• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.2
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• pp.89-102
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• 2024

Land Surface Phenology (LSP) plays a crucial role in understanding vegetation dynamics. The near-infrared reflectance of vegetation (NIRv) has been increasingly adopted in LSP studies, being recognized as a robust proxy for gross primary production (GPP). However, NIR v is sensitive to the terrain effects in mountainous areas due to artifacts in NIR reflectance cannot be canceled out. Because of this, estimating phenological metrics in mountainous regions have a substantial uncertainty, especially in the end of season (EOS). The topographically corrected NIRv (TCNIRv) employs the path length correction (PLC) method, which was deduced from the simplification of the radiative transfer equation, to alleviate limitations related to the terrain effects. TCNIRv has been demonstrated to estimate phenology metrics more accurately than NIRv, especially exhibiting improved estimation of EOS. As the topographic effect is significantly influenced by terrain properties such as slope and aspect, our study compared phenology metrics estimations between south-facing slopes (SFS) and north-facing slopes (NFS) using NIRv and TCNIRv in two distinct mountainous regions: Gwangneung Forest (GF) and Odaesan National Park (ONP), representing relatively flat and rugged areas, respectively. The results indicated that TCNIR v-derived EOS at NFS occurred later than that at SFS for both study sites (GF : DOY 266.8/268.3 at SFS/NFS; ONP : DOY 262.0/264.8 at SFS/NFS), in contrast to the results obtained with NIRv (GF : DOY 270.3/265.5 at SFS/NFS; ONP : DOY 265.0/261.8 at SFS/NFS). Additionally, the gap between SFS and NFS diminished after topographic correction (GF : DOY 270.3/265.5 at SFS/NFS; ONP : DOY 265.0/261.8 at SFS/NFS). We conclude that TCNIRv exhibits discrepancy with NIR v in EOS detection considering slope orientation. Our findings underscore the necessity of topographic correction in estimating photosynthetic phenology, considering slope orientation, especially in diverse terrain conditions.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.4
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• pp.76-91
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• 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 Environmental Impact Assessment
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• v.15 no.1
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• pp.1-12
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• 2006

Changes in the soil physical property and the topographic condition derived from agricultural activities like as farming activities, land clearance and cutting down resulted in environmental and economic problems including the outflow of nutrient from farms and the water pollution. Several theories on the soil conservation have been developed and reviewed to protect soil erosion in the regions having a high risk of erosion. This study was done using the USLE model developed by Wischmeier and Smith (1978), and model for the slope length and steepness made by Desmet and Govers (1996), and Nearing (1997) to evaluate the potential of the soil erodibility. Therefore, several results were obtained as follows. First, factors affecting the soil erosion based on the USLE could be extracted to examine the erosion potential in farms. Soil erodibility (K), slope length (L), and slope steepness (S) were used as main factors in the USLE in consideration of the soil, not by the land use or land cover. Second, the soil erodibility increased in paddy soils where it is low in soil content, and the very fine sandy loam exists. Analysis of the slope length showed that the value of a flat ground was 1, and the maximum value was 9.17 appearing on the steep mountain. Soil erodibility showed positive relationship to a slope. Third, the potential soil erodibility index (PSEI) showed that it is high in the PSEI of the areas of steep upland and orchard on the slope of mountainous region around Dokjigol mountain, Dunji mountain, and Deummit mountain. And the PSEI in the same land cover was different depending on the slope rather than on the physical properties in soil. Forth, the analysis of land suitability in soil erosion explained that study area had 3,672.35ha showing the suitable land, 390.88ha for the proper land, and 216.54ha for the unsuitable land. For unsuitable land, 8.71ha and 6.29ha were shown in fallow uplands and single cropping uplands, respectively.

• Korean Journal of Environmental Biology
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• v.25 no.2
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• pp.168-177
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• 2007

By using DEM and digital actual vegetation map with MGE GIS software program, topographic features (altitude, slope, latitude, etc.) quantitatively were analysed and their data integrated as the index of climatic conditions (WI, CI, air temperature, etc.) in South Korea. Warmth Index (WI) decreases $5.27^{\circ}C{\cdot}month$ with latitudinal $1^{\circ} degree, and $3.41^{\circ}C{\cdot}month$ with attitudinal 100 m increase. The relationship between CI and WI values is expressed as a linear regression, $WI=116.01+0.96{\times}CI,\;R^2=0.996$. The distributional peaks of different plant communities along Warmth Index gradient showed the sequence of Abies nephrolepis, Taxus cuspidata, Abies koreana, Quercus mongolica, Carpinus laxiflora, Q. dentata, C. tschonoskii, Q. serrate, Pinus densiflora, Q. aliena, Q. variabilis, Q. acutissima, P. thunbergii, Q. acute, Castanopsis cuspidata var. sieboldii, Camellia japonica, Machilus thunbergii community from lower to higher values. The Quercus mongolica forest occurred frequently on E-NW and SE slope aspect within WI $70{\sim}80^{\circ}C{\cdot}month$ optimal range at mesic sites, NW and SE slope than xeric sites S and SW slope. The Q. serrata forest showed the most distributional frequency in NW and W slope aspect within WI $90{\sim}100^{\circ}C{\cdot}month$ range, Q. variabilis and Q. acutissima forest showed the high frequency of distribution in SE slope in WI $95{\sim}100^{\circ}C{\cdot}month$ range. By the slope gradient analysis, five groups were found: 1. Abies nephrolepis, Machilus thunbergii, 2. Taxus cuspidata, Abies koreana, Quercus mongolica, Q. dentata, Q. serrata, Q. variabilis, Castanopsis cuspidata var. sieboldii 3. Pinus densiflora, Q. aliena, Q. acutissima, P. thunbergii, Q. acuta 4. Carpinus laxiflora, Camellia japonica 5. C. tschonoskii from steep slope to gentle slope sequence.

