• 한국콘텐츠학회논문지
• /
• 제16권7호
• /
• pp.31-41
• /
• 2016

하이퍼스펙트럴 영상을 이용하여 토지피복 분류를 정확히 수행하기 위해서는 전처리 작업으로서 대기보정을 거쳐야 한다. 항공 하이퍼스펙트럴 영상에 대하여 대기보정을 실시하고 대기보정 유 무에 따른 해수, 갯벌, 식생, 아스팔트, 콘크리트 등의 토지피복 항목별 분광반사율 특성을 비교하여 대기보정의 뚜렷한 효과를 확인할 수 있었다. 대기보정 후의 영상에 대하여 최대우도법, 분광각맵퍼법 등의 화소기반 감독분류기법으로 각각 토지피복 분류를 행하고 그 결과를 비교하였다. 분광각맵퍼법의 경우 임계각 $0.4^{\circ}$에서 노이즈를 최소화하면서 해수영역을 가장 양호하게 분류해 낼 수 있었다. 같은 개체라도 다양한 분광특성을 나타내는 하이퍼스펙트럴 영상의 경우 연안지역에서는 종래의 화소기반 분류기법보다는 축척, 분광 정보, 형태, 결 등을 종합적으로 고려하는 객체기반 분류기법이 더 우월할 것으로 사료된다.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
• /
• pp.196-200
• /
• 2004

The purpose of this study is to examine the image­based atmospheric correction models using the data from Landsat Enhanced Thermal Mapper Plus (ETM+) that have quite similar spectral characteristics to the forthcoming Korea Multi-Purpose SATellite (KOMPSAT)-2 Multi-Spectral Camera (MSC), and the in-situ measured surface reflectance data during satellite overflight. The main advantage of this type of correction is that it does not require in-situ measurements during each satellite overflight. While substantial differences are present between Top-Of-the Atmosphere (TOA) reflectance and in-situ measurements, the results showed that Case 1 based on COST model gives most accurate results among three cases. The accuracy of Case 2 is very close to Case 1 and its values are smaller than in-situ data. No notable features appear between some bands in the Case 3 and in-situ data. It is expected from this study that if the current methods are applied to the IKONOS high resolution data, we will be able to develop the suitable atmospheric correction methods for MSC data.

• 대한원격탐사학회지
• /
• 제25권6호
• /
• pp.487-499
• /
• 2009

Atmospheric correction of satellite measurements is a major step to estimate accurate surface reflectance of solar spectrum channels. In this study, Simplified Method for the Atmospheric Correction (SMAC) radiative transfer model used to retrieve surface reflectance from MODIS (MODerate resolution Imaging Spectrometer) top of atmosphere (TOA) reflectance. It is fast and simple atmospheric correction method, so it uses for work site operation in various satellite. This study attempts a test of accuracy of SMAC through a sensitivity test to detected error sources and to improve accuracy of surface reflectance using SMAC. The results of SMAC as compared with MODIS surface reflectance (MOD09) was represented that low accuracy ($R^2\;=\;0.6196$, Root Means Square Error (RMSE) = 0.00031, bias = - 0.0859). Thus sensitivity analysis of input parameters and coefficients was conducted to searching error sources. Among the input parameters, Aerosol Optical Depth (AOD) is the most influence input parameter. In order to modify AOD term in SMAC code, Stepwise multiple regression was performed with testing and remove variable in three stages with independent variables of AOD at 550nm, solar zenith angle, viewing zenith angle. Surface reflectance estimation by using Newly proposed AOD term in the study showed that improve accuracy ($R^2\;=\;0.827$, RMSE = 0.00672, bias = - 0.000762).

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
• /
• pp.418-421
• /
• 2005

In this study, we analyzed surface temperature of lakes in the Han River system, using Landsat-5 and -7 time-series images. Surface temperature was extracted using NASA equation and compared with in situ 10m-depth temperature in Lake Soyang and surface temperature on five other dam lakes downstream. The 24 images out of 29 showed standard deviation of temperature difference less than $2^{\circ}C$, to which a novel statistical atmospheric correction could be applied. The correlation coefficients were 0.950 at Lake Soyang and 0.979-0.997 at the other lakes after atmospheric correction.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
• /
• pp.404-408
• /
• 1998

Yellow sand event has been studied using SeaWiFS data in order to examine the aerosol optical characteristics in the Yellow Sea and their influences on the atmospheric correction for the ocean color remote sensing. Two SeaWiFS images of April 18 and April 25, 1998, representing Yellow Sand event and clear-sky case respectively, are selected for emphasizing the impact of high aerosol concentration on the ocean color remote sensing. It was shown that NASA's standard atmospheric correction algorithm treats yellow sand area as either too high radiance or cloud area, in which ocean color information is not generated. SeaWiFS aerosol optical thickness is compared with nearby ground-based sun photometer measurements and also is compared with radiative transfer simulation in conjunction with yellow sand model, examining the performance of NASA's atmospheric correction algorithm in case of the heavy dust event.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
• /
• pp.103-109
• /
• 1998

A technique on atmospheric correction algorithm for a single band (0.76-0.90 $\mu$m) reflective of Landsat TM imagery has been developed using a radiation transfer model simulation. It proceeds in two steps: First, calculation of the surface reflectance of each pixel based on precomputed planetary albedo functions for actual atmospheres(e. g. radiosonde) and two kinds of atmospheric visibility states. Second, approximate correction of the adjacency pixel effect by taking into account the average reflectance in an 7 $\times$ 7 pixel neighbourhood and using appropriate land cover classification in reflectance. The correction functions are provided by MODTRAN model.

