• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4D
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• pp.569-577
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• 2008

The purpose of this study is focused on the development of compound classification process by mixing multitemporal data and annexing a specific image enhancement technique with a specific image classification algorithm, to gain more accurate land information from satellite imagery. That is, this study suggests the classification process using canonical correlation classification technique after principal component analysis for the mixed multitemporal data. The result of this proposed classification process is compared with the canonical correlation classification result of one date images, multitemporal imagery and a mixed image after principal component analysis for one date images. The satellite images which are used are the Landsat 5 TM images acquired on July 26, 1994 and September 1, 1996. Ground truth data for accuracy assessment is obtained from topographic map and aerial photograph, and all of the study area is used for accuracy assessment. The proposed compound classification process showed superior efficiency to appling canonical correlation classification technique for only one date image in classification accuracy by 8.2%. Especially, it was valid in classifying mixed urban area correctly. Conclusively, to improve the classification accuracy when extracting land cover information using Landsat TM image, appling canonical correlation classification technique after principal component analysis for multitemporal imagery is very useful.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.1
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• pp.62-74
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• 2004

Baekdu-daegan is the greatest mountain chain as well as the major ecological axis of the Korean Peninsula. In recent year, however, this area is faced with the various kinds of developmental urge. To cope adequately with these problems, this study was executed to prepare synthetic and systematic management with conservation-oriented strategy for Baekdu-daegan and to suggest spatially definite zoning for the managerial area. This study is to take into consideration the traditional concepts of stream and watershed as well as the actual disturbance on Baekdu-daegan area. The study area is selected with semi-mountainous type, from Namdeokyusan to Sosagogae. To propose the process for reasonably establishing the managerial boundary adjacent to the Ridges, the analysis was carried out that ArcGIS was mainly used for its analysis with digital maps, Landsat TM image and ArcGIS Hydro Model. Landsat TM image was classified by 5 land use types such as cultivated land, urban area, barren area, water body and forest. Based on these analyses results, the managerial boundaries as alternatives from the Ridges were produced by watershed expansion process, and used for tracing the changes of areal ratio of various land use types to the relevant watersheds to search out the adequate managerial boundary. The results show that watershed expansion process could be effective tool for establishing the managerial boundary, and eighth expanded watershed toward Muju-Gun(west) and fifth expanded watershed toward Geochang-Gun(east) might be included for the adequate managerial boundary of the case site.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.262-266
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• 1999

Several commercial companies that plan to provide improved panchromatic and/or multi-spectral remote sensor data in the near future are suggesting that merge datasets will be of significant value. This study evaluated the utility of one major merging process-process components analysis and its inverse. The 6 bands of 30$\times$30m Landsat TM data and the 10$\times$l0m SPOT panchromatic data were used to create a new 10$\times$10m merged data file. For the image classification, 6 bands that is 1st, 2nd, 3rd, 4th, 5th and 7th band may be used in conjunction with supervised classification algorithms except band 6. One of the 7 bands is Band 6 that records thermal IR energy and is rarely used because of its coarse spatial resolution (120m) except being employed in thermal mapping. Because SPOT panchromatic has high resolution it makes 10$\times$10m SPOT panchromatic data be used to classify for the detailed classification. SPOT as the Landsat has acquired hundreds of thousands of images in digital format that are commercially available and are used by scientists in different fields. After the merged, the classifications used supervised classification and neural network. The method of the supervised classification is what used parallelepiped and/or minimum distance and MLC(Maximum Likelihood Classification) The back-propagation in the multi-layer perception is one of the neural network. The used method in this paper is MLC(Maximum Likelihood Classification) of the supervised classification and the back-propagation of the neural network. Later in this research SPOT systems and images are compared with these classification. A comparative analysis of the classifications from the TM and merged SPOT/TM datasets will be resulted in some conclusions.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.671-674
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• 2005

