Abstract: Radiative forces of greenhouse gases (GHG) increase the temperature of the Earth's surface, more on land, and less in oceans, due to their thermal capacities. Given this inertia, the temperature increase is delayed over time. Air temperature, however, is not delayed as air thermal capacity is much lower. In this study, through analysis and synthesis of multidisciplinary science and data, an estimate of atmospheric temperature increase is made. Then, this estimate is used to shed light on current observations of ice and snow loss, desertification and forest fires, and increased extreme air disturbances. The reason for this inquiry is due to the author’s skepticism that current changes cannot be explained by a "~1 oC" global average surface temperature rise within the last 50-60 years. The only other plausible cause to explore for understanding is that of atmospheric temperature rise. The study utilizes an analysis of air temperature rise from three different scientific disciplines: thermodynamics, climate science experiments, and climactic historical studies. The results coming from these diverse disciplines are nearly the same, within ± 1.6%. The direct radiative force of GHGs with a high level of scientific understanding is near 4.7 W/m2 on average over the Earth’s entire surface in 2018, as compared to one in pre-Industrial time in the mid-1700s. The additional radiative force of fast feedbacks coming from various forms of water gives approximately an additional ~15 W/m2. In 2018, these radiative forces heated the atmosphere by approximately 5.1 oC, which will create a thermal equilibrium average ground surface temperature increase of 4.6 oC to 4.8 oC by the end of this century. After 2018, the temperature will continue to rise without any additional increases in the concentration of the GHGs, primarily of carbon dioxide and methane. These findings of the radiative force of GHGs in 2018 were applied to estimates of effects on major Earth ecosystems. This additional force of nearly 20 W/m2 causes an increase in ice melting by an additional rate of over 90 cm/year, green leaves temperature increase by nearly 5 oC, and a work energy increase of air by approximately 40 Joules/mole. This explains the observed high rates of ice melting at all altitudes and latitudes, the spread of deserts and increases in forest fires, as well as increased energy of tornadoes, typhoons, hurricanes, and extreme weather, much more plausibly than the 1.5 oC increase in average global surface temperature in the same time interval. Planned mitigation and adaptation measures might prove to be much more effective when directed toward the reduction of existing GHGs in the atmosphere.
Abstract: The article presents results from the AF3 project “Advanced Forest Fire Fighting” focused on Unmanned Aircraft Systems (UAS)-based 3D surveillance and 3D area mapping using high-resolution photogrammetric methods from multispectral imaging, also taking advantage of the 3D scanning techniques from the SCAN4RECO project. We also present a proprietary embedded sensor system used for the detection of fire ignitions in the forest using near-infrared based scanner with weight and form factors allowing it to be easily deployed on standard commercial micro-UAVs, such as DJI Inspire or Mavic. Results from real-life pilot trials in Greece, Spain, and Israel demonstrated added-value in the use of UAS for precise and reliable detection of forest fires, as well as high-resolution 3D aerial modeling for accurate quantification of human resources and equipment required for firefighting.
Abstract: In this paper, we describe how Bayesian inferential reasoning will contributes in obtaining a well-satisfied prediction for Distributed Constraint Optimization Problems (DCOPs) with uncertainties. We also demonstrate how DCOPs could be merged to multi-agent knowledge understand and prediction (i.e. Situation Awareness). The DCOPs functions were merged with Bayesian Belief Network (BBN) in the form of situation, awareness, and utility nodes. We describe how the uncertainties can be represented to the BBN and make an effective prediction using the expectation-maximization algorithm or conjugate gradient descent algorithm. The idea of variable prediction using Bayesian inference may reduce the number of variables in agents’ sampling domain and also allow missing variables estimations. Experiment results proved that the BBN perform compelling predictions with samples containing uncertainties than the perfect samples. That is, Bayesian inference can help in handling uncertainties and dynamism of DCOPs, which is the current issue in the DCOPs community. We show how Bayesian inference could be formalized with Distributed Situation Awareness (DSA) using uncertain and missing agents’ data. The whole framework was tested on multi-UAV mission for forest fire searching. Future work focuses on augmenting existing architecture to deal with dynamic DCOPs algorithms and multi-agent information merging.
Abstract: In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.
