comparing the tree heights recorded by TLS and field data. Finally, the feasibility of TLS to estimate total dry biomass was investigated by comparing the TLS-derived total dry biomass values with those derived from field estimates using an allometric equation. The average estimate of biomass per hectare according to the TLS inventory data was 373.17 Mg/ha while that from field observations was 366.82 Mg/ha. The results confirm that TLS can provide non-destructive, high-resolution and precise determination of forest inventory parameters. The outcomes of this research will help researchers to better comprehend deviations in the accuracy of forest inventory variable retrieval resulting from the variation in the processing parameters supplied and additionally boost decision-making in forest management.

The rapid development of remote sensing has made it possible to study environmental processes and changes in agriculture and also to provide important assistance in relevant practices, even operationally. This chapter describes the latest developments in remote sensing for precision agriculture with particular emphasis placed on the use of hyperspectral sensors. This chapter provides practical information regarding the identification of research challenges, limitations, and advantages of different platforms and sensors for precision agriculture. Hyperspectral remote sensing (HRS) is more effective as compared to multispectral remote sensing because it records radiation in narrow contiguous spectral channels reflected from any feature or target. More accurate spectral information retrieved using HRS can be combined with other techniques to retrieve useful information for precision agriculture. The chapter includes information about HRS sensors and also includes a discussion on the advancement and challenges of spaceborne satellites faced during agriculture monitoring. It concludes with summarizing the hurdles faced during agriculture research using hyperspectral data discussing possible pathways in which relevant research should be directed.

During the last decades, climate and land use changes led to an increased prevalence of megafires in Mediterranean-type climate regions (MCRs). Here, we argue that current wildfire management policies in MCRs are destined to fail. Focused on fire suppression, these policies largely ignore ongoing climate warming and landscape-scale buildup of fuels. The result is a 'firefighting trap' that contributes to ongoing fuel accumulation precluding suppression under extreme fire weather, and resulting in more severe and larger fires. We believe that a 'business as usual' approach to wildfire in MCRs will not solve the fire problem, and recommend that policy and expenditures be rebalanced between suppression and mitigation of the negative impacts of fire. This requires a paradigm shift: policy effectiveness should not be primarily measured as a function of area burned (as it usually is), but rather as a function of avoided socio-ecological damage and loss., This work was financed by national funds through FCT—Foundation for Science and Technology, within the scope of project PCIF/AGT/0136/2017 (People&Fire: reducing risk, living with risk) and PTDC/AGR-FOR/2586/2014 (RurIntFIre: Fire in the Rural-Urban Interface: characterisation, risk mapping, and fuel break design). FM was funded through contract IF/01053/2015 (FCT). JMCP was supported by the Forest Research Centre, a research unit funded by Foundation for Science and Technology I.P. (FCT), Portugal (UID/AGR/00239/2019). PF work was carried under project UID/AGR/04033/2019 supported by FCT. JMM acknowledges funding from Ministerio de Ciencia, Innovación y Universidades (project CGL2016-78357-R)

