• Journal of Korean Society of Forest Science
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• 제52권1호
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• pp.72-78
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• 1981

On August 25, 1979 a heavy daily rainfall of 465 mm pured into Jinhae area by the influence of Typhoon Judy. In consequence of the typhoon, 38 persons were killed, houses and arable land were demolished and caused wide ranges of landslides in the area. According to the previous investigation, there had been five cases of such typhoons accompanied a daily precipitation over 300 mm for 27 years, however, there had not occurred any landslides before, even though it is reported that any typhoon accompanied by heavy daily rainfalls over 300 mm is normally known to cause various kinds of landslides. This phonomenon was described to the fact that there has been a qualitative change in the agents of landslides such as precipitation, geology, topography and forest. Thus, in this report, the relations of the agents to the development of landslides were to be analysed and brought forth the following confirmation: 1. In the district, 71 landslides of which area covered 15.3 ha were observed. 2. In terms of geology of the landslided sites. 89 and 11% in numbers were observed in the andesite and the granite respectively, and the areas of those landslide estimated 45 and 55% respectively. 3. In a topographical point of view, 44% of the numbers of landslides(55% in area basis) were occurred within the slopes of $26-35^{\circ}$, while no landslides were observed in either lower (below $9^{\circ}$) or upper (above $41^{\circ}$) slopes. In terms of slope patterns, 39 and 33% in numbers (52 and 46% on the basis of area) were observed in concave slopes and compound slopes respectively. 4. In terms of forest ages, the most landslides were observed in 5-15 year-old forest, of which averages were 2.19 landslides per 100 ha and 0.47 ha per 100 ha. However, no landslides were observed in the forest of over 26 years old. 5. Among the agents, precipitation, geology, topography are considered not to be controlled but the only agent, the forest, to be controlled by human beings. Thus, this firstly observed landslides at Jinhae District are conclusively considered as the result of qualitative changes of one agent, the forest, in the area.

• Journal of the Korean association of regional geographers
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• 제9권3호
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• pp.373-384
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• 2003

This study analyses the soil loss due to cropland increase in the Hoeryeung area of northeast Korea, using Landsat images of 1987 TM and 2001 ETM, together with DTED, soil and geological maps, and rainfall data of 20 years. Items of land cover and land use were categorized as cropland, settlement, forest, river zone, and sand deposit by supervised classification with spectral bands 1, 2 and 3. RUSLE model is used for estimation of soil loss, and AML language for calculation of soil loss volumes. Fourier transformation method is used for unification of the geographical grids between Landsat images and DTED. GTD was selected from 1:50,000 topographic map. Main sources of soil losses over 100 ton/year may be the river zone and settlement in the both times of 1987 and 2001, but the image of the 2001 shows that sources areas have developed up to the higher mountain slopes. In the cropland average, increases of hight and gradient are 24m and $0.8^{\circ}$ from 1987 to 2001. In the case of new developed cropland, average increases are 75m and $2.5^{\circ}$, and highest soil loss has occurred at the elevation between 300 and 500m. The soil loss 57 ton of 1987 year increased 85 ton of 2001 year. Soil loss is highest in $30{\sim}50^{\circ}$ slope zones in both years, but in 2001 year, soil loss increased under $30^{\circ}$ zones. The size of area over 200 ton/year, indicating higher risk of landslides, have increased from $28.6km^2$ of 1987 year to $48.8km^2$ of 2001 year.

• Korean Journal of Agricultural and Forest Meteorology
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• 제18권4호
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• pp.208-220
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• 2016

Automatic Mountain Meteorology Observation System (AMOS) is an important ingredient for several climatological and forest disaster prediction studies. In this study, we select the optimal sites for AMOS in the mountain areas of Honam and Jeju in order to prevent forest disasters such as forest fires and landslides. So, this study used spatial dataset such as national forest map, forest roads, hiking trails and 30m DEM(Digital Elevation Model) as well as forest risk map(forest fire and landslide), national AWS information to extract optimal site selection of AMOS. Technical methods for optimal site selection of the AMOS was the firstly used multifractal model, IDW interpolation, spatial redundancy for 2.5km AWS buffering analysis, and 200m buffering analysis by using ArcGIS. Secondly, optimal sites selected by spatial analysis were estimated site accessibility, observatory environment of solar power and wireless communication through field survey. The threshold score for the final selection of the sites have to be higher than 70 points in the field assessment. In the result, a total of 159 polygons in national forest map were extracted by the spatial analysis and a total of 64 secondary candidate sites were selected for the ridge and the top of the area using Google Earth. Finally, a total of 26 optimal sites were selected by quantitative assessment based on field survey. Our selection criteria will serve for the establishment of the AMOS network for the best observations of weather conditions in the national forests. The effective observation network may enhance the mountain weather observations, which leads to accurate prediction of forest disasters.

