• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.99-107
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• 2020

An underground integrated map is being built for underground safety management and is being updated periodically. The map update proceeds with the procedure of deleting all previously stored objects and saving newly entered objects. However, even unchanged objects are repeatedly stored, deleted, and stored. That causes the delay of the update time. In this study, in order to shorten the update time of the integrated map, an updated object and an unupdated object are separated, and only updated objects are reflected in the underground integrated map, and a system implementing this technology is described. For the updated object, an object comparison method using the center point of the object is used, and a quad tree is used to improve the search speed. The types of updated objects are classified into addition and deletion using the shape of the object, and change using its attributes. The proposed system consists of update object detection, extraction, conversion, storage, and history management modules. This system has the advantage of being able to update the integrated map about four times faster than the existing method based on the data used in the experiment, and has the advantage that it can be applied to both ground and underground facilities.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.4 s.34
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• pp.67-73
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• 2005

The urbanization of Korea has been rapidly progressed since 1960, but satellite imagery have provided the information only after 1975. Recently released CORONA imagery is one of the few source of satellite image which can provide 1960's topographic information of the Korean Peninsular. It can be applied to change detection in various fields such as urban, forest, and environmental planning. In this research mosaic image of past Korean Peninsular using CORONA imagery in the 1960s were generated. A polynomial equation and a modified collinearity equation were applied for geo-referencing and a comparative analysis was conducted. In this research the 2nd polynomial equations were used for geo-referencing of CORONA imagery. After carrying out geo-referencing, mosaic image was generated using Erdas Imagine. It is assumed that this result image is very useful for various fields such as generation of thematic maps, urban planning, and change detection.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.18 no.1
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• pp.51-57
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• 2000

With the emergence of laser mapping systems, higher resolution DTM of urban area can be acquired and can be used to generate precise orthoimage. But, when the conventional orthoimage generation methods are applied to the area containing features with height difference such as cliffs, bridges, banks. elevated highways and buildings, they cause problems such as occlusion and double mapping. Therefore, this study proposes a new algorithm by modifying and refining conventional orthoimage generation methods. With this algorithm, areas which have occlusion are detected from the base image using camera orientation parameters and DTM. Also, detected areas are restored using alternative images which does not have occlusion in that area. This study can be distinguished from the other studies in the aspects that the proposed algorithm in this paper doesn't need information on building and that uses DTM data and orientation parameters.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.3
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• pp.60-70
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• 1999

The purpose of this study is to analyze the spatial change of water quality pollutant in the upper-stream of Kumho River basin. For this purpose, it compared with ground survey data of water quality measurement, using GIS and Landsat TM image, and then constructed a database of water quality pollutants in the watershed by Arc/Info. Also the land cover classification maps of 1985 and 1997 were prepared using maximum likelihood classification. This study detected and analysed the classified images to produce the area of land cover change per sub-basin. In addition, choropleth maps were prepared with spatial change value of water quality pollutants, and overlay analysis was carried out with weight score for each layer. The results of this study revealed that population, animals and fruit orchards were main factors in the spatial change of water pollution of Kumho River basin. The Comparision of pollutions by sub-basins showed a high pollution value in Daechang-chun and Omok -chun stream which follows through the urban area.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.2
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• pp.197-206
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• 2010

Recently, developed countries have continuously been trying to recognize many issues about heat island in urban area and to make up countermeasures for them. This research is designed to extract change of land cover in the area under condition of land development with satellite images and to analyze its effect on the heat change in there. Heat change upon change of land cover in daejeon was analyzed with the four Landsat satellite images taken in April 1985, August 1994, May 2001, and May 2009. In order to measure the temperature on the surface in the city, the land surface temperature was produced with Landsat TM Band 6. Heat change is to detected with it. As a result, The urban area has been increased up to 23.59 percent. On the other hand, the forest area has been decreased up to 27.91%. Due to the urbanization, the temperature on the surface in urban center was higher than surrounding area. In that case, the temperature of urban center area was higher 2.4 to $5.7^{\circ}C$ compared with the forest area.

• Journal of the Korean Geographical Society
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• v.52 no.1
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• pp.123-141
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• 2017

This study predicted urban green spaces for 2020 based on two scenarios keeping or freeing the green-belt in the Daegu metropolitan city using a hybrid Cellular Automata(CA)-Markov model and analyzed the spatial dynamics of urban green spaces between 2009 and 2020 using a land cover change detection technique and spatial metrics. Markov chain analysis was employed to derive the transition probability for projecting land cover change into the future for 2020 based on two land cover maps in 1998 and 2009 provided by the Ministry of Environment. Multi-criteria evaluation(MCE) was adopted to develop seven suitability maps which were empirically derived in relation to the six restriction factors underlying the land cover change between the years 1998 and 2009. A hybrid CA-Markov model was then implemented to predict the land cover change over an 11 year period to 2020 based on two scenarios keeping or freeing the green-belt. The projected land cover for 2009 was cross-validated with the actual land cover in 2009 using Kappa statistics. Results show that urban green spaces will be remarkably fragmented in the suburban areas such as Dalseong-gun, Seongseo, Ansim and Chilgok in the year 2020 if the Daegu metropolitan city keeps its urbanization at current pace and in case of keeping the green-belt. In case of freeing the green-belt, urban green spaces will be fragmented on the fringes of the green-belt. It is thus required to monitor urban green spaces systematically considering the spatial change patterns identified by this study for sustainably managing them in the Daegu metropolitan city in the near future.

