共查询到19条相似文献，搜索用时 609 毫秒
1.
基于国内现行的森林火险气象指数和单因子火险贡献度模型,以及逻辑回归模型和随机森林模型,在林火预报中引入微波遥感土壤水分信息,使用MCD14DL火点数据集和地面气象观测资料对广东省不同时间尺度的林火发生概率进行预测。结果表明：逻辑回归模型和随机森林模型构建的林火预测模型显著优于现行的森林火险气象指数和单因子火险贡献度模型,预测精度提升约20%。其中,随机森林模型对林火频数的解释程度最高（两者相关系数为0.476）。此外,加入微波土壤水分信息后,相较原有的基于气象要素的林火预测模型,2种机器学习模型的预测精度均略有提升,体现了表层土壤水分信息在林火预报中的重要性。研究可为高效提取对地观测信息,以改进华南地区不同时间尺度的林火预报工作提供参考。 相似文献
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中国不同气候区基于火险气象指数的火险概率模型 总被引：2，自引：0，他引：2
目前,森林火险气象指数被广泛用于世界多个国家和地区.本研究目的为,基于火险气象指数,在中国不同气候区建立火险概率模型.本文在中国4个气候区,使用1998-2007年的气象及火灾数据,以位置变量、月份、海拔、加拿大、美国及澳大利亚的气象火险指数、植被指数为自变量,建立了半参数化Logistic回归模型,分析各自变量与着火概率及大火发生概率之间的非线性关系.在不同区域,模型所选自变量组合不同,这与各气候区不同气象及植被状况有关.通过模型模拟数据和实际观测数据散点图、火险概率图、大面积火灾数量预报曲线图,分析了模型的预测能力.研究结果表明,在4个气候区,海拔和NDVI指数对着火概率影响显著.模拟可燃物含水量的气象火险指数由于反映出了植被的季节变化特征,在中国北部成为火险概率模型中的重要因子.模拟土壤有机层可燃物状况的火险气象指数在中国南部(东南、西南)成为火险概率模型的重要因子.在中国4个气候区,应用半参数化Logistic回归模型,可以有效模拟月时间尺度着火概率及大火发生概率,并为分析火险气象指数的预报能力提供了有效途径.本研究为进一步分析气候与火险之间的动态关系提供了理论基础. 相似文献
3.
建立对黔南气象灾害历史数据库并应用GIS技术进行灾害区划,根据数学模型计算得到的重大灾害重现期指标,构建黔南城镇化建设中气象灾害影响的决策建议平台.用针对不同区域研究得到的气象灾害预警阈值,来自动过滤系统调取的区域自动气象站实时要素数据,同时结合提取的雷达回波和数值预报等气象预报指标,完成系统对各乡镇和重点区域的实时气象灾害监测预警. 相似文献
4.
玉溪滑坡泥石流与降水关系及气象预警预报研究 总被引：3，自引：1，他引：2
应用玉溪市的乡镇加密雨量站,分析2004-2006年不同地质结构山体滑坡泥石流与降水的关系.提出乡镇雨量点在气象地质灾害中三站平均雨量应用方法,重点分析了触发滑坡泥石流的降水类型、降水强度和地质结构.得出不同地质结构和降水条件下的滑坡泥石流等级预报指标,结合降水预报和实况降水的基础上建立玉溪市山体滑坡气象预警预报等级.2007年度试运行中准确率达83.3%,在气象防灾减灾中取得了突出成绩. 相似文献
5.
比较各地城市火险气象预报因子、方法和等级标准,选取普遍采用的5个气象因子;日最小相对湿度、连续无降水日数对城市火险的贡献最大,指数范围分别为0～40和0～30,日最高温度、日最大风力0～20,日降水量0～-20,综合指数范围一般为0～100进行等间隔划分,得到从低到高5级城市火险气象等级标准.通过两项试验来优化等级划分效果:1)从北到南选取5个城市,比较上述方法与各地方法计算的2001年1、4、7、10月逐日火险等级,经过反复调试,使两套方法计算的等级完全一致和相差一级合计在85%以上;2)统计全国31个中心城市2000～2003年逐日城市火险气象等级5级分布的概率,使之基本符合正态分布.从而得到各气象因子的划分范围、对应城市火险气象指数值以及综合城市火险气象等级标准,给出相应名称和指示意义. 相似文献
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7.