W dniach 12–14 marca 2019 r. w Instytucie Badawczym Leśnictwa odbyła się XI Sesja Zimowej Szkoły Leśnej (ZSL), której tematem było „Zastosowanie geoinformatyki w leśnictwie”. Współorganizatorem Sesji była Dyrekcja Generalna Lasów Państwowych. Merytoryczne aspekty XI Sesji zostały przygotowane i opracowane przez Radę Programową Zimowej Szkoły Leśnej w składzie: prof. dr hab. Andrzej Grzywacz, prof. dr hab. Jacek Hilszczański, dr inż. Krzysztof Janeczko, prof. dr hab. Andrzej Klocek, mgr inż. Jacek Przypaśniak, mgr inż. Marek Roman, dr inż. Jacek Sagan, dr hab. Krzysztof Stereńczak, prof. IBL (przewodniczący), mgr inż. Adam Wasiak, prof. dr hab. Tomasz Zawiła-Niedźwiecki. Rada Programowa określiła nie tylko zakres problematyki XI Sesji, ale także propozycje tematyczne referatów zamawianych oraz wytypowania ich autorów. W trakcie XI Sesji referaty wygłosili zaproszeni goście zagraniczni reprezentujący Remote Sensing Research and Consulting Ltd. (Szwajcaria), Wyższą Szkołę Techniczną w Zurychu (Szwajcaria), Norweski Uniwersytet Przyrodniczy – NMBU, Federalny Instytut Badawczy Lasu, Śniegu i Krajobrazu (Szwajcaria), Uniwersytet we Fryburgu (Niemcy), Uniwersytet Florencki (Włochy), Instytut Geografii i Geoekologii i Instytut Technologii w Karlsruhe (Niemcy), Instytut Lasu im. Sukaczewa Syberyjskiej Filii Rosyjskiej Akademii Nauk, Federalne Centrum Badawcze «Krasnoyarsk Science Center SB RAS» i Syberyjski Uniwersytet Federalny (Rosja) oraz Uniwersytet w Cambridge (Wielka Brytania). Poza gośćmi z zagranicy na Zimowej Szkole Leśnej wystąpiło szerokie grono autorów z Polski, prezentujących wiele przykładów wykorzystania geoinformatyki w leśnictwie. W tym miejscu składam serdeczne podziękowanie autorom za przygotowanie i wygłoszenie interesujących referatów, a także za opracowanie tekstów wystąpień, które znajdą Państwo w niniejszych materiałach posesyjnych. W XI Sesji ZSL wzięło udział prawie 400 osób reprezentujących m.in.: kierownictwo Lasów Państwowych oraz jednostki organizacyjne PGL LP i Ministerstwo Środowiska. Najliczniejszą grupę słuchaczy Szkoły stanowili zarówno geomatycyreprezentujący szeroko rozumiany świat nauki, jak i firmy zajmujące się wdrożeniami i praktyką, pracownicy nadleśnictw oraz biur urządzania lasu i geodezji leśnej, na co dzień korzystających z narzędzi geoinformatycznych. Liczne grono stanowili przedstawiciele ośrodków naukowych, a także studentów polskich wydziałów leśnych.

Fire events are among the natural disasters that affect both ecosystem functioning but also human lives. The present work deals with the assessment of the properties of vegetation phenology in areas affected by fire events during a 10-year period in the Peloponnese, Greece. The main objective is to identify special patterns in NDVI time series of fire-affected areas, that can be used either as precursory indicators or as a tool for assessment of regeneration patterns. Therefore, we constructed and analyzed time series of remotely sensed Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI at 250 m spatial resolution with a 16-day time step for affected and non-affected areas surrounding the burnt sites, where the majority of the area refers to the same land cover type. Analysis of changes of NDVI time series of both burnt and unburnt areas was conducted and results indicated that all fire events in the burnt sites caused breaks in the NDVI time series, demonstrated either as NDVI shifts to the lower and/or as changes in the trend and seasonality of the time series. Trends of the NDVI time series of the affected sites were almost doubled in the post fire period compared to the period before the event, indicating the evolution of the regenerating process. The basic statistics of the NDVI time series of the affected and non-affected areas correspond to greater minimum NDVI values of the affected areas throughout the study period, except of the two years after the fire event. Mean NDVI values were almost equal in burnt and unburnt areas before the events and reached the same values approximately seven years after the fire. Maximum NDVI values of the affected and non-affected sites were almost equal before the event but were abruptly reduced in the affected areas after the events and revert to their original state approximately ten years after. An alarming finding is the considerably lower standard deviation of the fire affected areas in comparison to non-fire-affected ones, during all years of the study period, except of a short period immediately after the fire event. It seems thus that areas covered by homogeneous vegetation with no fire breaks or other landforms to act as barriers to fire are the most vulnerable and most severely affected.

