• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.11 no.6
• /
• pp.703-710
• /
• 2018

Although various efforts have been made every year to reduce electric fire accidents such as accident analysis and inspection for electric fire accidents, there is no effective countermeasure due to lack of effective decision support system and existing cumulative data utilization method. The purpose of this study is to develop an algorithm for predicting electric fire based on data such as electric safety inspection data, electric fire accident information, building information, and weather information. Through the pre-processing of collected data for each institution such as Korea Electrical Safety Corporation, Meteorological Administration, Ministry of Land, Infrastructure, and Transport, Fire Defense Headquarters, convergence, analysis, modeling, and verification process, we derive the factors influencing electric fire and develop prediction models. The results showed insulation resistance value, humidity, wind speed, building deterioration(aging), floor space ratio, building coverage ratio and building use. The accuracy of prediction model using random forest algorithm was 74.7%.

• Journal of Korean Society for Geospatial Information Science
• /
• v.19 no.1
• /
• pp.87-96
• /
• 2011

Carbon emissions and storages that are strongly related to global warming has have emerged as one of the important issues while many governments and researchers have been interested in climate change and pollution. In this regards, forest biomass estimation is quite importance since forest biomass works as an important medium of the global carbon cycle between the atmosphere and soil. Forest biomass estimation through field survey needs lots of time and labors, and has accessibility issues. Hence, many researchers have focused on the forest biomass approaches based on remotely sensed data. This research comprehensively reviewed forty one international studies using remote sensing data according to five different categories (i.e., location of study area, size of study area, biome, used remote sensing data, and estimation technology). It would be expected that the results of this study can be used for suggesting domestic research directions; domestic research in this field is at the beginning stage in terms of level of technologies and useful materials. As results, 39% out of the reviewed studies used the areas located in North America. 59% out of the researches dealt with small size of the study areas (less than 3,600km2). In case of biome, around 30% of the studies focused on the boreal/taiga areas. Moreover, 35% and 16% of the studies were carried out using Landsat series and Lidar data, respectively. Finally, regression analysis method was most frequently used for forest biomass estimation by 71% out of 41 studies.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.26 no.2
• /
• pp.55-67
• /
• 2023

This study aims to develop a model that can automatically identify the rooftop shape of apartment buildings using GIS and machine learning algorithms, and apply it to analyze the relationship between rooftop shape and characteristics of apartment complexes. A database of rooftop data for each building in an apartment complex was constructed using geospatial data, and individual buildings within each complex were classified into flat type, tower type, and mixed types using the random forest algorithm. In addition, the relationship between the proportion of rooftop shapes, development density, height, and other characteristics of apartment complexes was analyzed to propose the potential application of geospatial information in the real estate field. This study is expected to serve as a basic research on AI-based building type classification and to be utilized in various spatial and real estate analyses.

• Journal of Korean Society for Geospatial Information Science
• /
• v.21 no.4
• /
• pp.83-93
• /
• 2013

Land Suitability Assessment can help to evaluate whether to preserve or to develop through analysis of various land characteristics. So, the evaluation index and method are very important for making the best result. The principle objective of this dissertation is to identify effective method that can make up for the distortion of land suitability value in the forest bordering the management area. The objective area of this study is comparative flat Jeungpyeong-gun. The procedures of the study are as follows. First, implement land suitability assessment as the normal index on Guideline. Second, verify land suitability grade about the forest bordering the management area. The third, redo land suitability assessment as two alternative index on $^*$Guideline. The fourth, identify effective method between normal index and alternative index. The results of this tests show that the development suitability value is higher than preservation suitability value in the forest bordering the management area near existing development area. For that reason, this study needed to use substitution index in order to make up for the weakness. The level of land price and distance from road were main considerations. Finally, the derivative model is as follows. The derivative model confirmed the best assessment method in the forest bordering the management area near existing development area.

• Journal of Korean Society for Geospatial Information Science
• /
• v.19 no.1
• /
• pp.29-36
• /
• 2011

The main purpose of this paper is to make a map showing canopy cover by using airborne Lidar data based on region. Watershed algorithm was applied to elevation data to conduct segmentation, and then canopy cover was estimated through the regions extracted. In the process of transforming point data to raster, we solved the problems about overestimation and underestimation by using frequency method. Also, canopy cover map could be produced with various scales by differing level of segmentation and it provides more accurate and precise information than ones of ordinary public forest map.

• Journal of Korean Society for Geospatial Information Science
• /
• v.1 no.2 s.2
• /
• pp.159-166
• /
• 1993

Decrease of forest is seriously caused by urbanization. Photographic interpretation is the act of examining photographic images for the purpose of identifying objects and judging their significance. A systematic study of aerial photographs usually involves a consideration of the basic characteristics of photographic images. Seven of these characteristics are shape, size, pattern, shadow, tone, texture, and site. Aerial photographs contain a detailed record of the ground at the time of exposure. Authors blow the changes of natural environment by database for interpretation of aerial photo. In this paper, authors choose the Pusan National University located at the Kum-Joung Koo, Pusan as model area. Ten year of interval in 1980 and 1990, authors know the rate of forest decreasing is approximately 41 percents and the necessity of the protection of foreast. Authors suggest the combination of construction and protection of environment.

