A new approach for forest fire risk modeling using fuzzy AHP and GIS in Hyrcanian forests of Iran

The presented research was performed in order to model the fire risk in a part of Hyrcanian forests of Iran. The fuzzy sets integrated with analytic hierarchy process (AHP) in a decision-making algorithm using geographic information system (GIS) was used to model the fire risk in the study area. The used factors included four major criteria (topographic, biologic, climatic, and human factors) and their 17 sub-criteria. Fuzzy AHP method was used for estimating the importance (weight) of the effective factors in forest fire. Based on this modeling method, the expert ideas were used to express the relative importance and priority of the major criteria and sub-criteria in forest fire risk in the study area. The expert ideas mean was analyzed based on fuzzy extent analysis. Then, the fuzzy weights of criteria and sub-criteria were obtained. The major criteria models and fire risk model were presented based on these fuzzy weights. On the other hand, the spatial data of 17 sub-criteria were provided and organized in GIS to obtain the sub-criteria maps. Each sub-criterion map was converted to raster format and it was reclassified based on risk of its classes to fire occurrence. Then, all sub-criteria maps were converted to fuzzy format using fuzzy membership function in GIS. The fuzzy map of each major criterion (topographic, biologic, climatic, and human criteria) was obtained by weighted overlay of its sub-criteria fuzzy maps considering to major criterion model in GIS. Finally, the fuzzy map of fire risk was obtained by weighted overlay of major criteria fuzzy maps considering to fire risk model in GIS. The actual fire map was used for validation of fire risk model and map. The results showed that the fuzzy estimated weights of human, biologic, climatic, and topographic criteria in fire risk were 0.301, 0.2595, 0.2315, and 0.208, respectively. The results obtained from the fire risk map showed that 38.74% of the study area has very high and high risk for fire occurrence. Results of validation of the fire risk map showed that 80% of the actual fires were located in the very high and high risk areas in fire risk map. It can show the acceptable accuracy of the fire risk model and map obtained from fuzzy AHP in this study. The obtained fire risk map can be used as a decision support system for predicting of the future fires in the study area.     

Landslide susceptibility maps comparing frequency ratio and artificial neural networks: a case study from the Nepal Himalaya

This study considers landslide susceptibility mapping by means of frequency ratio and artificial neural network approaches using geographic information system (GIS) techniques as a basic analysis tool. The selected study area was that of the Panchthar district, Nepal. GIS was used for the management and manipulation of spatial data. Landslide locations were identified from field survey and aerial photographic interpretation was used for location of lineaments. Ten factors in total are related to the occurrence of landslides. Based on the same set of factors, landslide susceptibility maps were produced from frequency ratio and neural network models, and were then compared and evaluated. The weights of each factor were determined using the back-propagation training method. Landslide susceptibility maps were produced from frequency ratio and neural network models, and they were then compared by means of their checking. The landslide location data were used for checking the results with the landslide susceptibility maps. The accuracy of the landslide susceptibility maps produced by the frequency ratio and neural networks is 82.21 and 78.25%, respectively.     

Geohazard reconnaissance mapping for a settlement area

To minimise the losses associated with natural hazards, it is necessary to compile and evaluate earth science data. This study describes and maps the geohazards that may affect the Egirdir (Isparta) settlement area. For these purposes, field studies were performed, and the data obtained were compiled using Geographical Information Systems (GIS). Four different types of earth slump were identified: paleo, small-scale shallow, active and potential earth slump. In addition, two rockfall source areas were identified and mapped. The ratio of the area affected by rockfall to the total area is 2.03%. Although there is no expected risk associated with active earth slump, displacement in the potential earth slump area represents a risk. The risk level calculated is 1.5% for 1 year. Based on all of the data, a geohazard reconnaissance map of the study area was prepared. Based on this map, it can be concluded that 83% of the overall study area has no risk of mass movement.     