The objective of this paper is to document the role of fire in shaping the landscape by identifying links between historical fire records and the current landscape indicating that fire favors certain land use/land cover (LULC) types. We geo-referenced fire records taken from 1922 to 2000 in Aitoloakarnania, the largest prefecture -in terms of surface area- of Greece and compared the past LULC classes where fires burned to the present landscape. The outputs indicated a shift of the historic fire ignition points from natural to agricultural-related LULC classes since a significant proportion of fire incidents that, according to the fire records, burnt natural vegetation units is currently located in agricultural landscape units. Additionally, a significant proportion of the fire-affected land cover classes retain their character thus supporting the argument that these classes, especially fire-prone or fire-resistant, have developed mechanisms to cope with fire. In such ecosystems the role of fire is to maintain rather than transform land cover classes. The findings of this research lead us to conclude that fire can be perceived as a long-term landscape modifier in the Mediterranean, although its effects may vary from region to region because of differences in regeneration patterns among the main land cover types, topographic constraints and local fire histories. Historical fire records extending back to the early 20th century proved to provide valuable information that can reveal interesting patterns of fire burning history and explain present land cover and use patterns. This knowledge, documented from historical records, can be used to develop fire management and land cover/land use management planning.

This study proposes and evaluates a relatively new concept for fire occurrence zoning based on documented historical fire records. The proposed method creates continuous kernel density surfaces based on wildland fire ignition observations. Kernels have the advantage of directly producing density estimates that are not influenced by grid size or localization effects. Within this scheme, kernel density surfaces have been created and reclassified to construct fire occurrence zones at local to global scales in the Mediterranean Basin. Specifically, fire occurrence zones were created for the European scale (European Mediterranean Basin), national scale (Greece), regional scale (Peloponnese, Greece) and local scale (Chalkidiki, Greece). To evaluate fire occurrence zones, we compared the observed with the expected distribution of the number of fires within these zones using a Monte Carlo randomization test, finding that these numbers were statistically different in all cases. The deviations observed from the expected distributions towards the high occurrence zone indicated their successful assessment and value. In this paper, we further discuss their potential role and use for multi-scale fire management and policy in a European context.

Fire has a diverse range of impacts on Earth's physical and social systems. Accurate and up to date information on areas affected by fire is critical to better understand drivers of fire activity, as well as its relevance for biogeochemical cycles, climate, air quality, and to aid fire management. Mapping burned areas was traditionally done from field sketches. With the launch of the first Earth observation satellites, remote sensing quickly became a more practical alternative to detect burned areas, as they provide timely regional and global coverage of fire occurrence. This review paper explores the physical basis to detect burned area from satellite observations, describes the historical trends of using satellite sensors to monitor burned areas, summarizes the most recent approaches to map burned areas and evaluates the existing burned area products (both at global and regional scales). Finally, it identifies potential future opportunities to further improve burned area detection from Earth observation satellites.

There is a long history of the use of Landsat data in burned land mapping mainly due to certain characteristics of the Landsat imagery including the spatial, spectral, and temporal data resolution, the low cost Landsat data are now freely available, and the existence of an almost 35-year historical archive excluding Landsat 1–3. Landsat 8 Operational Land Imager OLI and Thermal Infrared Sensor TIRS was launched on 11 February 2013 and it captures data in three new bands along with two additional thermal bands. However, is the spectral signal of burned surfaces in satellite remote-sensing data of Landsat series consistent and robust enough to allow the successful application of the techniques developed so far for Landsat 8? In this article, we compare the spectral signal of burned surfaces between Landsat 7 Enhanced Thematic Mapper Plus ETM+ and Landsat 8 OLI sensors using five case studies that correspond to five large fire events in different biophysical environments in Greece, for which both Landsat 7 ETM+ and Landsat 8 OLI data were available. From the comparative analysis using histogram data plots of burned post-fire image and vegetated pre-fire image areas, spectral signature plots and separability indices of certain land-cover types, estimated using the same sampling areas over both satellite images, a general consistency was observed between the two sensors. Slight differences between the sensors were attributed to differences in the acquisition dates and were related to the type of vegetation rather than the sensors used to record the satellite images. Neither sensor provided improved discrimination over the other.