Abstract: The present research addresses the role of place attachment and emotions in community resiliency and recovery within the context of a disaster. Natural disasters represent a disruption in the normal functioning of a community, leading to a general feeling of disorientation. This study draws on the trauma caused by a natural hazard such as a forest fire. The changes of the sense of togetherness are being assessed. Finally this research determines how the place attachment of the inhabitants was affected during the reorientation process of the community. The case study area is Mati, a small coastal town in eastern Attica, Greece. The fire broke out on July 23rd, 2018. A quantitative research was conducted through questionnaires via phone interviews, one year after the disaster, to address community resiliency in the long-run. The sample was composed of 159 participants from the rural community of Mati plus 120 coming from Skyros Island that was used as a control group. Inhabitants were prompted to answer items gauging their emotions related to the event, group identification and emotional significance of their community, and place attachment before and a year after the fire took place. Importantly, the community recovery and reorientation were examined within the context of a relative absence of government backing and official support. Emotions related to the event were aggregated into 4 clusters related to: activation/vigilance, distress/disorientation, indignation, and helplessness. The findings revealed a decrease in the level of place attachment in the impacted area of Mati as compared to the control group of Skyros Island. Importantly, initial distress caused by the fire prompted the residents to identify more with their community and to report more positive feelings toward their community. Moreover, a mediation analysis indicated that the positive effect of community cohesion on place attachment one year after the disaster was mediated by the positive feelings toward the community. Finally, place attachment contributes to enhanced optimism and a more positive perspective concerning Mati’s future prospects. Despite an insufficient state support to this affected area, the findings suggest an important role of emotions and place attachment during the process of recovery. Implications concerning the role of emotions and social dynamics in meshing place attachment during the disaster recovery process as well as community resiliency are discussed.
Abstract: Forest fire, which is, an uncontrolled fire occurring in nature has become a major concern for the Forestry Commission of Ghana (FCG). The forest fires in Ghana usually result in massive destruction and take a long time for the firefighting crews to gain control over the situation. In order to assess the effect of forest fire at local scale, it is important to consider the role fire plays in vegetation composition, biodiversity, soil erosion, and the hydrological cycle. The occurrence, frequency and behaviour of forest fires vary over time and space, primarily as a result of the complicated influences of changes in land use, vegetation composition, fire suppression efforts, and other indigenous factors. One of the forest zones in Ghana with a high level of vegetation stress is the Goaso forest area. The area has experienced changes in its traditional land use such as hunting, charcoal production, inefficient logging practices and rural abandonment patterns. These factors which were identified as major causes of forest fire, have recently modified the incidence of fire in the Goaso area. In spite of the incidence of forest fires in the Goaso forest area, most of the forest services do not provide a cartographic representation of the burned areas. This has resulted in significant amount of information being required by the firefighting unit of the FCG to understand fire risk factors and its spatial effects. This study uses Remote Sensing and Geographic Information System techniques to develop a fire risk hazard model using the Goaso Forest Area (GFA) as a case study. From the results of the study, natural forest, agricultural lands and plantation cover types were identified as the major fuel contributing loads. However, water bodies, roads and settlements were identified as minor fuel contributing loads. Based on the major and minor fuel contributing loads, a forest fire risk hazard model with a reasonable accuracy has been developed for the GFA to assist decision making.
Abstract: The role of volunteers in disaster management is of decisive importance and the need of their involvement is well recognized, both for prevention measures and for disaster management. During major catastrophes, whereas professional personnel are outsourced, the role of volunteers is crucial. In Greece experience has shown that various groups operating in the civil protection mechanism like local administration staff or volunteers, in many cases do not have the necessary knowledge and information on best practices to act against natural disasters. One of the major problems is the lack of volunteers’ education and training. In the above given framework, this paper presents the results of a survey aimed to identify the level of education and preparedness of civil protection volunteers in Greece. Furthermore, the implementation of earthquake protection measures at individual, family and working level, are explored. More specifically, the survey questionnaire investigates issues regarding pre-earthquake protection actions, appropriate attitudes and behaviors during an earthquake and existence of contingency plans in the workplace. The questionnaires were administered to citizens from different regions of the country and who attend the civil protection training program: “Protect Myself and Others”. A closed-form questionnaire was developed for the survey, which contained questions regarding the following: a) knowledge of self-protective actions; b) existence of emergency planning at home; c) existence of emergency planning at workplace (hazard mitigation actions, evacuation plan, and performance of drills); and, d) respondents` perception about their level of earthquake preparedness. The results revealed a serious lack of knowledge and preparedness among respondents. Taking into consideration the aforementioned gap and in order to raise awareness and improve preparedness and effective response of volunteers acting in civil protection, the EVANDE project was submitted and approved by the European Commission (EC). The aim of that project is to educate and train civil protection volunteers on the most serious natural disasters, such as forest fires, floods, and earthquakes, and thus, increase their performance.
