• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.313-316
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• 2003

Growing urban areas modify patterns of local land use and land cover. Land use changes associated with an urban area can be extensive. One way to understand and document land use change and urbanization is to establish benchmark maps compiled from satellite imagery The use of satellite imagery for monitoring urban growth has been widely demonstrated. Multi-temporal LANSAT TM image data has created the potential for monitoring urban change and land cover identification. In this study, for extracting urban boundary GLCM method and visual interpretation were used in CORONA imagery and SPOT imagery.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.3
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• pp.91-96
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• 2010

Depending on the transportation, information and communication technology development, urban such as the superficial spreading and the changing structure of internal space of the organism has various shape and speed of the changes. In particular, the main cause of these changes is the development of the traffic and this transport system is having a close connection with land use. This study presents the results about characteristics and changes of noise on each land use zoning. Therefore the result shows that the measured data could be used to evaluate noise distributions on urban land use and then make up the basis process for producing noise maps of land use zoning.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.47-49
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• 2003

Automatic land use and land cover change (LUCC) detection via remotely sensed imagery has a wide application in the area of LUCC research, nature resource and environment monitoring and protection. Under the condition that one time (T1) data is existed land use and land cover maps, and another time (T2) data is remotely sensed imagery, how to detect change automatically is still an unresolved issue. This paper developed a land use and land cover class knowledge guided method for automatic change detection under this situation. Firstly, the land use and land cover map in T1 and remote sensing images in T2 were registered and superimposed precisely. Secondly, the remotely sensed knowledge database of all land use and land cover classes was constructed based on the unchanged parcels in T1 map. Thirdly, guided by T1 land use and land cover map, feature statistics for each parcel or pixel in RS images were extracted. Finally, land use and land cover changes were found and the change class was recognized through the automatic matching between the knowledge database of remote sensing information of land use & land cover classes and the extracted statistics in that parcel or pixel. Experimental results and some actual applications show the efficiency of this method.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.383-387
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• 2007

The improved accuracy of the Land Cover/Land Use Map constructed using Hyperspectal Satellite Image and the possibility of real time classification of Land Use using optimal Band Selective Factor enable the change detection from automatic classification using the existed Land Cover/Land Use Map and the newly acquired Hyperspectral Satellite Image. In this study, the effective analysis techniques for automatic generation of training regions, automatic classification and automatic change detection are proposed to minimize the expert's interpretation for automatic update of the Land Cover/Land Use Map. The proposed algorithms performed successfully the automatic Land Cover/Land Use Map construction, automatic change detection and automatic update on the image which contained the changed region. It would increase applicability in actual services. Also, it would be expected to present the effective methods of constructing national land monitoring system.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.470-472
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• 2003

The primary goal in this paper is to analyze urban growth patterns using multi-temporal remote sensing images and geographic information data. In order to accomplish this purpose, firstly data pre-processing is carried out, and then land-use maps are generated with ancillary data source by heads-up on-screen digitizing. Lastly, using the results of the previous stages, the patterns of land-use and urban changes are monitored by the proposed scheme. In this research, using the multi-temporal images and geographic information data, monitoring of urban growth was carried out with the application of urban land-use changes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.275-284
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• 2023

Land monitoring involves systematically understanding changes in land use, leveraging spatial information such as satellite imagery and aerial photographs. Recently, the integration of deep learning technologies, notably object detection and semantic segmentation, into land monitoring has spurred active research. This study developed a web service to facilitate such integrations, allowing users to analyze aerial and drone images using CNN models. The web service architecture comprises AI, WEB/WAS, and DB servers and employs three primary deep learning models: DeepLab V3, YOLO, and Rotated Mask R-CNN. Specifically, YOLO offers rapid detection capabilities, Rotated Mask R-CNN excels in detecting rotated objects, while DeepLab V3 provides pixel-wise image classification. The performance of these models fluctuates depending on the quantity and quality of the training data. Anticipated to be integrated into the LX Corporation's operational network and the Land-XI system, this service is expected to enhance the accuracy and efficiency of land monitoring.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.402-405
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• 2008

