• Korean Journal of Agricultural Science
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• v.39 no.1
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• pp.87-95
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• 2012

Land surface temperature (LST) is an important factor in human health, thermal environment, heat balance, global change studies, and as control for climate change. The objective of this study was to assess the influence of Urban Heat Island (UHI) Effects on the LST and NDVI in Cheongju, Korea. The aim was to evaluate the effect of urban thermal environment for LST comparison of satellite-derived and in situ measured temperature. In this study, LANDSAT TM and KOMPSAT scene were used. The results indicated that the minimum LST is observed over dense forest as about $21{\sim}25^{\circ}C$ and maximum LST is observed over industrial area of about $28{\sim}32^{\circ}C$. The estimated LST showed that industrial area, bare soils and built-up areas exhibit higher surface temperatures, while forest, water bodies, agricultural croplands, and dense vegetations have lower surface temperatures during the summer daytime. Result corroborates the fact that LST over land use/land cover (LULC) types are greatly influenced by the amount of vegetation and water bodies present. The LST of industrial area and urban center is higher than that of suburban area, so it is clearly proved that there are obvious UHIE in Cheongju.

• Land and Housing Review
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• v.2 no.4
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• pp.439-452
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• 2011

The goal of this research is to suggest the desirable directions of the land policies implement system based on analysis of existing those of Korea with the paradigm shift of land policies. We classify the land policies into land ownership, land use, land development and land management ones, and then analyze their implement system characteristics. The results are follows : firstly, the land policies implement systems have been set to large scale and rapid development. Secondly, although the systems have been specialized by their areas, the comprehensive manage systems for the harmony between development and conservation are lacking. Thirdly, the parts of the central government powers related to land use has been hand covered to local governments. And the participations of residences private companies have enlarged in the land development. Fourthly, the purposes of the information management on land use have been changed from tax collection into planned land use, but the information management has not met the need of planned land use. This study shows that firstly, the implement system focusing on large development projects might be no longer effective because of high possibility of the property prices stabilization, so moderately small ones must be found. Secondly, the system cope with the climate change and to realize the efficient utility of land is needed. Thirdly, it is necessary to take the actual measures to participate a variety of subjects. Fourthly, the system modification of the land information manage system as land policies infra is also needed to establish integral land policies.

• Journal of Ecology and Environment
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• v.30 no.1
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• pp.101-105
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• 2007

Lammas growth, a rare phenomenon for Korean red pine (Pinus densiflora), occurred in 2006. Lammas shoots showed higher frequency and longer length in Seoul's hotter urban center than in urban boundary or suburban forest sites. Frequency and length showed a close correlation with urbanization density and vegetation cover expressed in NDVI. Air temperature in the late summer of 2006 was more than $1^{\circ}C$ higher than an average year. Of the predominant environmental signals that modulate bud flush, only temperature changed significantly during the year. Differences in temperature between the urban centers, urban boundaries and suburban forests correlated with varying land-use density. The rise in temperature likely spurred lammas growth of the Korean red pine. Symptoms of climate change are being detected throughout the world, and its consequences will be clearer in the future. Considerate interest in the responses of ecological systems to the variable changes is required to prepare for unforeseeable crises. Monitoring of diverse ecological phenomena at Long Term Ecological Research sites could offer harbingers of change.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.36-51
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• 2011

Global climate change is disturbing the water circulation balance by changing rates of precipitation, recharge and discharge, and evapotranspiration. Groundwater, which occupies a considerable portion of the world's water resources, is related to climate change via surface water such as rivers, lakes, and marshes. In this study, the authors selected a relevant climate change scenario, A1B from the Special Report on Emission Scenario (SRES) which is distributed at Korea Meteorological Administration. By using data on temperature, rainfall, soil, and land use, the groundwater recharge rate for the research area was estimated by periodically and embodied as geographic information system (GIS). In order to calculate the groundwater recharge quantity, Visual HELP3 was used as main model, and the physical properties of weather, temperature, and soil layers were used as main input data. General changes to water circulation due to climate change have already been predicted. In order to systematically solve problems of ground circulation system, it may be urgent to recalculate the groundwater recharge quantity and consequent change under future climate change. The space-time calculation of changes of the groundwater recharge quantity in the study area may serve as a foundation to present additional measures to improve domestic groundwater resource management.

• Journal of Korean Society of Rural Planning
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• v.28 no.2
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• pp.87-96
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• 2022

As part of strengthening energy security and responding to climate change, the government has promoted various renewable energy measures to increase the development of renewable energy facilities. As a result, small-scale solar installations in rural areas have increased rapidly. The number of complaints from local residents is increasing. Therefore, in this study, deep learning technology is applied to high-resolution aerial images on the internet to detect solar power plants installed in rural areas to determine whether or not solar power plants are installed. Specifically, I examined the solar facility detector generated by training the YOLO(You Only Look Once) v2 object detector and looked at its usability. As a result, about 800 pieces of training data showed a high object detection rate of 93%. By constructing such an object detection model, it is expected that it can be utilized for land use monitoring in rural areas, and it can be utilized as a spatial data construction plan for rural areas using technology for detecting small-scale agricultural facilities.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.269-282
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• 2023

The purpose of this study was to construct land cover maps using a deep learning model and to select the optimal deep learning model for land cover classification by adjusting the dataset such as input image size and Stride application. Two types of deep learning models, the U-net model and the DeeplabV3+ model with an Encoder-Decoder network, were utilized. Also, the combination of the two deep learning models, which is an Ensemble model, was used in this study. The dataset utilized RapidEye satellite images as input images and the label images used Raster images based on the six categories of the land use of Intergovernmental Panel on Climate Change as true value. This study focused on the problem of the quality improvement of the dataset to enhance the accuracy of deep learning model and constructed twelve land cover maps using the combination of three deep learning models (U-net, DeeplabV3+, and Ensemble), two input image sizes (64 × 64 pixel and 256 × 256 pixel), and two Stride application rates (50% and 100%). The evaluation of the accuracy of the label images and the deep learning-based land cover maps showed that the U-net and DeeplabV3+ models had high accuracy, with overall accuracy values of approximately 87.9% and 89.8%, and kappa coefficients of over 72%. In addition, applying the Ensemble and Stride to the deep learning models resulted in a maximum increase of approximately 3% in accuracy and an improvement in the issue of boundary inconsistency, which is a problem associated with Semantic Segmentation based deep learning models.

