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The Added Value of Stratified Topographic Correction of Multispectral Images

Department of Projects and Rural Engineering, Campus Arrosadía, Public University of Navarre, Pamplona 31006, Spain
Author to whom correspondence should be addressed.
Academic Editors: Richard Gloaguen and Prasad S. Thenkabail
Remote Sens. 2016, 8(2), 131;
Received: 20 November 2015 / Revised: 26 January 2016 / Accepted: 29 January 2016 / Published: 15 February 2016
PDF [5884 KB, uploaded 15 February 2016]


Satellite images in mountainous areas are strongly affected by topography. Different studies demonstrated that the results of semi-empirical topographic correction algorithms improved when a stratification of land covers was carried out first. However, differences in the stratification strategies proposed and also in the evaluation of the results obtained make it unclear how to implement them. The objective of this study was to compare different stratification strategies with a non-stratified approach using several evaluation criteria. For that purpose, Statistic-Empirical and Sun-Canopy-Sensor + C algorithms were applied and six different stratification approaches, based on vegetation indices and land cover maps, were implemented and compared with the non-stratified traditional option. Overall, this study demonstrates that for this particular case study the six stratification approaches can give results similar to applying a traditional topographic correction with no previous stratification. Therefore, the non-stratified correction approach could potentially aid in removing the topographic effect, because it does not require any ancillary information and it is easier to implement in automatic image processing chains. The findings also suggest that the Statistic-Empirical method performs slightly better than the Sun-Canopy-Sensor + C correction, regardless of the stratification approach. In any case, further research is necessary to evaluate other stratification strategies and confirm these results. View Full-Text
Keywords: topographic correction; stratification; NDVI; land cover; evaluation; quality assessment topographic correction; stratification; NDVI; land cover; evaluation; quality assessment

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Sola, I.; González-Audícana, M.; Álvarez-Mozos, J. The Added Value of Stratified Topographic Correction of Multispectral Images. Remote Sens. 2016, 8, 131.

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