• 제목/요약/키워드: Reflectance Map

검색결과 55건 처리시간 0.024초

프로브형 가시광-근적외선 센서를 이용한 토양의 탄소량 측정 (Soil Profile Measurement of Carbon Contents using a Probe-type VIS-NIR Spectrophotometer)

  • 권기영
    • Journal of Biosystems Engineering
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    • 제34권5호
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    • pp.382-389
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    • 2009
  • An in-situ probe-based spectrophotometer has been developed. This system used two spectrometers to measure soil reflectance spectra from 450 nm to 2200 nm. It collects soil electrical conductivity (EC) and insertion force measurements in addition to the optical data. Six fields in Kansas were mapped with the VIS-NIR (visible-near infrared) probe module and sampled for calibration and validation. Results showed that VIS-NIR correlated well with carbon in all six fields, with RPD (the ratio of standard deviation to root mean square error of prediction) of 1.8 or better, RMSE of 0.14 to 0.22%, and $R^2$ of 0.69 to 0.89. From the investigation of carbon variability within the soil profile and by tillage practice, the 0-5 cm depth in a no-till field contained significantly higher levels of carbon than any other locations. Using the selected calibration model with the soil NIR probe data, a soil profile map of estimated carbon was produced, and it was found that estimated carbon values are highly correlated to the lab values. The array of sensors (VIS-NIR, electrical conductivity, insertion force) used in the probe allowed estimating bulk density, and three of the six fields were satisfactory. The VIS-NIR probe also showed the obtained spectra data were well correlated with nitrogen for all fields with RPD scores of 1.84 or better and coefficient of determination ($R^2$) of 0.7 or higher.

석조문화재 모니터링을 위한 하이퍼스펙트럴 이미지분석의 활용 (Utilization of Hyperspectral Image Analysis for Monitoring of Stone Cultural Heritages)

  • 전유근;이명성;김유리;이미혜;최명주;최기현
    • 보존과학회지
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    • 제31권4호
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    • pp.395-402
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    • 2015
  • 이 연구에서는 하이퍼스펙트럴 이미지를 활용하여 석조문화재의 훼손상태 모니터링에 대한 활용성을 검토하였다. 이를 위해 하이퍼스펙트럴 데이터의 보정방법, 영상분류 및 정규화 식생지수 산출방법을 석조문화재에 적용하였다. 이 결과 각 물질의 분광정보를 기반으로 한 객관적인 훼손지도 작성, 정밀도 높은 훼손율의 산출 및 식생들의 활력도 모델작성 등 다양한 분석이 가능하였다. 따라서 하이퍼스펙트럴 이미지 분석을 활용하여 석조문화재를 모니터링 한다면 효율적으로 훼손상태 변화를 파악할 수 있을 것이다.

위치별 산란특성을 반영한 측정기반 얼굴 렌더링 (Measurement-based Face Rendering reflecting Positional Scattering Properties)

  • 박선용;오경수
    • 한국게임학회 논문지
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    • 제9권5호
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    • pp.137-144
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    • 2009
  • 이 논문은 피하산란의 정도가 다를 것으로 예상되는 얼굴의 6개의 부위를 촬영하여 각각의 산란특성을 추출하고 렌더링에 반영하여 얼굴의 사실감 있는 표현이 가능한 방법을 제안한다. 각 부위별 산란이미지는 프로젝터로부터 피부에 입사된 단위광선이 내부 산란을 거쳐 밖으로 드러나는 모양을 여러 노출로 촬영하여 HDR 이미지로 합성하고, 비선형 최소제곱합의 해법 중 Sequential Quadratic Programming을 이용하여 광선의 입사지점을 지나는 단면이 이루는 곡선에 '가우스 함수의 선형결합'을 적합한다. 가우스 함수는 산란곡선을 잘 근사하면서 필터로서 적용이 쉬운 장점을 가진다. 우리는 최소제곱합의 해가 지역 해에 빠지는 않도록 유전알고리듬을 이용해 초기 값을 설정한다. 근사된 식의 각 가우스 항은 얼굴에 입사되는 복사조도를 렌더링한 텍스처에 가우스 필터로 적용되어 피하산란효과를 표현. 이 논문에서는 최대 12회의 가우스 필터링을 효율적으로 처리하기 위해 쿠다의 병렬처리능력를 활용하였다.

