• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.120-131
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• 2020

Water body detection using remote sensing based on machine interpretation of satellite image is efficient for managing water resource, drought and flood monitoring. In this study, water body detection with SAR satellite image based on machine learning was performed. However, non water body area can be misclassified to water body because of shadow effect or objects that have similar scattering characteristic comparing to water body, such as roads. To decrease misclassifying, 8 combination of morphology open filtered band, DEM band, curvature band and Cosmo-SkyMed SAR satellite image band about Mokpo region were trained to semantic segmentation machine learning models, respectively. For 8 case of machine learning models, global accuracy that is final test result was computed. Furthermore, concordance rate between landcover data of Mokpo region was calculated. In conclusion, combination of SAR satellite image, morphology open filtered band, DEM band and curvature band showed best result in global accuracy and concordance rate with landcover data. In that case, global accuracy was 95.07% and concordance rate with landcover data was 89.93%.

• Korean Journal of Environment and Ecology
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• v.28 no.1
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• pp.45-54
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• 2014

This study was carried out to investigate the ecological succession sere and conservative value, and to provide the basic data in Woonsooam Valley, in Jogyesan (Mt.) (altitude 884m), Suncheon City, Korea by analysing the structure of the plant community. Fifteen plots (size is $20m{\times}20m$) were set up at an altitude of range from 255m to 495m. As a result of analysis of DCA which is one of the ordination technique, the plant communities were divided into five groups which are community I (Pinus densiflora community), community II (Quercus variabilis-Quercus serrata community), community III (Q. serrata-Q. variabilis community), and community IV (Carpinus tschonoskii-Q. serrata community) and community v(Deciduous broad-leaved forest community). We found out that the vegetation of the study site located in the South Temperate Climate Zone. The study site is found out that Q. serrata community 34.4%, part of slope in valley is the distribution that dominant species is Q. serrata-Q. variabilis community 32.1%. And in valley showed Carpinus tschonoskii community 5.5%. And Sasa borealis was dominant species in the shrub layer. We couldn't supposed that the ecological succession sere of the study site, however we should do a long-term monitoring to investigate the changes of the ecological succession each plant community, According to the index of Shannon's diversity (unit: $400m^2$), community III was ranged from 1.0102 to 1.1013, community V was 0.9945, community II was ranged from 0.7913 to 1.1503, community IV was ranged from 0.8081 to 1.0749 and community I was 0.9273.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.9
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• pp.24-33
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• 2017

Multitemporal MODIS vegetation index (VI) data are widely used in vegetation monitoring research into environmental and climate change, since they provide a profile of vegetation activity. However, MODIS data inevitably contain disturbances caused by the presence of clouds, atmospheric variability, and instrument problems, which impede the analysis of the NDVI time series data and limit its application utility. For this reason, preprocessing to reduce the noise and reconstruct high-quality temporal data streams is required for VI analysis. In this study, a data reconstruction method for MODIS NDVI is proposed to restore bad or missing data based on the statistical properties of the oscillations in the NDVI temporal dynamics. The first derivatives enable us to examine the monotonic properties of a function in the data stream and to detect anomalous changes, such as sudden spikes and drops. In this approach, only noisy data are corrected, while the other data are left intact to preserve the detailed temporal dynamics for further VI analysis. The proposed method was successfully tested and evaluated with simulated data and NDVI time series data covering Baekdu Mountain, located in the northern part of North Korea, over the period of interest from 2006 to 2012. The results show that it can be effectively employed as a preprocessing method for data reconstruction in MODIS NDVI analysis.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1661-1670
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• 2016

In this paper, we present a risk prediction system and customized evacuation pathfinding algorithm in fire scenarios. For the risk prediction, we apply a multi-level clustering mechanism using collected temperature at sensor nodes throughout the network in order to predict the temperature at the time that users actually evacuate. Based on the predicted temperature and its reliability, we suggest an evacuation pathfinding algorithm that finds a suitable evacuation path from a user's current location to the safest exit. Simulation results based on FDS(Fire Dynamics Simulator) of NIST for a wireless sensor network consisting of 47 stationary nodes for 1436.41 seconds show that our proposed prediction system achieves a higher accuracy by a factor of 1.48. Particularly for nodes in the most reliable group, it improves the accuracy by a factor of up to 4.21. Also, the customized evacuation pathfinding based on our prediction algorithm performs closely with that of the ground-truth temperature in terms of the ratio of safe nodes on the selected path, while outperforming the shortest-path evacuation with a factor of up to 12% in terms of a safety measure.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.168-168
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• 2017