• 대한원격탐사학회지
• /
• 제24권5호
• /
• pp.417-425
• /
• 2008

An image-based atmospheric correction software ATC is implemented using MATLAB and SML (Spatial Modeler Language in ERDAS IMAGINE), and it was tested using Landsat TM/ETM+ data. This ATC has two main functional modules, which are composed of a semiautomatic type and an automatic type. The semi-automatic functional module includes the Julian day (JD), Earth-Sun distance (ESD), solar zenith angle (SZA) and path radiance (PR), which are programmed as individual small functions. For the automatic functional module, these parameters are computed by using the header file of Landsat TM/ETM+. Three atmospheric correction algorithms are included: The apparent reflectance model (AR), one-percent dark object subtraction technique (DOS), and cosine approximation model (COST). The ACT is efficient as well as easy to use in a system with MATLAB and SML.

• 대기
• /
• 제24권4호
• /
• pp.491-502
• /
• 2014

As a part of the KIAPS (Korea Institute of Atmospheric Prediction Systems) Package for Observation Processing (KPOP), we have developed the modules for Advanced Microwave Sounding Unit-A (AMSU-A) pre-processing and its bias correction. The KPOP system calculates the airmass bias correction coefficients via the method of multiple linear regression in which the scan-corrected innovation and the thicknesses of 850~300, 200~50, 50~5, and 10~1 hPa are respectively used for dependent and independent variables. Among the four airmass predictors, the multicollinearity has been shown by the Variance Inflation Factor (VIF) that quantifies the severity of multicollinearity in a least square regression. To resolve the multicollinearity, we adopted simple linear regression and Principal Component Regression (PCR) to calculate the airmass bias correction coefficients and compared the results with those from the multiple linear regression. The analysis shows that the order of performances is multiple linear, principal component, and simple linear regressions. For bias correction for the AMSU-A channel 4 which is the most sensitive to the lower troposphere, the multiple linear regression with all four airmass predictors is superior to the simple linear regression with one airmass predictor of 850~300 hPa. The results of PCR with 95% accumulated variances accounted for eigenvalues showed the similar results of the multiple linear regression.

• 대한원격탐사학회지
• /
• 제25권1호
• /
• pp.11-20
• /
• 2009

우리나라는 황사발생 빈도가 증가하고 특히 하절기에 강우 및 구름 발생이 잦아 위성원격탐사영상의 대기보정처리를 필요로 한다. 본 연구에서는 대기보정 전후의 클래스별 화소값 분포 변화를 비교하여 대기보정이 영상화소분류에 미치는 영향을 분석하였다. 실험에 사용된 영상은 LANDSAT-5 TM이고, 대기보정 모듈로는 상용 소프트웨어인 ATCOR, FLAASH와 인터넷에 공개된 COST 모델 3가지를 적용하였다. 실험 결과, 건물밀집 지역 영역에서 클래스 분리도가 향상되는 것으로 나타났다.

• 대한원격탐사학회지
• /
• 제34권6_1호
• /
• pp.981-996
• /
• 2018

농업분야에서 지구관측위성을 활용한 원격탐사 자료는 시간적, 공간적, 그리고 효율성 측면에서 다른 방법에 비해 많은 이점을 가진다. 본 연구는 위성영상의 농업활용에 앞서 영상의 대기보정에 따른 반사도와 식생지수의 변화 분석을 위해 다중분광위성자료의 대기상층 반사도(Top of Atmosphere Reflectance; TOA Reflectance)와 대기보정을 통한 표면 반사도(Surface Reflectance)를 산출하여 각 밴드별 반사도, 식생지수를 비교하였다. 그 결과 지상계측센서와 위성에서 관측된 식생지수는 영상의 대기보정을 통해 산출된 표면반사도가 TOA Reflectance 보다 높은 일치율과 상관성을 나타났다. 다중시기 영상에 대하여 대기보정 전/후 NDVI를 비교한 결과 모든 시기에서 대기보정 수행 후 NDVI 상승하였다. 특히 식생 활력도가 높은 수확직전의 시기의 경우 NDVI 상승폭이 크게 나타났다. 서로 다른 반사 특성을 가지는 토지피복의 경우에도 식생 활력도가 높은 마늘, 양파 재배지역과 산림의 경우 0.1 이상의 NDVI 변화를 보였다. 이 같은 결과는 NIR 밴드대역이 수증기 흡수대역에 있어 대기보정으로 인해 영향을 받기 때문이다. 따라서 위성영상을 농업분야에 활용함에 있어 대기보정은 NDVI 분석에 있어 매우 중요한 과정으로 볼 수 있다.