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Original Articles

Relationship between canopy height and Landsat ETM+ response in lowland Amazonian rainforest

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Pages 203-212 | Received 12 May 2010, Accepted 21 Jul 2010, Published online: 27 Oct 2010
 

Abstract

This letter investigates the influence of within-pixel variation of canopy height on the spectral response recorded in Landsat Enhanced Thematic Mapper (ETM+) data for tropical rainforest. Forest canopy height is derived from airborne, small-footprint LiDAR data acquired using a Leica ALS50 II system. The field site is in the Tambopata National Reserve, in Peruvian Amazonia, where forest types include regenerating, swamp, floodplain and terra firme. For individual Landsat ETM+ bands, the strongest correlation for maximum, mean and standard deviation of canopy height occurred with ETM+ Band 4 (near infrared) for regenerating, floodplain and terra firme forest, and with ETM+ Band 5 (middle infrared) for swamp forest. For normalized difference band indices, ND42 and ND43 (i.e. the Normalized Difference Vegetation Index, NDVI) showed strong correlation with both mean and maximum canopy height for regenerating and terra firme forest, and with maximum and standard deviation of canopy height for floodplain forest. The palm-dominated swamp forest showed weaker relationships, with the strongest occurring for ND45 and ND52 with mean canopy height. Many papers have identified middle-infrared bands as being most sensitive to tropical rainforest structure, although these have often focussed on young regenerative forests. By focussing on older regenerative forest (of >25 years since land abandonment) and mature rainforest types, this work has shown that there is considerable variation with how structure may influence spectral reflectance and lends support to the hypothesis that canopy height distribution and shadowing effects caused by canopy complexity and the presence of emergent trees is what most significantly influences spectral response for tropical rainforests.

Acknowledgements

We are grateful to Dr. Bryan Mark of Ohio State University for providing the LiDAR data and to the USGS for access to Level 1 T Landsat ETM+ data.

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