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Remote Sens. 2016, 8(2), 87; doi:10.3390/rs8020087

Organismic-Scale Remote Sensing of Canopy Foliar Traits in Lowland Tropical Forests

1
Department of Global Ecology, Carnegie Institution for Science, Stanford, CA 94305, USA
2
Department of Earth System Science, Stanford University, Stanford, CA 94305, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Susan L. Ustin, Nicolas Baghdadi and Prasad S. Thenkabail
Received: 5 December 2015 / Revised: 9 January 2016 / Accepted: 14 January 2016 / Published: 23 January 2016
(This article belongs to the Special Issue Remote Sensing of Biodiversity)
View Full-Text   |   Download PDF [5255 KB, uploaded 25 January 2016]   |  

Abstract

Airborne high fidelity imaging spectroscopy (HiFIS) holds great promise for bridging the gap between field studies of functional diversity, which are spatially limited, and satellite detection of ecosystem properties, which lacks resolution to understand within landscape dynamics. We use Carnegie Airborne Observatory HiFIS data combined with field collected foliar trait data to develop quantitative prediction models of foliar traits at the tree-crown level across over 1000 ha of humid tropical forest. We predicted foliar leaf mass per area (LMA) as well as foliar concentrations of nitrogen, phosphorus, calcium, magnesium and potassium for canopy emergent trees (R2: 0.45–0.67, relative RMSE: 11%–14%). Correlations between remotely sensed model coefficients for these foliar traits are similar to those found in laboratory studies, suggesting that the detection of these mineral nutrients is possible through their biochemical stoichiometry. Maps derived from HiFIS provide quantitative foliar trait information across a tropical forest landscape at fine spatial resolution, and along environmental gradients. Multi-nutrient maps implemented at the fine organismic scale will subsequently provide new insight to the functional biogeography and biological diversity of tropical forest ecosystems. View Full-Text
Keywords: Carnegie Airborne Observatory; foliar chemistry; functional diversity; functional traits; hyperspectral; imaging spectroscopy; rock-derived nutrients Carnegie Airborne Observatory; foliar chemistry; functional diversity; functional traits; hyperspectral; imaging spectroscopy; rock-derived nutrients
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Chadwick, K.D.; Asner, G.P. Organismic-Scale Remote Sensing of Canopy Foliar Traits in Lowland Tropical Forests. Remote Sens. 2016, 8, 87.

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