Abstract: A biosphere reserve is developed to create harmony
amongst economic development, community development, and
environmental protection, through partnership between human and
nature. Giam Siak Kecil Bukit Batu Biosphere Reserve (GSKBB BR)
in Riau Province, Indonesia, is unique in that it has peat soil
dominating the area, many springs essential for human livelihood,
high biodiversity. Furthermore, it is the only biosphere reserve
covering privately managed production forest areas. In this research, we aimed at analyzing the threat of deforestation
and forest fire, and the potential of CO2 emission at GSKBB BR. We
used Landsat image, arcView software, and ERDAS IMAGINE 8.5
Software to conduct spatial analysis of land cover and land use
changes, calculated CO2 emission based on emission potential from
each land cover and land use type, and exercised simple linear
regression to demonstrate the relation between CO2 emission
potential and deforestation. The result showed that, beside in the buffer zone and transition
area, deforestation also occurred in the core area. Spatial analysis of
land cover and land use changes from years 2010, 2012, and 2014
revealed that there were changes of land cover and land use from
natural forest and industrial plantation forest to other land use types,
such as garden, mixed garden, settlement, paddy fields, burnt areas,
and dry agricultural land. Deforestation in core area, particularly at
the Giam Siak Kecil Wildlife Reserve and Bukit Batu Wildlife
Reserve, occurred in the form of changes from natural forest in to
garden, mixed garden, shrubs, swamp shrubs, dry agricultural land,
open area, and burnt area. In the buffer zone and transition area,
changes also happened, what once swamp forest changed into garden,
mixed garden, open area, shrubs, swamp shrubs, and dry agricultural
land. Spatial analysis on land cover and land use changes indicated
that deforestation rate in the biosphere reserve from 2010 to 2014 had
reached 16 119 ha/year. Beside deforestation, threat toward the
biosphere reserve area also came from forest fire. The occurrence of forest fire in 2014 had burned 101 723 ha of the
area, in which 9 355 ha of core area, and 92 368 ha of buffer zone
and transition area. Deforestation and forest fire had increased CO2
emission as much as 24 903 855 ton/year.
Abstract: Indonesia has experienced annual forest fires that have
rapidly destroyed and degraded its forests. Fires in the peat swamp
forests of Riau Province, have set the stage for problems to worsen,
this being the ecosystem most prone to fires (which are also the most
difficult, to extinguish). Despite various efforts to curb deforestation,
and forest degradation processes, severe forest fires are still
occurring. To find an effective solution, the basic causes of the
problems must be identified. It is therefore critical to have an indepth
understanding of the underlying causal factors that have
contributed to deforestation and forest degradation as a whole, in
order to attain reductions in their rates. An assessment of the drivers of deforestation and forest
degradation was carried out, in order to design and implement
measures that could slow these destructive processes. Research was
conducted in Giam Siak Kecil–Bukit Batu Biosphere Reserve
(GSKBB BR), in the Riau Province of Sumatera, Indonesia. A
biosphere reserve was selected as the study site because such reserves
aim to reconcile conservation with sustainable development. A
biosphere reserve should promote a range of local human activities,
together with development values that are in line spatially and
economically with the area conservation values, through use of a
zoning system. Moreover, GSKBB BR is an area with vast peatlands,
and is experiencing forest fires annually. Various factors were
analysed to assess the drivers of deforestation and forest degradation
in GSKBB BR; data were collected from focus group discussions
with stakeholders, key informant interviews with key stakeholders,
field observation and a literature review. Landsat satellite imagery was used to map forest-cover changes
for various periods. Analysis of landsat images, taken during the
period 2010-2014, revealed that within the non-protected area of core
zone, there was a trend towards decreasing peat swamp forest areas,
increasing land clearance, and increasing areas of community oilpalm
and rubber plantations. Fire was used for land clearing and most
of the forest fires occurred in the most populous area (the transition
area). The study found a relationship between the deforested/
degraded areas, and certain distance variables, i.e. distance from
roads, villages and the borders between the core area and the buffer
zone. The further the distance from the core area of the reserve, the
higher was the degree of deforestation and forest degradation. Research findings suggested that agricultural expansion may be
the direct cause of deforestation and forest degradation in the reserve,
whereas socio-economic factors were the underlying driver of forest
cover changes; such factors consisting of a combination of sociocultural,
infrastructural, technological, institutional (policy and governance), demographic (population pressure) and economic
(market demand) considerations. These findings indicated that local
factors/problems were the critical causes of deforestation and
degradation in GSKBB BR. This research therefore concluded that
reductions in deforestation and forest degradation in GSKBB BR
could be achieved through ‘local actor’-tailored approaches such as
community empowerment.
