• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.395-408
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• 2015

High-resolution satellite image mosaics are becoming increasingly important in the field of remote sensing image analysis as an essential image processing to create a large image constructed from several smaller images. In this paper, we present an automatic seamline extraction technique and the procedure to generate a mosaic image by this technique. For more effective seamline extraction in the overlap region of adjacent images, an NDVI-based seamline extraction technique is developed, which takes advantage of the computational time and memory. The Normalized Difference Vegetation Index(NDVI) is an index of plant "greeness" or photosynthetic activity that is employed to extract the initial seamline. The NDVI can divide into manmade region and natural region. The cost image is obtained by the canny edge detector and the buffering technique is used to extract the ranging cost image. The seamline is extracted by applying the Dijkstra algorithm to a cost image generated through the labeling process of the extracted edge information. Histogram matching is also conducted to alleviate radiometric distortion between adjacent images acquired at different time. In the experimental results using the KOMPSAT-2/3 satellite imagery, it is confirmed that the proposed method greatly reduces the visual discontinuity caused by geometric difference of adjacent images and the computation time.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.581-588
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• 2018

The aim of this study is to propose a fine co-registration approach for multi-temporal satellite images acquired from RapidEye, which has an advantage of availability for time-series analysis. To this end, we generate multitemporal ortho-rectified images using RPCs (Rational Polynomial Coefficients) provided with RapidEye images and then perform fine co-registration between the ortho-rectified images. A DEM (Digital Elevation Model) extracted from the digital map was used to generate the ortho-rectified images, and the RNCC (Registration Noise Cross Correlation) was applied to conduct the fine co-registration. Experiments were carried out using 4 RapidEye 1B images obtained from May 2015 to November 2016 over the Yeonggwang area. All 5 bands (blue, green, red, red edge, and near-infrared) that RapidEye provided were used to carry out the fine co-registration to show their possibility of being applicable for the co-registration. Experimental results showed that all the bands of RapidEye images could be co-registered with each other and the geometric alignment between images was qualitatively/quantitatively improved. Especially, it was confirmed that stable registration results were obtained by using the red and red edge bands, irrespective of the seasonal differences in the image acquisition.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.113-126
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• 2021

This study was conducted to analyze the forest status and deforestation area changes of the DMZ region in North Korea based on satellite images. Using growing and non-growing season's RapidEye satellite images, land cover of the North Korean DMZ was classified into stocking land(conifer, deciduous, mixed), deforested land(unstocked mountain, cultivated mountain, bare mountain), and non-forest areas. Deforestation rates in the Yeonan-baecheon, Beopdong-Pyeonggang, Heoyang-Geumgang and Tongcheon-Goseong district were calculated as 14.24%, 16.75%, 5.98%, and 16.63% respectively. Forest fire and land use change of forest were considered as the main causes of deforestation of DMZ. Changes in deforestation area were analyzed through Google Earth images. As a results, it was shown that the area of deforestation was on a decreasing trend. This study can be used as basic data for establishing inter-Korean border region's forest cooperation strategies by providing forest spatial information on the North Korea's DMZ.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.343-350
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• 2024

Since the release of Meta's Segment Anything Model (SAM), a large-scale vision transformer generation model with rapid image segmentation capabilities, several studies have been conducted to apply this technology in various fields. In this study, we aimed to investigate the applicability of SAM for water bodies detection and extraction using the QGIS Geo-SAM plugin, which enables the use of SAM with satellite imagery. The experimental data consisted of Compact Advanced Satellite 500 (CAS500)-1 images. The results obtained by applying SAM to these data were compared with manually digitized water objects, Open Street Map (OSM), and water body data from the National Geographic Information Institute (NGII)-based hydrological digital map. The mean Intersection over Union (mIoU) calculated for all features extracted using SAM and these three-comparison data were 0.7490, 0.5905, and 0.4921, respectively. For features commonly appeared or extracted in all datasets, the results were 0.9189, 0.8779, and 0.7715, respectively. Based on analysis of the spatial consistency between SAM results and other comparison data, SAM showed limitations in detecting small-scale or poorly defined streams but provided meaningful segmentation results for water body classification.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.3
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• pp.80-92
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• 2007

Forest fire is the dominant large-scale disturbance mechanism in the Korean temperate forest, and it strongly influences forest structure and function. Moreover burn severity incorporates both short- and long-term post-fire effects on the local and regional environment. Burn severity is defined by the degree to which an ecosystem has changed owing to the fire. Vegetation rehabilitation may specifically vary according to burn severity after fire. To understand burn severity and process of vegetation rehabilitation at the damaged area after large-fire is required a lot of man powers and budgets. However the analysis of burn severity in the forest area using satellite imagery can acquire rapidly information and more objective results remotely in the large-fire area. Space and airbone sensors have been used to map area burned, assess characteristics of active fires, and characterize post-fire ecological effects. For classifying fire damaged area and analyzing burn severity of Samcheok fire area occurred in 2000, Cheongyang fire in 2002, and Yangyang fire in 2005 we utilized Normalized Burn Ratio(NBR) technique. The NBR is temporally differenced between pre- and post-fire datasets to determine the extent and degree of change detected from burning. In this paper we use pre- and post-fire imagery from the Landsat TM and ETM+ imagery to compute the NBR and evaluate large-scale patterns of burn severity at 30m spatial resolution. 65% in the Samcheok fire area, 91% in the Cheongyang fire area and 65% in the Yangyang fire area were corresponded to burn severity class above 'High'. Therefore the use of a remotely sensed Differenced Normalized Burn Ratio(${\Delta}NBR$) by RS and GIS allows for the burn severity to be quantified spatially by mapping damaged domain and burn severity across large-fire area.