Wildfires change the infiltration properties of soil, reduce the amount of interception and result in increased runoff. A wildfire at Northeast Attica, Central Greece, in August 2009, destroyed approximately one third of a study area consisting of a mixture of shrublands, pastures and pines. The present study simultaneously models multiple semi-arid, shrubland-dominated Mediterranean catchments and assesses the hydrological response (mean annual and monthly runoff and runoff coefficients) during the first few years following wildfires. A physically based, hydrological model (MIKE SHE) was chosen. Calibration and validation results of mean monthly discharge presented very good agreement with the observed data for the pre-wildfire and post-wildfire period for two subcatchments (Nash–Sutcliffe Efficiency coefficient of 79.7%). The model was then used to assess the pre-wildfire and post-wildfire runoff responses for each of seven catchments in the study area. Mean annual surface runoff increased for the first year and after the second year following the wildfires increased by 112% and 166%, respectively. These values are within the range observed in similar cases of monitored sites. This modelling approach may provide a way of prioritizing catchment selection with respect to post-fire remediation activities. Additionally, this modelling assessment methodology would be valuable to other semi-arid areas because it provides an important means for comprehensively assessing post-wildfire response over large regions and therefore attempts to address some of the scaled issues in the specific literature field of research. Copyright © 2015 John Wiley & Sons, Ltd.

Long-term fire history reconstructions provide fruitful information in the context of global change. Global remotely-sensed burned areas offer a uniform estimate of fire regimes worldwide, but hardly capture small fire events and cover only the last 20 years. Burned areas from national statistics often lack credibility due to discrepancies in fire report protocols between countries, partial data records and uncertain burned area estimates from field observations. However, they constitute a unique and valuable alternative long-term key source of information. We provide here a detailed critical analysis of the fire database in Tunisia, on the southern boundary of the Mediterranean basin and with a contrasted socio-economic environment compared to the more studied European side. We analyzed the fire record database with a quality checking protocol, combined with remote sensing burned area characterization from Landsat images. The high uncertainties in fire numbers could not lead to any conclusion for an accurate trend estimate. The corrected burned area lead to an average yearly burned area of 1799 ha year−1 compared to previous estimates of 1017 ha year−1, leading to a fraction of burnable land affected by fires of 0.19%, on the lowest range of observations in the Mediterranean basin. From this corrected database, we revised the usually assumed burned area decrease in this region, with no significant trend detected over the 1985–2010 period. We conclude on the need for thorough assessment of data quality in fire history reconstruction from national statistics to prevent misleading conclusions, and for an increased credibility, in order to be further used in fire models benchmarking or fire weather analysis. Our results can contribute to the under-represented fire regime analysis on the southern boundary of the Mediterranean basin.

Background Singular value decomposition (SVD), as an alternative solution to principal components analysis (PCA), may enhance the spectral profile of burned areas in satellite image composites. Methods In this regard, we combine the pre-processing options of centering, non-centering, scaling, and non-scaling the input multi-spectral data, prior to the matrix decomposition, and treat their combinations as four different SVD-based PCA versions. Using both unitemporal and bi-temporal data sets, we test all four combinations to derive principal components. We assess the effects of the transformations based on multiresponse permutation procedures and quantify the enhanced spectral separability between burned areas and other major land cover classes via the Jeffries-Matusita metric. Lastly, we evaluate visually and numerically all principal components and select a subset of interest. Results The best transformation for the subset of selected components, is the uncentered-unscaled one. Conclusions The results indicate that an uncentered and unscaled SVD may improve the spectral separability of burned areas in some of the higher order components.

