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Validation of aerosol estimation in atmospheric correction algorithm ATCOR

Pflug, Bringfried and Main-Knorn, Magdalena and Makarau, Aliaksei and Richter, Rudolf (2015) Validation of aerosol estimation in atmospheric correction algorithm ATCOR. In: Proceedings of International Symposium on Remote Sensing of Environment (ISRSE) 2015, XL-7 (W3), pp. 677-683. Copernicus Publications. 36th International Symposium on Remote Sensing of Environment (ISRSE), 11.-15. Mai 2015, Berlin, Germany. DOI: 10.5194/isprsarchives-XL-7-W3-677-2015

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Official URL: http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-7-W3/677/2015/

Abstract

Atmospheric correction of satellite images is necessary for many applications of remote sensing, i.e. computation of vegetation indices and biomass estimation. The first step in atmospheric correction is estimation of the actual aerosol properties. Due to the spatial and temporal variability of aerosol amount and type, this step becomes crucial for an accurate correction of satellite data. Consequently, the validation of aerosol estimation contributes to the validation of atmospheric correction algorithms. In this study we present the validation of aerosol estimation using own sun photometer measurements in Central Europe and measurements of AERONET-stations at different locations in the world. Our ground-based sun photometer measurements of vertical column aerosoloptical thickness (AOT) spectra are performed synchronously to overpasses of the satellites RapidEye, Landsat 5, Landsat 7 and Landsat 8. Selected AERONET data are collocated to Landsat 8 overflights. The validation of the aerosol retrieval is conducted by a direct comparison of ground-measured AOT with satellite derived AOT using the ATCOR tool for the selected satellite images. The mean uncertainty found in our experiments is ΔAOT550nm ≈ 0.03±0.02 for cloudless conditions with cloud+haze fraction below 1%. This AOT uncertainty approximately corresponds to an uncertainty in surface albedo of Δρ ≈ 0.003. Inclusion of cloudy and hazy satellite images into the analysis results in mean ΔAOT550nm ≈ 0.04±0.03 for both RapidEye and Landsat imagery. About ⅓ of samples perform with the AOT uncertainty better than 0.02 and about ⅔ perform with AOT uncertainty better than 0.05.

Item URL in elib:https://elib.dlr.de/95870/
Document Type:Conference or Workshop Item (Speech)
Additional Information:© Author(s) 2015. This work is distributed under the Creative Commons Attribution 3.0 License.
Title:Validation of aerosol estimation in atmospheric correction algorithm ATCOR
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Pflug, Bringfriedbringfried.pflug (at) dlr.deUNSPECIFIED
Main-Knorn, Magdalenamagdalena.main-knorn (at) dlr.deUNSPECIFIED
Makarau, Aliakseialiaksei.makarau (at) dlr.deUNSPECIFIED
Richter, Rudolfrudolf.richter (at) dlr.deUNSPECIFIED
Date:May 2015
Journal or Publication Title:Proceedings of International Symposium on Remote Sensing of Environment (ISRSE) 2015
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Volume:XL-7
DOI :10.5194/isprsarchives-XL-7-W3-677-2015
Page Range:pp. 677-683
Editors:
EditorsEmail
Schreier, G.UNSPECIFIED
Skrovseth, P. E.UNSPECIFIED
Staudenrausch, H.UNSPECIFIED
Publisher:Copernicus Publications
Series Name:ISPRS Archive
Status:Published
Keywords:Image processing, Atmospheric correction, ATCOR, validation, aerosol retrieval, RapidEye, Landsat
Event Title:36th International Symposium on Remote Sensing of Environment (ISRSE)
Event Location:Berlin, Germany
Event Type:international Conference
Event Dates:11.-15. Mai 2015
Organizer:International Society for Photogrammetry and Remote Sensing
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben Entwicklung und Erprobung von Verfahren zur Gewässerfernerkundung (old)
Location: Berlin-Adlershof , Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By:INVALID USER
Deposited On:17 Apr 2015 10:06
Last Modified:31 Jul 2019 19:52

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