• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
• /
• pp.1055-1057
• /
• 2003

In this research, the concrete with paint film was classified using hyper-spectral remote sensing. First, spectral characteristics of concrete and concrete with some kinds of paint films were investigated with a spectrometer. Second, using reflectance and first order derivative, spectral characteristics of the normal concrete and the concrete with paint film were classified. By using hyper-spectral remote sensing, not only extraction of crack but also inspection of paint film distribution is possible.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
• /
• pp.820-824
• /
• 2003

One of the most important research areas on remote sensing is spectral unmixing of hyper-spectral data. For spectral unmixing of hyper spectral data, accurate land cover information is necessary. But obtaining accurate land cover information is difficult process. Obtaining land cover information from high-resolution data may be a useful solution. In this study spectral signature of endmembers on ASTER acquired in October was calculated from land cover information on IKONOS acquired in September. Then the spectral signature of endmembers applied to ASTER images acquired on January and March. Then the result of spectral unmxing of them evauateted. The spectral signatures of endmembers could be applied to different seasonal images. When it applied to an ASTER image which have similar zenith angle to the image of the spectral signatures of endmembers, spectral unmixing result was reliable. Although test data has different zenith angle from the image of spectral signatures of endmembers, the spectral unmixing results of urban and vegetation were reliable.

• 대한원격탐사학회지
• /
• 제25권3호
• /
• pp.233-242
• /
• 2009

This paper presents two different types of supervised classifiers such as support vector machine (SVM) and spectral angle mapper (SAM). The Compact Airborne Spectrographic Imager (CASI) high resolution aerial image was classified with the above two classifier. The image was classified into eight land use /land cover classes. Accuracy assessment and Kappa statistics were estimated for SVM and SAM separately. The overall classification accuracy and Kappa statistics value of the SAM were 69.0% and 0.62 respectively, which were higher than those of SVM (62.5%, 0.54).

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
• /
• pp.65-65
• /
• 2008

See Full Text

• 대한원격탐사학회지
• /
• 제34권6_2호
• /
• pp.1203-1213
• /
• 2018

북극해 및 남극해는 접근이 어려운 지역으로 해양환경 모니터링을 위해 원격탐사 기술을 이용한 관측이 효과적이다. 원격탐사 플랫폼인 인공위성, 무인기와 선박 등에 관측센서를 장착하여 연구지역의 환경변화를 모니터링하고 있지만 극지역의 다양한 환경에서는 시계열자료 및 광범위한 데이터가 필요하다. 특히 고위도 지역에서는 낮은 태양고도의 영향으로 광학원격탐사를 적용하기는 쉽지않다. 본 논문에서는 2010년도 부터 극지연구소 쇄빙연구선 아라온호에 초분광계 HyperSAS(Satlantic inc.)를 설치하여 연구항해 및 이동항해 동안 해수의 분광학적 정보를 연속적으로 획득하고, 극지 해색 원격탐사자료 성능개선을 위해 현장에서 해수샘플을 채수하며 수행하고 있는 연구를 소개한다. 해수 상부의 반사도와 현장 해수샘플링은 2010년부터 연속적으로 획득하고 있어 동일 지역에 대한 반사도의 시계열 변화를 모니터링할 수 있다. 또한 고위도에서부터 저위도까지 연속적으로 관측하여 위도별 반사도 값의 연속 변화를 파악할 수 있다. 본 논문에서 취득한 자료는 극지역에서 남극해, 북극해 해수의 반사도가 어떻게 변화하는지 이해하고, 반사도를 통한 엽록소, 부유물질 등의 다양한 인자를 추정하는 알고리즘 개발에 활용될 것이다.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
• /
• pp.280-282
• /
• 2003

The downlink data rates of the space-born payloads such as high-resolution optical cameras, synthetic aperture radars (SAR) and hyper-spectral sensors are being rapidly increased. For example, the image transmission rates of KOMPSAT-2 MSC(Multi-Spectral Camera) is 320Mbps even if on-board image compression scheme is used.[1] In the near future, the data rates are expected to be a level 500${\sim}$600Mbps because the required resolution will be higher and the swath width will be increased. This paper describes many techniques they enable 500Mbps data receiving and archiving system.