• Journal of the Korean association of regional geographers
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• v.23 no.1
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• pp.136-150
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• 2017

This study analyzed the spatial change of urban green spaces in Daegu from 1989 to 2009 using cell based spatial metrics. To do so, the conversion process of land covers during the past 20 years was explored using a land cover change detection matrix. The synoptic analysis with a moving window sampling strategy was conducted to quantify cell based spatial metrics related to size, shape, cohesion, and diversity and to explain the spatial change at the local level. Difference maps were then generated by subtracting the 1989 maps of spatial metrics from the 1998 maps and the 1998 maps from the 2009 maps. The gradient analysis was performed to identify the directional change of spatial metrics along an urban development axis in Daegu. The results from this study show that urban green spaces in Daegu during the past 20 years have been gradually fragmented around the new town housing development districts such as Dalseong-gun, Seongseo, and Ansim. Forests were most prominently fragmented in the Hwawon area while most rapidly in the Chilgok area. Grasslands were largely fragmented in many areas due to the decrease in size and cohesion indices and most fragmented in the Ansim area. The spatial pattern of the decreased and fragmented urban green spaces identified by this study can be used as a base data for establishing the environment-friendly urban development strategy in Daegu.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.09a
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• pp.119-125
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• 2010

본 연구에서는 항공 라이다 데이터로부터 지표의 유형을 분류하는 과정에서 필요한 처리시간을 감소시켜 보다 효율적인 지형 분류가 가능하도록 타일 단위의 샘플링을 이용한 지형 분류 기법을 제안하였다. 또한 실험을 통하여 샘플링 정도에 따라 정확도와 시간효율을 비교분석하여 최적의 샘플링 정도를 제시하였다. 본 연구에서 제안한 타일 단위의 샘플링을 이용한 지형 분류기법을 이용해 자연재해내 도시 구조 변화 등의 지형정보의 변화를 탐지하기 위한 모니터링 목적으로 활용할 경우에 지형분류의 정확도 손실을 최소화하면서 빠른 처리가 가능하기 때문에 실시간 서비스가 가능해 질 수 있다.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1685-1695
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• 2021

To generate a deep learning model with high performance, a large training dataset should be required. However, it requires a lot of time and cost to generate a large training dataset in remote sensing. Therefore, the importance of transfer learning of deep learning model using a small dataset have been increased. In this paper, we performed transfer learning of trained model based on open datasets by using orthoimages and digital maps to detect changes of building objects in multitemporal orthoimages. For this, an initial training was performed on open dataset for change detection through the HRNet-v2 model, and transfer learning was performed on dataset by orthoimages and digital maps. To analyze the effect of transfer learning, change detection results of various deep learning models including deep learning model by transfer learning were evaluated at two test sites. In the experiments, results by transfer learning represented best accuracy, compared to those by other deep learning models. Therefore, it was confirmed that the problem of insufficient training dataset could be solved by using transfer learning, and the change detection algorithm could be effectively applied to various remote sensed imagery.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.765-779
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• 2022

This study evaluates the accuracy in identifying the burned area in South Korea using multi-temporal data from Sentinel-2 MSI and Landsat 8/9 OLI. Spectral indices such as the Difference Normalized Burn Ratio (dNBR), Relative Difference Normalized Burn Ratio (RdNBR), and Burned Area Index (BAI) were used to identify the burned area in the March 2022 forest fire in Uljin. Based on the results of six indices, the accuracy to detect the burned area was assessed for four satellites using Sentinel-2 and Landsat 8/9, respectively. Sentinel-2 and Landsat 8/9 produce images every 16 and 10 days, respectively, although it is difficult to acquire clear images due to clouds. Furthermore, using images taken before and after a forest fire to examine the burned area results in a rapid shift because vegetation growth in South Korea began in April, making it difficult to detect. Because Sentinel-2 and Landsat 8/9 images from February to May are based on the same date, this study is able to compare the indices with a relatively high detection accuracy and gets over the temporal resolution limitation. The results of this study are expected to be applied in the development of new indices to detect burned areas and indices that are optimized to detect South Korean forest fires.