• Proceedings of the National Institute of Ecology of the Republic of Korea
• /
• v.2 no.1
• /
• pp.1-14
• /
• 2021

The study has been carried out with an objective to prepare Siberian roe deer habitat potential maps in South Korea based on three geographic information system-based models including frequency ratio (FR) as a bivariate statistical approach as well as convolutional neural network (CNN) and long short-term memory (LSTM) as machine learning algorithms. According to field observations, 741 locations were reported as roe deer's habitat preferences. The dataset were divided with a proportion of 70:30 for constructing models and validation purposes. Through FR model, a total of 10 influential factors were opted for the modelling process, namely altitude, valley depth, slope height, topographic position index (TPI), topographic wetness index (TWI), normalized difference water index, drainage density, road density, radar intensity, and morphological feature. The results of variable importance analysis determined that TPI, TWI, altitude and valley depth have higher impact on predicting. Furthermore, the area under the receiver operating characteristic (ROC) curve was applied to assess the prediction accuracies of three models. The results showed that all the models almost have similar performances, but LSTM model had relatively higher prediction ability in comparison to FR and CNN models with the accuracy of 76% and 73% during the training and validation process. The obtained map of LSTM model was categorized into five classes of potentiality including very low, low, moderate, high and very high with proportions of 19.70%, 19.81%, 19.31%, 19.86%, and 21.31%, respectively. The resultant potential maps may be valuable to monitor and preserve the Siberian roe deer habitats.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2018.05a
• /
• pp.427-427
• /
• 2018

최근 집중호우나 극한 강우사상으로 인하여 산사태나 토석류와 같은 산지재해가 빈번하게 발생하고 있으며 특히 우리나라는 지형 특성상 주거지역이 산지와 인접해 있는 경우가 많아 재해발생 시 피해를 가중시키는 원인이 되고 있다. 산지재해는 예측하기가 어렵고 산지에서 발생한 토석류가 계곡을 따라 흘러 내려와 도심지 및 산지와 인접한 도로나 주택지에 많은 피해를 발생 시키고 있다. 본 연구에서는 해마다 반복적으로 발생하고 있는 산사태나 토석류와 같은 재해의 피해저감과 원인분석을 위하여 강원도 삼척시 도계읍 일대를 대상지역으로 선정하고 산지유역의 위험성 분석을 위하여 사면안정성 예측 모델인 SINMAP 모형을 사용하여 산지재해가 발생 가능한 위험지역 및 안전한 구간을 분석하고 지형분류기법 중의 하나인 Topographic Position Index(TPI) 분석방법을 통해 대상지역의 지형위치지수를 계산하여 위험지형을 분류하였다.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.19 no.4
• /
• pp.76-91
• /
• 2016

The purpose of this study is to analyze the effects of spatial characteristics, such as land cover and topography, on heat wave days from the city of Milyang, which has recently drawn attention for its heat wave problems. The number of heat wave days was calculated utilizing RCP-based South Korea climate data from 2000 to 2010. Land cover types were reclassified into urban area, agricultural area, forest area, water, and grassland using 2000, 2005, and 2010 land cover data constructed by the Ministry of Environment. Topographical features were analyzed by topographic position index (TPI) using a digital elevation model (DEM) with 30 m spatial resolution. The results show that the number of heat wave days was 31.4 days in 2000, which was the highest, followed by 26.9 days in 2008, 24.2 days in 2001, and 24.0 days in 2010. The heat wave distribution was relatively higher in agricultural areas, valleys, and rural areas. The topography of Milyang contains more mountainous slope (51.6%) than flat (19.7%), while large-scale valleys (12.2%) are distributed across some of the western region. Correlation analysis between heat wave and spatial characteristics showed that the correlation between forest area land cover and number of heat wave days was negative (-0.109), indicating that heat wave can be mitigated. Topographically, flat areas and heat wave showed a positive correlation (0.305). These results provide important insights for urban planning and environmental management for understanding the impact of land development and topographic change on heat wave.