Abstract: The purpose of this study was to investigate
perceptions of climate change risk to forest ecosystems and forestbased
communities as well as perceived effectiveness of adaptation
strategies for climate change as well as challenges for adaptation.
Data was gathered using a pre-tested semi-structured questionnaire.
Simple random selection technique was applied. For the majority of
issues, the responses were obtained on multi-point likert scales, and
the scores provided were, in turn, used to estimate the means and
other useful estimates. A composite knowledge index developed
using correct responses to a set of self-rated statements were used to
evaluate the issues. The mean of the knowledge index was 0.64. Also
all respondents recorded values of the knowledge index above 0.25.
Increase forest fire was perceived by respondents as the greatest risk
to forest eco-system. Decrease access to water supplies was perceived
as the greatest risk to livelihoods of forest based communities. The
most effective adaptation strategy relevant to climate change risks to
forest eco-systems and forest based communities livelihoods in
Kathmandu valley in Nepal as perceived by the respondents was
reforestation and afforestation. As well, lack of public awareness was
perceived as the major limitation for climate change adaptation.
However, perceived risks as well as effective adaptation strategies
showed an inconsistent association with knowledge indicators and
social-cultural variables. The results provide useful information to
any party who involve with climate change issues in Nepal, since
such attempts would be more effective once the people’s perceptions
on these aspects are taken into account.
Abstract: Forest areas are particularly susceptible to fires, which are often manmade. One of the most fire affected forest regions in the world is the Mediterranean. Libya, in the Mediterranean region, has soils that are considered to be arid except in a small area called Aljabal Alakhdar (Green mountain), which is the geographic area covered by this study. Like other forests in the Mediterranean it has suffered extreme degradation. This is mainly due to people removing fire wood, or sometimes converting forested areas to agricultural use, as well as fires which may alter several soil chemical and physical properties. The purpose of this study was to evaluate the effects of fires on the physical properties of soil of Aljabal Alakhdar forest in the north-east of Libya. The physical properties of soil following fire in two geographic areas have been determined, with those subjected to the fire compared to those in adjacent unburned areas in one coastal and one mountain site. Physical properties studied were: soil particle size (soil texture), soil water content, soil porosity and soil particle density. For the first time in Libyan soils, the effect of burning on the magnetic susceptibility properties of soils was also tested. The results showed that the soils in both study sites, irrespective of burning or depth fell into the category of a silt loam texture, low water content, homogeneity of porosity of the soil profiles, relatively high soil particle density values and there is a much greater value of the soil magnetic susceptibility in the top layer from both sites except for the soil water content and magnetic susceptibility, fire has not had a clear effect on the soils’ physical properties.