ICT 융합 스마트팜 내의 환경계측 센서, 영상 및 사양관리 시스템의 증가에도 불구하고 이들 장비에서 확보되는 데이터를 적절히 유효하게 활용하는 기술이 미흡한 실정이다. 돈사의 경우 가축의 복지수준, 성장 변화를 실시간으로 모니터링 및 예측할 수 있는 데이터 분석 및 모델링 기술 확보가 필요하다. 이를 위해선 가축의 생리적 변화 및 행동적 변화를 조기에 감지하고 가축의 복지수준을 실시간으로 감시하고 분석 및 예측 기술이 필요한데 이를 위한 대표적인 정보 통신 공학적 접근법 중에 하나가 Data mining 이다. Data mining에 대한 연구 수행에 필요한 다양한 소프트웨어 중에서 Open source로 제공이 되는 4가지 도구를 비교 분석하였다. 스마트 돈사 내에서 열환경 모델링을 목표로 한 데이터 분석에서 고려해야할 요인으로 데이터 분석 알고리즘 도출 시간, 시각화 기능, 타 라이브러리와 연계 기능 등을 중점 적으로 분석하였다. 선정된 4가지 분석 도구는 1) R(https://cran.r-project.org), 2) OpenCV(http://opencv.org), 3) OpenNN (http://www.opennn.net), 4) Orange(http://orange.biolab.si) 이다. 비교 분석을 수행한 운영체제는 Linux-Ubuntu 16.04.4 LTS(X64)이며, CPU의 클럭속도는 3.6 Ghz, 메모리는 64 Gb를 설치하였다. 개발언어 측면에서 살펴보면 1) R 스크립트, 2) C/C++, Python, Java, 3) C++, 4) C/C++, Python, Cython을 지원하여 C/C++ 언어와 Python 개발 언어가 상대적으로 유리하였다. 데이터 분석 알고리즘의 경우 소스코드 범위에서 라이브러리를 제공하는 경우 Cross-Platform 개발이 가능하여 여러 운영체제에서 개발한 결과를 별도의 Porting 과정을 거치지 않고 사용할 수 있었다. 빌트인 라이브러리 경우 순서대로 R 의 경우 가장 많은 수의 Data mining 알고리즘을 제공하고 있다. 이는 R 운영 환경 자체가 개방형으로 되어 있어 온라인에서 추가되는 새로운 라이브러리를 클라우드를 통하여 공유하기 때문인 것으로 판단되었다. OpenCV의 경우 영상 처리에 강점이 있었으며, OpenNN은 신경망학습과 관련된 라이브러리를 소스코드 레벨에서 공개한 것이 강점이라 할 수 있다. Orage의 경우 라이브러리 집합을 제공하는 것에 중점을 둔 다른 패키지와 달리 시각화 기능 및 망 구성 등 사용자 인터페이스를 통합하여 운영한 것이 강점이라 할 수 있다. 열환경 모델링에 요구되는 시간 복잡도에 대응하기 위한 부가 정보 처리 기술에 대한 연구를 수행하여 스마트팜 열환경 모델링을 실시간으로 구현할 수 있는 방안 연구를 수행할 것이다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.499-506
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• 2019

NDSM (Normalized Digital Surface Model) is key information for the detailed analysis of remote sensing data. Although NDSM can be simply obtained by subtracting a DTM (Digital Terrain Model) from a DSM (Digital Surface Model), in case of UAV (Unmanned Aerial Vehicle) data, it is difficult to get an accurate DTM due to high resolution characteristics of UAV data containing a large number of complex objects on the ground such as vegetation and urban structures. In this study, RGB-based UAV vegetation index, ExG (Excess Green) was used to extract initial seed points having low ExG values for region growing such that a DTM can be generated cost-effectively based on high resolution UAV data. For this process, local window analysis was applied to resolve the problem of erroneous seed point extraction from local low ExG points. Using the DSM values of seed points, region growing was applied to merge neighboring terrain pixels. Slope criteria were adopted for the region growing process and the seed points were determined as terrain points in case the size of segments is larger than 0.25 ㎡. Various slope criteria were tested to derive the optimized value for UAV data-based NDSM generation. Finally, the extracted terrain points were evaluated and interpolation was performed using the terrain points to generate an NDSM. The proposed method was applied to agricultural area in order to extract the above ground heights of crops and check feasibility of agricultural monitoring.

