• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1837-1846
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• 2022

The annual increase in chemical accidents is causing damage to life and the environment due to the spread and residual of substances. Environmental damage investigation is more difficult to determine the geographical scope and timing than human damage investigation. Considering the reality that there is a lack of professional investigation personnel, it is urgent to develop an efficient quantitative evaluation method. In order to improve this situation, this paper conducted a chemical accidents investigation using unmanned aerial vehicles(UAV) equipped with various sensors. The damaged area was calculated by Ortho-image and strength of agreement was calculated using the normalized difference vegetation index image. As a result, the Cohen's Kappa coefficient was 0.649 (threshold 0.7). However, there is a limitation in that analysis has been performed based on the pixel of the normalized difference vegetation index. Therefore, there is a need for a chemical accident investigation plan that overcomes the limitations.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.689-698
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• 2017

In this paper, a new classification method based on the combination of semi-supervised learning with spatial similarity of adjacent pixels is presented for crop classification in inaccessible areas. Iterative classification based on semi-supervised learning is applied to extract reliable training data from both the initial classification result with a small number of training data, and classification results of adjacent pixels are also considered to extract new training pixels with less uncertainty. To evaluate the applicability of the proposed method, a case study of the classification of field crops was carried out using multi-temporal Landsat-8 OLI acquired in the Daehongdan region, North Korea. From a case study, the misclassification of crops and forests, and isolated pixels in the initial classification result were greatly reduced by applying the proposed semi-supervised learning method. In addition, the combination of classification results of adjacent pixels for the extraction of new training data led to the great reduction of both misclassification results and isolated pixels, compared to the initial classification and traditional semi-supervised learning results. Therefore, it is expected that the proposed method would be effectively applied to classify areas in which it is difficult to collect sufficient training data.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.2
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• pp.59-74
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• 2015

The purpose of this study is to analyze reasonable green area ratios for mitigating urban heat island considering various land use types. Land uses of 5 types such as single residential, multi residential, commercial area, public facility, and industrial area were considered. Green areas were extracted from the tree attribution of land cover. Effect of urban heat island was analysed by the surface temperature of ASTER thermal infrared radiance scanned daytime and nighttime. Mitigation effect of green area at daytime was higher than nighttime. Surface temperature of green area was low in single residential at daytime. But the difference of surface temperature by each land use type was small. The effect of surface temperature mitigation of green area was lower in industrial area. The results of reasonable green area ratios for mitigating urban heat island indicate that surface temperature was the lowest with green area ratio of 40~50% in single residential, multi residential, and commercial area at daytime. Surface temperature of nighttime was not changed much by green area ratios. Therefore, the results of this study will be suggested in urban development planning to construct effectively green area for mitigating urban heat island.

• Journal of Korea Water Resources Association
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• v.48 no.2
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• pp.79-90
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• 2015

In this study, the water quality parameters of Geum-river were estimated using Landsat 8 satellite image data which had launched in March 2013. The goal of this research is to predict HAB and to monitor spatial pattern of total nitrogen (TN) and total phosphorus (TP) because both TN and TP are the dominant factors of the growth of harmful algal blooms (HABs). To investigate the relationship between satellite band reflectance and in situ measurement value, Pearson' correlation coefficient analysis was used. The band2, 3, 4 and 5 reflectance values among 11 bands of Landsat 8 were used which was highly associated with detecting TN and TP. The 20 in situ data set with satellite's overpass time were identified. TN showed positive relation with band 2 (0.48), band3 (0.62), band4 (0.57) at a significance level of p<0.05. TP also showed high correlation for band2 (0.59), band3 (0.59), band4 (0.58) at a significance level of p<0.01. The optimal regression equation models were constructed for TN and TP based on multiple regression equations. The estimated concentration based on derived regression equations of TN and TP were compared with in situ measurement data. Finally, the spatial pattern of the two parameters was able be monitored through mapping on November 12, 2013 and April 21, 2014.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.11a
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• pp.260-265
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• 1999