Abstract: This study focused on the estimation of carbon released to the atmosphere from dry dipterocarp forest (DDF) fires in Thailand. Laboratory experiments were conducted using a cone calorimeter to simulate the DDF fires. The leaf litter collected from DDF in western Thailand was used as biomass fuel. Three different masses of leaf litter were employed, 7g, 10g and 13g, to estimate the carbon released from this type of vegetation fire to the atmosphere. The chemical analysis of the leaf litter showed that the carbon content in the experimental biomass fuel was 46.0±0.1%. From the experiments, it was found that more than 95% of the carbon input was converted to carbon released to the atmosphere, while less than 5% were left in the form of residues, and returned to soil. From the study, the carbon released amounted 440.213±2.243 g/kgdry biomass, and the carbon retained in the residues was 19.786±2.243 g/kgdry biomass. The quantity of biomass fuel consumed to produce 1 g of carbon released was 2.27±0.01gkgdry biomass. Using these experimental data of carbon produced by the DDF fires, it was estimated that this type of fires in 2009 contributed to 4.659 tonnes of carbon released to the atmosphere, and 0.229 tonnes of carbon in the residues to be returned to soil in Thailand.
Abstract: Spatial outliers in remotely sensed imageries represent
observed quantities showing unusual values compared to their
neighbor pixel values. There have been various methods to detect the
spatial outliers based on spatial autocorrelations in statistics and data
mining. These methods may be applied in detecting forest fire pixels
in the MODIS imageries from NASA-s AQUA satellite. This is
because the forest fire detection can be referred to as finding spatial
outliers using spatial variation of brightness temperature. This point is
what distinguishes our approach from the traditional fire detection
methods. In this paper, we propose a graph-based forest fire detection
algorithm which is based on spatial outlier detection methods, and test
the proposed algorithm to evaluate its applicability. For this the
ordinary scatter plot and Moran-s scatter plot were used. In order to
evaluate the proposed algorithm, the results were compared with the
MODIS fire product provided by the NASA MODIS Science Team,
which showed the possibility of the proposed algorithm in detecting
the fire pixels.
Abstract: In the past few years, the use of wireless sensor networks (WSNs) potentially increased in applications such as intrusion detection, forest fire detection, disaster management and battle field. Sensor nodes are generally battery operated low cost devices. The key challenge in the design and operation of WSNs is to prolong the network life time by reducing the energy consumption among sensor nodes. Node clustering is one of the most promising techniques for energy conservation. This paper presents a novel clustering algorithm which maximizes the network lifetime by reducing the number of communication among sensor nodes. This approach also includes new distributed cluster formation technique that enables self-organization of large number of nodes, algorithm for maintaining constant number of clusters by prior selection of cluster head and rotating the role of cluster head to evenly distribute the energy load among all sensor nodes.
Abstract: The forest fires in Thailand are annual occurrence which is the cause of air pollutions. This study intended to estimate the emission from forest fire during 2005-2009 using MODerateresolution Imaging Spectro-radiometer (MODIS) sensor aboard the Terra and Aqua satellites, experimental data, and statistical data. The forest fire emission is estimated using equation established by Seiler and Crutzen in 1982. The spatial and temporal variation of forest fire emission is analyzed and displayed in the form of grid density map. From the satellite data analysis suggested between 2005 and 2009, the number of fire hotspots occurred 86,877 fire hotspots with a significant highest (more than 80% of fire hotspots) in the deciduous forest. The peak period of the forest fire is in January to May. The estimation on the emissions from forest fires during 2005 to 2009 indicated that the amount of CO, CO2, CH4, and N2O was about 3,133,845 tons, 47,610.337 tons, 204,905 tons, and 6,027 tons, respectively, or about 6,171,264 tons of CO2eq. They also emitted 256,132 tons of PM10. The year 2007 was found to be the year when the emissions were the largest. Annually, March is the period that has the maximum amount of forest fire emissions. The areas with high density of forest fire emission were the forests situated in the northern, the western, and the upper northeastern parts of the country.
Abstract: In Southeast Asia, during the dry season (August to
October) forest fires in Indonesia emit pollutants into the atmosphere.
For two years during this period, a total of 67 samples of 2.5 μm
particulate matters were collected and analyzed for total mass and
elemental composition with ICP - MS after microwave digestion. A
study of 60 elements measured during these periods suggest that the
concentration of most of elements, even those usually related to
crustal source, are extremely high and unpredictable during the haze
period. In By contrast, trace element concentration in non - haze
months is more stable and covers a lower range. Other unexpected
events and their effects on the findings are discussed.