• Journal of Korean Society of Forest Science
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• v.90 no.4
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• pp.465-475
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• 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 the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.1-14
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• 2012

A river is defined as the watercourse flowing through its channel, and the mapping tasks of a river plays an important role for the research on the topographic changes in the riparian zones and the research on the monitoring of flooding in its floodplain. However, the utilization of the ground surveying technologies is not efficient for the mapping tasks of a river due to the irregular surfaces of the riparian zones and the dynamic changes of water level of a river. Recently, the spatial information data sets are widely used for the coastal mapping tasks due to the acquisition of the topographic information without human accessibility. In this research, we tried to extract a river from the RapidEye imagery by using the ISODATA(Iterative Self_Organizing Data Analysis) classification algorithm with the two different parameters(NIR (Near Infra-Red) band and NDVI(Normalized Difference Vegetation Index)). First, the two different images(the NIR band image and the NDVI image) were generated from the RapidEye imagery. Second, the ISODATA algorithm were applied to each image and each river was generated in each image through the post-processing steps. River boundaries were also extracted from each classified image using the Sobel edge detection algorithm. Ground truths determined by the experienced expert are used for the assessment of the accuracy of an each generated river. Statistical results show that the extracted river using the NIR band has higher accuracies than the extracted river using the NDVI.

• Journal of Korean Society of Forest Science
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• v.103 no.4
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• pp.537-546
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• 2014

The purpose of this study was to interpret ecological characteristics and to estimate successional trend for seven classified forest cover types (Quercus mongolica pure forest, Q. mongolica-Q. serrata forest, Mixed mesophytic forest, Abies koreana-Q. mongolica forest, Fraxinus mandshurica forest, Q. serrata forest, and Carpinus laxiflora forest) in the natural forest of Western Jirisan. Q. mongolica pure forest and A. koreana-Q. mongolica forest which were distributed in a high-altitude ridge had the lowest species diversity index. On the other hand, mixed mesophytic forest and F. mandshurica forest which were mainly distributed in the valley had higher index. Based on characteristics of species diversity and topographic conditions, successional trends for forest cover types were estimated as follows; 1) Q. mongolica pure forest and A. koreana-Q. mongolica forest would be changed toward Q. mongolica-A. koreana forest. 2) Q. mongolica-Q. serrata forest, distributed between ridge and mid-slope, would be changed toward Q. mongolica-C. laxiflora-C. cordata forest. 3) Q. serrata forest, distributed in mid-slope, would be changed toward Q. serrata-Q. mongolica-C. laxiflora forest. 4) Mixed mesophytic forest, F. mandshurica forest and C. laxiflora forest, distributed in valley, would maintain the current condition in terms of species composition.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1723-1735
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• 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 the Korean Association of Geographic Information Studies
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• v.21 no.3
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• pp.48-62
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• 2018

In this study, landslide of debris flow occurred at 51 sites around Daeryounsan located in between Chuncheon-si and Hongcheon-gun during July in 2013 were investigated in field and behavior characteristics of debris flow were analyzed on the basis of records of rainfall and site investigation. According to debris flow types of channelized and hill slope, location and slope angle of initiation and deposit zone, and width and depth of erosion were investigated along entire runout of debris flow. DEM(Digital Elevation Model) of Daeryounsan was constructed with digital map of 1:5,000 scale. Land slide hazard was estimated using SINMAP(Stability INdex MAPping) and the predicted results were compared with field sites where debris flow occurred. As analyzed results, for hill slope type of debris flow, predicted sites were quite comparable to actual sites. On the other hand, for channelized type of debris flow, debris flow occurrence sites were predicted by using stability index associated with topographic wetness index. As analyzed results of 4 different conditions with the parameter T/R, Hydraulic transmissivity/Effective recharge rate, proposed by NRCS (Natual Resources Conservation Service), predicted results showed more or less different actual sites and the degree of hazard tended to increase with decrease of T/R value.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.5_2
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• pp.194-205
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• 2010

To predict urban growth according to changes in landcover, probability factors werecal culated and mapped. Topographic, geographic and social and political factors were used as prediction variables for constructing probability maps of urban growth. Urban growth-related factors included elevation, slope, aspect, distance from road,road ratio, distance from the main city, land cover, environmental rating and legislative rating. Accounting for these factors, probability maps of urban growth were constr uctedusing frequency ratio (FR) and logistic regression (LR) methods and the effectiveness of the results was verified by the relative operating characteristic (ROC). ROC values of the urban growth probability index (UGPI) maps by the FR and LR models were 0.937 and 0.940, respectively. The LR map had a slightly higher ROC value than the FR map, but the numerical difference was slight, with both models showing similar results. The FR model is the simplest tool for probability analysis of urban growth, providing a faster and easier calculation process than other available tools. Additionally, the results can be easily interpreted. In contrast, for the LR model, only a limited amount of input data can be processed by the statistical program and a separate conversion process for input and output data is necessary. In conclusion, although the FR model is the simplest way to analyze the probability of urban growth, the LR model is more appropriate because it allows for quantitative analysis.