Journal of The Korean Society of Agricultural Engineers
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v.53
no.5
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pp.9-16
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2011
Curve Numbers (CN) for the combination of land use and hydrologic soil group were regionalized at Imha Watershed using Long-term Hydrologic Impact Assessment (L-THIA) coupled with SCE-UA. The L-THIA was calibrated during 1991-2000 and validated during 2001-2007 using monthly observed direct runoff data. The Nash-Sutcliffe (NS) coefficients for calibration and validation were 0.91 and 0.93, respectively, and showed high model efficiency. Based on the criteria of model calibration, both calibration and validation represented 'very good' fit with observe data. The spatial distribution of direct surface runoff by L-THIA represented runoff from Thiessen pologen at Subi and Sukbo rain gage station much higher than other area due to the combination of poor hydrologic condition (hydrologic soil C and D group) and locality heavy rainfall. As a results of hydrologic condition and treatment for land use type based on calibrated CNs, forest is recommended to be hydrologically modelled dived into deciduous, coniferous, and mixed forest due to the hydrological difference. The CNs for forest and upland showed the poor hydrologic condition. The steep slope of forest and alpine agricultural field make high runoff rate which is the poor hydrologic condition because CN method can not consider field slope. L-THIA linded with SCE-UA could generated a regionalized CNs for land use type with minimized time and effort, and maximized model's accuracy.
Accurate knowledge of land use/land cover (LULC) features and their relative changes over upon the time are essential for sustainable urban management. Urban sprawl growth has been always also a worldwide concern that needs to carefully monitor particularly in a developing country where unplanned building constriction has been expanding at a high rate. Recently, remotely sensed imageries with a very high spatial/spectral resolution and state of the art machine learning approaches sent the urban classification and growth monitoring to a higher level. In this research, we classified the Quickbird satellite imagery by object-based image analysis of Dempster-Shafer (OBIA-DS) for the years of 2002 and 2015 at Karbala-Iraq. The real LULC changes including, residential sprawl expansion, amongst these years, were identified via change detection procedure. In accordance with extracted features of LULC and detected trend of urban pattern, the future LULC dynamic was simulated by using land transformation model (LTM) in geospatial information system (GIS) platform. Both classification and prediction stages were successfully validated using ground control points (GCPs) through accuracy assessment metric of Kappa coefficient that indicated 0.87 and 0.91 for 2002 and 2015 classification as well as 0.79 for prediction part. Detail results revealed a substantial growth in building over fifteen years that mostly replaced by agriculture and orchard field. The prediction scenario of LULC sprawl development for 2030 revealed a substantial decline in green and agriculture land as well as an extensive increment in build-up area especially at the countryside of the city without following the residential pattern standard. The proposed method helps urban decision-makers to identify the detail temporal-spatial growth pattern of highly populated cities like Karbala. Additionally, the results of this study can be considered as a probable future map in order to design enough future social services and amenities for the local inhabitants.
Land use and land cover (LULC) mapping is an important factor in geospatial analysis. Although highly precise ground-based LULC monitoring is possible, it is time consuming and costly. Conversely, because the synthetic aperture radar (SAR) sensor is an all-weather sensor with high resolution, it could replace field-based LULC monitoring systems with low cost and less time requirement. Thus, LULC is one of the major areas in SAR applications. We developed a LULC model using only KOMPSAT-5 single co-polarized data and digital elevation model (DEM) data. Twelve HH-polarized images and 18 VV-polarized images were collected, and two HH-polarized images and four VV-polarized images were selected for the model testing. To train the LULC model, we applied the conditional generative adversarial network (cGAN) method. We used U-Net combined with the residual unit (ResUNet) model to generate the cGAN method. When analyzing the training history at 1732 epochs, the ResUNet model showed a maximum overall accuracy (OA) of 93.89 and a Kappa coefficient of 0.91. The model exhibited high performance in the test datasets with an OA greater than 90. The model accurately distinguished water body areas and showed lower accuracy in wetlands than in the other LULC types. The effect of the DEM on the accuracy of LULC was analyzed. When assessing the accuracy with respect to the incidence angle, owing to the radar shadow caused by the side-looking system of the SAR sensor, the OA tended to decrease as the incidence angle increased. This study is the first to use only KOMPSAT-5 single co-polarized data and deep learning methods to demonstrate the possibility of high-performance LULC monitoring. This study contributes to Earth surface monitoring and the development of deep learning approaches using the KOMPSAT-5 data.