멀티빔 음향측심기(Multibeam Echo Sounder)는 기존의 단빔 음향측심기(Singlebeam Echo Sounder)와 달리 탐사선 진행방향의 수직(Crosstrack)으로 해저면을 주사(Swath)하여, 한 번의 송수신(Ping)으로 다중의 빔 자료 - 수심, 후방산란된 음압(Backscattered Amplitude), 사이드 스캔 소나(Side Scan Sonar) 자료 - 를 취득하는 장비이다. 멀티빔 음향 측심기를 이용한 해저면 탐사의 경우, 수심이 변함에 따라 주사폭(Swath width)이 변화하고, 각 빔의 수평 해상도(Footprint)는 수심과 더불어 빔폭(Beam width)에 의하여 동적으로 변화한다. 멀티빔 음향 측심기는 해저면을 전역탐사 할 수 있을 뿐만 아니라, 연속된 음향 탐사를 통하여 이웃한 핑 사이에 발생하는 전방중첩영역(Endlap)과 이웃 측선(Trackline)을 따라 겹쳐지는 측방중첩영역(Sidelap)의 자료들을 이용하여 멀티 뎀 자료들의 전반적인 정확도 및 신뢰도를 평가할 수 있다. 본 논문은 수로 측량(Hydrographic Survey)에서 사용되는 멀티빔 음향 측심기를 운영하여 얻어진 측심 자료를 처리하는 알고리즘 개발에 관한 연구이다. 본 논문에서는 L3사의 Sea Beam 2100 벌티빔 음향 측심기를 대상으로, 멀티빔의 측심 원리와 해저 지형에 대한 일반적 이해를 통하여 획득된 측심 자료의 통계적 특성을 파악하고, 오측심된 수심 자료를 제거하는 방법을 제안하며, 측심 구간의 대표격자 크기를 결정하는 기준을 제시한다. 또한, 항공원격탐사에서 고도 추정시 사용되고 있는, 평균보간법, 가중평균 보간법과, 본 논문에서 제안하는 격자 대표값 선정 알고리즘(Gridding Algorithms)의 결과를 비교하고, 최종적으로 얻어지는 해저 수치지형모델(DEM, Digital Elevation Model)과 후방산란 영상을 제시한다. 빠른 한지형잔디들이 지표면을 피복하도록 하고 여름의 고온기와 장마시기에는 뿌리전단력이 우수한 이러한 초종들로 지표면이 피복되도록 하는 것이 이상적이라 생각된다. 4. 혼파처리간의 토사유출량을 비교한 결과 토사 유출 억제효과는 한지형과 나지형잔디들의 혼합형(MixtureIII)과 자생처리구(MixtureV), Italian ryegrass와 자생식물의 혼합형(MixtureIV)등에서 비교적 낮은 수치를 토사유출량을 기록하였다. 이러한 결과는 자생식물들이 비록 초기생육속도는 외래도입초종에 떨어지지만 토사유출의 억제효과면에서는 이들 외래초종에 필적할 수 있음을 나타낸다고 할 수 있겠다.중량이 약 115kg/$m^2$정도로 나타났다.소 들(환경의 의미, 사람의 목적과 지식)보다 미학적 경험에 주는 영향이 큰 것으로 나타났으며, 모든 사람들에게 비슷한 미학적 경험을 발생시키는 것 이 밝혀졌다. 다시 말하면 모든 사람들은 그들의 문화적인 국적과 사회적 인 직업의 차이, 목적의 차이, 또한 환경의 의미의 차이에 상관없이 아름다 운 경관(High-beauty landscape)을 주거지나 나들이 장소로서 선호했으며, 아름답다고 평가했다. 반면에, 사람들이 갖고 있는 문화의 차이, 직업의 차 이, 목적의 차이, 그리고 환경의 의미의 차이에 따라 경관의 미학적 평가가 달라진 것으로 나타났다.corner$적 의도에 의한 경관구성의 일면을 확인할수 있지만 엄밀히 생각하여 보면 이러한 예의 경우도 최락의 총체적인 외형은 마찬가지로 $\ulcorner$순응$\lrcorner$의 범위를 벗어나지 않는다. 그렇기 때문에도 $\ulcorner$순응$\lrcorner$과 $\ulcorner$표현$\lrcorner$의 성격과 형태를 외형상으로 더욱이 공간상에서는 뚜렷하게 경계

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.681-692
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• 2019

In this paper, a hybrid deep learning model, called 2D convolution with bidirectional long short-term memory (2DCBLSTM), is presented that can effectively combine both spatial and temporal features for crop classification. In the proposed model, 2D convolution operators are first applied to extract spatial features of crops and the extracted spatial features are then used as inputs for a bidirectional LSTM model that can effectively process temporal features. To evaluate the classification performance of the proposed model, a case study of crop classification was carried out using multi-temporal unmanned aerial vehicle images acquired in Anbandegi, Korea. For comparison purposes, we applied conventional deep learning models including two-dimensional convolutional neural network (CNN) using spatial features, LSTM using temporal features, and three-dimensional CNN using spatio-temporal features. Through the impact analysis of hyper-parameters on the classification performance, the use of both spatial and temporal features greatly reduced misclassification patterns of crops and the proposed hybrid model showed the best classification accuracy, compared to the conventional deep learning models that considered either spatial features or temporal features. Therefore, it is expected that the proposed model can be effectively applied to crop classification owing to its ability to consider spatio-temporal features of crops.