降水精细化数值预报模式的发展是开展精细化降水预报业务的理想途径,而模式本地化中的误差评估是当前开展业务应用的重要环节。基于此,运用误差分析、晴雨预报准确率、降水TS评分方法评估陕西精细化数值预报攻关团队提供的2016年5月1日~9月30日安康水电站降水预报。结果表明：随着降水时效的增长,降水的预报准确率呈减小趋势;大雨以上的降水过程预报较好且未出现漏报,但量值与实况有差异,预报值小于实况值;20时起报的预报准确率大于08时起报的准确率且夜间的高于白天;降水日数多的月份TS评分预报准确率高于降水日数少的月份。比较安康和石泉的结果发现,安康的预报准确率明显优于石泉,主要原因是安康降水日数比石泉多,且大的降水过程比石泉少。逐1 h、3 h的72 h以内的降水预报可以为安康水电厂水利调度提供参考。 相似文献
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采用ECMWF数值预报产品资料,首先用PP法和MOS方法建立溪洛渡水电站坝区三坪站气温预报逐步回归方程,寻找消空（漏）指标进行预报后处理,然后根据000～168时效的ECMWF数值预报产品资料制作未来24～144 h三坪站的最高、最低、平均气温预报。并研制出能自动运行的预报业务系统。2011年业务运行效果检验评估表明：系统预报效果较稳定,6 d平均、最高、最低气温平均预报准确率分别为70.8%、62.7%和76.0%,在水电气象预报服务中短期气温预报实时业务中有较好的指导作用。平均、最高、最低气温准确率随着预报时效的延长效果降低,平均气温和最低气温比最高气温的预报准确率高。预报方法对制作单站气温预报是可行的。 相似文献
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利用河西走廊伏旱和伏期降水资料序列,张掖观象台的地面气温、降水、探空等气象资料,以及国家气候中心提供的74个环流因子,借助BP神经网络可以逼近任意非线性函数的能力和特点,构建了一个用于预测伏旱和伏期降水的模型,并对模型的预报效果进行验证。结果表明:BP神经网络模型能够对伏期干旱进行有效地预测,该预测模型对伏旱和伏期降水有比较理想的预报效果,伏旱预报历史拟合率高达97.6%、模型试报准确率为84.6%,伏期降水预测历史拟合率高达97.6%、模型试报准确率为76.9%,其性能指标符合实际要求,具有很好的实际应用价值。 相似文献
10.
区域和沟谷相结合的泥石流预报及其应用 总被引：10，自引：1，他引：10
在分析泥石流预报现状和泥石流减灾决策对泥石流预报的要求的基础上,提出了建立区域和单沟相结合的泥石流预报的问题。以泥石流发育的基础数据库、降水的动态预报与监测和泥石流预报模型为基础,以GIS技术为工具,建立泥石流预报平台。泥石流预报模型采用基于模糊数学的泥石流预报模型,预报结果应用概率分级进行表述,以适应泥石流预报准确率低的不足,并最大程度地克服了过分依赖临界降水量进行泥石流预报的不足。将该泥石流预报方法应用到北京山区泥石流预报中,建立了北京山区泥石流预报系统。 相似文献
11.
遥感、地图和地理信息系统（ＯＩＳ）三者呈“你中有我，我中有你”的相辅相成关系．三者一体化应用使地球科学得以进展，又能在资源开发、环境保护、自然灾害监测评价等方面发挥重要作用．一体化应用的基础是掌握三者的学科一技术特性与相通关系． 相似文献
12.
A.C. Teodoro L. Duarte 《International journal of geographical information science》2013,27(4):699-720
Forest fires are widely recognized as one of the most critical events in global change. Successful fire management depends on effective fire prevention, detection, and presuppression, having an adequate fire suppression capability, and consideration of fire ecology relationships. Geographical information systems (GIS) provide tools to create, transform, and combine georeferenced variables. In Portugal, as in many other countries, it is mandatory that all the municipalities produce forest fire risk maps on an annual basis, following the rules of the Portuguese Forest Authority, a governmental association. This article presents the results of a research project aimed at producing forest fire risk maps in a GIS open source environment in Portugal. The requirements of an open source application are better quality, higher reliability, more flexibility, lower cost, and an end to predatory vendor lock-in. Three different open source desktop GIS software projects were evaluated: Quantum GIS (QGIS), generalitat valenciana, Sistema d'Informacio Geografica, and Kosmo. Taking into account the skills and experience of the authors, the main advantage of QGIS relies on the easiness and quickness in developing new plug-ins, using Python language. Therefore, this project was developed in QGIS platform and the interface was created in Python. This application incorporates seven procedures under a single toolbar. The production of the forest fire risk map comprises several steps and the production of several maps: probability, susceptibility, hazard, vulnerability, economic value, potential loss, and finally the forest fire risk map. The forest fire risk map comprises five classes: very low risk (dark green), low risk (green), medium risk (yellow), high risk (orange), and very high risk (red). This application was tested in three different municipal governments of the Norwest zone of Portugal. This application has the advantages of grouping in a unique toolbar all the procedures needed to produce forest fire risk maps and is free for the institution/user. Beyond being an open source application, this application may be faster and easier when compared with the GIS proprietary solutions that usually comprise several steps and the use of different software extensions. This work presents several contributions for the area of the GIS open source applications to forest fire risk management. 相似文献
13.
