• Land and Housing Review
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• v.4 no.1
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• pp.89-98
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• 2013

In recent years, it was recognized that aurban policy paradigm of sustainable urban growth management and transportation policies have been shifted : from the era of automobile-oriented policy to the era of public transport policy. Against this backdrop, the introduction of the multi-modal transfer center is very consequential. Therefore, it is necessary for the introduction of wide-area and local-centric transfer facilities, as well as the center of the country-led national backbone transfer center. This study was applicable at the multi-modal transfer center plans to introduce guidelines to provide transit facilities, considering the regional and functional characteristics to classify the types of multi-modal transfer center. The final types of multi-modal transfer center were classified into six, and by considering the combination of the criteria to be classified. The multi-modal transfer center type classification based on the case analysis of the types of facilities at domestic and abroad. If the data of multi-modal transfer are accumulated continuously, can expect a more reliable type classification.

• Korean Journal of Remote Sensing
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• v.12 no.2
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• pp.169-198
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• 1996

The objectives of this investigation are : 1. To analyze spectral signature and the associated vegetation index for geometric illumination conditions inf1uenced by low solar elevation and high slope orientations in mountainous forest. 2. To assess the accuracy of the spectral angle mapper classification for the a winter land cover in comparison with the maximum likelihood classification. 3. To produce the image of water quality and water properties that could be used to estimate the water pollution sources and the tide-included by turbid water in estuarine and coastal areas. These objectives are to characterize environmental and ecological monitoring applications of the Nak-Dong River Basin by using Fuyo-1 OPS VNIR data acquired on December 26, 1992. The results of this paper are as follows : 1. The spectral digital numbers and vegetation indexes (NDVI and TVI) of mountainous forest are higher on the slope facing the sun than on the slope hidden the sun under low sun elevation condition. 2. The spectral angle mapper algorithm produces a more accurate land cover classification of areas with steep slope, various aspects and low solar elevation than the maximum likelihood classifier. 3. The maximum likelihood classification images can be used for identifying the location and movement of both freshwater and salt water, regardless of geometric illumination conditions. 4. The color-coded density sliced image of selected water bodies by using the near-infrared band 3 can provide distribution of the water quality of the Lower Nak-Dong River. 5. The color-coded normalized difference vegetation index image of the selected mountain forest is suitable to classify winter vegetation cover types, i.e., forest canopy densities for slope orientations.

• Journal of The Geomorphological Association of Korea
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• v.25 no.3
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• pp.1-18
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• 2018

In Korea, 64% of the land is known as mountain area, but the definition and classification standard of mountain are not clear. Demand for utilization and development of mountain area is increasing. In this situation, the unclear definition and scope of the mountain area can lead to the destruction of the mountain and the increase of disasters due to indiscreet permission of forestland use conversion. Therefore, this study analyzed the variables and criteria that can extract the mountain boundaries through the questionnaire survey and the terrain analysis. We developed a mountain boundary extraction algorithm that can classify topographic mountain by using selected variables. As a result, 72.1% of the total land was analyzed as mountain area. For the three catchment areas with different mountain area ratio, we compared the results with the existing data such as forestland map and cadastral map. We confirmed the differences in boundary and distribution of mountain. In a catchment area with predominantly mountainous area, the algorithmbased mountain classification results were judged to be wider than the mountain or forest of the two maps. On the other hand, in the basin where the non-mountainous region predominated, algorithm-based results yielded a lower mountain area ratio than the other two maps. In the two maps, we was able to confirm the distribution of fragmented mountains. However, these areas were classified as non-mountain areas in algorithm-based results. We concluded that this result occurred because of the algorithm, so it is necessary to refine and elaborate the algorithm afterward. Nevertheless, this algorithm can analyze the topographic variables and the optimal value by watershed that can distinguish the mountain area. The results of this study are significant in that the mountain boundaries were extracted considering the characteristics of different mountain topography by region. This study will help establish policies for stable mountain management.

