An easy,accurate and efficient procedure to create forest fire risk maps using the SEXTANTE plugin Modeler

To prevent, detect, and protect against forest fires, forest personnel need to define rules for determining forest fire risk. In Portugal, all municipalities must annually produce forest fire risk （FFR） maps. To produce more reliable FFR maps more easily, we developed an open source model using the Modeler plugin of SEXTANTE in the program QGIS version 2.0 Dufour. The model provides all the maps involved in the FFR model （susceptibility map, hazard map, vulnerability map, economic value map, and potential loss map） and was produced according to Portuguese Forest Authority＇s （AFN, Autoridade Florestal Nacional） rules for determining the FFR. This model was tested for the Portuguese municipality Santa Maria da Feira, where 40 % of the total municipality area falls in the category ＂very high＂ or ＂high＂ fire risk. The ＂very high＂ fire risk area is mainly classified as broad-leaved forest and has the steepest slopes （〉15 %）. The distance of burned areas to roads was also analyzed; the proportion of burned areas increased with increasing distance to the main roads. In addition, 92.6 % of the ＂high＂ and ＂very high＂ risk zones were located in areas with lower elevation. These results confirmed that forest fire is strongly influenced not only by environmental factors but also by anthropogenic factors. The procedure implemented here was compared with our open source application already available in QGIS and also to the same procedure implemented in GIS pro- prietary software. Although the results were obviously the same, the model developed here presents several advan- tages over the other two approaches. Besides being faster, it is easy to change the model parameters according to user needs （i.e., to the rules of different countries）, and can be modified and adapted to other variables and other areas to create risk maps for different natural phenomena （e.g., floods, earthquakes, landslides）. The model is easy to use and to create risk and hazard maps rapidly in a free, open source environment that does not require any programming knowledge.

Evolution Analysis of Societal Risk Events by Risk Maps

Event evolution analysis which provides an effective approach to capture the main context of a story from explosive increased news texts has become the critical basis for many real applications,such as crisis and emergency management and decision making.Especially,the development of societal risk events which may cause some possible harm to society or individuals has been heavily concerned by both the government and the public.In order to capture the evolution and trends of societal risk events,this paper presents an improved algorithm based on the method of information maps.It contains an event-level cluster generation algorithm and an evaluation algorithm.The main work includes:1)Word embedding representation is adopted and event-level clusters are chosen as nodes of the events evolution chains which may comprehensively present the underlying structure of events.Meanwhile,clusters that consist of risk-labeled events enable to illustrate how events evolve along the time with transitions of risks.2)One real-world case,the event of"Chinese Red Cross",is studied and a series of experiments are conducted.3)An evaluation algorithm is proposed on the basis of indicators of map construction without massive human-annotated dataset.Our approach for event evolution analysis automatically generates a visual evolution of societal risk events,displaying a clear and structural picture of events development.

Forest fire risk indices and zoning of hazardous areas in Sorocaba,Sao Paulo state,Brazil

This study compares the performance of three fire risk indices for accuracy in predicting fires in semideciduous forest fragments,creates a fire risk map by integrating historical fire occurrences in a probabilistic density surface using the Kernel density estimator(KDE)in the municipality of Sorocaba,Sao Paulo state,Brazil.The logarithmic Telicyn index,Monte Alegre formula(MAF)and enhanced Monte Alegre formula(MAF+)were employed using data for the period 1 January 2005 to 31 December 2016.Meteorological data and numbers of fire occurrences were obtained from the National Institute of Meteorology(INMET)and the Institute for Space Research(INPE),respectively.Two performance measures were calculated:Heidke skill score(SS)and success rate(SR).The MAF+index was the most accurate,with values of SS and SR of 0.611%and 62.8%,respectively.The fire risk map revealed two most susceptible areas with high(63 km^2)and very high(47 km^2)risk of fires in the municipality.Identification of the best risk index and the generation of fire risk maps can contribute to better planning and cost reduction in preventing and fighting forest fires.