Proceedings of the Korea Water Resources Association Conference
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2008.05a
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pp.194-198
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2008
Significant soil erosion and water quality degradation issues are occurring at highland agricultural areas of Kangwon province because of agronomic and topographical specialities of the region. Thus spatial and temporal modeling techniques are often utilized to analyze soil erosion and sediment behaviors at watershed scale. The Soil and Water Assessment Tool (SWAT) model is one of the watershed scale models that have been widely used for these ends in Korea. In most cases, the SWAT users tend to use the readily available input dataset, such as the Ministry of Environment (MOE) land cover data ignoring temporal and spatial changes in land cover. Spatial and temporal resolutions of the MOE land cover data are not good enough to reflect field condition for accurate assesment of soil erosion and sediment behaviors. Especially accelerated soil erosion is occurring from agricultural fields, which is sometimes not possible to identify with low-resolution MOD land cover data. Thus new land cover data is prepared with cadastral map and high spatial resolution images of the Doam-dam watershed. The SWAT model was calibrated and validated with this land cover data. The EI values were 0.79 and 0.85 for streamflow calibration and validation, respectively. The EI were 0.79 and 0.86 for sediment calibration and validation, respectively. These EI values were greater than those with MOE land cover data. With newly prepared land cover dataset for the Doam-dam watershed, the SWAT model better predicts hydrologic and sediment behaviors. The number of HRUs with new land cover data increased by 70.2% compared with that with the MOE land cover, indicating better representation of small-sized agricultural field boundaries. The SWAT estimated annual average sediment yield with the MOE land cover data was 61.8 ton/ha/year for the Doam-dam watershed, while 36.2 ton/ha/year (70.7% difference) of annual sediment yield with new land cover data. Especially the most significant difference in estimated sediment yield was 548.0% for the subwatershed #2 (165.9 ton/ha/year with the MOE land cover data and 25.6 ton/ha/year with new land cover data developed in this study). The results obtained in this study implies that the use of MOE land cover data in SWAT sediment simulation for the Doam-dam watershed could results in 70.7% differences in overall sediment estimation and incorrect identification of sediment hot spot areas (such as subwatershed #2) for effective sediment management. Therefore it is recommended that one needs to carefully validate land cover for the study watershed for accurate hydrologic and sediment simulation with the SWAT model.
This paper examines the increasingly popular belief that higher holding tax will be the ultimate solution for Korea's land problems which include excessive concentration of ownership, high and rapidly increasing land prices, and rampant speculation. In principle, land holding tax can supplement capital gains tax in recapturing capital gains from land or suppress returns from land investment returns in line with other forms of asset. This paper shows, however, that the tax burden must be drastically increased for the tax to achieve such goals, and the resistance from tax payers is sure to be intense. As long as the price expectation remains high, as in Korea where land prices have increased 19% annually during the past 18 years, even such increase in the tax may have little impact on landlords' behaviors, the price trend, or the ownership structure. More effective solutions for Korea's land problems are relaxing land use regulations to encourage the supply for urban land and improving the performance of capital gains tax to recapture windfall gains from land. This paper also notes that the so-called "lock-in effect" of the capital gains tax seems to be exaggerated. Land holding tax should be viewed as a revenue raiser for local governments rather than an anti-speculative policy tool. Abandoning unattainable policy goals and adhering to the general principles of taxation, will make land holding tax much simpler, and will better function as a local revenue source.
Park, Jae Hong;Lee, Su Woong;Park, Ju Hyun;Rhew, Doug Hee;Jung, Dong Il;Choi, Hye Mi;Jeon, Woo Song
Journal of Korean Society on Water Environment
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v.25
no.2
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pp.193-204
/
2009
The study was conducted investigation on land of D-dong in N city which is an urban area and D myeon of N city which is a suburban area, based on high resolution satellite image, to find out actual land usage. As for D-dong in N city, different rate between actual usage and official land information was 0.5~4.8% in terms of 5 major land types (paddy field, farm, ground, forest, and others). D myeon in N city posted 1.4~8.4%, which is higher than that of its counterpart. As for unit load, "land" which is large in terms of load presented a big difference between official information and actual usage. On the other hand, the levels of paddy, field, forest and others posted only small changes in load. In case of T-P, in particular, unit of each land type is lower than BOD and T-N, showing almost no changes in pollution loads.