• Korean Journal of Remote Sensing
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• v.30 no.2
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• pp.275-292
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• 2014

The objective of this study is to determine Tasseled Cap Transformation (TCT) coefficients for the Geostationary Ocean Color Imager (GOCI). TCT is traditional method of analyzing the characteristics of the land area from multi spectral sensor data. TCT coefficients for a new sensor must be estimated individually because of different sensor characteristics of each sensor. Although the primary objective of the GOCI is for ocean color study, one half of the scene covers land area with typical land observing channels in Visible-Near InfraRed (VNIR). The GOCI has a unique capability to acquire eight scenes per day. This advantage of high temporal resolution can be utilized for detecting daily variation of land surface. The GOCI TCT offers a great potential for application in near-real time analysis and interpretation of land cover characteristics. TCT generally represents information of "Brightness", "Greenness" and "Wetness". However, in the case of the GOCI is not able to provide "Wetness" due to lack of ShortWave InfraRed (SWIR) band. To maximize the utilization of high temporal resolution, "Wetness" should be provided. In order to obtain "Wetness", the linear regression method was used to align the GOCI Principal Component Analysis (PCA) space with the MODIS TCT space. The GOCI TCT coefficients obtained by this method have different values according to observation time due to the characteristics of geostationary earth orbit. To examine these differences, the correlation between the GOCI TCT and the MODIS TCT were compared. As a result, while the GOCI TCT coefficients of "Brightness" and "Greenness" were selected at 4h, the GOCI TCT coefficient of "Wetness" was selected at 2h. To assess the adequacy of the resulting GOCI TCT coefficients, the GOCI TCT data were compared to the MODIS TCT image and several land parameters. The land cover classification of the GOCI TCT image was expressed more precisely than the MODIS TCT image. The distribution of land cover classification of the GOCI TCT space showed meaningful results. Also, "Brightness", "Greenness", and "Wetness" of the GOCI TCT data showed a relatively high correlation with Albedo ($R^2$ = 0.75), Normalized Difference Vegetation Index (NDVI) ($R^2$ = 0.97), and Normalized Difference Moisture Index (NDMI) ($R^2$ = 0.77), respectively. These results indicate the suitability of the GOCI TCT coefficients.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.4
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• pp.1-9
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• 2015

The development of drought index that provides detailed-spatial-resolution drought information is essential for improving drought planning and preparedness. The objective of this study was to develop the concept of using satellite-based hybrid drought index called the Vegetation Drought Response Index in South Korea (VegDRI-SKorea) that could improve spatial resolution for monitoring local and regional drought. The VegDRI-SKorea was developed using the Classification And Regression Trees (CART) algorithm based on remote sensing data such as Normalized Difference Vegetation Index (NDVI) from MODIS satellite images, climate drought indices such as Self Calibrating Palmer Drought Severity Index (SC-PDSI) and Standardized Precipitation Index (SPI), and the biophysical data such as land cover, eco region, and soil available water capacity. A case study has been done for the 2012 drought to evaluate the VegDRI-SKorea model for South Korea. The VegDRI-SKorea represented the drought areas from the end of May and to the severe drought at the end of June. Results show that the integration of satellite imageries and various associated data allows us to get improved both spatially and temporally drought information using a data mining technique and get better understanding of drought condition. In addition, VegDRI-SKorea is expected to contribute to monitor the current drought condition for evaluating local and regional drought risk assessment and assisting drought-related decision making.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.3
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• pp.1-11
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• 2017

The main source of water pollution in Doam Lake is turbid incoming water from upland fields in the upper watershed. The large scale, elevation, and slope of this region means that it is inaccessible, and it is difficult to collect information and update data. Field survey results show that there is a difference between classification of upland fields and grasslands in the cadastral data and land-cover map. In this study, MODIS NDVI was calculated from May 2000 to September 2015 in order to improve classification accuracy of upland fields.