Comprehensive Risk Analysis of Storm Surge Flood Based on WebGIS

The comprehensive risk analysis of storm surge flood is vital to the safety management of sea embank- ment, the scientific assessment of storm surge disaster and the improvement of emergent treatment in storm surge haz- ard. Based on the research of disaster-causing, disaster-pregnant and disaster-bearing factors, the influencing factors of storm surge risk are concluded to be flood natural risk, embankment position, embankment width and height. The membership degree of the factors of stoma surge risk is firstly determined by storm surge flood evolution based on WebGIS, and the comprehensive risk membership and risk grade of each influencing factor are obtained. Then the effects of a single factor on comprehensive risk and sensitivity analysis are discussed, and the storm surge flood risk map is obtained. Finally, the storm surge of Tianjin Binhai New Area is taken as a case. The results show that the in- fluencing degree of the factors on the comprehensive risk membership is in decreasing order of flood natural risk, em- bankment position, embankment width and height. The flood risk map of the case is drawn, which is useful to decrease losses caused by storm surge disaster.

Exploration risk evaluation using object-based modeling,an example from the Tertiary fractured play,western Qaidam Basin of China

Geological risk evaluation reveals the uncertainty of converting an anticipated resource potential in an identified exploration target into an economic petroleum accumulation prior to drilling. Providing consistent and unbiased estimates of geological risk for all exploration targets in an area of interest is essential in risk evaluation. This paper discusses the potential use of an object-based stochastic procedure for geological risk evaluation at the play level. The object-based model of Super SD, as a data integration tool, can integrate geological information of petroleum system elements that control occurrences of petroleum pools with the spatial correlation characteristics of the discoveries in a play. Other information, such as the estimated total play potential and size characteristics, from conventional resource assessments can be also incorporated into the model as geological constraints. The uncertainty associated with the data and domain knowledge in the predicted pool locations is expressed as a probability map, representing the geological exploration risk of the play. By incorporating all available inibrmation and checking the consistency of models with geological constraints, the object-based model improves predictions of petroleum occurrences, thus enhancing the associated risk evaluation. The proposed method was applied to the fractured petroleum play of the western Qaidam Basin in northwestern China in order to illustrate the use of the object-based method for risk evaluation.

PSO/ACO Algorithm-based Risk Assessment of Human Neural Tube Defects in Heshun County,China

Abstract Objective To develop a new technique for assessing the risk of birth defects, which are a major cause of infant mortality and disability in many parts of the world. Methods The region of interest in this study was Heshun County, the county in China with the highest rate of neural tube defects （NTDs）. A hybrid particle swarm optimization/ant colony optimization （PSO/ACO） algorithm was used to quantify the probability of NTDs occurring at villages with no births. The hybrid PSO/ACO algorithm is a form of artificial intelligence adapted for hierarchical classification. It is a powerful technique for modeling complex problems involving impacts of causes. Results The algorithm was easy to apply, with the accuracy of the results being 69.5%＋7.02% at the 95% confidence level. Conclusion The proposed method is simple to apply, has acceptable fault tolerance, and greatly enhances the accuracy of calculations.

Risk Assessment Mapping of Landscape Development Based on Ecological Service and Goods in Malaysia Lowland Tropical Rainforest

Amongst the impacts of converting forest to agricultural activities are soil erosion and degradation of ecology service values and goods （ESVG）. The soil erosion can be seen as on-site impacts, such as the problems of decreasing soil fertility and also its off-site impact such as the problems of sedimentation of the nearby rivers, whilst the degradation of ESVG are more holistie in nature, These impacts can be devastating in environmental, biological, and socio-economic manners. This paper reports the study undertaken on the impacts of agricultural development in 0.8 million ha of forest dominated landscape in Pasoh Forest Region （PFR）, Malaysia, within period of 8 years from 1995 to 2003. Three folds of impacts on agricultural development examined and analysed, are： （i） relationship of total soil loss and changes in land use pattern, （ii） mapping trends of ESVG for PFR in 1995 and 2003, and （iii） risk assessment of ESVG based on simulation of converting 339,630 ha of primary forest into mass-scale oil palm plantation. Results of this study indicated that although only minor changes of about 1464 ha （about 0.2% of PFR） of primary forest was converted to agricultural activities, it have significantly increased the total soil loss from 59 to 69 million ton/ha/yr. The mean rate of soil is loss for PFR is 0.8 mil ton/ha/yr and if translated into ESVG term, the soil loss costs about US$ 4.8mil/yr. However, majority of the soil loss within all land use classes are within range of very low-low risk categories （〈10 ton/ha/yr）. ESVG for PFR were costing US$ 179 millions in 1995, declined to US$114 millions in 2003 due to 0.2% reduction of forested land. The ESVG of converting 339,630 ha primary forest into mass plantation cost less than original forest within period of 20 years examined; the 20th year of conversion, the ESVG of plantation and to-remain as forest cost US$ 963 and US$ 575 millions, respectively. However, this difference is only marginal when full attributes of ESVG are considered.

