• Journal of Environmental Impact Assessment
• /
• v.14 no.6
• /
• pp.387-402
• /
• 2005

In this study, we tried to predict the change of future land-cover and relationships between land-cover change and geo-spatial information in the Gongju area by using fuzzy logic operation. Quantitative evaluation of prediction models was carried out using a prediction rate curve using. Based on the analysis of correlations between the geo-spatial information and land-cover change, the class with the highest correlation was extracted. Fuzzy operations were used to predict land-cover change and determine the land-cover prediction maps that were the most suitable. It was predicted that in urban areas, the urban expansion of old and new towns would occur centering on the Gem-river, and that urbanization of areas along the interchange and national roads would also expand. Among agricultural areas, areas adjacent to national roads connected to small tributaries of the Gem-river and neighboring areas would likely experience changes. Most of the forest areas are located in southeast and from this result we can guess why the wide chestnut-tree cultivation complex is located in these areas and the possibility of forest damage is very high. As a result of validation using the prediction rate curve, it was indicated that among fuzzy operators, the maximum fuzzy operator was the most suitable for analyzing land-cover change in urban and agricultural areas. Other fuzzy operators resulted in the similar prediction capabilities. However, in the prediction rate curve of integrated models for land-cover prediction in the forest areas, most fuzzy operators resulted in poorer prediction capabilities. Thus, it is necessary to apply new thematic maps or prediction models in connection with the effective prediction of changes in the forest areas.

• Journal of the Korean Geotechnical Society
• /
• v.37 no.12
• /
• pp.117-125
• /
• 2021

The occurrence of ground subsidence and sinkhole in downtown areas, which threatens the safety of citizens, has been frequently reported. Among the various mechanisms of a sinkhole, soil erosion through the damaged part of the sewer pipe was found to be the main cause in Seoul. In this study, a random forest model for predicting the occurrence of sinkholes caused by damaged sewer pipes based on sewage pipe information was trained using the information on the sewage pipe and the locations of the sinkhole occurrence case in Seoul. The random forest model showed excellent performance in the prediction of sinkhole occurrence after the optimization of its hyperparameters. In addition, it was confirmed that the sewage pipe length, elevation above sea level, slope, depth of landfill, and the risk of ground subsidence were affected in the order of sewage pipe information used as input variables. The results of this study are expected to be used as basic data for the preparation of a sinkhole susceptibility map and the establishment of an underground cavity exploration plan and a sewage pipe maintenance plan.

• Korean Journal of Remote Sensing
• /
• v.35 no.6_2
• /
• pp.1037-1052
• /
• 2019

We had developed in preceding study a classification model for the Korean pine and Larch with an accuracy of 98 percent using Hyperion and Sentinel-2 satellite images, texture information, and geometric information as the first step for tree species mapping in the inaccessible North Korea. Considering a share of major tree species in North Korea, the classification model needs to be expanded as it has a large share of Oak(29.5%), Pine (12.7%), Fir (8.2%), and as well as Larch (17.5%) and Korean pine (5.8%). In order to classify 5 major tree species, national forest type map of South Korea was used to build 11,039 training and 2,330 validation data. Sentinel-2 data was used to derive spectral information, and PlanetScope data was used to generate texture information. Geometric information was built from SRTM DEM data. As a machine learning algorithm, Random forest was used. As a result, the overall accuracy of classification was 80% with 0.80 kappa statistics. Based on the training data and the classification model constructed through this study, we will extend the application to Mt. Baekdu and North and South Goseong areas to confirm the applicability of tree species classification on the Korean Peninsula.

• Proceedings of the KSRS Conference
• /
• 2009.03a
• /
• pp.270-274
• /
• 2009

한반도의 정밀관측을 목적으로 개발된 KOMPSAT-2위성의 영상을 활용하기 위해서는 촬영 시 발생하는 기하학적 왜곡의 보정이 필요하다. 본 연구에서는 지상기준점(Ground Control Point: GCP) 선택의 세 가지 특성을 각각 적용하여 기하보정을 하였다. 보정 영상의 정확도 검정을 위하여 수치지도(digital map)를 이용한 평균제곱근오차(Root Mean Square Error: RMSE)와 육안검사를 통해 정확도를 비교하였다. 그 결과 영상의 중앙은 선형 교차점을 선택한 방법이 가장 정확하였고, 가장자리는 건물의 모서리 또는 건물의 중심을 선택한 방법이 우수하였다.

• Journal of Korean Society of Forest Science
• /
• v.84 no.3
• /
• pp.369-376
• /
• 1995

Black and White aerial photogrphs are much useful to obtain the information on the channel-bed fluctuation in the following aspects. 1. In the decision of river width, the linear regression formula between the value of aerial photograph interpretation and that of field surveying is Y=1.0+0.94X(the decision coefficient is $r^2=0.98$). Therefore, aerial photographs are proved effective for the measurement of river width. 2. Aerial photograph interpretation makes it possible to classify the plane channel and the deposits in river, and suggests the situation of the plane distribution of deposits, the size of channel and the course of channel formation. 3. The periodical channel situation can be figured out through the interpretation of aerial photographs pictured in different times. Also, the comparing and analyzing each interpretated information can be able to guess the course of the variation of channel influencing powerfully channel - bed fluctuation. 4. The microtopographic map of river can be made through the decision of river with, the interpretation of the plane shape of channel - bed and the analysis of variation of channel. On the basis of this map, the plane analysis of deposit is possible.