Estimating the depth of underground coal fires using data integration techniques

Underground coal fires in China cause serious environmental problems, in addition to the loss of valuable coal resources. The present study aims at developing a quick and practical method to estimate the depth of coal fires using data integration techniques.
  In coal fields which have underground coal fires, the subsurface fires are associated with surface thermal anomalies. Airborne thermal infrared scanner data and colour infrared photographs were used in this study to depict the coal fire front and the outcrop of coal seams, respectively. A Digital Elevation Model (DEM) of the study area was produced from topographic maps at 1:25 000 scale. Finally, taking into account the spreading direction of the coal fires and the relationships between thermal anomalies, relief factors and the occurrence of coal seams, the depths of the coal fires were obtained automatically by means of integration of remote sensing data and GIS techniques. This helped to target the fire fighting operations and made them more cost effective.     

Flood monitoring, mapping and assessing capabilities using RADARSAT remote sensing, GIS and ground data for Bangladesh

Remote sensing is the most practical method available to managers of flood-prone areas for quantifying and mapping flood impacts. This study explored large inundation areas in the Maghna River Basin, around the northeastern Bangladesh, as determined from passive sensor LANDSAT data and the cloud-penetrating capabilities of the active sensors of the remote imaging microwave RADARSAT. This study also used passive sensor LANDSAT wet and dry images for the year 2000. Spatial resolution was 30 m by 30 m for comparisons of the inundation area with RADARSAT images. RADARSAT images with spatial resolution of 50 m by 50 m were used for frequency analysis of floods from 2000 to 2004. Time series images for 2004 were also used. RADARSAT remote sensing data, GIS data, and ground data were used for the purpose of flood monitoring, mapping and assessing. A supervised classification technique was used for this processing. They were processed for creating a maximum water extent map and for estimating inundation areas. The results of this study indicated that the maximum extent of the inundation area as estimated using RADARSAT satellite imaging was about 29, 900.72 km² in 2004, which corresponded well with the heavy rainfall around northeast region, as seen at the Bhairab Bazar station and with the highest water level of the Ganges–Brahmaputra–Meghna (GBM) Rivers. A composite of 5 years of RADARSAT inundation maps from 2000 to 2004, GIS data, and damage data, was used to create unique flood hazard maps. Using the damage data for 2004 and the GIS data, a set of damage maps was also created. These maps are expected to be useful for future planning and flood disaster management. Thus, it has been demonstrated that RADARSAT imaging data acquired over the Bangladesh have the ability to precisely assess and clarify inundation areas allowing for successful flood monitoring, mapping and disaster management.     

Integrated application of the analytic hierarchy process and the geographic information system for flood risk assessment and flood plain management in Taiwan

Flooding is one of the major natural hazards in Taiwan, and most of the low-lying areas in Taiwan are flood-prone areas. In order to minimize loss of life and economic losses, a detailed and comprehensive decision-making tool is necessary for both flood control planning and emergency service operations. The objectives of this research were (i) to develop a hierarchical structure through the analytic hierarchy process (AHP) to provide preferred options for flood risk analysis, (ii) to map the relative flood risk using the geographic information system (GIS), and (iii) to integrate these two methodologies and apply them to one urban and one semi-rural area in central Taiwan. Fushin Township and the floodplain of Fazih River (1 km on either side of the channel) in Taichung City were selected for this study. In this paper, the flood risk is defined as the relative flood risk due to broken dikes or the failure of stormwater drainage systems. Seven factors were considered in relation to the failure of stormwater drainage, and five to that of broken dikes. Following well-defined procedures, flood maps were drawn based on the data collected from expert responses to a questionnaire, the field survey, satellite images, and documents from flood management agencies. The relative values of flood risk are presented using a 200-m grid for the two study areas. It is concluded that integration of AHP and GIS in flood risk assessment can provide useful detailed information for flood risk management, and the method can be easily applied to most areas in Taiwan where required data sets are readily available.     

