• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.82-86
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• 2009

원격탐사 근적외선(NIR)과 Red 밴드의 반사도로부터 계산되는 정규식생지수(NDVI)는 구름에 오염된 곳에서는 실제보다 낮은 값으로 계산된다. 식생지수에서 구름오염 문제를 극복하는 기존의 대표적인 방법에는 보름 정도 장기간 식생지수 값 중에서 최대인 값을 취하는 MVC(Maximum Value Composite) 방법이 있다. 하지만 MVC 방법으로는 식생지수의 단기간 변동을 파악할 수 없으며, 장기간 계속 구름으로 오염된 곳은 잘못된 식생지수 값으로 계산되는 문제점이 있다. 가시광 RGB 자료로부터 snapshot 영상자료의 구름을 마스크(mask)하는 새로운 방법인 CIM(Color Index Manipulation) 알고리즘을 개발하였다. 이 알고리즘을 사용하면 snapshot 영상자료에서 구름에 오염된 곳은 제외하고 오염되지 않은 곳에 대한 식생지수를 계산할 수 있다. RGB 자료에 대한 정규색상지수 NCI (Normalized Color Index) 3개 성분을 $120^{\circ}$ 간격으로 벌어진 3개 축상의 좌표로 나타낸 후 이들 3개 값의 벡터합(vector sum) 정보를 이용하여 구름을 식별하는 CIM 방법으로 위성영상에서 두꺼운 구름과 않은 구름을 구분하여 식별할 수 있다. 이 구름식별 기법을 MODIS snapshot 위성영상 자료에 적용하여 한반도의 일별(daily) 식생지수 자료를 계산하였다. 그리고 수년간의 일별 식생지수 자료로부터 한반도 식생지수의 계절적 변동을 조사하였다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2D
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• pp.325-333
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• 2006

Recently, in the case of observing the global environment, satellite remote sensing technology has been important. It's because satellite remote sensing is valuable for assessing relatively large areas. But now, small scale remote sensing techniques are needed which can be applicable to the detail investigation of plant tree areas which afforest land after the large scale construction of roads, dams and airports. In this study, we tried to develop and propose a lower altitude sensing technique which can be used in ground remote sensing by using a CCD camera. As a result of this investigation the following can be concluded: We recognized the transference characteristics of filters which were used in comparative tests about the four ground remote sensing devices. We also found that the near-IR camera could be used for an imaging spectral radiometer in the extraction of the vegetation index. Furthermore, we found that the vegetation index has varied hour by hour during the day of the experiment. Finally, we brought about an increase phase of the NDVI in a forest fire, which caused considerable damage, by developing new ground remote sensing technology.

• Korean Journal of Remote Sensing
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• v.29 no.2
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• pp.173-182
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• 2013

The early Sea-viewing Wide Field-of-view Sensor(SeaWiFS) atmospheric correction algorithm which is the basis of the atmospheric correction algorithm for Geostationary Ocean Color Imager(GOCI) assumes that water-leaving radiances is negligible at near-infrared(NIR) wavelengths. For this reason, all of the satellite measured radiances at the NIR wavelengths are assigned to aerosol radiances. However that assumption would cause underestimation of water-leaving radiances if it were applied to turbid Case-2 waters. To overcome this problem, Management Unit of the North Sea Mathematical Models(MUMM) atmospheric correction algorithm has been developed for turbid waters. This MUMM algorithm introduces new parameter ${\alpha}$, representing the ratio of water-leaving reflectance at the NIR wavelengths. ${\alpha}$ is calculated by statistical method and is assumed to be constant throughout the study area. Using this algorithm, we can obtain comparatively accurate water-leaving radiances in the moderately turbid waters where the NIR water-leaving reflectance is less than approximately 0.01. However, this algorithm still underestimates the water-leaving radiances at the extremely turbid water since the ratio of water-leaving radiance at two NIR wavelengths, ${\alpha}$ is changed with concentration of suspended particles. In this study, we modified the MUMM algorithm to calculate appropriate value for ${\alpha}$ using an iterative technique. As a result, the accuracy of water-leaving reflectance has been significantly improved. Specifically, the results show that the Root Mean Square Error(RMSE) of the modified MUMM algorithm was 0.002 while that of the MUMM algorithm was 0.0048.