森林火灾能对森林资源造成巨大的危害,因此发现林区火源并进行科学决策具有重要意义.本系统数据主要包括1∶1万地形图、1∶1万森林资源二类调查数据、扑火队分布数据、瞭望台站数据、扑火物资储备数据、林业局管理机构分布数据、研究区2010年landsat TM遥感影像图等;系统功能主要包括数据的处理和管理、森林火灾监测、最佳扑火路径分析、防火扑火预案制定和决策、森林火险等级评价、林火趋势模拟和预测、灾害损失评估、相关图表和报告制作等.系统采用Microsoft Visual Studio 2005(C#)作为开发语言,基于Arc Engine 9.3组件进行二次开发,三维地图显示采用skyline Terra Explorer开发平台,数据库采用SQL Server 2005数据库管理系统,利用Arc SDE 9.3空间数据库引擎对空间数据进行管理. 相似文献
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Tomàs Artés Andrés Cencerrado Ana Cortés Tomàs Margalef 《International journal of geographical information science》2016,30(3):594-611
AbstractForest fires are a kind of natural hazard with a high number of occurrences in southern European countries. To avoid major damages and to improve forest fire management, one can use forest fire spread simulators to predict fire behavior. When providing forest fire predictions, there are two main considerations: accuracy and computation time. In the context of natural hazards simulation, it is well known that part of the final forecast error comes from uncertainty in the input data. These data typically consist of a set of GIS files, which should be appropriately conflated. For this reason, several input data calibration methods have been developed by the scientific community. In this work, the Two-Stage calibration methodology, which has been shown to provide good results, is used. This calibration strategy is computationally intensive and time-consuming because it uses a Genetic Algorithm as a solution. Taking into account the aspect of urgency in forest fire spread prediction, it is necessary to maintain a balance between accuracy and the time needed to calibrate the input parameters. In order to take advantage of this technique, one must deal with the problem that some of the obtained solutions are impractical, since they involve simulation times that are too long, preventing the prediction system from being deployed at an operational level. A new method which finds the minimum resolution reduction for such long simulations, keeping accuracy loss to a known interval, is proposed. The proposed improvement is based on a time-aware core allocation policy that enables real-time forest fire spread forecasting. The final prediction system is a cyberinfrastructure, which enables forest fire spread prediction at real time. 相似文献
15.
Sanjay K. Srivastava Sameer Saran Rolf A. de By V. K. Dadhwal 《International journal of geographical information science》2014,28(3):427-454
Innumerable forest fire spread models exist for taking a decision, but far less focus is on the real causative factors which initiate/ignite fire in an area. It has been observed that the majority of the forest fires in India are initiated due to anthropogenic factors. In this study, we develop a geo-information system approach for management of forest fire in Mudumalai Wildlife Sanctuary, Tamil Nadu, India, with the objective to develop a forest fire likelihood model, integrating GIS and knowledge-based approach for predicting fire-sensitive initiation areas considering major causative and anti-causative factors. Amongst the various causative factors investigated, it was found that wildlife-dependent factor (antler collection and poaching) contributed significantly to fire occurrence followed by management-dependent factors (uncontrolled tourism and grazing), with much less influence of demographic factors. Similarly, anti-causative factor (stationing of anti-poaching/ fire camps) was considered as quite significant.
The likelihood model so developed, envisaging various factors and flammability, accounted for different scenarios as a result of pair-wise comparison on an ordinal scale in a knowledge matrix. The inferential statistics computed indicated the robustness of the model and its insensitivity to moderate changes. It makes it possible for this forest fire likelihood model to predict and prevent a forest fire in an effective and scientific manner because it can assume forest fire likelihood in real time and present in proper time. 相似文献
16.
Deforestation and forest degradation are proceeding rapidly in the lowland forests of Indonesian Borneo. Time series analysis of satellite imagery provides an ideal means of quantifying landscape change and identifying the pathways which lead to the changes. This study investigates the forest and land cover changes by classifying Landsat MSS (Multispectral Scanner), TM (Thematic Mapper) and ETM+ (Enhanced Thematic Mapper Plus) images over three time periods (1983–90, 1990–98, and 1998–2000), creating land cover maps for each year and change trajectories for each year-pair. The study area chosen covers an area of 2160 km2 of undulating topography and alluvial plains in the East Kutai District of East Kalimantan Province, which in the 1980s was covered mostly with lowland dipterocarp forest; today the landscape is a patchwork dominated by oil palm and timber plantations and degraded forest. We relate land cover change data to land use allocation and to fire impacts based on fire hotspot distribution and fire damage information. The multidate land cover change trajectories provide an insight into the forest loss and degradation pathways over the 17-year period spanning the first entry of commercial logging concessionaires, followed by a government-sponsored transmigration scheme, government-licensed timber and oil palm plantations and, finally, the devastating fires of 1998. The results show a mean deforestation rate of 42 km2 or 6 per cent per year for 1983–2000, rising to 10 per cent per year for 1990–98; by 2000, 70 per cent of forest initially damaged by fire and drought during the 1982–83 El Niño event was classified as non-forest. Although our study area is perhaps a worst-case scenario in terms of land use planning outcomes, the lessons from this research are directly applicable to scenario prediction for informed forest and land use planning and monitoring. 相似文献
17.
