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문제 정의
- Efficient tools for extracting information from geo-spatial data generate and manage large geo-spatial data sets. The focus of this work can be of importance to the organization which own large geo-spatial data sets. Data mining products can be a useful tool in decision-making and planning just as they are cur- rently in the business world.
제안 방법
- forest fire hazardous area. And then, predictive power of each model has been evaluated, after carrying out cross validation between the models. Next, forest fire hazardous areas have been mapped using the most effective model.
- The geographic database sets for fire ignition prediction analysis were described in section 4. In first, an analysis of the rela tionship of each individual independent attribute with the response attribute was performed to get an idea of the rela tive importance of each attribute in explaining fire ignition. The results of the analysis of relevance of each independent attribute for the data sets corresponding to fire ignition is that forest type, elevation, slope, road networks, farm and building boundaries thematic maps have significant attri butes in the data set corresponding to fire ignition.
- The organization which make decisi ons based on large spatial data sets spreads across many domains including ecology and environmental management, public safety, transportation, public health and business. In this study, we focused on the application domain of forest fire prevention where forestry managers are interested in finding spatio-temporal distribution of forest fires and pre dicting forest fire hazardous areas from large spatial/non- spatial data sets such as forest maps, topography maps and fire history data. Forest fire provides a good example to stu dy spatio-temporal representations for GIS applications be cause of its spatio-temporal variability.
- spatial data sets. In this study, we proposed and applied two prediction models for spatial data mining based on spa tial statistics. These are conditional probability and like^ lihood ratio methods.
- We show that, by analyzing historical data on fire ignition point locations, we can gain the necessary predictive capa bility, making it possible to quantify ignition probability in space. The analysis is performed using inductive approaches in a raster geographic information system (GIS), and it ex plores the information contained in the spatial attributes of the phenomenon.
- The forest fire hazardous area prediction model described in this paper provided an effective method for estimation of the degree of forest fire hazard. It is based upon the forestry, topography, human activity attributes, which contribute to fire hazard and risk.
- that year. The occurrences play s pivotal role in construc ting prediction models by establishing probabilistic r이ation- ships between the pre-1996 forest fires and the remainder of the input data set. The predictions based on those rela tionships were then evaluated by comparing the estimated hazard classes with the distribution of the forest fire ignition locations that had occurred after 1996, i.
- The occurrences play s pivotal role in construc ting prediction models by establishing probabilistic r이ation- ships between the pre-1996 forest fires and the remainder of the input data set. The predictions based on those rela tionships were then evaluated by comparing the estimated hazard classes with the distribution of the forest fire ignition locations that had occurred after 1996, i.e., during the period 1997 to 2001.
- The proposed model for prediction of forest fire hazardous area would be helpful to increase the efficiency of forest fire management such as prevention of forest fire occurrence and effective placement of forest fire monitoring equipment and manpower. The ability to quantify ignition risk can be the key to a more informed allocation of fire prevention resour ces.
- To make forest fire hazardous area map using the two proposed methods and evaluate the performance of predic tion power, we applied a FHR (Forest Fire Hazard Rate) and a PRC (Prediction Rate Curve) respectively. The FHR for each prediction models was calculated by formula described in section 4.
- In these approaches, the prediction mo dels and estimation procedures are depending on the basic quantitative relationships of spatial data sets relevant forest fire with respect to selected the past forest fire ignition areas. To m아ce forest fire hazardous area map using the two pro posed methods and evaluate the performance of prediction power, we applied a FHR (Forest Fire Hazard Rate) and a PRC (Prediction Rate Curve) respectively.
대상 데이터
- A key element in the forest fire hazardous area prediction modeling is a forest fire hazard model, which estimates the fire hazard potential based upon forest attributes, forest utilization, and topography. In this study, a forest fire risk prediction model using pre dictive spatial data mining is developed to a forest in the Youngdong region of Kangwon province, Republic of Korea. We show that, by analyzing historical data on fire ignition point locations, we can gain the necessary predictive capa bility, making it possible to quantify ignition probability in space.
- The study area to predict forest fire hazardous area is Sam- chok city. The largest forest fire in modem history of Korea occurred in April, 2000 in Samchok city, eastern Korea (Fi gure 3).
성능/효과
- We have found out the multiple thematic maps emerged as affective to forest fire occurrence are el evation, slope, forest type, road network, farm and habitat zone condition. The effectiveness of the models estimated and tested and showed acceptable degree of goodness. The proposed model developed would be helpful to increase the efficiency of forest fire management such as detection of for est fire occurrence and effective disposition of forest fire prevention resources.
- In first, an analysis of the rela tionship of each individual independent attribute with the response attribute was performed to get an idea of the rela tive importance of each attribute in explaining fire ignition. The results of the analysis of relevance of each independent attribute for the data sets corresponding to fire ignition is that forest type, elevation, slope, road networks, farm and building boundaries thematic maps have significant attri butes in the data set corresponding to fire ignition. However, tree diameter, density, ages and aspect maps have the less significant attributes in the data set.
후속연구
- The effectiveness of the models estimated and tested and showed acceptable degree of goodness. The proposed model developed would be helpful to increase the efficiency of forest fire management such as detection of for est fire occurrence and effective disposition of forest fire prevention resources.
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