In this study, we examine how land use zoning affects the land price controlling other variables such as road-facing condition of the land, land form, land age after its development and land size. We employ geographically weighted regression analysis which reflects spatial dependency as methodology with a data sample of land transaction price data of Jangyu, a new town, in Korea. The results of our empirical analysis show that the respective coefficients of traditional regression and geographically weighted regression are not significantly different. However, after calculating Moran's Index with residuals of both OLS and GWR models, we find that Moran's Index of GWR decreases around 26% compared to that of OLS model, thus improving the problem of spatial autoregression of residuals considerably. Unlike our expectation, though, in both traditional regression and geographically weighted regression where residential exclusive area is used as a reference variable, the dummy variable of the residential land for both housing and shops shows a negative sign. This may be because the residential land for both housing and shops is usually located in the level area while the residential exclusive area is located at the foot of a mountain or on a gentle hill where the residents can have good quality air and scenery. Although the utility of the residential land for both housing and shops is higher than its counterpart's since it has higher floor area ratio, amenity which can be explained as high quality of air and scenery in this study seems to have higher impact in purchase of land for housing. On the other hand, land for neighbourhood living facility seems to be valued higher than any other land zonings used in this research since it has much higher floor area ratio than the two land zonings above and can have a building with up to 5 stories constructed on it. With regard to road-facing condition, land buyers seem to prefer land which faces a medium-width road as expected. Land facing a wide-width road may have some disadvantage in that it can be exposed to noise and exhaust gas from cars and that entrance may not be easy due to the high speed traffic of the road. In contrast, land facing a narrow road can be free of noise or fume from cars and have privacy protected while it has some inconvenience in that entrance may be blocked by cars parked in both sides of the narrow road. Finally, land age variable shows a negative sign, which means that the price of land declines over time. This may be because decline of the land price of Jangyu was bigger than that of other regions in Gimhae where Jangyu, a new town, also belong, during the global financial crisis of 2008.
Biotop map can be utilized for nature conservation and assessment of environmental impact for human activities in urban area. High resolution satellite images such as IKONOS and KOMPSAT1-EOC were interpreted to classify land use, hydrology, impermeable pavement ratio and vegetation for biotop mapping. Wildlife habitat map and detailed vegetation map obtained from former study results were used as ground truth data. Vegetation was investigated directly for the area where the detailed vegetation map is not available. All these maps were combined and the boundaries were delineated to produce the biotop map. Within the boundary, the characteristics of each polygon were identified, and named. This study investigates the possibility of biotop mapping using high resolution satellite remote sensing data together with field data with the goal of contributing to nature conservation in urban area.
Journal of Korean Society for Atmospheric Environment
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v.31
no.1
/
pp.1-14
/
2015
This study investigates the impact of enhanced regional meteorological fields on improvement of wind energy forecasting accuracy in the southwestern coast of the Korean Peninsula. To clarify the effect of detailed surface boundary data and application of analysis nudging technique on simulated meteorological fields, several WRF simulations were carried out. Case_LT, which is a simulation with high resolution terrain height and land use data, shows the most remarkable accuracy improvement along the shoreline mainly due to modified surface characteristics such as albedo, roughness length and thermal inertia. Case_RS with high resolution SST data shows accurate SST distributions compared to observation data, and they led to change in land and sea breeze circulation. Case_GN, grid nudging applied simulation, also shows changed temperature and wind fields. Especially, the application of grid nudging dominantly influences on the change of horizontal wind components in comparison with vertical wind component.
Kim, Ga-Ya;Chung, Chang-Sik;Ryu, Jae-Hong;Kim, Jeong-Ho
Journal of the Korean Association of Geographic Information Studies
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v.8
no.4
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pp.52-60
/
2005
This paper attempted to investigate not only the correlativity of land price and residential environment elements but also the effect that the residential environment elements influence on the land price, focusing on the Suyoung-Gu and Haeundae-Gu which are representative residential and waterfront area in Pusan. For this purpose, regression analysis and correlation analysis as the residential environment elements in independent variable and the land price in dependent variable were carried out. First of all, from the correlation analysis between the land price and the residential environment elements, it become clear that the variables such as the land use, the distance to arterial road and, the distance to subway station have high correlativity with land price in all the research area. Then from the individual power of explanation and accumulative power of explanation of the each variable to the land price through the regression analysis, it was become clear that 7 variables which are the land use, the distance to trunk road, the distance to subway station etc. have 67% of the power of explanation to land price at the Suyoung-Gu, and 50.5% at the Haeundae-Gu. Moreover, researchers had an special interest in the correlativity between the distance to the coastal line and land price as well as the power of explanation of the distance to the coastal line for the land price. It means that researchers expected the variable of the distance to the coastal line have a strong correlativity and high power of explanation for land price. However, from the regression analysis and correlation analysis, it was become clear that the variable of the distance to the coastal line have a weak correlativity, and low power of explanation which is just form 6.4% to 7.6% in all the research area. In other words, it might be said that the variable of the distance to the coastal line is not so important one to presume the land price.
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