Spatial prediction of wildfire probability in the Hyrcanian ecoregion using evidential belief function model and GIS

Accurate estimates of wildfire probability and production of distribution maps are the first important steps in wildfire management and risk assessment. In this study, geographical information system (GIS)-automated techniques were integrated with the quantitative data-driven evidential belief function (EBF) model to predict spatial pattern of wildfire probability in a part of the Hyrcanian ecoregion, northern Iran. The historical fire events were identified using earlier reports and MODIS hot spot product as well as by carrying out multiple field surveys. Using the GIS-based EBF model, the relationships among existing fire events and various predictor variables predisposing fire ignition were analyzed. Model results were used to produce a distribution map of wildfire probability. The derived probability map revealed that zones of moderate, high, and very high probability covered nearly 60% of the landscape. Further, the probability map clearly demonstrated that the probability of a fire was strongly dependent upon human infrastructure and associated activities. By comparing the probability map and the historical fire events, a satisfactory spatial agreement between the five probability levels and fire density was observed. The probability map was further validated by receiver operating characteristic using both success rate and prediction rate curves. The validation results confirmed the effectiveness of the GIS-based EBF model that achieved AUC values of 84.14 and 81.03% for success and prediction rates, respectively.     

Volcanic Risk Assessment and Mapping in the Vesuvian Area Using GIS

This paper assesses the risk to people and property from lava flow hazard in the Vesuvian area of Italy using a Geographical Information System (GIS). The intense urbanisation and dense population near Mt. Vesuvius make the area very hazardous. Due to the large amount of available data, GIS is an essential tool to facilitate risk evaluation and constant monitoring of the zone. This analysis is based mainly on a lava flow hazard map of Mt. Vesuvius, determined from volcanic activity between 1631 and 1944. A land-use zonation map of the area was created in order to show areal distribution of the resources, built-up centres and population. For each of the 17 municipalities in the area, demographic and urban data were entered into the GIS database and linked to each appropriate geographic unit in order to create a set of reference maps at the 1:50 000 scale. The lava flow hazard map was overlain on the land use map, and spatial and numerical information of risk were extracted from the resulting maps.     

GIS-based weights-of-evidence modelling of rainfall-induced landslides in small catchments for landslide susceptibility mapping

Landslide susceptibility mapping is a vital tool for disaster management and planning development activities in mountainous terrains of tropical and subtropical environments. In this paper, the weights-of-evidence modelling was applied, within a geographical information system (GIS), to derive landslide susceptibility map of two small catchments of Shikoku, Japan. The objective of this paper is to evaluate the importance of weights-of-evidence modelling in the generation of landslide susceptibility maps in relatively small catchments having an area less than 4 sq km. For the study area in Moriyuki and Monnyu catchments, northeast Shikoku Island in west Japan, a data set was generated at scale 1:5,000. Relevant thematic maps representing various factors (e.g. slope, aspect, relief, flow accumulation, soil depth, soil type, land use and distance to road) that are related to landslide activity were generated using field data and GIS techniques. Both catchments have homogeneous geology and only consist of Cretaceous granitic rock. Thus, bedrock geology was not considered in data layering during GIS analysis. Success rates were also estimated to evaluate the accuracy of landslide susceptibility maps and the weights-of-evidence modelling was found useful in landslide susceptibility mapping of small catchments.     

A polygon-based modeling approach to assess exposure of resources and assets to wildfire

Spatially explicit burn probability modeling is increasingly applied to assess wildfire risk and inform mitigation strategy development. Burn probabilities are typically expressed on a per-pixel basis, calculated as the number of times a pixel burns divided by the number of simulation iterations. Spatial intersection of highly valued resources and assets (HVRAs) with pixel-based burn probability estimates enables quantification of HVRA exposure to wildfire in terms of expected area burned. However, statistical expectations can mask variability in HVRA area burned across all simulated fires. We present an alternative, polygon-based formulation for deriving estimates of HVRA area burned. This effort enhances investigations into spatial patterns of fire occurrence and behavior by overlaying simulated fire perimeters with mapped HVRA polygons to estimate conditional distributions of HVRA area burned. This information can be especially useful for assessing risks where cumulative effects and the spatial pattern and extent of area burned influence HVRA response to fire. We illustrate our modeling approach and demonstrate application across real-world landscapes for two case studies: first, a comparative analysis of exposure and area burned across ten municipal watersheds on the Beaverhead-Deerlodge National Forest in Montana, USA, and second, fireshed delineation and exposure analysis of a geographically isolated and limited area of critical wildlife habitat on the Pike and San Isabel National Forests in Colorado, USA. We highlight how this information can be used to inform prioritization and mitigation decisions and can be used complementarily with more traditional pixel-based burn probability and fire intensity metrics in an expanded exposure analysis framework.     