• Korean Journal of Remote Sensing
• /
• v.25 no.5
• /
• pp.445-454
• /
• 2009

Localized unprecedented torrential rain and heavy rainfall cause repeated damages and make it difficult to detect and predict the landslide caused by heavy rainfall. To analyze the landslide characteristics of Inje area this study used satellite images photographed after the occurrence of landslide caused by the typhoon Ewiniar occurred in July, 2006, and for GIS analysis purpose, interpreted the satellite images (SPOT5) visually to digitize into developing parts, water traveling parts and sediment parts. For analysis of spatial characteristics, landslide areas obtained from visual interpretation of digital map, 3rd & 4th forest vegetation maps and detailed soil map and grids were overlaid and analyzed. As a result, in regard to topographic features, landslide occurred at places, of which average slope is $26.34^{\circ}$, had south, south-east, south-west aspects and average altitude of 627m. From hydrological analysis, it was found out that water traveling area rapidly spread approaching water traveling area and sediment area. From forest type analysis, it was found out that landslide occurrence was high in pine woods, and in terms of girth class attribute, landslide occurred in small-sized woods, in which the crown occupancy of trees that have the diameter at breast height, 6~16cm, was greater than 50%. From the analysis of soil series, landslide areas constitute 37.85% of OdF and 37.35% of SmF, which had sandy loam soil and excellent drainage capacity. Through this study, landslides in Inje area were characterized and SPOT5 images of 2.5m resolution could be used. But there was a difficulty in determining water traveling parts adjacent to urban area.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.33 no.2
• /
• pp.73-81
• /
• 2015

The objective of this study is in investigating the research for more accurately quantify the information on mountain forest by using the data on high density LiDAR. For the quantitative analysis of mountain forest resources, we investigated the method to acquire the data on high density LiDAR and extract mountain forest resources. Consequently, the height and girth of a tree each mountain forest resources could be extracted by using the data on high density LiDAR. When using the data on low density LiDAR of 2.5points/m² in average used to produce digital map, it was difficult to extract the exact height and girth of mountain forest resources. If using the data on high density LiDAR of 7points/m² by considering topography, the property of mountain forest resources, data capacity and process velocity, etc, it was found that multitudinous entities could be extracted. It was found that mountain topography and mixed topography were generally denser than plane topography and multitudinous mountain forest resources could be extracted. Furthermore, it was also found that the entity at the border could not be extracted, when each partition was individually processed and the area should be subdivided and extracted by considering the process time and property of target area rather than processing wide area at once. We expect to be studied more profoundly the absorption quantity of greenhouse gas later by using information on mountain forest resources in the future.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.5
• /
• pp.27-35
• /
• 2019

The purpose of this study is to analyze the displacement characteristics in slow-moving landslide area using digital elevation model and airborne LiDAR when unpredictable disaster such as slow-moving landslide occurred. We also aimed to provide basic data for establishing a rapid, reasonable and effective restoration plan. In this study, slow-moving landslide occurrence cracks were selected through the airborne LiDAR data, and the topographic changes and the scale of occurrence were quantitatively analyzed. As a result of the analysis, the study area showed horseshoe shape similar to the general form of slow-moving landslide occurrence in Korea, and the direction of movement was in the north direction. The total area of slow-moving landslide damage was estimated to about 2.5ha, length of landsldie scrap 327.3m, average width 19.3m, and average depth 8.6m. The slow-moving landslides did not occur on a large scale but occurred on the adjacent slope where roads were located, caused damage to retaining walls and roads. The field survey of slow-moving landslides was limited by accessibility and safety issues, but there was an advantage that accurate analysis was possible through the airborne LiDAR. However, because airborne LiDAR has costly disadvantages, it has proposed a technique to mount LiDAR on UAV for rapidity, long-term monitoring. In a slow-moving landslide damage area, information such as direction of movement of cracks and change of scale should be acquired continuously to be used in restoration planning and prevention of damage.

• Journal of Cadastre & Land InformatiX
• /
• v.53 no.2
• /
• pp.39-52
• /
• 2023

Cadastral maps are important official documents that affect property rights and have experienced issues due to over 100 years of usage. The accuracy of these old cadastral maps has decreased due to damage, wear, and the accumulation of errors during the rewriting process. These errors have persisted into the digitalization process, creating difficulties in map management. A nationwide project to revise cadastral and forest maps is underway, but there are technical and legal challenges in making corrections. This study addresses the technical aspects of map maintenance and proposes a method to reduce errors and improve maintenance rates by preceding with boundary adjustments. The results show that by preceding with boundary adjustments, the average distance discrepancy decreases from 22.56cm to 8.12cm, and the maintenance rate increases by more than 10%.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
• /
• 2007.10a
• /
• pp.221-225
• /
• 2007

산림은 탄소저장능력이 있어 대표적인 온실가스인 이산화탄소를 저감시킨다. 따라서 산림의 탄소저장능력 특성을 규명하고 그것을 산림경영에 반영함으로써 온실가스 저감이라는 국제적 노력에 동참하는 수단으로 활용할 수 있다. 일반적으로 임분에서의 탄소저장능력(Carbon Storage, CS)은 식생탄소저장능력(Vegetation Carbon Storage, VCS)과 토양탄소저장능력(Soil Carbon Storage, SCS)의 합으로 볼 수 있다. 본 연구에서는 우리나라 대표적인 자생수종인 소나무림 VCS의 공간분포를 지엽적 범위(spot level)에서 광역적 범위(regional level)로 확대하여 그 특성을 규명하는 방법을 제시하고자 한다. 지엽적 범위의 조사 및 연구에서 VCS는 임목의 흉고직경(Diameter at Breast Height)과 밀접한 관계가 있는 것으로 확인되었다. 이러한 관계와 Quickbird 고해상도 위성영상에서 추출한 소나무림 공간분포도를 이용해 경관범위(landscape level)에서 소나무림 탄소저장능력의 공간분포를 추정할 수 있었으며,그 결과를GIS 및 RS를 통해 광역적 범위로 확대하였다.