• Journal of Korean Society of Forest Science
• /
• v.90 no.4
• /
• pp.465-475
• /
• 2001

Based on the community structural attributes, such as species composition, diameter and height distribution, topographic position, and species diversity in the natural deciduous forest of Mt. Gari area, this study suggested desirable species and composition ratio to achieve ecological management of forests so as to maintain forest stability and enhance economical values. The results are as follows : 1. Twenty-five tree species were growing in the study forest. Of these Quercus mongolica, Pinus densiflora, Juglans mandshurica, Quercus serrata, Cornus controversa, Acer mono, Fraxinus rhynchophylla, and Tilia mandshurica were selected for desirable species through the evaluation of dominant and dominant potential. Kalopanax pictus, considered to be highly valuable species, was also included. 2. Taking account of different species composition pattern by topographic positions, we select as desirable species of J. mandshurica, C. controversa, Q. mongolica, A. mono, T. mandshurica, and F. rhynchophylla in the valley area, Q. mongolica, Q. serrata, A. mono, T. mandshurica, F. rhynchophylla, and K. pictus in the mid-slope area, and Q. mongolica, P. densiflora, Q. serrata, and Fraxinus rhynchophylla in the ridge area. 3. Based on the estimation of species diversity index for the overstory components, the reasonable forest stability levels of the indices were estimated at 1.96, 1.68, 1.94, and 1.27 for whole forest, valley, midslope, and ridge, respectively. 4. The recommended species composition ratios in the study forest were suggested Q. mongolica to be 30%, A. mono, F. rhynchophylla, Q. serrata, and T. mandshurica to be 10%~15%, J. mandshurica, P. densiflora, and C. controversa to be 5%~10%, and K. pictus to be 5%.

• Journal of Korean Society of Forest Science
• /
• v.96 no.1
• /
• pp.7-13
• /
• 2007

This study was done to develop PDA based application system for forest geographic information with GPS. The major results obtained in this study were as follows. A PDA based application program was developed to work on $Microsoft^{TM}$ PocketPC 2002 and 2003 operating system. The screen of PDA displays a 1:25,000 digital topographical map adopted DXF format converted from PC, and the map data with 1:2,500 to 1:30,000 on PDA can be zoomed in or out to five levels. Current position and navigating path received from GPS can be displayed on the screen and be saved in PDA. Information selected among layers of digital topographic map in DXF format can be converted into binary files which can be used on forest geographic information software. This can compress DXF files to 90% in size, and the processing speed of PDA was improved. The forest geographic information management system can be used to manage sample plots on which forest inventory is done, with the help of the sub-menus and grid index values with position information received from GPS. Forest workers can in quire forest geographic information such as forest type, location, forest roads, soil erosion control dams using forest geographic information management system in the field. The forest geographic information management system can provide current position and mobile path information to people who enjoy forest related activities like mountain-climbing, sightseeing, and visiting to historic spots.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_2
• /
• pp.1723-1735
• /
• 2022

Landslides are one of the most prevalent natural disasters, threating both humans and property. Also landslides can cause damage at the national level, so effective prediction and prevention are essential. Research to produce a landslide susceptibility map with high accuracy is steadily being conducted, and various models have been applied to landslide susceptibility analysis. Pixel-based machine learning models such as frequency ratio models, logistic regression models, ensembles models, and Artificial Neural Networks have been mainly applied. Recent studies have shown that the kernel-based convolutional neural network (CNN) technique is effective and that the spatial characteristics of input data have a significant effect on the accuracy of landslide susceptibility mapping. For this reason, the purpose of this study is to analyze landslide vulnerability using a pixel-based deep neural network model and a patch-based convolutional neural network model. The research area was set up in Gangwon-do, including Inje, Gangneung, and Pyeongchang, where landslides occurred frequently and damaged. Landslide-related factors include slope, curvature, stream power index (SPI), topographic wetness index (TWI), topographic position index (TPI), timber diameter, timber age, lithology, land use, soil depth, soil parent material, lineament density, fault density, normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used. Landslide-related factors were built into a spatial database through data preprocessing, and landslide susceptibility map was predicted using deep neural network (DNN) and CNN models. The model and landslide susceptibility map were verified through average precision (AP) and root mean square errors (RMSE), and as a result of the verification, the patch-based CNN model showed 3.4% improved performance compared to the pixel-based DNN model. The results of this study can be used to predict landslides and are expected to serve as a scientific basis for establishing land use policies and landslide management policies.