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마이크로네시아 웨노섬 연안 서식지 분포의 현장조사와 위성영상 분석법 비교 (Comparison between in situ Survey and Satellite Imagery with Regard to Coastal Habitat Distribution Patterns in Weno, Micronesia)

  • 김태훈;최영웅;최종국;권문상;박흥식
    • Ocean and Polar Research
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    • 제35권4호
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    • pp.395-405
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    • 2013
  • The aim of this study is to suggest an optimal survey method for coastal habitat monitoring around Weno Island in Chuuk Atoll, Federated States of Micronesia (FSM). This study was carried out to compare and analyze differences between in situ survey (PHOTS) and high spatial satellite imagery (Worldview-2) with regard to the coastal habitat distribution patterns of Weno Island. The in situ field data showed the following coverage of habitat types: sand 42.4%, seagrass 26.1%, algae 14.9%, rubble 8.9%, hard coral 3.5%, soft coral 2.6%, dead coral 1.5%, others 0.1%. The satellite imagery showed the following coverage of habitat types: sand 26.5%, seagrass 23.3%, sand + seagrass 12.3%, coral 18.1%, rubble 19.0%, rock 0.8% (Accuracy 65.2%). According to the visual interpretation of the habitat map by in situ survey, seagrass, sand, coral and rubble distribution were misaligned compared with the satellite imagery. While, the satellite imagery appear to be a plausible results to identify habitat types, it could not classify habitat types under one pixel in images, which in turn overestimated coral and rubble coverage, underestimated algae and sand. The differences appear to arise primarily because of habitat classification scheme, sampling scale and remote sensing reflectance. The implication of these results is that satellite imagery analysis needs to incorporate in situ survey data to accurately identify habitat. We suggest that satellite imagery must correspond with in situ survey in habitat classification and sampling scale. Subsequently habitat sub-segmentation based on the in situ survey data should be applied to satellite imagery.

다중 위성정보를 활용한 폭설재난 대응 (Heavy Snowfall Disaster Response using Multiple Satellite Imagery Information)

  • 김성삼;최재원;구신회;박영진
    • 대한공간정보학회지
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    • 제20권4호
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    • pp.135-143
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    • 2012
  • 전조 모니터링, 피해규모 조사, 응급 구조 및 대응, 긴급 복구 등 국가적 재난관리 분야에 주기적으로 지구를 관측하는 원격탐측과 GIS 기반 의사결정 기술의 활용성이 점차 확대되고 있다. 여기에, 광역적이고 준실시간적 대응을 위해 단일 위성센서가 아닌 통합센서가 탑재된 위성의 운용과 각 국가별 우주개발기구간 협력을 통해 다수의 인공위성을 공동 활용함으로써 재난시 적시에 위성영상을 확보하기 위한 여러 방안이 강구되고 있다. 본 연구에서는 지난 2011년 발생했던 국내 폭설재난 대응을 위해 국제재난기구 등 다양한 경로로 수집된 저 고해상도 위성영상을 분석하고 MODIS 영상의 파장대 특성을 고려한 눈지수나 변화탐지 기법을 적용하여 적설지역을 추출하였다. 또한, 작성된 적설분포도와 다양한 공간자료와의 GIS 공간분석을 수행하여 재난상황에서 적시적으로 의사결정을 지원한 국립방재연구원의 현업적용 사례를 제시하였다.

