Cited by 92Remote Sensing in AgricultureRemote-Sensing Image ClassificationRemote Sensing and LiDAR Applications

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

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Gond, Valéry, Fayolle, Adeline, Pennec, Alexandre, Cornu, Guillaume, Mayaux, Philippe, Camberlin, Pierre, Doumenge, Charles, Fauvet, Nicolas +1 more·2013·Philosophical Transactions of the Royal Society B: Biological Sciences

Abstract

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.

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Authors
Gond, V., Fayolle, A., Pennec, A., Cornu, G., Mayaux, P., Camberlin, P., Doumenge, C., Fauvet, N., & Gourlet-Fleury, S.
Affiliations
  • Centre de Coopération Internationale en Recherche Agronomique pour le Développement (FR)
  • European Commission (BE)
  • Centre National de la Recherche Scientifique (FR)
  • CIRAD, BSEF, 34098 Montpellier, France
Corresponding author
Gond, Valéry
Venue
Philosophical Transactions of the Royal Society B: Biological Sciences
Published
2013-09-05
Volume
368
Issue
1625
Pages
20120309
ISSN
  • 0962-8436 (ISSN-L)
  • 1471-2970
OpenAlex
W2142291736
Cited by
92
References
44
Citations by year
2026: 4 · 2025: 4 · 2024: 10 · 2023: 5 · 2022: 4 · 2021: 6 · 2020: 15 · 2019: 8 · 2018: 5 · 2017: 6 · 2016: 11 · 2015: 5 · 2014: 5 · 2013: 4
FWCI
7.36
Type
journal article
Language
en
Open access
Locations
  • Philosophical Transactions of the Royal Society B Biological Sciences (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • HAL (submittedVersion)
  • Agritrop (Cirad) (submittedVersion)
  • Open Repository and Bibliography (University of Liège) (submittedVersion)
  • Joint Research Centre (European Commission) (submittedVersion)
Funders
  • Agence Nationale de la Recherche (ANR-08-BDVA-0001)
  • Natural Environment Research Council
Topics
  • Physical Sciences › Environmental Science › Ecology › Remote Sensing in Agriculture
  • Physical Sciences › Engineering › Media Technology › Remote-Sensing Image Classification
  • Physical Sciences › Environmental Science › Environmental Engineering › Remote Sensing and LiDAR Applications
Keywords
vegetation mapping, vegetation structure, vegetation greenness, Congo Basin forests, savanna, swamp forest, evergreen forest, semideciduous seasonal forest, seasonal dynamics, rainfall, light regime, forest carbon stocks, forest fragmentation, Central Africa
MeSH terms
Africa, Central, Congo, Humans, Rain, Seasons, Time Factors, Trees, Databases, Factual, Ecosystem, Climate Change, Carbon Cycle, Ecological Parameter Monitoring

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