This paper is a proposal of Sentinel Asia for Environment (SAFE). The essential to this project is to help environmental agencies in Asia to set up an environmental monitoring system with satellite observation data. It is focused on an environmental issues originated from anthropogenic events detected as land cover and land use change in Asians' daily human life including; agriculture, global warming gas, urban environment and forest resources. It is leaded by Japan Aerospace Exploration Agency (JAXA) along with University of Tokyo and Asian Institute of Technology in Thailand under the umbrella of Sentinel Asia which is dedicated to disaster monitoring issues. It is expected to initiate a information outgoing through WWW for Asian countries to set up their national land information system focusing on environmental changes.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.6
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• pp.415-426
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• 1997

Some arguments have been about over the representativeness of government-run air quality monitoring stations among scholars and non-governmental organizations (NGOs). However, it is not a simple problem to move monitoring stations because of continuity of data and high cost. So it is necessary to complement the monitoring data if it do not represent the ambient air quality properly. The purpose of this study was to evaluate the representativeness of some monitoring stations using passive $NO_2$ samplers and to find a complementary method from linear regression. Two stations were chosen for the evaluation: Shinlim Station was one of the most controversial stations in Seoul and Banpo Station had the best reputation. Air qualities were surveyed at seven points around each monitoring station with consideration of land use and distance. The ratios of the average $NO_2$ levels of the areas to these at the monitoring stations were 1.59 for Shinlim Station and 1.03 for Banpo Station. The differences between the average $NO_2$ levels and those at the monitoring stations were 10.75 ppb for Shilim Station and 0.34 ppb for Banpo Station. The correlation coefficients between the two levels were 0.7668 for Shinlim and 0.7662 for Banpo. The average coefficients of determination $(R^2)$ were 0.61 for Shinlim and 0.61 for Banpo. The Shinlim Station could not represent the air quality of Shinlim-Dong good because it is located in a green area at an outskirt of Shinlim-Dong. But the Banpo Station located in a central residential area of Banpo-Dong showed a fair representativeness. However, air quality turned out to be different with land use such as residential area, green area or road: the air quality data from a monitoring station located at a certain land use should not be interpreted as representing the air quality at any sites around the station. Equations to predict the average $NO_2$ levels of each area from the data from the monitoring stations were presented based on linear regression.

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.E
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• pp.63-71
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• 1995

Three types of land use were investigated to describe the effect of land use on both surface and ground water quality. Typical land uses of a grazing pasture, Sudan grass field and paddy in Kangwon province were selected and flumes and monitoring wells were installed. Land managements were carefully monitored, water samples were collected periodically and analyzed with respect to nitrate, TP and TKN at a laboratory of Kangwon Provincial Institute of Health and Environment from August, 1993 to May, 1994. Runoff from the pasture was formed mostly with seeping subsurface flow in the lower areas of the pasture. A few overland flows were observed during heavy storms, and when it occurred, runoff increased sharply. For the Sudan grass field, runoff was formed with overland flow. Nitrate concentration in runoff from both land uses seemed not affected by runoff and ranged from 0.241 to 4.137mg'/1. TP and TKN concentrations from the pasture were affected by overland flow. When overland flow occurred, TP and TKN concentrations abruptly increased to 5.726 and 12.841mg/1, respectively, from less than 1.0mg/l. However, these concentrations from the Sudan grass field were quite stable ranging from 0.191 to 0.674mg/l for TP and 0A70 and 1.650mg/l for TKN. Nitrate concentration was significantly affected by land use(Sudan grass field) and the concentration increase reached about 2mg/l per lOOm ground water flow. Nitrate concentration from a well located in the middle of rice fields also was significantly higher than that measured from a well located relatively undisturbed mountain toe area. TP and TKN concentrations in shallow ground water affected by the depth of the monitoring wells. The deeper the monitoring wells, the less TP and TKN concentrations were measured.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.09a
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• pp.651-659
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• 2009

There are a great number of man-made and natural slopes in many parts of the world including Hong Kong and Mainland China. For example, there are over 40,000 slopes in Hong Kong registered by the Hong Kong Government. Landslides due to slope failures can often cause catastrophes that involve the loss of both lives and important facilities. GPS has been demonstrated to have great potentials for use in monitoring slope stability and landslides. However, the high hardware cost of GPS has limited the wide spread use of GPS for such applications. The multi-antenna GPS technology initiated by the research group and our collaborators has significantly reduced the cost of GPS and provided a solution to a number of associated problems such as data management and power supply. This paper discusses practical applications of multi-antenna GPS technology in slope monitoring, including system design, setting up, data transmission and management, and data quality analysis and control. Some slope monitoring examples are given to illustrate the points discussed.