Alexandre Pennec

Vegetation structure and greenness in Central Africa from Modis multi-temporal data

African forests within the Congo Basin are generally mapped at a regional scale as broad-leaved evergreen forests, with the main distinction being between terra-firme and swamp forest types. At the same time, commercial forest inventories, as well as national maps, have highlighted a strong spatial heterogeneity of forest types. A detailed vegetation map generated using consistent methods is needed to inform decision makers about spatial forest organization and their relationships with environmental drivers in the context of global change. We propose a multi-temporal remotely sensed data approach to characterize vegetation types using vegetation index annual profiles. The classifications identified 22 vegetation types (six savannas, two swamp forests, 14 forest types) improving existing vegetation maps. Among forest types, we showed strong variations in stand structure and deciduousness, identifying (i) two blocks of dense evergreen forests located in the western part of the study area and in the central part on sandy soils; (ii) semi-deciduous forests are located in the Sangha River interval which has experienced past fragmentation and human activities. For all vegetation types enhanced vegetation index profiles were highly seasonal and strongly correlated to rainfall and to a lesser extent, to light regimes. These results are of importance to predict spatial variations of carbon stocks and fluxes, because evergreen/deciduous forests (i) have contrasted annual dynamics of photosynthetic activity and foliar water content and (ii) differ in community dynamics and ecosystem processes.

Tropical forest phenology in French Guiana from MODIS time series

Despite a growing need for knowledge on how terrestrial ecosystems function, phenological studies are rather rare. This study characterizes the temporal evolution of forest covers in French Guiana using variations in the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite signal and vegetation indices, such as the Shortwave Infrared Water Stress Index and the Enhanced Vegetation Index. The principle consists of reconstructing a temporal cycle mosaiced from a 9-year database. Rather than extract the phenological information from each pixel, dynamics were extracted from homogeneous groups of forest pixels enabling the identification of different phenological phases in forest ecosystems. A north–south gradient of chlorophyll activity emerged. The further we moved to the south, the more forest groups consist of fast-growing and drought-tolerant species, whereas a north–south shift appeared at the start dates of phenological cycles. This is a promising approach that paves the way for a much deeper understanding of the mechanisms governing the rainforest in French Guiana, as well as the responses of the Amazon forest to climate change and drought in the long term.