내부 산란함수를 이용한 효과적인 옷감 렌더링 (An Effective Cloth Rendering using Internal Scatter Function)

  • 박선용;전영재;오경수
    • 한국게임학회 논문지
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    • 제9권3호
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    • pp.97-105
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    • 2009
  • 본 논문에서는 빛이 옷감 내부에서 산란되어 나타나는 패턴을 측정하고 이를 이용해 옷감을 표현하는 새로운 형태의 렌더링 방법을 제안한다. 지금까지는 BTF(Bidirectional Texture Function)가 옷감과 같은 구조를 표현할 수 있는 최적의 방법으로 생각되어져 왔다. 하지만 BTF에 의한 재질 복원은 그 품질이 측정된 데이터의 양에 비례하고, 측정된 데이터를 각종 빛의 현상이 통합된 상태로 사용해야 한다는 단점을 지닌다. 우리는 옷감 구조 내에서의 빛의 산란현상이 옷감의 색감을 드러내는데 중요한 역할을 하고 있음을 확인하였다. 이러한 사실을 이용하여 어떤 지점에 입사된 단위광선이 옷감 내부의 메소구조와 섬유를 통과하면서 외부로 나타나는 산란패턴(산란이미지:Scatter Image)을 샘플의 충분히 많은 지점에서 획득하고, 각 임의의 지점의 밝기는 그 주변 지점에서 현 픽셀까지 도달하는 빛의 양을 합하여 결정한다. 본 논문은 제안하는 방법은 옷감의 각 지점에 입사되는 광선을 개별적으로 조절 가능케 하여 옷감과 같이 내부 산란이 불규칙한 패턴을 보이는 재질을 더욱 사실적으로 표현할 수 있도록 하는 단서를 제공한다.

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Classification Strategies for High Resolution Images of Korean Forests: A Case Study of Namhansansung Provincial Park, Korea

  • Park, Chong-Hwa;Choi, Sang-Il
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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    • pp.708-708
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    • 2002
  • Recent developments in sensor technologies have provided remotely sensed data with very high spatial resolution. In order to fully utilize the potential of high resolution images, new image classification strategies are necessary. Unfortunately, the high resolution images increase the spectral within-field variability, and the classification accuracy of traditional methods based on pixel-based classification algorithms such as Maximum-Likelihood method may be decreased (Schiewe 2001). Recent development in Object Oriented Classification based on image segmentation algorithms can be used for the classification of forest patches on rugged terrain of Korea. The objectives of this paper are as follows. First, to compare the pros and cons of image classification methods based on pixel-based and object oriented classification algorithm for the forest patch classification. Landsat ETM+ data and IKONOS data will be used for the classification. Second, to investigate ways to increase classification accuracy of forest patches. Supplemental data such as DTM and Forest Type Map of 1:25,000 scale are used for topographic correction and image segmentation. Third, to propose the best classification strategy for forest patch classification in terms of accuracy and data requirement. The research site for this paper is Namhansansung Provincial Park located at the eastern suburb of Seoul Metropolitan City for its diverse forest patch types and data availability. Both Landsat ETM+ and IKONOS data are used for the classification. Preliminary results can be summarized as follows. First, topographic correction of reflectance is essential for the classification of forest patches on rugged terrain. Second, object oriented classification of IKONOS data enables higher classification accuracy compared to Landsat ETM+ and pixel-based classification. Third, multi-stage segmentation is very useful to investigate landscape ecological aspect of forest communities of Korea.

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Estimation of the Flood Area Using Multi-temporal RADARSAT SAR Imagery