四川省林草火险等级评价 总被引：1，自引：0，他引：1
把四川建设成为长江上游生态屏障是四川省的一项重大战略决策。森林和草地资源防火是生态屏障和生态安全保障体系建设的重要内容。林草火险等级的评价对森林和草地资源的防火具有重要的意义。本文利用遥感、GIS和层次分析法对四川省林草火险等级进行了评价。研究表明,就全省而言,火险等级为5级的占0.8%,为4级的占20.2%,为3级的占47.2%;极高火险区主要出现在甘孜州、凉山州、阿坝州、攀枝花市和雅安市,其所占面积百分比分别为49.2%、24.7%、15.7%、3.5%和3.4%;高火险区主要出现在甘孜州、凉山州和阿坝州,其所占面积百分比共达到了72.1%。建议将甘孜州、凉山州、阿坝州、攀枝花以及雅安市作为四川省林草防火的重点区域,在防火的人、财、物上给予优先考虑。 相似文献
18.
KRISHNA PRASAD VADREVU 《Geografiska Annaler: Series A, Physical Geography》2008,90(4):315-328
Vegetation fires are one of the most serious environmental problems in several ecoregions of India. The purpose of this study is to characterize spatio‐temporal characteristics of fire events in Orissa state, eastern India. In this study, ATSR satellite remote sensing data have been used to quantify fire events from 1997 to 2006. The spatial scan statistic that quantifies ‘hotspot’ areas of fire risk has been used to identify statistically significant fire clusters during the ten‐year time period. To assess the causative factors of fires, topographic, vegetation, climatic, anthropogenic and accessibility factors were used in a robust multivariate statistical framework. Results suggested a clear variation in hotspots of fire occurrences among districts. Of the several districts, the most likely cluster of fire events has been identified in Jharsuguda district followed by secondary clusters in Gajapati, Phulbani, Anugul, Debagarh, Balangir and Raygada. The first three principal components (PCs) from multivariate statistical analysis could explain 70.48% of variance in biophysical and socio‐economic indicators of fire events. The loadings were fairly large and highly positive for deciduous forest percentage, elevation, slope mean, aspect mean, and rural population density in the first PC explaining 40.21% of variance. The second PC included drought index, average temperature and illiteracy explaining nearly 19.2% variance. The third PC had a strong positive association with cropped area and forest cover explaining 10.98% of the total variance. Overall, by quantifying the disparities in fire events in space and time, this study demonstrates the utility of the spatial scan statistic in identifying priority areas of fire risk. Our results on fire hotspots and causative factors of risk can guide forest managers toward the best management strategies for avoiding damage to forests, human life, and personal property in the study area. 相似文献
19.
Kostas Kalabokidis Nikolaos Athanasis Christos Vasilakos Palaiologos Palaiologou 《International journal of geographical information science》2014,28(3):541-552
Effective wildfire management is an essential part of forest firefighting strategies to minimize damage to land resources and loss of human lives. Wildfire management tools often require a large number of computing resources at a specific time. Such computing resources are not affordable to local fire agencies because of the extreme upfront costs on hardware and software. The emerging cloud computing technology can be a cost- and result-effective alternative. The purpose of this paper is to present the development and the implementation of a state-of-the-art application running in cloud computing, composed of a wildfire risk and a wildfire spread simulation service. The two above applications are delivered within a web-based interactive platform to the fire management agencies as Software as a Service (SaaS). The wildfire risk service calculates and provides daily to the end-user maps of the hourly forecasted fire risk for the next 112 hours in high spatiotemporal resolution, based on forecasted meteorological data. In addition, actual fire risk is calculated hourly, based on meteorological conditions provided by remote automatic weather stations. Regarding the wildfire behavior simulation service, end users can simulate the fire spread by simply providing the ignition point and the projected duration of the fire, based on the HFire algorithm. The efficiency of the proposed solution is based on the flexibility to scale up or down the number of computing nodes needed for the requested processing. In this context, end users will be charged only for their consumed processing time and only during the actual wildfire confrontation period. The system utilizes both commercial and open source cloud resources. The current prototype is applied in the study area of Lesvos Island, Greece, but its flexibility enables expansion in different geographical areas. 相似文献