• Journal of Korean Society of Forest Science
• /
• v.98 no.6
• /
• pp.639-645
• /
• 2009

The objective of this research was to introduce the TPI approach for interpreting land-forms of mountain forests in South Korea. We develop an objective procedure to decide the scale factor as a basic analytical unit in land-form classification of rugged mountain areas using TPI. In order to determine the scale factor associated with the pattern of slope profiles, the gradient variance curve was derived from a revised hypsometric curve developed using the relief energy of topographic profiles. Using the gradient variance curve, found was the grid size with which the change in relief energy got the peak point. The grid size at the peak point was determined as the scale factor for the study area. In order to investigate the performance of the procedure based on the gradient variance curve, it was applied to determination of the site-specific scale factors of 3 different terrain conditions; highly-rugged, moderately-rugged and relatively less-rugged. The TPI associated with the corresponding scale factors by study site was, then, determined and used in classifying the land-forms. According to the results of this study, the scale factor gets shorter with more rugged terrain conditions. It was also found that the numbers of valleys and ridges estimated with TPI show almost the same trends as those of the observed and the scale factors tends to approach to the mean distance of ridges.

• Journal of the Korean Geographical Society
• /
• v.50 no.5
• /
• pp.485-503
• /
• 2015

This study aims at evaluating geomorphological classification systems to predict the occurrence of landslides in mountainous region in Korea. Geomorphological classification systems used in this study are Catena, TPI, and Geomorphons. Study sites are Gapyeong-gun, Hoengseong-gun, Gimcheon-si, Yeoju-si/Yicheon-si in which landslide occurrence data were collected by local governments from 2001-2014. Catena method has objective classification standard to compare among regions objectively and understand the result intuitively. However, its procedure is complicated and hard to be automated for the general public to use it. Both TPI and Geomorphons have simple procedure and GIS-extension, therefore it has high accessibility. However, the results of both systems are highly dependent on the scale, and have low relevance to geomorphological formation process because focusing on shape of terrain. Three systems have low compatibility, therefore unified concept are required for broad use of landform classification. To assess the effectiveness of prediction on landslide by each geomorphological classification system, 50% of geomorphological classes with higher landslide occurrence are selected and the total landslide occurrence in selected classes are calculated and defined as 'predictive ability'. The ratio of terrain categorized by 'predictive ability' to whole region is defined as 'vulnerable area ratio'. An indicator to compare three systems which is predictive ability divided by vulnerable area ratio was developed to make a comprehensive judgment. As a result, Catena ranked the highest in suitability.

• Journal of The Geomorphological Association of Korea
• /
• v.17 no.2
• /
• pp.63-76
• /
• 2010

The Jangdo wetland is located on a very gentle slope of the mountain area in Daejangdo island, Shinan-gun, Korea, in which the area of the watershed is estimated at 147,000 m². The wetland has been regarded as a peat bog without any sedimentological evidence. This study was conducted to analyze the geomorphological and sedimentological characteristics of the wetland. The geographic information system (GIS) was used to analyze the drainage system, and field surveys were conducted to measure the range and depth of wetland deposits. The grain size analysis, organic matter determination, elements analysis and radiocarbon dating were performed on samples from the wetland. As a result, the wetland deposits were about 30 cm deep on average, the mean grain sizes ranged from 50 to 500 μm, and the average C/N ratio was 11.5. The portion of organic matter it contained was only 5~26%, which did not satisfy the peat standards. The radiocarbon ages from the wetland deposits range 180±50 ¹⁴C yr BP to modern, which indicated that natural and anthropogenic interferences including agricultural activities have continuously happened. We conclude that the Jangdo wetland is still in its infancy, not a steady state, so that it could be very sensitive to a small disturbance.