• Journal of Korean Society of Water and Wastewater
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• v.35 no.2
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• pp.163-174
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• 2021

Heatwaves are one of the most common phenomena originating from changes in the urban thermal environment. They are caused mainly by the evapotranspiration decrease of surface impermeable areas from increases in temperature and reflected heat, leading to a dry urban environment that can deteriorate aspects of everyday life. This study aimed to calculate daily maximum ground surface temperature affecting heatwaves, to quantify the effects of urban thermal environment control through water cycle restoration while validating its feasibility. The maximum surface temperature regression equation according to the impermeable area ratios of urban land cover types was derived. The estimated values from daily maximum ground surface temperature regression equation were compared with actual measured values to validate the calculation method's feasibility. The land cover classification and derivation of specific parameters were conducted by classifying land cover into buildings, roads, rivers, and lands. Detailed parameters were classified by the river area ratio, land impermeable area ratio, and green area ratio of each land-cover type, with the exception of the rivers, to derive the maximum surface temperature regression equation of each land cover type. The regression equation feasibility assessment showed that the estimated maximum surface temperature values were within the level of significance. The maximum surface temperature decreased by 0.0450℃ when the green area ratio increased by 1% and increased by 0.0321℃ when the impermeable area ratio increased by 1%. It was determined that the surface reduction effect through increases in the green area ratio was 29% higher than the increasing effect of surface temperature due to the impermeable land ratio.

• Korean Journal of Remote Sensing
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• v.28 no.2
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• pp.203-214
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• 2012

The physical environment of urban areas covered mostly by concrete and asphalt is the main cause of the urban heat island effect, primarily becoming apparent through increased land surface temperature. This study examined the effect of different urban land cover types on the land surface temperature using MODIS, Landsat ETM+ and RapidEye satellite data. As a result, the remote sensing based land surface temperature showed a marked difference according to the land use pattern in the case study of Ilsan new city. The high-rise apartment residential districts with less building-to-land ratio and higher green area ratio revealed lower land surface temperature than the low-story single-family housing districts characterized by relatively high building-to-land ratio and low green area ratio. From the view of climate zone and land cover types, there is a strong linear correlation between the impervious land cover ratio and the land surface temperature; the land surface temperature increases as the impervious built-up areas expand. In contrast, vegetation;water and shadow areas affect the decrease of land surface temperature. There is also a negative (-) correlation between NDVI and land surface temperature but the seasonal variation of NDVI can be hardly corrected.

• Journal of the Korean earth science society
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• v.23 no.1
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• pp.1-14
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• 2002

The land-cover of two regions of South and North Korea included in one Landsat TM scene was investigated by comparing different seasons and different band data over the multiple land-cover types. The relationships between the intensities of two bands in the 2-D plot are mainly linear in band2 versus band1 and band3 versus band1, polygonal sporadic in band5 versus band1 and band7 versus band1, and almost tri-polarized in band4 versus band3. The 2-D plot of band4/band3 shows the best capability to discriminate different main land-cover such as water, vegetation and dry soil. Some discriminations are not clear between city and dry field, or mountain and plain field in the scene of September. The digital number data of band4 from vegetated zones show stronger reflectance in September rather than April, while other band values tend to be lager in April than in September over each land-cover. NDVI presents high value in both regions in September. However the image of Wonsan area in April suggests weak vigor of vegetation in comparison with Cholwon area. Band ratios are very effective in eliminating the influence of the complex topography. The proper pairing of the band ratio improved the discrimination capability of the land-cover; band5/band2 for dry soil, band4/band3 for vegetation and band1/band7 for the water. The RGB combination of the three band ratio pairs showed the best results in the discrimination of the land-cover of Wonsan, Cholwon and even the Demilitarized Zone.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.3
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• pp.135-152
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• 2018

