Abstract
Abstract. The characterization of leaf phenology in tropical forests is of major importance for forest typology as well as to improve our understanding of earth–atmosphere–climate interactions or biogeochemical cycles. The availability of satellite optical data with a high temporal resolution has permitted the identification of unexpected phenological cycles, particularly over the Amazon region. A primary issue in these studies is the relationship between the optical reflectance of pixels of 1 km or more in size and ground information of limited spatial extent. In this paper, we demonstrate that optical data with high to very-high spatial resolution can help bridge this scale gap by providing snapshots of the canopy that allow discernment of the leaf-phenological stage of trees and the proportions of leaved crowns within the canopy. We also propose applications for broad-scale forest characterization and mapping in West-Central Africa over an area of 141 000 km2. Eleven years of the Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) data were averaged over the wet and dry seasons to provide a data set of optimal radiometric quality at a spatial resolution of 250 m. Sample areas covered at a very-high (GeoEye) and high (SPOT-5) spatial resolution were used to identify forest types and to quantify the proportion of leaved trees in the canopy. The dry-season EVI was positively correlated with the proportion of leaved trees in the canopy. This relationship allowed the conversion of EVI into canopy deciduousness at the regional level. On this basis, ecologically important forest types could be mapped, including young secondary, open Marantaceae, Gilbertiodendron dewevrei and swamp forests. We show that in West-Central African forests, a large share of the variability in canopy reflectance, as captured by the EVI, is due to variation in the proportion of leaved trees in the upper canopy, thereby opening new perspectives for biodiversity and carbon-cycle applications.
Highlights
Tropical forests are widely accepted as an important component of the global carbon cycle, little is known about the actual dynamics of these ecosystems and their response to the ever-changing constraints of natural and anthropic inputs at temporal scales ranging from ice age to seasonal cycles (Maley, 2009; Richards, 1996)
Our results show that the mean, dry-season Enhanced Vegetation Index (EVI) is linearly and positively correlated with the proportion of leaved trees in the canopy, as can be assessed using high- and very-highspatial-resolution images
This correlation provides strong evidence that a large share of the variability in canopy reflectance summarized in the EVI at stand level (250 m pixels) in the mixed forests (MF) of West-Central Africa is due to variation in the proportion of leaved trees in the upper canopy
Summary
Tropical forests are widely accepted as an important component of the global carbon cycle, little is known about the actual dynamics of these ecosystems and their response to the ever-changing constraints of natural and anthropic inputs at temporal scales ranging from ice age to seasonal cycles (Maley, 2009; Richards, 1996). The resulting increase in carbon uptake may explain a significant part of the dynamics observed in atmospheric carbon concentrations (Lewis et al, 2009a) This example illustrates the importance of undertaking large-scale and long-term investigations in these ecosystems. Field methods allowing an indirect assessment at these scales include the flux tower (Malhi et al, 1998; Saleska et al, 2003) and litter trap observations (Chave et al, 2008). These methods do not allow the direct estimation of the extent and duration of the leafless stage. Pheno-cameras (Saitoh et al, 2012) are an alternative, automating data processing may prove complex if one is to obtain quantitative data over significant forest extents
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