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

Lee, Hwa-Seon; Lee, Kyu‐Sung

doi:10.7780/kjrs.2015.31.4.4

Cited by 6 publications

(6 citation statements)

References 17 publications

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“…In addition, BRDF was not considered. Moreover, the atmospheric correction result of multi-temporal high spatial resolution images from different satellite sensors was inconsistent owing to unstable radiometric calibration coefficients and different sun-sensor geometries (Lee and Lee, 2015).…”

Section: Resultsmentioning

confidence: 99%

High Spatial Resolution Satellite Image Simulation Based on 3D Data and Existing Images

La¹,

Jeon²,

Eo³

et al. 2016

Journal of the Korean Society of Surveying, Geodesy, Photogramm

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This study proposes an approach for simulating high spatial resolution satellite images acquired under arbitrary sun-sensor geometry using existing images and 3D (three-dimensional) data. First, satellite images, having significant differences in spectral regions compared with those in the simulated image were transformed to the same spectral regions as those in simulated image by using the UPDM (Universal Pattern Decomposition Method). Simultaneously, shadows cast by buildings or high features under the new sun position were modeled. Then, pixels that changed from shadow into non-shadow areas and vice versa were simulated on the basis of existing images. Finally, buildings that were viewed under the new sensor position were modeled on the basis of open library-based 3D reconstruction program. An experiment was conducted to simulate WV-3 (WorldView-3) images acquired under two different sun-sensor geometries based on a Pleiades 1A image, an additional WV-3 image, a Landsat image, and 3D building models. The results show that the shapes of the buildings were modeled effectively, although some problems were noted in the simulation of pixels changing from shadows cast by buildings into non-shadow. Additionally, the mean reflectance of the simulated image was quite similar to that of actual images in vegetation and water areas. However, significant gaps between the mean reflectance of simulated and actual images in soil and road areas were noted, which could be attributed to differences in the moisture content. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http:// creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Section: Resultsmentioning

confidence: 99%

High Spatial Resolution Satellite Image Simulation Based on 3D Data and Existing Images

La¹,

Jeon²,

Eo³

et al. 2016

Journal of the Korean Society of Surveying, Geodesy, Photogramm

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“…It underwent geometric correction utilizing Rational Function Coefficients (RPCs), with further corrections made by selecting Ground Control Points (GCPs) using the Landsat OLI image as a reference. The Top of Atmosphere (TOA) radiance was calculated from gain values and subsequently converted to reflectance [39]. The Landsat OLI data, acquired as Level 1 products from the USGS website, received atmospheric correction through the QUAC model in ENVI 5.6.3 software (NV5 geospatial, Broomfield, CO, USA) [40].…”

Section: Dye Observationsmentioning

confidence: 99%

Near-Surface Dispersion and Current Observations Using Dye, Drifters, and HF Radar in Coastal Waters

Kim,

Tran,

Song

et al. 2024

Remote Sensing

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This study explores the near-surface dispersion mechanisms of contaminants in coastal waters, leveraging a comprehensive method that includes using dye and drifters as tracers, coupled with diverse observational platforms like drones, satellites, in situ sampling, and HF radar. The aim is to deepen our understanding of surface currents’ impact on contaminant dispersion, thereby improving predictive models for managing environmental incidents such as pollutant releases. Rhodamine WT dye, chosen for its significant fluorescent properties and detectability, along with drifter data, allowed us to investigate the dynamics of near-surface physical phenomena such as the Ekman current, Stokes drift, and wind-driven currents. Our research emphasizes the importance of integrating scalar tracers and Lagrangian markers in experimental designs, revealing differential dispersion behaviors due to near-surface vertical shear caused by the Ekman current and Stokes drift. During slow-current conditions, the elongation direction of the dye patch aligned well with the direction of a depth-averaged Ekman spiral, or Ekman transport. Analytical calculations of vertical shear, based on the Ekman current and Stokes drift, closely matched those derived from tracer observations. Over a 7 h experiment, the vertical diffusivity near the surface was first observed at the early stages of scalar mixing, with a value of 1.9×10−4 m2/s, and the horizontal eddy diffusivity of the dye patch and drifters reached the order of 1 m2/s at a 1000 m length scale. Particle tracking models demonstrate that while HF radar currents can effectively predict the trajectories of tracers near the surface, incorporating near-surface currents, including the Ekman current, Stokes drift, and windage, is essential for a more accurate prediction of the fate of surface floats.

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“…HS data from different sources often overlap spatially and spectrally, but their integration (to leverage relative advantages or differences in coverage of the various available sensors) and comparison (to assess their relative consistency and resolving ability) radiance, and then we must remove atmospheric and topographic effects to estimate surface reflectance [23]. These pre-processing and correction workflows can be very complex and are a significant source of uncertainty that can greatly influence geological mapping results (e.g., [21,24,25]).…”

Section: Introductionmentioning

confidence: 99%

A Spectral and Spatial Comparison of Satellite-Based Hyperspectral Data for Geological Mapping

Chakraborty,

Rachdi,

Thiele

et al. 2024

Remote Sensing

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The new generation of satellite hyperspectral (HS) sensors provides remarkable potential for regional-scale mineralogical mapping. However, as with any satellite sensor, mapping results are dependent on a typically complex correction procedure needed to remove atmospheric, topographic and geometric distortions before accurate reflectance spectra can be retrieved. These are typically applied by the satellite operators but use different approaches that can yield different results. In this study, we conduct a comparative analysis of PRISMA, EnMAP, and EMIT hyperspectral satellite data, alongside airborne data acquired by the HyMap sensor, to investigate the consistency between these datasets and their suitability for geological mapping. Two sites in Namibia were selected for this comparison, the Marinkas-Quellen and Epembe carbonatite complexes, based on their geological significance, relatively good exposure, arid climate and data availability. We conducted qualitative and three different quantitative comparisons of the hyperspectral data from these sites. These included correlative comparisons of (1) the reflectance values across the visible-near infrared (VNIR) to shortwave infrared (SWIR) spectral ranges, (2) established spectral indices sensitive to minerals we expect in each of the scenes, and (3) spectral abundances estimated using linear unmixing. The results highlighted a notable shift in inter-sensor consistency between the VNIR and SWIR spectral ranges, with the VNIR range being more similar between the compared sensors than the SWIR. Our qualitative comparisons suggest that the SWIR spectra from the EnMAP and EMIT sensors are the most interpretable (show the most distinct absorption features) but that latent features (i.e., endmember abundances) from the HyMap and PRISMA sensors are consistent with geological variations. We conclude that our results reinforce the need for accurate radiometric and topographic corrections, especially for the SWIR range most commonly used for geological mapping.

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

Cited by 6 publications

References 17 publications

High Spatial Resolution Satellite Image Simulation Based on 3D Data and Existing Images

High Spatial Resolution Satellite Image Simulation Based on 3D Data and Existing Images

Near-Surface Dispersion and Current Observations Using Dye, Drifters, and HF Radar in Coastal Waters

A Spectral and Spatial Comparison of Satellite-Based Hyperspectral Data for Geological Mapping

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