• Proceedings of the Korean Society of Crop Science Conference
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• 2005.08a
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• pp.75-87
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• 2005

Remote sensing(RS)- and geographic information system(GIS)-based information management to measure and assess agri-environment schemes, and to quantify and map environment indicators for nature and land use, climate change, air, water and energy balance, waste and material flow is in high demand because it is very helpful in assisting decision making activities of farmers, government, researchers, and consumers. The versatility and ability of RS and GIS containing huge soil database to assess agricultural environment spatially and temporally at various spatial scales were investigated. Spectral and microwave observations were carried out to characterize crop variables and soil properties. Multiple sources RS data from ground sensors, airborne sensors, and also satellite sensors were collected and analyzed to extract features and land cover/use for soils, crops, and vegetation for support precision agriculture, soil/land suitability, soil property estimation, crop growth estimation, runoff potential estimation, irrigated and the estimation of flooded areas in paddy rice fields. RS and GIS play essential roles in a management and monitoring information system. Biosphere-atmosphere interection should also be further studied to improve synergistic modeling for environment and sustainability in agri-environment schemes.

• Journal of Korea Water Resources Association
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• v.53 no.6
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• pp.427-436
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• 2020

It is uncertain how global climate change will influence future drought characteristics over the Korean peninsula. This study aims to project the future droughts using climate change and land use change scenarios over the Korean peninsula with the land surface modeling system, i.e., Weather Research and Forecasting Model Hydrological modeling system (WRF-Hydro). The Representative Concentration Pathways (RCPs) 2.6 and 8.5 are used as future climate scenarios and the Shared Socio-economic Pathways (SSPs), specifically SSP2, is adopted for the land use scenario. The using Threshold Level Method (TLM), we identify future hydrological and ecological drought events with runoff and Net Primary Productivity (NPP), respectively, and assess drought characteristics of durations and intensities in different scenarios. Results show that the duration of drought is longer over RCP2.6-SSP2 for near future (2031-2050) and RCP8.5-SSP2 (2080-2099) for the far future for hydrological drought. On the other hand, RCP2.6-SSP2 for the far future and RCP8.5-SSP2 for the near future show longer duration for ecological drought. In addition, the drought intensities in both hydrological and ecological drought show different characteristics with the drought duration. The intensity of the hydrological droughts was greatly affected by threshold level methods and RCP2.6-SSP2 for far future shows the severest intensity. However, for ecological drought, the difference of the intensity among the threshold level is not significant and RCP2.6-SSP2 for near future and RCP2.6-SSP2 for near future show the severest intensity. This study suggests a possible future drought characteristics is in the Korea peninsula using combined climate and land use changes, which will help the community to understand and manage the future drought risks.

• Journal of Environmental Science International
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• v.22 no.5
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• pp.625-638
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• 2013

Recently, the occurrences of droughts have been increased because of global warming and climate change. Water resources that mostly rely on groundwater are particularly vulnerable to the impact of precipitation variation, one of the major elements of climate change, are very sensitive to changes in the seasonal distribution as well as the average annual change in the viewpoint of agricultural activity. In this study, the status of drought for the present and future on Jeju Island which entirely rely on groundwater using SPI and PDSI were analyzed considering regional distribution of crops in terms of land use and fluctuation of water demand. The results showed that the precipitation distribution in Jeju Island is changed in intensity as well as seasonal variation of extreme events and the amount increase of precipitation during the dry season in the spring and fall indicated that agricultural water demand and supply policies would be considered by regional characteristics, especially the western region with largest market garden crops. Regarding the simulated future drought, the drought would be mitigated in the SPI method because of considering total rainfall only excluding intensity variation, while more intensified in the PDSI because it considers the evapotranspiration as well as rainfall as time passed. Moreover, the drought in the northern and western regions is getting worse than in the southern region so that the establishment of regional customized policies for water supply in Jeju Island is needed.

• Journal of Environmental Impact Assessment
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• v.20 no.2
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• pp.107-121
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• 2011

To assess the impact of climate change on water quality in an impounded river basin, this study estimated future air temperature and rainfall in the years of 2020, 2050 and 2080 by statistically downscaling the simulation results from two GCM models combined with two emission scenarios (A2 and B1). Both scenarios were selected from the Special Report on Emission Scenarios (SRES) suggested by IPCC. The A2 scenario represents an extreme condition whereas the B1 scenario represents a clean and energy efficient condition which is similar to that of study basin. With the results of estimated climate factors and land use data, the discharge and the concentrations of BOD, TN and TP in the Andong dam basins were simulated using the SWAT model. The change in BOD concentration for the B1 emission scenario was greater than the A2 scenario in the annual increase range and the pollution level. The concentration of TN was decreased during March? June which is drought period and increased again afterward. In contrast to TN, the concentration of TP was generally decreased. The change in TP concentration was greater for the B1 scenario than the A2 scenario.