• Korean Journal of Remote Sensing
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• v.32 no.5
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• pp.529-538
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• 2016

This study, multispectral and hyperspectral sensors were utilized to use radiometric cross validation for the purpose of radiometric quality evaluation of a 'KOMPSAT-3'. Images of EO-1 Hyperion and Landsat-8 OLI sensors taken in PICS site were used. 2 sections that have 2 different types of ground coverage respectively were selected as the site of cross validation based on aerial hyperspectral sensor and TOA Reflectance. As a result of comparison between the TOA reflectance figures of KOMPSAT-3, EO-1 Hyperion and CASI-1500, the difference was roughly 4%. It is considered that it satisfies the radiological quality standard when the difference of figure of reflectance in a comparison to the other satellites is found within 5%. The difference in Blue, Green, Red band was approximately 3% as a comparison result of TOA reflectance. However the figure was relatively low in NIR band in a comparison to Landsat-8. It is thought that the relatively low reflectance is because there is a difference of band passes in NIR band of 2 sensors and in a case of KOMPSAT-3 sensor, a section of 940nm, which shows the strong absorption through water vapor, is included in band pass resulting in comparatively low reflectance. To overcome these conditions, more detailed analysis with the application of rescale method as Spectral Bandwidth Adjustment Factor (SBAF) is required.

• Korean Journal of Remote Sensing
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• v.14 no.3
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• pp.277-284
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• 1998

To establish a monthly data collection planning for the Ocean Scanning Multispectral Imager (OSMI), we have examined the global patterns of three impacting factors: pigment concentration, cloud cover, and sun glint. Other than satellite mission constraints (e.g., duty cycle), these three factors are considered critical for the OSMI data collection. The Nimbus-7 Coastal Zone Color Scanner (CZCS) monthly mean products and the International Satellite Cloud Climatology Project (ISCCP) monthly mean products (C2) were used for the analysis of pigment concentration and cloud cover distributions, respectively. And the monthly-simulated patterns of sun glint were produced by performing the OSMI orbit prediction and the calculation of sun glint radiances at the top-of-atmosphere (TOA). Using monthly statistics (mean and/or standard deviation) of each factor in the above for a given 10$^{\circ}$ latitude by 10$^{\circ}$ longitude grid, we generated the priority map for each month. The priority maps of three factors for each month were subsequently superimposed to visualize the impact of three factors in all. The initial results illustrated that a large part of oceans in the summer hemisphere was classified into the low priority regions because of seasonal changes of clouds and sun illumination. Sensitivity tests for different sets of classifications were performed and demonstrated the seasonal effects of clouds and sun glint to be robust.

• Korean Journal of Remote Sensing
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• v.29 no.1
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• pp.81-94
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• 2013

The Radar altimeter transmits radio signals to the surface, receives the backscattered signals and measures the distance between the airplane and the nadir surface. The measurements of radar altimeter are affected by various factors on the surface below the aircraft. This study performed flight campaigns in June 2012 and acquired raw data from radar altimeter, LiDAR and other sensors. Based on the LiDAR DSM (Digital Surface Model) as a reference data, the characteristics of radar altimeter were analyzed in the respect of range and surface area affecting on the receiving power of the radar altimeter. Consequently, the radar altimeter was strongly affected by the surface area within beam width and reflectivity related to RCS (Radar Cross Section) rather than range.

• Proceedings of the KSRS Conference
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• 2007.03a
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• pp.153-157
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• 2007

본 논문은 지표면 현상의 관측에 날씨의 영향을 거의 받지 않는 마이크로파 L-밴드(1.95 GHz)와 C-밴드(5.3 GHz) scatterometer 시스템을 이용하여 농업과학기술원 내의 논에서 자라는 추청벼를 대상으로 2006년 5월 29일부터 10월 9일까지 생육에 따른 군락의 후방산란계수를 관측한 데이터와 작물의 생육과의 관계를 살펴보고 또한，측정 시스템의 개요，측정 시스템의 보정 방법들을 기술하고자 한다. Scatterometer 시스템의 송 수신기로 HP 8753D 벡터 네트워크 분석기를 사용하며，타워 위에 안테나를 설치하여 3.4 m의 높이에서 측정하도록 하였다. L-밴 드와 C-밴드 scatterometer는 VV-, VH-, HV-, HH-편파를 측정하여 fully polarimetric한 데이터를 얻도록 설계된 레이더시스템으로 입사각을 $30^{\circ}{\sim}60^{\circ}$에서 $10^{\circ}$간격으로 각각 30개의 독립적인 샘플을 측정하여 통계적으로 후방산란계수를 얻었다. 타워에서 발생하는 전파 잡음과 안테나 패턴의 부엽에 의한 지면에서의 수직반사(coherent 성분) 전파를 제거하기 위해 네트워크 분석기의 time gating 기능을 사용하며，55 cm 크기의 trihedral 전파반사기를 보정용 반사기로 사용하고， STCT(single target calibration technique) 방법을 이용하여 시스템을 보정하였다. 측정 결과를 분석하여 주파수， 입사각도， 편파의 변화에 대한 벼의 후방산란 특성과 벼의 생육상태과의 관계를 살펴보았다. L-밴드와 C-밴드 모두 벼의 생육과 밀접한 결과를 나타내었으나，입사각이 작을 때는 C-밴드와의 상관이 높게 나타났고 입사각이 커질수록 L-밴드와의 상관이 높게 나타났다. 편파는 L-밴드 와 C-밴드 모두 hh 편파가，입사각은 50도에서 가장 생육의 변이를 잘 설명하는 것으로 나타났다. 생육 데이터 모두를 이용한 경우보다는 유수형성기 또는 출수기 등 벼 생육의 질적인 변화를 보이는 시기에 따라 나누어 분석하는 것이 변화추이를 더 잘 설명하는 것으로 나타났다.