An Empirical Study of Risk Factors of the Gaming Industry in Macao

Beyond doubt, the gaming industry is the most important to the sustained success for Macao. While the industry has been growing spectacularly well since its liberalization in 2004, now, it is time to critically review the risk factors that may adversely affect its long-term, healthy, and harmonious development. People and organizations need to be vigilant in peace time. Being able to think of possible crises while living in a safe environment has been our traditional wisdom. There is an obvious need to develop and maintain a risk management mechanism for the gaming industry in Macao. Appropriate precautionary measures developed through rigorous study can help mitigate the damage brought by crises and in turn will ensure the sustained development of Macao. Risks and crises, if handled properly, can possibly be transformed into opportunities. This research adopts an integrative approach through systematic and comprehensive investigation to establish an approach to monitor and predict risks and crises for the gaming industry in Macao. This would provide a useful reference for the society and government of Macao in handling them.

Influence of Seasonal Ground Water Level Fluctuations on the Stability of the Rohingya Refugee Camp Hills of Ukhiya, Teknaf, Cox’s Bazar, Bangladesh—A Threat for Sustainable Development

Bangladesh is a south Asian Monsoonal Country and the recent precipitation pattern in the Cox’s Bazar area of Bangladesh is changing and increasing the number of monsoonal slope failures and landslide hazards in the Kutubpalong & Balukhali Rohingya camp area. An attempt has been made to see the influence of seasonal variation of ground water level (G.W.L.) fluctuations on the stability of the eco hills and forests of Ukhiya Teknaf region. Ukhiya hills are in great danger because of cutting trees from the hill slopes and it is well established that due to recent change of climate, short term rainfall for few consecutive days during monsoon might show an influence on the factor of safety (Fs) values of the camp hill slopes. A clear G.W.L. variation between dry and wet seasons has an influence on the stability (Fs) values indicating that climate has a strong influence on the stability and threatening sustainable development. A stable or marginally stable slope might be unstable during raining and show a variation of ground water level (G.W.L.). The generation of pore water pressure (P.W.P.) is also influenced by seasonal variation of ground water level. During wet season negative P.W.P. called suction plays an important role to occur slope failures in the Ukhiya hills. Based on all calculated factor of safety values (Fs) at different locations, four (4) susceptible landslide risk zones are identified. They are very high risk (Fs = 0.18 to 0.46), high risk (Fs = 0.56 to 0.75), medium risk (Fs = 0.76 to 1.0) and marginally stable areas (Fs ≈ 1). Proper geo-engineering measures must be taken by the concerned authorizes to reduce P.W.P. during monsoon by installing rain water harvesting system, allowing sufficient drainage & other geotechnical measures to reduce the risk of slope failures in the Ukhiya hills. Based on the stability factor (Fs) at different slope locations of the camp hills, a risk map of the investigated area has been produced for the local community for their safety and to build up awareness & to motivate them to evacuate the site during monsoonal slope failures. The established “Risk Maps” can be used for future geological engineering works as well as for sustainable planning, design and construction purposes relating to adaptation and mitigation of landslide risks in the investigated area.

Risk mapping of wildlife-vehicle collisions across thestate of Montana,USA:a machine-learning approach forimbalanced data along rural roads

Wildlife-vehicle collisions(WVCs)with large animals are estimated to cost the USA over 8 billion USD in property damage,tens of thousands of human injuries and nearly 200 human fatalities each year.Most WVCs occur on rural roads and are not collected evenly among road segments,leading to imbalanced data.There are a disproportionate number of analysis units that have zero WVC cases when investigating large geographic areas for collision risk.Analysis units with zero WVCs can reduce prediction accuracy and weaken the coefficient estimates of statistical learning models.This study demonstrates that the use of the synthetic minority over-sampling technique(SMOTE)to handle imbalanced WVC data in combination with statistical and machine-learning models improves the ability to determine seasonal WVC risk across the rural highway network in Montana,USA.An array of regularized variables describing landscape,road and traffic were used to develop negative binomial and random forest models to infer WVC rates per 100 million vehicle miles travelled.The random forest model is found to work particularly well with SMOTE-augmented data to improve the prediction accuracy of seasonal WVC risk.SMOTE-augmented data are found to improve accuracy when predicting crash risk across fine-grained grids while retaining the characteristics of the original dataset.The analyses suggest that SMOTE augmentation mitigates data imbalance that is encountered in seasonally divided WVC data.This research provides the basis for future risk-mapping models and can potentially be used to address the low rates of WVCs and other crash types along rural roads.