• 대한원격탐사학회지
• /
• 제20권3호
• /
• pp.175-188
• /
• 2004

The objectives of this study were to estimate leaf area index (LAI) as a function of image-derived vegetation indices, and to compare measured and estimated LAI to the results of crop model simulation. Soil moisture, crop phenology, and LAI data were obtained several times during the 2001 growing season at monitoring sites established in two central Missouri experimental fields, one planted to com (Zea mays L.) and the other planted to soybean (Glycine max L.). Hyper- and multi-spectral images at varying spatial. and spectral resolutions were acquired from both airborne and satellite platforms, and data were extracted to calculate standard vegetative indices (normalized difference vegetative index, NDVI; ratio vegetative index, RVI; and soil-adjusted vegetative index, SAVI). When comparing these three indices, regressions for measured LAI were of similar quality $(r^2$ =0.59 to 0.61 for com; $r^2$ =0.66 to 0.68 for soybean) in this single-year dataset. CERES(Crop Environment Resource Synthesis)-Maize and CROPGRO-Soybean models were calibrated to measured soil moisture and yield data and used to simulate LAI over the growing season. The CERES-Maize model over-predicted LAI at all corn monitoring sites. Simulated LAI from CROPGRO-Soybean was similar to observed and image-estimated LA! for most soybean monitoring sites. These results suggest crop growth model predictions might be improved by incorporating image-estimated LAI. Greater improvements might be expected with com than with soybean.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
• /
• pp.142-145
• /
• 2007

In order to analyze hyper-spectral properties of Sand and Dust Storm (SDS), dust observation experiment has been performed at the Korea Global Atmosphere Watch Center (KGAW) in Anmyeon form early March to middle of May, 2007. We measured down-welling radiances by using ground-based Fourier Transform Infrared Spectroscopy (FT-IR) at the time of overpass of AIRS. And radiative transfer model simulation has been carried out to estimate the effects of size distribution, components, and altitude of SDS over the high resolution infrared spectrum in the range of 500-1500 $cm^{-1}$ with a line-by-line radiative transfer model and compared them with FT-IR and AIRS/Aqua observing data.

• 한국재난정보학회 논문집
• /
• 제6권2호
• /
• pp.87-106
• /
• 2010

This research focused on the effect of the GIS, uIT, and RS based smart disaster systems. Ubiquitous IT strongly involved in intelligent analysis for the natural disasters. Remote sensing technologies, such as hyper-spectral imaging, MODIS, LiDAR, Radar, and optical imaging processes, can contribute many means of investigation for the natural and unnatural problems in the atmosphere, hydrosphere, and lithosphere. Recent IT trends guides abundant smart solutions, such as automatic sensing using USN, RFID, and wireless communication devices. Smart monitoring systems using intelligent LBSs will produce many ways of checking, processes, and controls for the human safeties. In results, u-smart GIS, uIT, and RS based disaster systems must be using ubiquitous IT involved smart systems using intelligent GIS methods.

• 한국물환경학회지
• /
• 제31권3호
• /
• pp.272-285
• /
• 2015

Accurate assessment of chlorophyll-a (Chl-a) concentrations in inland waters using remote sensing is challenging due to the optical complexity of case 2 waters. and the inherent optical properties (IOPs) of natural waters are the most significant factors affecting light propagation within water columns, and thus play indispensable roles on estimation of Chl-a concentrations. Despite its importance, no IOPs retrieval model was specifically developed for inland water bodies, although significant efforts were made on oceanic inversion models. So we have applied and validated a recently developed Red-NIR three-band model and an IOPs Inversion Model for estimating Chl-a concentration and deriving inland water IOPs in Lake Uiam. Three band and IOPs based Chl-a estimation model accuracy was assessed with samples collected in different seasons. The results indicate that this models can be used to accurately retrieve Chl-a concentration and absorption coefficients. For all datasets the determination coefficients of the 3-band models versus Chl-a concentration ranged 0.65 and 0.88 and IOPs based model versus Chl-a concentration varied from 0.73 to 0.83 respectively. and Comparison between 3-band and IOPs based models showed significant performance with decrease of root mean square error from 18% to 33.6%. The results of this study provides the potential of effective methods for remote monitoring and water quality management in turbid inland water bodies using hyper-spectral remote sensing.