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Article

Predicting Tropical Tree Species Richness from Normalized Difference Vegetation Index Time Series: The Devil Is Perhaps Not in the Detail

1
Institut Agronomique néo-Calédonien (IAC), 98800 Noumea, New Caledonia
2
Zhejiang Provincial Key Laboratory of Plant Evolutionary Ecology and Conservation, Taizhou University, Taizhou 317000, China
3
Department of Geography, University of California, Los Angeles, CA 90095, USA
4
UMR AMAP, Université de Montpellier, CIRAD, CNRS, INRA, IRD, 34398 Montpellier, France
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(5), 698; https://doi.org/10.3390/rs10050698
Received: 4 February 2018 / Revised: 16 April 2018 / Accepted: 25 April 2018 / Published: 3 May 2018
(This article belongs to the Special Issue Remote Sensing of Tropical Forest Biodiversity)
The normalized difference vegetation index (NDVI) derived from remote sensing is a common explanatory variable inputted in correlative biodiversity models in the form of descriptive statistics summarizing complex time series. Here, we hypothesized that a single meaningful remotely-sensed scene can provide better prediction of species richness than any usual multi-scene statistics. We tested this idea using a 15-year time series of six-day composite MODIS NDVI data combined with field measurements of tree species richness in the tropical biodiversity hotspot of New Caledonia. Although some overall, seasonal, annual and monthly statistics appeared to successfully correlate with tree species richness in New Caledonia, a range of individual scenes were found to provide significantly better predictions of both the overall tree species richness (|r| = 0.68) and the richness of large trees (|r| = 0.91). A preliminary screening of the NDVI-species richness relationship within each time step can therefore be an effective and straightforward way to maximize the accuracy of NDVI-based correlative biodiversity models. View Full-Text
Keywords: biodiversity hotspot; multispectral remote sensing; productivity; species richness; tropical forests biodiversity hotspot; multispectral remote sensing; productivity; species richness; tropical forests
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MDPI and ACS Style

Pouteau, R.; Gillespie, T.W.; Birnbaum, P. Predicting Tropical Tree Species Richness from Normalized Difference Vegetation Index Time Series: The Devil Is Perhaps Not in the Detail. Remote Sens. 2018, 10, 698. https://doi.org/10.3390/rs10050698

AMA Style

Pouteau R, Gillespie TW, Birnbaum P. Predicting Tropical Tree Species Richness from Normalized Difference Vegetation Index Time Series: The Devil Is Perhaps Not in the Detail. Remote Sensing. 2018; 10(5):698. https://doi.org/10.3390/rs10050698

Chicago/Turabian Style

Pouteau, Robin, Thomas W. Gillespie, and Philippe Birnbaum. 2018. "Predicting Tropical Tree Species Richness from Normalized Difference Vegetation Index Time Series: The Devil Is Perhaps Not in the Detail" Remote Sensing 10, no. 5: 698. https://doi.org/10.3390/rs10050698

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