• Korean Journal of Remote Sensing
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• v.35 no.6_3
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• pp.1251-1260
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• 2019

Existing environmental spatial information, which has been concentrated on spatial resolution, has limitations in solving realistic environmental problems that must be accompanied by physical and chemical characterization. Accordingly, there is a need for an image radar capable of identifying physical characteristics of an object regardless of weather conditions, day and night, and sunlight. Image radar is used in various fields in the United States and Europe. The next generation of medium-sized satellite No. 5 in Korea, which is under development with the aim of monitoring water disasters, is also looking for ways to expand the scope to various applications based on the existing application range. To this end, we analyzed domestic and international papers (100 works) using image radar, and reviewed KEI 2016 report, domestic papers, and foreign papers. Based on this, various environmental issues were summarized and the effects of when the image radar was used were analyzed and land cover was selected as an environmental issue. In the future, we will embody the technology to improve the accuracy of the land cover map, which is the environmental issue selected in this study, and build the foundation system for the stable use of the land cover map.

• KSBB Journal
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• v.14 no.2
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• pp.230-234
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• 1999

To improve the crossflow untrafiltration flux, we applied periodic oscillations in transmembrane pressure gradient in order to promote fluid turbulence by inducing repeated compression and relaxation of the cake/gel layer. The oscillatory forms used were square-, sine-, triangle-wave, and pumping interruption. The permeate flux profiles were mathematically simulated and compared with the experimental data. The result showed the periodic pumping interruption most effectively improved the overall flux by up to about 32%. Enough pumping off-time, at least on the order of tens of seconds, was needed to allow the solutes in the layer to diffuse back to the bulk phase. It was better to start the oscillations earlier before the layer was fully established. The square-wave oscillation yielded about 11% increase, which was particularly pronounced in the later part of the filtration. Either the amplitude or the period of the oscillations resulted little influence on flux.actate ester, and lactate ester produced in esterification reaction was distilled simultaneously with hydrolysis reaction into lactic acid. When the yields of lactic acid recovered by batch reactive distillations with various alcohols were compared, the yield of lactic acid was increased as the volatility of lactate ester was increased. In this batch reactive distillation, because the mixtures condensed in partial condensor were flown to reboiler through distillation column, the recovery yield of lactic acid was affected by operation temperature of partial condensor. Hydrolysis reaction into lactic acid in distillation column rarelyoccurred because of short retention time of lactate ester and water. Lactate ester was reacted into lactic acid in reboiler.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.4
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• pp.393-399
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• 2005

Since vegetations are near the wavelength range in 700nm and have absorbent as well as reflective wavelength ranges, there is a much difference in terms of its reflection rate. There are currently many researches on vegetation index being conducted in order to apply the remote-sensing technology to vegetations rising their characteristics of absorbent and reflective wavelength ranges. Normalized Difference Vegetation Index (NDVI) and Perpendicular Vegetation Index (PVI) have been most commonly used. It is usually the evaporation, carbon-dioxide consumption, and chlorophyll density that represent the activity of vegetation, but chlorophyll density is the most commonly used among them. Since the red wavelength range used to obtain the NDVI and PVI has a strong extinction of chlorophyll, it is also useful to test chlorophyll density. The NDVI, in particular, is used to identify the vegetation conditions summarily, and thus, is suitable for initiative researches. Nevertheless, since these vegetation index produce mixed information of the Vegetation vigor and vegetation cover, it is essential to monitor a wavelength range that is independent from redundancy of the Vegetation vigor and vegetation cover. Although many vegetation indices have evaluated both the vegetation vigor and Vegetation cover simultaneously, this research intends to emphasize the utility of separable evaluations of the Vegetation vigor and Vegetation Cover rate through an experiment with grasses. As a result of evaluating vegetation index using spectral reflectance, a separable evaluation of the vegetation vigor and cover has been found more useful.

• Korean Journal of Remote Sensing
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• v.33 no.6_2
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• pp.1139-1149
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• 2017

Measuring tree's volume is very important input data of various environmental analysis modeling However, It's difficult to use economical and equipment to measure a fragmented small green space in the city. In addition, Trees are sensitive to seasons, so we need new and easier equipment and quantification methods for measuring trees than lidar for high frequency monitoring. In particular, the tree's size in a city affect management costs, ecosystem services, safety, and so need to be managed and informed on the individual tree-based. In this study, we aim to acquire image data with UAV(Unmanned Aerial Vehicle), which can be operated at low cost and frequently, and quickly and easily quantify a single tree using SfM-MVS(Structure from Motion-Multi View Stereo), and we evaluate the impact of reducing number of images on the point density of point clouds generated from SfM-MVS and the quantification of single trees. Also, We used the Watertight model to estimate the volume of a single tree and to shape it into a 3D structure and compare it with the quantification results of 3 different type of 3D models. The results of the analysis show that UAV, SfM-MVS and solid model can quantify and shape a single tree with low cost and high time resolution easily. This study is only for a single tree, Therefore, in order to apply it to a larger scale, it is necessary to follow up research to develop it, such as convergence with various spatial information data, improvement of quantification technique and flight plan for enlarging green space.