Atmospheric correction over the ocean part is more important than that over the land because the signal from the ocean is very small about one tenth of that reflected from land. In this study, the Spectral Shape Matching Method (SSMM) developed by Ahn and Shanmugam (2004) is evaluated using Landsat imagery acquired over the highly turbid Saemangeum Coastal Area. The result of SSMM is compared with COST model developed by Chavez (1991 and 1997). In principle, SSMM is simple and easy to implement on any satellite imagery, relying on both field and image properties. To assess the potential use of these methods, several field campaigns were conducted in the Saemangeum coastal area corresponding with Landsat-7 satellite's overpass on 29 May 2005. In-situ data collected from the coastal waters of Saemangeum using optical instruments (ASD field spectroradiometer) consists of ChI, Ap, SS, aooM, F(d). In order to perform SSMM, we use the in-situ water-leaving radiance spectra from clear oceanic waters to estimate the the path radiance from total signal recorded at the top of the atmosphere (TOA), due to the reason that the shape of clear water-leaving radiance spectra is nearly stable than turbid water-leaving radiance spectra. The retrieved water-leaving radiance after subtraction of path signal from TOA signal in this way is compared with that estimated by COST model. The result shows that SSMM enabled retrieval of water-leaving radiance spectra that are consistent with in-situ data obtained from Saemangeum coastal waters. The COST model yielded significantly high errors in these areas.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1691-1707
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• 2022

Cheonji Lake, the caldera of Baekdu Mountain, located on the border of the Korean Peninsula and China, alternates between melting and freezing seasonally. There is a magma chamber beneath Cheonji, and variations in the magma chamber cause volcanic antecedents such as changes in the temperature and water pressure of hot spring water. Consequently, there is an abnormal region in Cheonji where ice melts quicker than in other areas, freezes late even during the freezing period, and has a high-temperature water surface. The abnormal area is a discharge region for hot spring water, and its ice gradient may be used to monitor volcanic activity. However, due to geographical, political and spatial issues, periodic observation of abnormal regions of Cheonji is limited. In this study, the degree of ice change in the optimal region was quantified using a Landsat -5/-7/-8 optical satellite image and a Modified U-Net regression model. From January 22, 1985 to December 8, 2020, the Visible and Near Infrared (VNIR) band of 83 Landsat images including anomalous regions was utilized. Using the relative spectral reflectance of water and ice in the VNIR band, unique data were generated for quantitative ice variability monitoring. To preserve as much information as possible from the visible and near-infrared bands, ice gradient was noticed by applying it to U-Net with two encoders, achieving good prediction accuracy with a Root Mean Square Error (RMSE) of 140 and a correlation value of 0.9968. Since the ice change value can be seen with high precision from Landsat images using Modified U-Net in the future may be utilized as one of the methods to monitor Baekdu Mountain's volcanic activity, and a more specific volcano monitoring system can be built.

• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.287-299
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• 2017

The Southern Volcanic Zone (SVZ) of Chile consists of many volcanoes, including the Mt.Villarrica and Mt.Llaima, and the two volcanoes are covered with snow at the top of Mountain. The purpose of this study is to analyze the relationship between the ice caps and the volcanic activity of the two volcanoes for 25 years by using the satellite image data are available in a time series. A total of 60 Landsat-5 TM and Landsat-7 ETM + data were used for the study from September 1986 to February 2011. Using NDSI (Normalized Difference Snow Index) algorithm and SRTM DEM, snow cover and snowline were extracted. Finally, the snow cover area, lower-snowline, and upper-snowline, which are quantitative indicators of snow cover change, were directly or indirectly affected by volcanic activity, were extracted from the satellite images. The results show that the volcanic activity of Villarrica volcano is more than 55% when the snow cover is less than 20 and the lower-snowline is 1,880 m in Llaima volcano. In addition, when the upper-snowline of the two volcanoes is below -170m, it can be confirmed that the volcano is differentiated with a probability of about 90%. Therefore, the changes in volcanic snowfall are closely correlated with volcanic activity, and it is possible to indirectly deduce volcanic activity by monitoring the snow.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1935-1943
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• 2022