• Korean Journal of Remote Sensing
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• v.34 no.6_4
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• pp.1545-1553
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• 2018

Recent eruptive activity at Kīlauea Volcano started on at the end of April in 2018 showed rapid ground deflation between May and June in 2018. On summit area Halema'uma'u lava lake continued to drop at high speed and Kīlauea's summit continued to deflate. GPS receivers and electronic tiltmeters detected the surface deformation greater than 2 meters. We explored the time-series surface deformation at Kīlauea Volcano, focusing on the early stage of eruptive activity, using multi-temporal COSMO-SkyMed SAR imagery. The observed maximum deformation in line-of-sight (LOS) direction was about -1.5 meter, and it indicates approximately -1.9 meter in subsiding direction by applying incidence angle. The results showed that summit began to deflate just after the event started and most of deformation occurred between early May and the end of June. Moreover, we confirmed that summit's deflation rarely happened since July 2018, which means volcanic activity entered a stable stage. The best-fit magma source model based on time-series surface deformation demonstrated that magma chambers were lying at depths between 2-3 km, and it showed a deepening trend in time. Along with the change of source depth, the center of each magma model moved toward the southwest according to the time. These results have a potential risk of including bias coming from single track observation. Therefore, to complement the initial results, we need to generate precise magma source model based on three-dimensional measurements in further research.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1747-1761
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• 2023

Wetlands, defined as lands periodically inundated or exposed during the year, are crucial for sustaining biodiversity and filtering environmental pollutants. The importance of mapping and monitoring their topographical changes is therefore paramount. This study focuses on the topographical variations at the Incheon River estuary wetland post-restoration, noting a lack of adequate prior measurements. Using a multi-temporal Sentinel-1 dataset from October 2014 to March 2023, we mapped long-term variations in water bodies and detected topographical change anomalies using a pixel-frequency approach. Our analysis, based on 196 Sentinel-1 acquisitions from an ascending orbit, revealed significant topography changes. Since 2020, employing the pixel-frequency technique, we observed area increases of +0.0195, 0.0016, 0.0075, and 0.0163 km² in water level sections at depths of 2-3 m, 1-2 m, 0-1 m, and less than 0 m, respectively. These findings underscore the effectiveness of the wetland restoration efforts in the area.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1559-1572
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• 2021

The response of vegetation under the crop stress condition was evaluated using structural, biochemical, and physiological vegetation indices based on unmanned aerial vehicle (UAV) images and field-spectrometer data. A high concentration of herbicide was sprayed at the different growth stages of garlic to process crop stress, the above ground dry matter of garlic at experimental area (EA) decreased about 46.2~84.5% compared to that at control area. The structural vegetation indices clearly responded to these crop damages. Spectral reflectance at near-infrared wavelength consistently decreased at EA. Most biochemical vegetation indices reflected the crop stress conditions, but the meaning of physiological vegetation indices is not clear due to the effect of vinyl mulching. The difference of the decreasing ratio of vegetation indices after the herbicide spray was 2.3% averagely in the case of structural vegetation indices and 1.3~4.1% in the case of normalization-based vegetation indices. These results meant that appropriate vegetation indices should be utilized depending on the types of crop stress and the cultivation environment and the normalization-based vegetation indices measured from the different spatial scale has the minimized difference.

• Korean Journal of Ecology and Environment
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• v.48 no.3
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• pp.176-187
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• 2015

In this study, we hypothesized that the size of wintering crane population would change due to the climate factors. We assumed that wintering population size would differ by climate values in January, which is the coldest period in year. Especially, White-naped cranes were able to choose wintering site between Cheorwon and other alternative place where snow coverage had low influence, differing from Red crowned cranes. For this reason, we predicted the population size of White-naped cranes would fluctuate according to the extent of snow coverage in Cheorwon. Therefore we used snow coverage data based on MODIS and climate data from KMA (Korea Meteorological Administration) that are generally used. We analyzed the crane's population size in Cheorwon in January from 2002 to 2014. The temperature in the Cheorwon increased from 2002 to wintering period in 2007~ 2008 and went down, showing the lowest temperature in 2011~ 2012. With this phenomenon, warmth index showed the similar pattern with temperature. Amount of newly accumulated snow (the amount of snow that fallen from 0:01 am to 11:29 pm in a day) was low after 2002, but rapidly increased in 2010~ 2011 and 2011~ 2012. The area of snow coverage rapidly declined from 2002 to 2005~ 2006 but suddenly expanded in wintering period in 2009~ 2010 and 2010~ 2011. Wintering population size of the White-naped cranes decreased as snow coverage area increased in January and the highest correlation was found between them, compared to the other climatic factors. However, the number of individuals of Red crowned cranes had little relationship with general climate factors including snow cover range. Therefore it seems that population size of the Red crowned crane varied by factors related with habitat selection such as secure roosting site and area of foraging place, not by climatic factors. In multiple regression analysis, wintering population of White-naped cranes showed significant relationship with logarithmic value of snow cover range and its period. Therefore, it suggests that the population size of the White-naped crane was affected by snow cover range n wintering period and this was because it was hard for them to find out rice grains which are their main food items, buried in snow cover. The population size variation in White-naped cranes was caused by some individuals which left Cheorwon for Izumi where snow cover had little influence on them. The wintering population in Izumi and Cheorwon had negative correlation, implying they were mutually related.