西昌市经久乡森林火灾火烧区特点及火后泥石流易发性评价

2020年3月30日四川省凉山彝族自治州西昌市经久乡发生特大森林火灾,大火持续3 d,过火面积超30 km2。山火后在坡面堆积了厚度1~5 cm不等的灰烬层,同时火烧迹地本身结构被扰动,在强降雨条件下极易诱发火后泥石流灾害,对附近学校、居民集中居住点,尤其是泸山—邛海风景区等重要基础设施及人民生命财产构成了严重威胁。通过遥感解译、野外调查及勘查,查明了不同火烈度及对应火烧迹地灰烬层和结构扰动特点,表明重度、中度和轻度火烧区分别占比46.8%、37.9%和15.3%,且火烧区火烧迹地坡面灰烬及土壤结构扰动层平均厚度与火烈度成正比,其中轻度、中度和重度火烧区平均厚度分别为1.20 cm,3.23 cm和5.04 cm。提出了基于中度及重度火烈度区面积占比、火烧迹地坡面灰烬及结构扰动层厚度、产沙区平均坡度、主沟平均纵比降、沟道流域面积5个影响因子,采用专家经验法对火烧区共63条潜在泥石流沟道进行火后泥石流易发性评价,结果表明:火烧区所有沟道中,有29条为高易发,占总数的46.0%;23条为中等易发,占总数的36.5%;8条为低等易发,占总数的12.7%;3条为不易发性,占总数的4.8%。考虑火烧区超过50%以上的沟道流域面积不足0.2 km2,且这些沟道平均纵比降大,坡面灰烬、泥沙等松散物源堆积较厚,使得中等及高等易发性泥石流沟道数量占比高达82.5%,一遇集中降雨,发生火后泥石流可能性极大。     

大兴安岭西北坡火烧迹地湿地格局变化及其影响因子研究

选取大兴安岭1987年特大森林火灾主要过火区的图强林业局育英和奋斗两林场作为研究区,利用地理信息系统软件,对其火后湿地格局变化以及森林水文功能恢复状况进行了分析。结果显示,与过火前相比湿地面积增加了77.56%,且分布趋于集中;森林的平均水文调节能力已得到初步恢复,但具有较高调节能力的林地所占面积有所减少;森林的水文调节能力、地形因子以及火烧强度对湿地分布格局的变化均有明显影响。在森林水文调节功能下降地区、地势较低的谷地,坡度平缓的坡地以及火烧强度较大的地区,湿地面积增加明显。     

Modelling wind-erosion risk in the Laghouat region (Algeria) using geomatics approach

Wind-erosion risk is a challenge that threatens land development in dry-land regions. Soil analysis, remote sensing, climatic, vegetal cover and topographic data were used in a geographic information system (GIS), using multi-criteria analysis (MCA) to map wind-erosion risk (R_we) in Laghouat, Algeria. The approach was based on modelling the risk and incorporating topographic and climatic effects. The maps were coded according to their sensitivity to wind erosion and to their socio-economic potential, from low to very high. By overlapping the effects of these layers, qualitative maps were drawn to reflect the potential sensitivity to wind erosion per unit area. The results indicated that severe wind erosion affects mainly all the southern parts and some parts in the north of Laghouat, where wind-erosion hazard (H_we) is very high in 43% of the total area, and which was affected mainly by natural parameters such as soil, topography and wind. The results also identified features vulnerable to R_we. The product of the hazard and the stake maps indicated the potential risk areas that need preventive measures; this was more than half of the study area, making it essential to undertake environmental management and land-use planning.     

