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Remote Sens. 2013, 5(12), 6767-6789; doi:10.3390/rs5126767

Evaluation of Different Topographic Corrections for Landsat TM Data by Prediction of Foliage Projective Cover (FPC) in Topographically Complex Landscapes

1
School of Environment, Science and Engineering, Southern Cross University, Lismore, NSW 2480, Australia
2
Office of Environment and Heritage, Alstonville, NSW 2477, Australia
3
Faculty of Science & Information Technology, University of Newcastle, Callaghan, NSW 2308, Australia
Current Address: Faculty of Science and Technology, Uva Wellassa University, Badulla 90000, Sri Lanka.
*
Author to whom correspondence should be addressed.
Received: 25 September 2013 / Revised: 21 November 2013 / Accepted: 25 November 2013 / Published: 6 December 2013
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Abstract

The reflected radiance in topographically complex areas is severely affected by variations in topography; thus, topographic correction is considered a necessary pre-processing step when retrieving biophysical variables from these images. We assessed the performance of five topographic corrections: (i) C correction (C), (ii) Minnaert, (iii) Sun Canopy Sensor (SCS), (iv) SCS + C and (v) the Processing Scheme for Standardised Surface Reflectance (PSSSR) on the Landsat-5 Thematic Mapper (TM) reflectance in the context of prediction of Foliage Projective Cover (FPC) in hilly landscapes in north-eastern Australia. The performance of topographic corrections on the TM reflectance was assessed by (i) visual comparison and (ii) statistically comparing TM predicted FPC with ground measured FPC and LiDAR (Light Detection and Ranging)-derived FPC estimates. In the majority of cases, the PSSSR method performed best in terms of eliminating topographic effects, providing the best relationship and lowest residual error when comparing ground measured FPC and LiDAR FPC with TM predicted FPC. The Minnaert, C and SCS + C showed the poorest performance. Finally, the use of TM surface reflectance, which includes atmospheric correction and broad Bidirectional Reflectance Distribution Function (BRDF) effects, seemed to account for most topographic variation when predicting biophysical variables, such as FPC. View Full-Text
Keywords: topographic correction; surface reflectance; FPC; Landsat-5 TM; LiDAR; BRDF; vegetation; field data; validation topographic correction; surface reflectance; FPC; Landsat-5 TM; LiDAR; BRDF; vegetation; field data; validation
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Ediriweera, S.; Pathirana, S.; Danaher, T.; Nichols, D.; Moffiet, T. Evaluation of Different Topographic Corrections for Landsat TM Data by Prediction of Foliage Projective Cover (FPC) in Topographically Complex Landscapes. Remote Sens. 2013, 5, 6767-6789.

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