• Korean Journal of Remote Sensing
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• 제34권6_4호
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• pp.1479-1488
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• 2018

On September 3rd 2017, strong artificial seismic signals from North Korea were detected in KMA (Korea Meteorological Administration) seismic network. The location of the epicenter was estimated to be Punggye-ri nuclear test site and it was the most powerful to date. The event was not studied well due to accessibility and geodetic measurements. Therefore, we used remote sensing data to analyze surface changes around Mt. Mantap area. First of all, we tried to detect surface deformation using InSAR method with Advanced Land Observation Satellite-2 (ALOS-2). Even though ALOS-2 data used L-band long wavelength, it was not working well for this particular case because of decorrelation on interferogram. The main reason would be large deformation near the Mt. Mantap area. To overcome this limitation of decorrelation, we applied offset tracking method to measure deformation. However, this method is affected by window kernel size. So we applied various window sizes from 32 to 224 in 16 steps. We could retrieve 2D surface deformation of about 3 m in maximum in the west side of Mt. Mantap. Second, we used Pleiadas-A/B high resolution satellite optical images which were acquired before and after the 6th nuclear test. We detected widespread surface damage around the top of Mt. Mantap such as landslide and suspected collapse area. This phenomenon may be caused by a very strong underground nuclear explosion test. High-resolution satellite images could be used to analyze non-accessible area.

• Journal of Korean Society of Forest Science
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• 제100권3호
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• pp.483-493
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• 2011

Erosion control dams play a primary role in preventing or controlling natural disasters (landslide and debris flow etc.) and also conserve ecosystem in forested watersheds. This study examines structural characteristics of the dams such as the height of ecosystem control and the ecosystem permeability of the erosion control dams under standard drawings and the existing construction works. The objective of this study was to characterize the type classification of erosion control dams as ecosystem. Average permeability was highest on eco-piller dam (63.0%), followed in increasing order by wire rope (13.9%), silt dam (10.9%), multifunctional dam (7.2%), and gravity dam (0.4%). The height of ecosystem control was highest on gravity dam (3.2 m), followed in increasing order by multifunctional dam (1.7 m), wire rope dam (1.2 m), silt dam (0.6 m), and eco-piller dam (0.0 m). Criteria for defining the height of ecosystem control was indefinite. We grouped erosion control dams into three functional types (eco-connection, eco-semi connection, and eco-disconnection) by considering physical and structural characteristics such as the ecosystem permeability and the height of ecosystem control. The type of eco-connection (permeability > 20%) had connection areas from streambed to adjacent riparian areas, and these connection areas serve as ecosystem corridors for fauna and flora. Typical wildlife species includes mammals, reptiles, amphibians, and fishes. The type of eco-semi connection (5% < permeability < 20%) had < 2 m in the eco-barrier height from streambed, however, this type of dams partially serve as wildlife corridors and often provide fish ways. The type of eco-disconnection (permeability < 5%) had > 2 m in the eco-barrier height from streambed, thereby preventing wildlife movement.

• Korean Journal of Remote Sensing
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• 제39권5_1호
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• pp.715-727
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• 2023

To provide detailed and appropriate meteorological information in mountainous areas, the Korea Forest Service has established an Automatic Mountain Meteorology Observation Station (AMOS) network in major mountainous regions since 2012, and 464 stations are currently operated. In this study, we proposed an optimal kriging technique with lapse rate correction to produce gridded temperature data suitable for Korean forests using AMOS point observations. First, the outliers of the AMOS temperature data were removed through statistical processing. Then, an optimized theoretical variogram, which best approximates the empirical variogram, was derived to perform the optimal kriging with lapse rate correction. A 500-meter resolution Kriging map for temperature was created to reflect the elevation variations in Korean mountainous terrain. A blind evaluation of the method using a spatially unbiased validation sample showed a correlation coefficient of 0.899 to 0.953 and an error of 0.933 to 1.230℃, indicating a slight accuracy improvement compared to regular kriging without lapse rate correction. However, the critical advantage of the proposed method is that it can appropriately represent the complex terrain of Korean forests, such as local variations in mountainous areas and coastal forests in Gangwon province and topographical differences in Jirisan and Naejangsan and their surrounding forests.

• Korean Journal of Remote Sensing
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• 제39권6_1호
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• pp.1341-1352
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• 2023

The normalized difference vegetation index (NDVI) derived from satellite images is a crucial tool to monitor forests and agriculture for broad areas because the periodic acquisition of the data is ensured. However, optical sensor-based vegetation indices(VI) are not accessible in some areas covered by clouds. This paper presented a synthetic aperture radar (SAR) based approach to retrieval of the optical sensor-based NDVI using machine learning. SAR system can observe the land surface day and night in all weather conditions. Radar vegetation indices (RVI) from the Sentinel-1 vertical-vertical (VV) and vertical-horizontal (VH) polarizations, surface elevation, and air temperature are used as the input features for an automated machine learning (AutoML) model to conduct the gap-filling of the Sentinel-2 NDVI. The mean bias error (MAE) was 7.214E-05, and the correlation coefficient (CC) was 0.878, demonstrating the feasibility of the proposed method. This approach can be applied to gap-free nationwide NDVI construction using Sentinel-1 and Sentinel-2 images for environmental monitoring and resource management.