Integration of GIS,AHP and TOPSIS for earthquake hazard analysis

Worldwide, earthquakes and related disasters have persistently had severe negative impacts on human livelihoods and have caused widespread socioeconomic and environmental damage. The severity of these disasters has prompted recognition of the need for comprehensive and effective disaster and emergency management (DEM) efforts, which are required to plan, respond to and develop risk mitigation strategies. In this regard, recently developed methods, known as multi-criteria decision analysis (MCDA), have been widely used in DEM domains by emergency managers to greatly improve the quality of the decision-making process, making it more participatory, explicit, rational and efficient. In this study, MCDA techniques of the Analytical Hierarchical Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), integrated with GIS, were used to produce earthquake hazard and risk maps for earthquake disaster monitoring and analysis for a case study region of Küçükçekmece in Istanbul, Turkey. The five main criteria that have the strongest influence on the impact of earthquakes on the study region were determined: topography, distance to epicentre, soil classification, liquefaction and fault/focal mechanism. AHP was used to determine the weights of these parameters, which were also used as input into the TOPSIS method and GIS (ESRI ArcGIS) for simulating these outputs to produce earthquake hazard maps. The resulting earthquake hazard maps created by both the AHP and TOPSIS models were compared, showing high correlation and compatibility. To estimate the elements at risk, population and building data were used with the AHP and TOPSIS hazard maps for potential loss assessment; thus, we demonstrated the potential of integrating GIS with AHP and TOPSIS in generating hazard maps for effective earthquake disaster and risk management.     

GIS Techniques for Mapping Groundwater Contamination Risk

The groundwater contamination risk map of a samplealluvial area was produced by using the IlwisGeographical Information System (GIS) to construct andto overlay thematic maps. The risk map has beenderived from the vulnerability map, the hazard map,where the potential contaminating sources wereidentified, and the socio-economic value of thegroundwater resource, represented by the wells. Thegroundwater quality map allowed thereliability of hazard and risk maps to be tested.The final map shows interesting results and stressesthe need for the GIS to test and improve on thegroundwater contamination risk assessment methods.     

Risk assessment of water soil erosion in upper basin of Miyun Reservoir,Beijing, China

This research selected water soil erosion indicators (land cover, vegetation cover, slope) to assess the risk of soil erosion, ARCMAP GIS ver.9.0 environments and ERDAS ver.9.0 were used to manage and process satellite images and thematic tabular data. Landsat TM images in 2003 were used to produce land/cover maps of the study area based on visual interpreting method and derived vegetation cover maps, and the relief map at the scale of 1:50,000 to calculate the slope gradient maps. The area of water soil erosion was classified into six grades by an integration of slope gradients, land cover types, and vegetation cover fraction. All the data were integrated into a cross-tabular format to carry out the grid-based analysis of soil erosion risk. Results showed that the upper basin of Miyun Reservoir, in general, is exposed to a moderate risk of soil erosion, there is 715,848 ha of land suffered from water soil erosion in 2003, occupied 46.62% of total area, and most of the soil erosion area is on the slight and moderate risk, occupied 45.60 and 47.58% of soil erosion area, respectively.     

RETRACTED ARTICLE: Assessment of soil erosion using RUSLE and GIS: a case study of the Maotiao River watershed,Guizhou Province,China

Due to the existence of fragile karst geo-ecological environments, such as environments with extremely poor soil cover, low soil-forming velocity, and fragmentized terrain and physiognomy, as well as inappropriate and intensive land use, soil erosion is a serious problem in Guizhou Province, which is located in the centre of the karst areas of southwestern China; evaluation of soil loss and spatial distribution for conservation planning is urgently needed. This study integrated the revised universal soil loss equation (RUSLE) with a GIS to assess soil loss and identify risk erosion areas in the Maotiao River watershed of Guizhou. Current land use/cover and management practices were evaluated to determine their effects on average annual soil loss and future soil conservation practices were discussed. Data used to generate the RUSLE factors included a Landsat Thematic Mapper image (land cover), digitized topographic and soil maps, and precipitation data. The results of the study compare well with the other studies and local data, and provide useful information for decision makers and planners to take appropriate land management measures in the area. It thus indicates the RUSLE–GIS model is a useful tool for evaluating and mapping soil erosion quantitatively and spatially at a larger watershed scale in Guizhou.     