Background Principal components analysis (PCA) is based conventially on the eigenvector decomposition (EVD). Mean-centering the input data prior to the eigenanalysis is treated as an integral part of the algorithm. It ensures that the first principal component is proportional to the maximum variance of the input data. Equivalent to EVD, but numerically more robust, is the singular value decomposition (SVD). Mean-centered data subjected to SVD, yield transformation coefficients identical to EVD. Nevertheless, mean-centering is optional in SVD. Avoiding to center the input data, results in generic first component that mainly reflects their mean. This may, however, detect more accurately distinct clusters in PCA-based change detection applications. Methods In remote sensing, PCA transforms multi-spectral bands into a new coordinate system. The first, among the transformed components, contain the variance of unchanged landscape features. Succeeding components may contain an enhanced variance of changed features. Such is the case of burned surfaces appearing as distinct clusters in multitemporal composites. Conclusions Within this framework, a non-centered SVD may increase the spectral separability of burned clusters among other features in some of the higher order principal components.

Pinus nigra (black pine) is an ecologically and economically important species widely distributed around the Mediterranean Basin. P. nigra ecosystems have recently been affected by high severity fires occurring over the mountainous forest ecosystems of Southern Europe. The aim of this study is to investigate the post-fire regeneration patterns of black pine after a high severity crown fire which occurred on Mt Taygetos in Southern Greece. A network of 18 sites was selected to study black pine natural post-fire regeneration. Regeneration density was higher at the edges of patches that have remained unburned within the periphery of fire (0.406 individuals/m2) as compared to isolated burned areas (0.007 individuals/m2) although a significant between sites heterogeneity was recorded. Boosted regression trees analysis was used to explore the effects of environmental and microhabitat variables on black pine post-fire regeneration. The number of fires a site has experienced had a negative effect on regeneration density, while the presence of recovering ferns had a positive effect. The most important variable related to the black pine post-fire regeneration was distance from unburned patches. The result of the current study substantiates the importance of maintaining fire-resistant stands with large trees that are more likely to survive after a surface fire and which can also serve as seed sources for the recolonization of the burned area after severe crown fires.

The aims of this study were to map and analyze land use/land cover transitions and landscape changes in the Parnitha and Penteli mountains, which surround the Athens metropolitan area of Attica, Greece over a period of 62 years. In order to quantify the changes between land categories through time, we computed the transition matrices for three distinct periods (1945–1960, 1960–1996, and 1996–2007), on the basis of available aerial photographs used to create multi-temporal maps. We identified systematic and stationary transitions with multi-level intensity analysis. Forest areas in Parnitha remained the dominant class of land cover throughout the 62 years studied, while transitional woodlands and shrublands were the main classes involved in LULC transitions. Conversely, in Penteli, transitional woodlands, along with shrublands, dominated the study site. The annual rate of change was faster in the first and third time intervals, compared to the second (1960–1996) time interval, in both study areas. The category level analysis results indicated that in both sites annual crops avoided to gain while discontinuous urban fabric avoided to lose areas. At the transition level of analysis, similarities as well as distinct differences existed between the two areas. In both sites the gaining pattern of permanent crops with respect to annual crops and the gain of forest with respect to transitional woodland/shrublands were stationary across the three time intervals. Overall, we identified more systematic transitions and stationary processes in Penteli. We discussed these LULC changes and associated them with human interference (activity) and other major socio-economic developments that were simultaneously occurring in the area. The different patterns of change of the areas, despite their geographical proximity, throughout the period of analysis imply that site-specific studies are needed in order to comprehensively assess the driving forces and develop models of landscape transformation in Mediterranean areas.

The focus of our study was to create a Main Map of fire occurrence zones from historical wildland fire ignition observations at national level in Greece using a Kernel Density estimation procedure. Kernel density estimation, a non parametric statistical method for estimating probability densities, has been widely used for home range estimation in wildlife ecology. It has the advantage of directly producing density estimates that are not influenced by grid size and localization effects. Furthermore, it produces densities of any shape and analyzes any data distributed multi-modally or non-normally. Under this perspective, kernel density surfaces have been created to construct fire occurrence zones. Their observed distribution was statistically significantly different than the expected one that arises under complete spatial randomness. A smoothing effect is certainly observed when increasing the bandwidth size of the kernel density interpolation. Excluding the kernel size of 1000 meters, then the results do not prove any influence of kernel size or control points on the kernel density surfaces.