  • Sohn, Hong-Gyoo;Song, Yeong-Sun;Yoo, Hwan-Hee;Jung, Won-Jo
    • Korean Journal of Geomatics
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    • 제2권1호
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    • pp.37-46
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    • 2002
  • Accurate classification of water area is an preliminary step to accurately analyze the flooded area and damages caused by flood. This step is especially useful for monitoring the region where annually repeating flood is a problem. The accurate estimation of flooded area can ultimately be utilized as a primary source of information for the policy decision. Although SAR (Synthetic Aperture Radar) imagery with its own energy source is sensitive to the water area, its shadow effect similar to the reflectance signature of the water area should be carefully checked before accurate classification. Especially when we want to identify small flood area with mountainous environment, the step for removing shadow effect turns out to be essential in order to accurately classify the water area from the SAR imagery. In this paper, the flood area was classified and monitored using multi-temporal RADARSAT SAR images of Ok-Chun and Bo-Eun located in Chung-Book Province taken in 12th (during the flood) and 19th (after the flood) of August, 1998. We applied several steps of geometric and radiometric calculations to the SAR imagery. First we reduced the speckle noise of two SAR images and then calculated the radar backscattering coefficient $(\sigma^0)$. After that we performed the ortho-rectification via satellite orbit modeling developed in this study using the ephemeris information of the satellite images and ground control points. We also corrected radiometric distortion caused by the terrain relief. Finally, the water area was identified from two images and the flood area is calculated accordingly. The identified flood area is analyzed by overlapping with the existing land use map.

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An Extraction of Solar-contaminated Energy Part from MODIS Middle Infrared Channel Measurement to Detect Forest Fires

  • Park, Wook;Park, Sung-Hwan;Jung, Hyung-Sup;Won, Joong-Sun
    • 대한원격탐사학회지
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    • 제35권1호
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    • pp.39-55
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    • 2019
  • In this study, we have proposed an improved method to detect forest fires by correcting the reflected signals of day images using the middle-wavelength infrared (MWIR) channel. The proposed method is allowed to remove the reflected signals only using the image itself without an existing data source such as a land-cover map or atmospheric data. It includes the processing steps for calculating a solar-reflected signal such as 1) a simple correction model of the atmospheric transmittance for the MWIR channel and 2) calculating the image-based reflectance. We tested the performance of the method using the MODIS product. When compared to the conventional MODIS fire detection algorithm (MOD14 collection 6), the total number of detected fires was improved by approximately 17%. Most of all, the detection of fires improved by approximately 30% in the high reflection areas of the images. Moreover, the false alarm caused by artificial objects was clearly reduced and a confidence level analysis of the undetected fires showed that the proposed method had much better performance. The proposed method would be applicable to most satellite sensors with MWIR and thermal infrared channels. Especially for geostationary satellites such as GOES-R, HIMAWARI-8/9 and GeoKompsat-2A, the short acquisition time would greatly improve the performance of the proposed fire detection algorithm because reflected signals in the geostationary satellite images frequently vary according to solar zenith angle.

Atmospheric Correction of Sentinel-2 Images Using Enhanced AOD Information

  • Kim, Seoyeon;Lee, Yangwon
    • 대한원격탐사학회지
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    • 제38권1호
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    • pp.83-101
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    • 2022
  • Accurate atmospheric correction is essential for the analysis of land surface and environmental monitoring. Aerosol optical depth (AOD) information is particularly important in atmospheric correction because the radiation attenuation by Mie scattering makes the differences between the radiation calculated at the satellite sensor and the radiation measured at the land surface. Thus, it is necessary to use high-quality AOD data for an appropriate atmospheric correction of high-resolution satellite images. In this study, we examined the Second Simulation of a Satellite Signal in the Solar Spectrum (6S)-based atmospheric correction results for the Sentinel-2 images in South Korea using raster AOD (MODIS) and single-point AOD (AERONET). The 6S result was overall agreed with the Sentinel-2 level 2 data. Moreover, using raster AOD showed better performance than using single-point AOD. The atmospheric correction using the single-point AOD yielded some inappropriate values for forest and water pixels, where as the atmospheric correction using raster AOD produced stable and natural patterns in accordance with the land cover map. Also, the Sentinel-2 normalized difference vegetation index (NDVI) after the 6S correction had similar patterns to the up scaled drone NDVI, although Sentinel-2 NDVI had relatively low values. Also, the spatial distribution of both images seemed very similar for growing and harvest seasons. Future work will be necessary to make efforts for the gap-filling of AOD data and an accurate bi-directional reflectance distribution function (BRDF) model for high-resolution atmospheric correction. These methods can help improve the land surface monitoring using the future Compact Advanced Satellite 500 in South Korea.