Soil erosion and sediment yield modeling using RS and GIS techniques: a case study, Iran

Water erosion is a serious and continuous environmental problem in many parts of the world. The need to quantify the amount of erosion, sediment delivery, and sediment yield in a spatially distributed form has become essential at the watershed scale and in the implementation of conservation efforts. In this study, an effort to predict potential annual soil loss and sediment yield is conducted by using the Revised Universal Soil Loss Equation (RUSLE) model with adaptation in a geographic information system (GIS). The rainfall erosivity, soil erosivity, slope length, steepness, plant cover, and management practice and conservation support practice factors are among the basic factors that are obtained from monthly and annual rainfall data, soil map of the region, 50-m digital elevation model, remote sensing (RS) techniques (with use of Normalized Difference Vegetation Index), and GIS, respectively. The Ilam dam watershed which is located southeast part of Ilam province in western Iran is considered as study area. The study indicates that the slope length and steepness of the RUSLE model are the most effective factors controlling soil erosion in the region. The mean annual soil loss and sediment yield are also predicted. Moreover, the results indicated that 45.25%, 12.18%, 12.44%, 10.79%, and 19.34% of the study area are under minimal, low, moderate, high, and extreme actual erosion risks, respectively. Since 30.13% of the region is under high and extreme erosion risk, adoption of suitable conservation measures seems to be inevitable. So, the RUSLE model integrated with RS and GIS techniques has a great potential for producing accurate and inexpensive erosion and sediment yield risk maps in Iran.     

四川省冕宁县华岩子沟火后泥石流成灾机理

以四川省冕宁县腊窝乡华岩子沟2019年7月发生的火后泥石流为典型案例,通过对火烧迹地现场地质勘察、降雨模拟试验研究了与火后泥石流形成相关的地形地貌、火行为分布、松散物源规模、产流产沙特征以及相应的灰烬层、斥水性、渗透性等相关试验。结果表明:（1）火烧迹地的斥水性强度越强,径流产流量越大;（2）严重火烧区的产沙量明显高于中度和轻度火烧区;（3）火烧迹地的斥水性与火烈度大致呈正相关,而渗透性恰好与之相反。研究揭示了火后泥石流的演变过程,为火后泥石流的防治和预警提供了理论依据。     

Landslide vulnerability and risk assessment for multi-hazard scenarios using airborne laser scanning data (LiDAR)

Landslide hazard, vulnerability, and risk-zoning maps are considered in the decision-making process that involves land use/land cover (LULC) planning in disaster-prone areas. The accuracy of these analyses is directly related to the quality of spatial data needed and methods employed to obtain such data. In this study, we produced a landslide inventory map that depicts 164 landslide locations using high-resolution airborne laser scanning data. The landslide inventory data were randomly divided into a training dataset: 70 % for training the models and 30 % for validation. In the initial step, a susceptibility map was developed using logistic regression approach in which weights were assigned to every conditioning factor. A high-resolution airborne laser scanning data (LiDAR) was used to derive the landslide conditioning factors for the spatial prediction of landslide hazard areas. The resultant susceptibility was validated using the area under the curve method. The validation result showed 86.22 and 84.87 % success and prediction rates, respectively. In the second stage, a landslide hazard map was produced using precipitation data for 15 years. The precipitation maps were subsequently prepared and show two main categories (two temporal probabilities) for the study area (the average for any day in a year and abnormal intensity recorded in any day for 15 years) and three return periods (15-, 10-, and 5-year periods). Hazard assessment was performed for the entire study area. In the third step, an element at risk map was prepared using LULC, which was considered in the vulnerability assessment. A vulnerability map was derived according to the following criteria: cost, time required for reconstruction, relative risk of landslide, risk to population, and general effect to certain damage. These criteria were applied only on the LULC of the study area because of lack of data on the population and building footprint and types. Finally, risk maps were produced using the derived vulnerability and hazard information. Thereafter, a risk analysis was conducted. The LULC map was cross-matched with the results of the hazard maps for the return period, and the losses were aggregated for the LULC. Then, the losses were calculated for the three return periods. The map of the risk areas may assist planners in overall landslide hazard management.