The contribution of maps to the challenges of risk communication to the public

Risk communication is a significant challenge in risk management.It serves different purposes;an important one is to improve the public risk awareness and mitigation.Because of the strong spatio-temporal component of natural hazards,maps can play a decisive role in communicating risk information.The application and design of maps for risk communication especially to the public has not been investigated comprehensively.Specific constraints and challenges of risk communication have not been considered systematically in the map design process so far.This study aims at developing a frame for the application and design of interactive risk and hazard maps for the public which is based on the specific constraints and challenges of risk communication.In a literature review it introduces concepts and methods from social sciences and psychology,which have been assessed as important for communicating risk information.The concepts and methods are adapted to map-mediated risk communication according to the approaches of Activity Theory.Communication objectives and tasks which are essential to improve risk mitigation are identified and geovisualization methods for information presentation are related according to the degree which they are able to serve them.Based on this,some principles for map-based risk communication are established.

Towards Sustainable Land Uses within the Elbe River Biosphere Reserve in Lower Saxony, Germany by Means of TerraSAR-X Images

Floods are one of the major hazards worldwide. They are the source of huge risks in rural and urban areas, resulting in severe impacts on the civil society, industry and the economy. The Elbe River has suffered from many severe floods during recent decades. In this study, the zones flooded during 2011 were analyzed using TerraSAR-X images and a digital elevation model for the area in order to identify possible ways to mitigate flood hazards in the future, regarding sustainable land-use. Two study areas are investigated, around the Walmsburg oxbow and the Wehningen oxbow. These are located between Elbe-Kilometer (505-520) and (533-543), respectively, within the Lower Saxonian Elbe River Biosphere Reserve. Those areas are characterized by several types of land use, with agricultural land use being predominant. The study investigated the possibility of using a Decision-Tree object-based classifier for determining the major land uses and the extent of the inundation areas. The inundation areas identify for 2011 submerged some agricultural fields that must be added to existing flood risk maps, and future cultivation activities there prevented to avoid the possible economic losses. Furthermore, part of the residential area is located within the high flood zone, and must be included in risk maps to avoid the possible human and economic losses, to achieve sustainable land use for the areas studied.

Is multi-hazard mapping effective in assessing natural hazards and integrated watershed management?

Natural hazards are often studied in isolation.However,there is a great need to examine hazards holistically to better manage the complex of threats found in any region.Many regions of the world have complex hazard landscapes wherein risk from individual and/or multiple extreme events is omnipresent.Extensive parts of Iran experience a complex array of natural hazards-floods,earthquakes,landslides,forest fires,subsidence,and drought.The effectiveness of risk mitigation is in part a function of whether the complex of hazards can be collectively considered,visualized,and evaluated.This study develops and tests individual and collective multihazard risk maps for floods,landslides,and forest fires to visualize the spatial distribution of risk in Fars Province,southern Iran.To do this,two well-known machine-learning algorithms-SVM and MARS-are used to predict the distribution of these events.Past floods,landslides,and forest fires were surveyed and mapped.The locations of occurrence of these events(individually and collectively) were randomly separated into training(70%) and testing(30%) data sets.The conditioning factors(for floods,landslides,and forest fires) employed to model the risk distributions are aspect,elevation,drainage density,distance from faults,geology,LULC,profile curvature,annual mean rainfall,plan curvature,distance from man-made residential structures,distance from nearest river,distance from nearest road,slope gradient,soil types,mean annual temperature,and TWI.The outputs of the two models were assessed using receiver-operating-characteristic(ROC) curves,true-skill statistics(TSS),and the correlation and deviance values from each models for each hazard.The areas-under-the-curves(AUC) for the MARS model prediction were 76.0%,91.2%,and 90.1% for floods,landslides,and forest fires,respectively.Similarly,the AUCs for the SVM model were 75.5%,89.0%,and 91.5%.The TSS reveals that the MARS model was better able to predict landslide risk,but was less able to predict flood-risk patterns and forest-fire risk.Finally,the combination of flood,forest fire,and landslide risk maps yielded a multi-hazard susceptibility map for the province.The better predictive model indicated that 52.3% of the province was at-risk for at least one of these hazards.This multi-hazard map may yield valuable insight for land-use planning,sustainable development of infrastructure,and also integrated watershed management in Fars Province.