• Spatial Information Research
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• v.23 no.2
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• pp.31-38
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• 2015

Remote sensing data is used to increasing efficiency on benthic cover type survey. Satellite and aerial imagery has variance of reflectance by water column effect even if bottom is consisted with same cover type and condition. This study tried to analyze advances of surveying extent and accuracy through water column correction of CASI-1500 hyperspectral image. Study area is coast of Gangneung city, South Korea where benthic environment is rapidly changing with bleaching of coral reef. Water column correction coefficient was estimated using regression models between water reflectance ($R_W$) and depth for sand bottom then the coefficients were applied to whole image. The results shows that expanded interpretable depth from 6-7m to 15m and decreased variation of reflectance by depth. Additionally, water column corrected reflectance image shows 13%p increased accuracy on benthic cover type classification.

• Korean Journal of Remote Sensing
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• v.11 no.3
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• pp.117-127
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• 1995

In this paper several methods for retriving appropriate values of effective soil moisture contents from natural soil surfaces are introduced and compared each other. The soil medium has usually a nonuniform moisture profile; i.e., relatively dry at the top layer and relatively wet at the bottom layer. The effective soil moisture represents the quantitative value of soil moisture of the inhomogeneous soil medium in an average sense. A simple method is an arithmetic averaging of soil moisture values obtained from several layers of a soil surface. Otherwise, the penetration depths can be computed from a homogeneous and an inhomogeneous soil surfaces and compared in order to obtain the effective soil mosture. The other method is to obtain the effective soil moisture by comparing the reflectivities from both of a homogeneous and an inhomogeneous surfaces. Those methods are compared and the reflectivity technique is examined in more detail since the rader scattering is dominated by the reflectivity instead of the penetration.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.5
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• pp.779-787
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• 2011

This study was conducted to evaluate the usefulness of ground-based remote sensing for the estimation of rice yield and application rate of N-fertilizer during growing season. Dongjin-1, Korean cultivar of rice was planted on May 30, 2006 and harvested on October 9, 2006. Chlorophyll content and LAI (leaf area index) were measured using Minolta SPAD-502 and AccuPAR model LP-80, respectively. Reflectance indices were determined with passive sensors using sunlight and four types of active sensors using modulated light, respectively. Reflectance indices and growth rate were measured three times from 29 days to 87 days after rice plating and at harvesting day. The result showed that values of growing characteristics and reflectance indices were highly correlated. Growing characteristics to show significant correlation with reflectance indices were in order of followings: fresh weight > N uptake > dry weight > height > No. of tiller > N content. Chlorophyll contents measured by chlorophyll meter (SPAD 502) showed high correlation with nitrogen concentration (r=$0.743^{**}$), although the correlation coefficients between remote sensing data and nitrogen concentration were higher. LAI was highly correlated with dry weight (r=$0.931^{**}$), but relationship between LAI and nitrogen concentration (r=$0.505^*$) was relatively low. The data of CC-passive sensor were negatively correlated with those of the near-infrared. NDVI correlation coefficients found more useful to identify the growth characteristics rather than data from single wavelength. Both passive sensor and active sensor were highly significantly correlated with growth characteristics. Consequently, quantifying the growth characteristics using reflectance indices of ground-based remote sensing could be a useful tool to determine the application rate of N fertilizer non-destructively and in real-time.