The development and application of a high-resolution soil moisture mapping method using satellite imagery has been considered one of the major research themes in remote sensing. In this study, soil moisture mapping in the test area of Jeju Island was performed. The soil moisture was calculated with optical images using linearly adjusted Synthetic Aperture Radar (SAR) polarization images and incident angle. SAR Backscatter data, Analysis Ready Data (ARD) provided by Google Earth Engine (GEE), was used. In the soil moisture processing process, the optical image was applied to normalized difference vegetation index (NDVI) by surface reflectance of KOMPSAT-3 satellite images and the land cover map of Environmental Systems Research Institute (ESRI). When the SAR image and the optical images are fused, the reliability of the soil moisture product can be improved. To validate the soil moisture mapping product, a comparative analysis was conducted with normalized difference water index (NDWI) products by the KOMPSAT-3 image and those of the Landsat-8 satellite. As a result, it was shown that the soil moisture map and NDWI of the study area were slightly negative correlated, whereas NDWI using the KOMPSAT-3 images and the Landsat-8 satellite showed a highly correlated trend. Finally, it will be possible to produce precise soil moisture using KOMPSAT optical images and KOMPSAT SAR images without other external remotely sensed images, if the soil moisture calculation algorithm used in this study is further developed for the KOMPSAT-5 image.

• Korean Journal of Remote Sensing
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• v.2 no.2
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• pp.79-94
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• 1986

TM data, which have better resolution in spatial and spectral than MSS data, were used for this study, and several Image Processing Techniques (IPT) were examined for finding the best IPT to fit to lineament extraction and mineralized zone mapping. The Ryeongnam area was selected as test area, because the area is one of major mineralized zones in Korea and its hydrothermal alteration zone is wider and deeper than other areas. The spatial filtering method is most optimum one for limeament extraction: that is, the directional spatial filtering is most efficient to detect N-S, E-W direction lineaments on the image, and the high boost filtering can be applied for mapping all direction lineaments. The ratio method was selected for detecting altered zone. It is possible to make several tens combinations in ratio with 7 bands of TM data, but considering spectral characteristics of each band of TM to the geological meterials and vegetation, the band 4/band 3(A), band 5/band 7(B), and B/A ratio methods were chosen among them. The 5/7 ratio image did not show clearly the altered area due to noise from vegetation cover, so the 4/3 ratio imae was used for trying to decrease the effect of vegetation. As a result the B/A ratio image showed quite nicely the altered zone of the test area. In conclusion, the spatial filtering is the best image processing techniques for lineament mapping, and the B/A ratio image in TM data is useful for the mineralized zone mapping.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.355-355
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• 2011

토지피복의 분류는 토지표면의 물리적인 지표면의 상태를 나타내는 자료로 환경, 행정, 수자원, 재해 등 다방면으로 이용되고 있다. 특히 수자원과 관련하여 식생의 증산과 토양의 증발을 통칭하는 증발산과 유출, 토양수분 등과 연관되어 있다. 광범위한 토지피복의 산정에는 경제성 및 주기성 등의 장점으로 인하여 인공위성 영상을 이용하는 기법이 적합하다. 위성영상분류법은 훈련지역의 선정 여부에 따라 감독분류와 무감독 분류로 나누어지며 각각의 알고리즘의 특성에 따라 더욱 세분화된다. 본 연구에서는 Landsat-TM (Thematic Mapper) 영상을 이용하여 감독 분류와 무감독 분류를 각각 적용하여 한강유역의 토지피복을 수역, 시가, 나지 습지, 초지, 산림, 농지의 7가지 부분으로 대분류로 산정하고 비교하였다. 두 경우의 정확도는 각각 91.6%, 90.9%의 비슷한 정확도를 나타내었으며, 세부적으로 우리나라의 대부분의 면적에 분포하는 산림, 농지, 시가, 수역의 정확도가 높게 나타났다. 또한 각 항목별로 정확도를 비교하였을 때 감독분류가 무감독분류에 비해 다소 정확한 것을 확인할 수 있었다. 추후 외부자료를 도입하면 비교적 낮은 정확도를 나타낸 초지, 습지, 나지의 정확도를 보완할 수 있을 것이다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.7 no.1
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• pp.49-57
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• 1989

On this study, we performed the landuse classification using the Landsat data acquired before and after reclamation, and extracted the ground temperature from infrared band(TM band6) data. Using the satellite data, it was possible to extract changes of landuses effectively according to the reclamation, and could obtain the thermal characteristics of the reclaimed area and the surroundings by converting infrared data value into temperatures of surfaces of ground and water. The result of this analysis will be used for the land management of large-scale reclaimed area applying the satellite data and related information.