• Korean Journal of Remote Sensing
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• v.34 no.2_2
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• pp.327-338
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• 2018

The possibility of ship detection monitoring at operational level using KOMPSAT-5 Synthetic Aperture Radar (SAR) and Automatic Identification System (AIS) data is investigated. For the analysis, the KOMPSAT-5 SLC images, which are collected from the west coast of Shinjin port and the northern coast of Jeju port are used along with portable AIS data from near the coast. The ship detection algorithm based on HVAS (Human Visual Attention System) was applied, which has significant advantages in terms of detection speed and accuracy compared to the commonly used CFAR (Constant False Alarm Rate). As a result of the integrated analysis, the ship detection from KOMPSAT-5 and AIS were generally consistent except for small vessels. Some ships detected in KOMPSAT-5 but not in AIS are due to the data absence from AIS, while it is clearly visible in KOMPSAT-5. Meanwhile, SAR imagery also has some false alarms due to ship wakes, ghost effect, and DEM error (or satellite orbit error) during object masking in land. Improving the developed ship detection algorithm and collecting reliable AIS data will contribute for building wide integrated surveillance system of marine territory at operational level.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.20 no.6
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• pp.151-160
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• 2017

This study was conducted by using a Nikon Coolpix S800c camera equipped with a NIR filter to measure the NDVI(Normalized Difference Vegetation Index). It was used for the measurement of the three trees of Pinus densiflora, Taxus cuspidata, Zelkova serrata and Acer palmatum in Kangwon National University. The NDVI value of the surface of the building was compared and analyzed. The average value of NDVI in August and September was high in all species. The NDVI distribution of Taxus cuspidata was higher than the other trees. The NDVI distribution of Pinus densiflora and Taxus cuspidata did not show any significant seasonal differences, but The NDVI distribution of Zelkova serrata and Acer palmatum were relatively low in May and June, which are leafless periods. Previous studies related to NDVI value were generally analyzed using satellite imagery. However, it was scarce related to study the NDVI value of each tree or study the changing process of NDVI by time series. Previous studies have used NDVI values on the ground but this study used NDVI values in the ground section. Future studies will be necessary to measure the NDVI value at different times for various species and also to make efforts to generalize the measurement method. In addition, research related to various fields such as the relationship between NDVI and carbon stocks and the relationship with LAI needs to be conducted.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.9 no.2
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• pp.81-91
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• 1991

This thesis aims to improve the analysis accuracy of remotely sensed digital imagery, and the improvement is achieved by considering the weight factors(a priori probabilities) of Bayesian MLC in the classification stage. To be concrete, Bayesian decision theory is studied from remote sensing field of view, and the equations in the n-dimensional form are derived from normal probability density functions. The amount of the misclassified pixels is extracted from probability function data using the thres-holding, and this is a basis of evaluating the classification accuracy. The results indicate that 5.21% of accuracy improvement was carried out. The data used in this study is LANDSAT TM(1985.10.21 ; 116-34), and the study area is within the administrative boundary of Seoul.

• Spatial Information Research
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• v.14 no.3 s.38
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• pp.285-297
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• 2006

We aim to investigate the morphological and environmental characteristics of royal tombs of Chosun Dynasty by using GIS technique and remotely-sensed data. Most of the royal tombs are located on the banded gneiss and granite and over the south- and east. facing slopes and have altitudinal ranges of 150 to 200 meters. Due to the time gaps, exact locational preferences of the royal families can not be understood at this moment and also proximity to the running water is hard to be quantified. Close examination of Gwangneung indicates that the artificial modification and weathering have severe impacts on the slope and stone artefacts. The results from this research can be useful to preserve the valueless cultural heritages.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.1-12
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• 2012

The agricultural area was classified into dry and paddy fields in this study using the near-infrared band of Landsat TM to extract land cover classes that need to the application of Expected Mean Concentration (EMC) in nonpoint source works. The accuracy of image classification of the land cover map from Landsat TM image showed 83.61% and 78.41% respectively by comparing with the large and middle scale land cover map of Ministry of Environment. As the result of Soil Conservation Service (SCS) Curve Number (CN) using the land cover map from image classification, Dongbok dam and Dongbok stream basin were analyzed high. Also Geymbaek water-gage and Bosunggang upstream basin showed high in the analysis of EMC of BOD, TN, TP by basin. And also Geymbaek water-gage and Bosunggang upstream basin showed high in the analysis of non-point source through coupling with direct runoff. Therefore these basins were selected with the main area for the management of nonpoint source.