• Journal of Korean Society of Rural Planning
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• v.16 no.3
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• pp.87-101
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• 2010

This research has a significance on providing basic material of landscape ecological planning and open space planning of the future site by selecting Sinseo innovative city area, large residential land development district in rural area, by classifying biotope types and implementing recreational value assessment in the level of area. First of all, as a result of classification of biotope types in research site, total 11 biotope type groups including stream biotope and its subordinate 51 biotope types. Also, as a result of the first value assessment of classified biotopes, there are total 5 types such as vegetation-full natural river, fallow ground in I grade. In addition, it is analyzed that grade II have 18 types, III are 10, IV are 12, the least valuable V are 6. Especially, grassland biotope(GD) was classified into grade II, which is one grade raised, because it is analyzed that it has high value in terms of normal access and availability although it was assessed as grade ill in terms of natural experience quality. Lastly, as a result of the second assessment, special areas for natural experience and recreation(1a, 1b) are 15, areas for natural experience and recreation(2a, 2b, 2c) are 47. Especially, the 52th drawing mark space was grade II in the first assessment but its value grade was upgraded because of its high value in terms of use evidence, size of the area, accessibility with housing area, history and cultural character and so on.

• Journal of Satellite, Information and Communications
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• v.12 no.1
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• pp.6-12
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• 2017

Recently, the demand for SAR imaging is growing to monitor natural disasters or military sites to foresee topographic changes, where optical sensing is not easily available. High-resolution SAR images are useful in exploring topography and monitoring artificial land objects in all weather conditions. In this paper,high resolution SAR images acquired from KOMPSAT-5 are exploited for the applications of change detection and classification. In order to detect change areas, amplitude change detection (ACD) and coherence change detection (CCD) algorithms are employed and their performances are compared in practical applications. For enhanced performance, the potential of small scaled change detection is explored by combining multi-temporary SAR images. The k-means and SVM methods are applied for land classifications and their performances are compared by applying to the real spaceborne SAR images.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.5
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• pp.25-30
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• 2017

Hydrologic soil group is one of the important factors to determine runoff potential and curve number. This study was conducted to classify the hydrologic soil groups of Korean soils by considering saturated hydraulic conductivity and depth of impermeable layer. Saturated hydraulic conductivity of Korean soils was estimated by pedotransfer functions developed in the previous studies. Most of paddy soils were classified as D type due to shallow impermeable layer and low saturated hydraulic conductivity in B soil horizon. For upland and forest, soils classified to A and D types increased compared with former classification method because underestimated permeabilities and overestimated drainages were corrected and rock horizon in shallow depth was regarded as impermeable layer. Soils in mountainous land showed the highest distribution in A type, followed by D type. More than 60 % of soils in mountain foot-slope, fan and valley, alluvial plains, and fluvio-marine deposits were classified to D type because of land use such as paddy and upland.

• Journal of The Korean Society of Grassland and Forage Science
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• v.35 no.3
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• pp.251-256
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• 2015

The study was conducted to determine greenhouse gas (GHG) inventories in grasslands. After 'Low Carbon Green Growth' was declared a national vision on 2008, Medium-term greenhouse gas reduction was anticipated for 30% reduction compared to Business As Usual (BAU) by 2020. To achieve the reduction targets and prepare to enforce emissions trading (2015), national GHG inventories were measured based on the 1996 Intergovernmental Panel on Climate Change Guidelines (IPCC GL). The national Inventory Report (NIR) of Korea is published every year. Grassland sector measurement was officially added in 2014. GHG removal of grassland soil was measured from 1990 to 2012. Grassland area data of Korea was used for farmland area data in the "Cadastral Statistical Annual Report (1976~2012)". Annual grassland area corresponding to the soil classification was used "Soil classification and commentary in Korea (2011)". Grassland area was divided into 'Grassland remaining Grassland' and 'Land converted to Grassland'. The accumulated variation coefficient was assumed to be the same without time series changes in grassland remaining grassland. Therefore, GHG removal of soil carbon was calculated as zero (0) in grassland remaining grassland. Since the grassland area increases constantly, the grassland soil sinks constantly . However, the land converted to grassland area continued to decrease and GHG removal of soil carbon was reduced. In 2012 (127.35Gg $CO_2$), this removal decreased by 76% compared to 1990 (535.71 Gg $CO_2$). GHG sinks are only grasslands and woodlands. The GHG removaled in grasslands was very small, accounting for 0.2% of the total. However, the study provides value by identifying grasslands as GHG sinks along with forests.