Groundwater Vulnerability Assessment for the Corridor Wellfield Using DRASTIC and Modified DRASTIC Models: A Case Study of Eastern Jordan

Groundwater vulnerability maps were created for the Corridor wellfield (~300 km2) in the eastern Jordan using the DRASTIC and modified DRASTIC groundwater vulnerability assessment models. The study area is considered as one of the most important well fields therein providing partially three governorates with the needed drinking water. Detailed geological and hydrogeological parameters as well as the land-use map of the area were obtained from various sources to utilize both models. ArcGIS software was used for calculations and maps preparation. As a result, the generic DRASTIC vulnerability index ranges between 109 and 168. Thus, two vulnerability classes were observed, moderate (9.9%) and high (90.1%) vulnerability classes. On the other hand, the modified DRASTIC model (risk map) is taking into account the land-use map classes in the study area. The output risk map reveals two main classes, the moderate and high-risk areas. The moderate-risk areas occupy 9.3% of the total volume of the study area while the high-risk areas are 90.7%. Due to the high depth to groundwater within the area (between 90 m and 390 m), the depth to groundwater intervals was modified in the model to become more comfortable with the situation in Jordan. The high percentage of the high vulnerable areas against pollutants reflects the need to do more investigation for the studied area.

Transmission risk of Oropouche fever across the Americas

Background Vector-borne diseases(VBDs)are important contributors to the global burden of infectious diseases due to their epidemic potential,which can result in signifcant population and economic impacts.Oropouche fever,caused by Oropouche virus(OROV),is an understudied zoonotic VBD febrile illness reported in Central and South America.The epidemic potential and areas of likely OROV spread remain unexplored,limiting capacities to improve epidemiological surveillance.Methods To better understand the capacity for spread of OROV,we developed spatial epidemiology models using human outbreaks as OROV transmission-locality data,coupled with high-resolution satellite-derived vegetation phe‑nology.Data were integrated using hypervolume modeling to infer likely areas of OROV transmission and emergence across the Americas.Results Models based on one-support vector machine hypervolumes consistently predicted risk areas for OROV transmission across the tropics of Latin America despite the inclusion of diferent parameters such as diferent study areas and environmental predictors.Models estimate that up to 5 million people are at risk of exposure to OROV.Nevertheless,the limited epidemiological data available generates uncertainty in projections.For example,some out‑breaks have occurred under climatic conditions outside those where most transmission events occur.The distribu‑tion models also revealed that landscape variation,expressed as vegetation loss,is linked to OROV outbreaks.Conclusions Hotspots of OROV transmission risk were detected along the tropics of South America.Vegetation loss might be a driver of Oropouche fever emergence.Modeling based on hypervolumes in spatial epidemiology might be considered an exploratory tool for analyzing data-limited emerging infectious diseases for which little understand‑ing exists on their sylvatic cycles.OROV transmission risk maps can be used to improve surveillance,investigate OROV ecology and epidemiology,and inform early detection.

How Participatory is Participatory Flood Risk Mapping? Voices from the Flood Prone Dharavi Slum in Mumbai

Participatory flood risk mapping(PFRM) is a well-recognized and widely implemented tool for meaningful community involvement in disaster risk reduction(DRR). The effectiveness of PFRM remains anecdotal. The PFRM exercise has rarely been applied identically in two different places by two different organizations, which produces varied and uncertain outcomes. In the absence of any agreed and comprehensive framework for participatory DRR, existing studies struggle to provide a scientific account of how the structure, design, and process of PFRM ensure the effective participation of local communities.This study, examines what factors and methods make PFRM an effective participatory DRR tool. In this study,we first identified the process-based criteria of participation. Then we briefly introduced a participatory flood risk mapping exercise conducted in a flood-prone informal settlement in Dharavi, Mumbai. The exercise was carefully designed to meet the process criteria of effective participation. Finally, using qualitative research methods, we evaluated the effectiveness of our PFRM from the local community perspective. The findings show that ensuring community livelihood security and true involvement of marginalized groups, preparing an action plan, and incorporating fun and cultural connotations into the facilitation process are critical components that enhance community participation through PFRM in DRR.