• Journal of Korean Society for Geospatial Information Science
• /
• v.15 no.3
• /
• pp.69-76
• /
• 2007

Kangwondo area is mountainous and landslide is easily happened easily during the rainy period in summer time. Especially, when there is torrential downpour caused by the unusual weather change, there will be greater possibility to see landslide. Another reason behind landslide is the continuous forest fire in these several years. Since the surface of the earth has been changed by the fire, when rainfall comes, landslide just happens easily. Also, it is reported that landcover condition, excepted rainfall condition, is the most effect for determining landslide susceptibility area. In this study, it is determined a landslide vulnerable area and landcover information is extracted from four satellite image(Landsat TM), about the landslide vulnerable area, which is pictured for each year. And which distribution change is analyzed. also, NDVI picture is made and distribution change of vegetation vitality is analyzed to study that change of landcover have a effect on landslide. As a result, could know that forest and NDVI are decreasing in landslide vulnerable area.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.13 no.1
• /
• pp.35-40
• /
• 2011

While high-definition precipitation maps with a 270 m spatial resolution are available for South Korea, there is little information on geospatial availability of precipitation water for the famine - plagued North Korea. The restricted data access and sparse observations prohibit application of the widely used PRISM (Parameter-elevation Regressions on Independent Slopes Model) to North Korea for fine-resolution mapping of precipitation. A hybrid method which complements the PRISM grid with a sub-grid scale elevation function is suggested to estimate precipitation for remote areas with little data such as North Korea. The fine scale elevation - precipitation regressions for four sloping aspects were derived from 546 observation points in South Korea. A 'virtual' elevation surface at a 270 m grid spacing was generated by inverse distance weighed averaging of the station elevations of 78 KMA (Korea Meteorological Administration) synoptic stations. A 'real' elevation surface made up from both 78 synoptic and 468 automated weather stations (AWS) was also generated and subtracted from the virtual surface to get elevation difference at each point. The same procedure was done for monthly precipitation to get the precipitation difference at each point. A regression analysis was applied to derive the aspect - specific coefficient of precipitation change with a unit increase in elevation. The elevation difference between 'virtual' and 'real' surface was calculated for each 270m grid points across North Korea and the regression coefficients were applied to obtain the precipitation corrections for the PRISM grid. The correction terms are now added to the PRISM generated low resolution (~2.4 km) precipitation map to produce the 270 m high resolution map compatible with those available for South Korea. According to the final product, the spatial average precipitation for entire territory of North Korea is 1,196 mm for a climatological normal year (1971-2000) with standard deviation of 298 mm.

• Journal of Digital Convergence
• /
• v.18 no.11
• /
• pp.427-432
• /
• 2020

In order to establish an effective forest management plan, it is necessary to investigate tree management information such as tree height and DBH(Diameter at breast height). However, research on convergence and application of data acquisition technology to improve the efficiency of existing forest survey methods is insufficient. Therefore, in this study, tree management information was constructed and analyzed using point cloud data acquired through a 3D scanner. Data on the study site was acquired using fixed and mobile 3D scanners, and the efficiency of the mobile 3D scanner was presented through comparison of working hours. In addition, tree management information for object management was constructed by classifying vegetation by object using point cloud data, and by constructing information on chest height diameter and height. As a result of the accuracy evaluation compared with the conventional measurement method, the difference in tree height was 0.02-0.09m and DBH was 0.01-0.04m. If information on the location of vegetation and crowns of each object is constructed through additional research in the future, the efficiency of the work related to forest management information construction can be greatly increased.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.21 no.3
• /
• pp.146-157
• /
• 2019

One of the most distinctive features of the South Korean rural environment is that the variation of weather or climate is large even within a small area due to complex terrains. The Geospatial Schemes based on Topo-Climatology (GSTP) was developed to simulate such variations effectively. In the present study, we reviewed the progress of the geospatial schemes for production of farm-scale agricultural weather data. Efforts have been made to improve the GSTP since 2000s. The schemes were used to provide climate information based on the current normal year and future climate scenarios at a landscape scale. The digital climate maps for the normal year include the maps of the monthly minimum temperature, maximum temperature, precipitation, and solar radiation in the past 30 years at 30 m or 270 m spatial resolution. Based on these digital climate maps, future climate change scenario maps were also produced at the high spatial resolution. These maps have been used for climate change impact assessment at the field scale by reprocessing them and transforming them into various forms. In the 2010s, the GSTP model was used to produce information for farm-specific weather conditions and weather forecast data on a landscape scale. The microclimate models of which the GSTP model consists have been improved to provide detailed weather condition data based on daily weather observation data in recent development. Using such daily data, the Early warning service for agrometeorological hazard has been developed to provide weather forecasts in real-time by processing a digital forecast and mid-term weather forecast data (KMA) at 30 m spatial resolution. Currently, daily minimum temperature, maximum temperature, precipitation, solar radiation quantity, and the duration of sunshine are forecasted as detailed weather conditions and forecast information. Moreover, based on farm-specific past-current-future weather information, growth information for various crops and agrometeorological disaster forecasts have been produced.