Radiometric characterization of IKONOS multispectral imagery

Pagnutti, Mary; Ryan, Robert; Kelly, Michelle; Holekamp, Kara; Zanoni, Vicki; Thome, Kurtis J.; Schiller, Stephen

doi:10.1016/j.rse.2003.07.008

Cited by 60 publications

(38 citation statements)

References 16 publications

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“…Calibration coefficients for the IKONOS-2 images were officially provided (Dial et al, 2003;Pagnutti et al, 2003).…”

Section: ) Atmospheric Correctionmentioning

confidence: 99%

Atmospheric Correction Problems with Multi-Temporal High Spatial Resolution Images from Different Satellite Sensors

Lee¹,

Lee²

2015

Korean Journal of Remote Sensing

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Since the launch of the IKONOS-1 in 1999 and several other following commercial satellites, High Spatial Resolution (HSR) satellite images have been widely used for topographic mapping, Digital Elevation Model (DEM) data generation, and urban and land cover classifications. On the other hand, it has been relatively rare to find quantitative applications for extracting biophysical parameters from HSR images.Although there have been a few cases of using HSR images to extract information regarding the physical conditions of vegetation (Imukova et al., 2015;Pu and Cheng, 2015;Tillack et al., 2014;Sprintsin et al., 2007) and water quality (Choe et al., 2015; Chang et al., 2009) Department of Geoinformatic Engineering, Inha UniversityAbstract : Atmospheric correction is an essential part in time-series analysis on biophysical parameters of surface features. In this study, we tried to examine possible problems in atmospheric correction of multitemporal High Spatial Resolution (HSR) images obtained from two different sensor systems. Three KOMPSAT-2 and two IKONOS-2 multispectral images were used. Three atmospheric correction methods were applied to derive surface reflectance: (1) Radiative Transfer (RT) -based absolute atmospheric correction method, (2) the Dark Object Subtraction (DOS) method, and (3) the Cosine Of the Uun zeniTh angle (COST) method. Atmospheric correction results were evaluated by comparing spectral reflectance values extracted from invariant targets and vegetation cover types. In overall, multi-temporal reflectance from five images obtained from January to December did not show consistent pattern in invariant targets and did not follow a typical profile of vegetation growth in forests and rice field. The multi-temporal reflectance values were different by sensor type and atmospheric correction methods. The inconsistent atmospheric correction results from these multi-temporal HSR images may be explained by several factors including unstable radiometric calibration coefficients for each sensor and wide range of sun and sensor geometry with the off-nadir viewing HSR images.Key Words : Atmospheric correction, high spatial resolution, calibration coefficients, multi-temporal, surface reflectance, KOMPSAT, IKONOS Atmospheric Correction MethodsAtmospheric correction of optical imagery is mainly to derive purely reflected portion of energy from the atsensor radiance (Lt) by removing the amount of radiance influenced by atmospheric effects. The radiance (Lt) received on-board sensor can be expressed in a simple form of equation (Eq. 1) and atmospheric correction is the process of extracting surface reflectance (ρ) from Lt.where ρ = surface reflectance, E = solar and diffuse irradiance on surface, T = transmittance of atmosphere, and Lp = path radiance.Atmospheric correction methods of optical imagery can be divided into two major categories by means of obtaining the unknown variables of T and Lp in (Eq. 1).Absolute atmospheric correction is based on the calculation of physical processes of radiative trans...

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“…Calibration coefficients for the IKONOS-2 images were officially provided (Dial et al, 2003;Pagnutti et al, 2003).…”

Section: ) Atmospheric Correctionmentioning

confidence: 99%

Atmospheric Correction Problems with Multi-Temporal High Spatial Resolution Images from Different Satellite Sensors

Lee¹,

Lee²

2015

Korean Journal of Remote Sensing

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“…Radiometric calibration coefficients developed by the NASA calibration team (Pagnutti et al, 2003) were used for IKONOS images.…”

Section: ) Image Data Used and Image Processingmentioning

confidence: 99%

Comparing LAI Estimates of Corn and Soybean from Vegetation Indices of Multi-resolution Satellite Images

Kim¹,

Hong²,

Sudduth³

et al. 2012

Korean Journal of Remote Sensing

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: Leaf area index (LAI) is important in explaining the ability of the crop to intercept solar energy for biomass production and in understanding the impact of crop management practices. This paper describes a procedure for estimating LAI as a function of image-derived vegetation indices from temporal series of IKONOS, Landsat TM, and MODIS satellite images using empirical models and demonstrates its use with data collected at Missouri field sites. LAI data were obtained several times during the 2002 growing season at monitoring sites established in two central Missouri experimental fields, one planted to soybean (Glycine max L.) and the other planted to corn (Zea mays L.). Satellite images at varying spatial and spectral resolutions were acquired and the data were extracted to calculate normalized difference vegetation index (NDVI) after geometric and atmospheric correction. Linear, exponential, and expolinear models were developed to relate temporal NDVI to measured LAI data. Models using IKONOS NDVI estimated LAI of both soybean and corn better than those using Landsat TM or MODIS NDVI. Expolinear models provided more accurate results than linear or exponential models.

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“…Relevant instruments include multispectral photogrammetric cameras and other hyper-and multi-spectral sensors, and laser scanners. The elementary requirements of radiometric test sites are to provide targets or surfaces with traceable radiance and reflectance values and targets for point spread function (PSF) measurement [2][3][4][5][6].…”

Section: Open Accessmentioning

confidence: 99%

“…In Europe, the idea of a European-wide test site network for geometry and radiometry has been established [8], but currently only individual test site concepts are available [10][11][12]. Existing permanent test sites for the radiometric calibration of airborne systems are the Sjökulla test site of the Finnish Geodetic Institute (FGI) in Finland (Section 3.1) [12] and the Stennis Space Center (SSC) test site in the US [3,4].…”

Section: Open Accessmentioning

confidence: 99%

Analysis of Properties of Reflectance Reference Targets for Permanent Radiometric Test Sites of High Resolution Airborne Imaging Systems

et al. 2010

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Reliable and optimal exploitation of rapidly developing airborne imaging methods requires geometric and radiometric quality assurance of production systems in operational conditions. Permanent test sites are the most promising approach for cost-efficient performance assessment. Optimal construction of permanent radiometric test sites for high resolution airborne imaging systems is an unresolved issue. The objective of this study was to assess the performance of commercially available gravels and painted and unpainted concrete targets for permanent, open-air radiometric test sites under sub-optimal climate conditions in Southern Finland. The reflectance spectrum and reflectance anisotropy and their stability were characterized during the summer of 2009. The management of reflectance anisotropy and stability were shown to be the key issues for better than 5% reflectance accuracy.

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Radiometric characterization of IKONOS multispectral imagery

Cited by 60 publications

References 16 publications

Atmospheric Correction Problems with Multi-Temporal High Spatial Resolution Images from Different Satellite Sensors

Atmospheric Correction Problems with Multi-Temporal High Spatial Resolution Images from Different Satellite Sensors

Comparing LAI Estimates of Corn and Soybean from Vegetation Indices of Multi-resolution Satellite Images

Analysis of Properties of Reflectance Reference Targets for Permanent Radiometric Test Sites of High Resolution Airborne Imaging Systems

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