The purpose of this study is to propose an optimal fusion method of aerial multi - sensor data to improve the accuracy of land cover classification. Recently, in the fields of environmental impact assessment and land monitoring, high-resolution image data has been acquired for many regions for quantitative land management using aerial multi-sensor, but most of them are used only for the purpose of the project. Hyperspectral sensor data, which is mainly used for land cover classification, has the advantage of high classification accuracy, but it is difficult to classify the accurate land cover state because only the visible and near infrared wavelengths are acquired and of low spatial resolution. Therefore, there is a need for research that can improve the accuracy of land cover classification by fusing hyperspectral sensor data with multispectral sensor and aerial laser sensor data. As a fusion method of aerial multisensor, we proposed a pixel ratio adjustment method, a band accumulation method, and a spectral graph adjustment method. Fusion parameters such as fusion rate, band accumulation, spectral graph expansion ratio were selected according to the fusion method, and the fusion data generation and degree of land cover classification accuracy were calculated by applying incremental changes to the fusion variables. Optimal fusion variables for hyperspectral data, multispectral data and aerial laser data were derived by considering the correlation between land cover classification accuracy and fusion variables.

• Journal of Korean Society on Water Environment
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• v.39 no.2
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• pp.142-152
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• 2023

Infiltration is a process by which precipitation infuses into subsurface soils. The process determines the surface flow and baseflow volume, and it is one of most important hydrological processes regarding nonpoint source pollution management. Therefore, the Ministry of Environment has developed a guideline to determine the impervious area ratio to understand the hydrological process in administrative districts and watersheds. The impervious area ratio can be determined using land use or land cover maps. Three approaches were explored to determine the impervious area ratio in 25 districts in Seoul. The impervious area ratio was determined by employing the Land registration map and Land property data in the first approach, Land property map in the second approach, and Land cover map in the third approach. The ratio ranged from 38.96% to 83.01% in the first approach, 38.98% to 83.02% in the second approach, and 37.62% to 76.63% in the third approach. Although the ranges did not provide any significant differences in the approaches, some districts displayed differences up to 9.48% by the approach. These differences resulted from the fact that the data were land use or land cover, especially in the area of airport, residential complex area, and school sites. In other words, division of the pervious and impervious areas in an individual plot was not allowed in the Land registration map, while it was allowed in the Land cover map. Therefore, it was concluded that there is a need to revise the guideline so that a reasonable impervious area ratio can be determined in the districts.

• Journal of Environmental Impact Assessment
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• v.22 no.5
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• pp.397-408
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• 2013

The purpose of this study is to analyze water cycle area ratio and spatial evaluation of water cycle in urban area of Changwon-si, Gyeongsangnam-do. Water cycle area ratio are analyzed by using spatial data of land-cover and land-use, and Hot spot analysis of GIS program was used for spatial evaluation of water cycle. The results are as below. Firstly, the high water cycle area ratio areas were forests, parks, and rivers, but urban areas covered asphalt and concrete were low under 40%. Public institutions and co-residential of urban areas were higher than others because of high area ratio of pervious land-cover. Spatial evaluation of water cycle was analyzed to vulnerable areas there are dense residential and commercial area. These areas are really occurring frequently flooding and immersion, therefore, is required water management facilities and improvement of land-cover from impervious to pervious. In the future, it will require additionally analysis of water cycle area ratio supplemented data of water management facility and ground water.

• Journal of Environmental Policy
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• v.7 no.3
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• pp.121-140
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• 2008

The impervious cover ratio has been used as an important measure for tracing water environment characteristics in watershed. Impervious cover is divided into total impervious cover and effective impervious cover, and its size varies depending on the land use characteristics of a watershed. Total impervious cover can be easily measured using existing land use maps or land cover map, while it takes a considerable amount of time and labor to measure the effective impervious cover, as water flow should be identified at each site. This study is intended to calculate the total impervious cover and effective cover of a sample site, compare their characteristics, and find a method to apply effective and total impervious cover ratios toward watershed management. The analysis of the sample site showed that the effective impervious cover rate(39.7%) was less than the total impervious cover rate(43%). This suggests that it would be acceptable, in terms of time and cost, if total impervious cover is applied as the representative impervious cover ratio of a watershed considering that it was used as basic data to analyze the effect that impervious cover has on the water environment.