Basin flood control system risk evaluation based on variable sets

Flood control system risk evaluation is an effective measure for flood risk management and decisions.In order to make better flood risk decisions and thereby improve social and economic benefits,the flood control risk evaluation index system should be built to quantify and normalize flood risk effectively and efficiently.Because the current evaluation index has the binary miscibility characteristic of fuzziness and clarity,this paper establishes a new flood control system risk evaluation method based on the theory of variable sets(VS).Through a comparison of flood control risk evaluation with variable fuzzy sets(VFS) in the same basin flood control system risk evaluation,it is revealed that the new method,i.e.,flood control risk evaluation with variable fuzzy/clear mixture sets(variable sets),will be reasonable in all cases.Finally,in one case study,i.e.,the flood control system risk evaluation of Fengman Reservoir Basin,which is located in the southeast central of Jilin Province in China,the risk evaluation levels for each county in the basin as well as the whole flood risk distribution map of the basin could be provided with the new method.This provides useful information for basin flood control planning and design.

Biosecurity risk mapping and gap analysis in South East Asia

Introduction:In today’s globalized world where travel is commonplace,a threat in one region can easily spread throughout the whole world.It is,therefore,essential for multi-disciplinary risk assessment,risk mitigation,and collaborative strategies to take place among various stakeholders to mitigate this.Any strategic plan to deal with biosecurity,therefore,needs to be a complete loop,top to bottom and bottom to top.This paper describes the results of Project 62,which involved mapping and biosecurity risk assessment in South East Asia.Materials and methods:The mapping and biosecurity risk assessment activities for the participating partner countries was carried out in two phases.The first phase involved risk assessment by six partnercountry bio-experts for their own countries and the second phase involved conducting a joint Strengths,Weaknesses,Opportunities,and Threats(SWOT)analysis and risk assessment for the South East Asian region as whole,together with international bio-experts at a workshop.Results and discussion:The following key recommendations of the project show that biosecurity needs to be addressed through stakeholder engagement at multiple levels starting from the top echelons of the government to the worker who needs to recognize and understand the threats they might face:1.Systematic analysis of existing information from BWC ISU Article 10,IHR capacities,JEE,UN Security Council Resolution 1540 Action Plan,EU CBRN NAP,and other relevant sources to develop a common understanding of the definition of biosecurity for all stakeholders in the region.2.Creation of programs for awareness building in biosecurity,not limiting them to laboratory biosecurity but using an all-inclusive approach to include border biosecurity,pandemic response,etc.3.Creation of a country-specific list of high-risk biological materials.4.Compulsory standardized biosecurity training,including responsible conduct in biosecurity research.5.Framework for one-health and security interface addressing biosecurity threats.6.Framework for ensuring information security in relation to biosecurity.7.Involvement of local/regional experts in the implementation of EU-CBRN CoE projects.

SIRENE: A Spatial Data Infrastructure to Enhance Communities' Resilience to Disaster-Related Emergency

Planning in advance to prepare for and respond to a natural hazard-induced disaster-related emergency is a key action that allows decision makers to mitigate unexpected impacts and potential damage. To further this aim, a collaborative, modular, and information and communications technology-based Spatial Data Infrastructure(SDI)called SIRENE—Sistema Informativo per la Preparazione e la Risposta alle Emergenze(Information System for Emergency Preparedness and Response) is designed and implemented to access and share, over the Internet, relevant multisource and distributed geospatial data to support decision makers in reducing disaster risks. SIRENE flexibly searches and retrieves strategic information from local and/or remote repositories to cope with different emergency phases. The system collects, queries, and analyzes geographic information provided voluntarily by observers directly in the field(volunteered geographic information(VGI) reports) to identify potentially critical environmental conditions. SIRENE can visualize and cross-validate institutional and research-based data against VGI reports,as well as provide disaster managers with a decision support system able to suggest the mode and timing of intervention, before and in the aftermath of different types of emergencies, on the basis of the available information and in agreement with the laws in force at the national andregional levels. Testing installations of SIRENE have been deployed in 18 hilly or mountain municipalities(12 located in the Italian Central Alps of northern Italy, and six in the Umbria region of central Italy), which have been affected by natural hazard-induced disasters over the past years(landslides, debris flows, floods, and wildfire) and experienced significant social and economic losses.

Development and prospects of the fire space monitoring system in Kazakhstan

This article provides a brief description of the fire space monitoring system in Kazakhstan, including the GIS-technology incorporated in its structure. The system performs operative space monitoring of fire areas and burnt areas, mapping of large fire areas, analysis of seasonal and long-term dynamics of burnt areas, and estimation of fire risk zones. Examples of output information obtained from space monitoring of fires are given. Possible directions of development of fire space monitoring in Kazakhstan are specified.