• Atmosphere
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• v.21 no.4
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• pp.405-414
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• 2011

In this study, the influence of a change in land use on the local weather fields is investigated around the Lake Shihwa area using synthetic land cover data and a high-resolution mesoscale model - the Weather Research and Forecasting (WRF). The default land cover data generally used in the WRF is based on the land use category of the United States Geological Survey (USGS), which erroneously presents most land areas of the Korean Peninsula as savannas. To revise such a fault, a multi-temporal land cover data, provided by the Ministry of Environment of Korea, was employed to generate a land cover map of 2005 subject to the land use in Korea at that time. A new land cover map of 1989, before the construction of the Lake Shihwa, was made based on the 2005 map and the Landsat 4-5 TM satellite images of two years. Over the areas where the land use had been changed (e.g., from sea to wetlands, towns, etc.) due to the Lake Shihwa development project, the skin temperature decreased by up to $8^{\circ}C$ in the winter case while increased by as much as $14^{\circ}C$ in the summer case. Changes in the water vapor mixing ratio were mostly affected by advection and topography in both seasons, with considerable increase in the summer case due to continuous sea breeze. Local decrease in water vapor occurred over high land use change areas and/or over downstream of such areas where alteration in wind fields were induced by changes in skin temperature and surface roughness at the areas of land use changes. The albedo increased by about 0.1% in the regions where sea was converted into wetland. In the regions where urban areas were developed, such as Songdo New Town and Incheon International Airport, the albedo increased by up to 0.16%.

• Atmosphere
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• v.17 no.2
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• pp.159-169
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• 2007

A comparison of the three land cover data sets (United States Geological Survey: USGS, International Geosphere Biosphere Programme: IGBP, and University of Maryland: UMd), derived from 1992-1993 Advanced Very High Resolution Radiometer(AVHRR) data sets, was performed over the Asian continent. Preprocesses such as the unification of map projection and land cover definition, were applied for the comparison of the three different land cover data sets. Overall, the agreement among the three land cover data sets was relatively high for the land covers which have a distinct phenology, such as urban, open shrubland, mixed forest, and bare ground (>45%). The ratios of triple agreement (TA), couple agreement (CA) and total disagreement (TD) among the three land cover data sets are 30.99%, 57.89% and 8.91%, respectively. The agreement ratio between USGS and IGBP is much greater (about 80%) than that (about 32%) between USGS and UMd (or IGBP and UMd). The main reasons for the relatively low agreement among the three land cover data sets are differences in 1) the number of land cover categories, 2) the basic input data sets used for the classification, 3) classification (or clustering) methodologies, and 4) level of preprocessing. The number of categories for the USGS, IGBP and UMd are 24, 17 and 14, respectively. USGS and IGBP used only the 12 monthly normalized difference vegetation index (NDVI), whereas UMd used the 12 monthly NDVI and other 29 auxiliary data derived from AVHRR 5 channels. USGS and IGBP used unsupervised clustering method, whereas UMd used the supervised technique, decision tree using the ground truth data derived from the high resolution Landsat data. The insufficient preprocessing in USGS and IGBP compared to the UMd resulted in the spatial discontinuity and misclassification.

• Journal of the Korean Geographical Society
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• v.39 no.5 s.104
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• pp.786-803
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• 2004

These days, interests on land cover classification using not only multi-sensor data but also thematic GIS information, are increasing. Often, although we have useful GIS information for the classification, the traditional classification method like maximum likelihood estimation technique (MLE) does not allow us to use the information due to the fact that the MLE and the existing computer programs cannot handle GIS data properly. We proposed a new method for updating the image classification using multi-spectral and multi-temporal images. In this study, we have simultaneously extended the MLE to accommodate both multi-spectral images data and land cover data for land cover classification. In addition to the extended MLE method, we also have extended the empirical likelihood ratio estimation technique (LRE), which is one of non-parametric techniques, to handle simultaneously both multi-spectral images data and land cover data. The proposed procedures were evaluated using land cover map based on Landsat ETM+ images in the Anmyeon-do area in South Korea. As a result, the proposed methods showed considerable improvements in classification accuracy when compared with other single-spectral data. Improved classification images showed that the overall accuracy indicated an improvement in classification accuracy of $6.2\%$ when using MLE, and $9.2\%$ for the LRE, respectively. The case study also showed that the proposed methods enable the extraction of the area with land cover change. In conclusion, land cover classification produced through the combination of various GIS spatial data and multi-spectral images will be useful to involve complementary data to make more accurate decisions.