@phdthesis{fdi:010085721,
  title = {{T}owards ecologically consistent remote sensing mapping of tree communities in {F}rench {G}uiana are forest types identifaible from spatio-temporal canopy reflectance patterns ?},
  author = {{C}heriington, {E}.{A}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}ropical forests, which provide important ecosystem functions and services, are increasingly threatened by anthropogenic pressures. {T}his has resulted in an urgent need to understand tree species diversity of those forests. {W}here knowledge of that diversity is largely from the botanical surveys and local ecological studies, data must inevitably be up-scaled from point observations to the landscape and regional level if a holistic perspective is required. {T}his thesis explores aspects of the spatio-temporal heterogeneity of canopy reflectance patterns over the forests of {F}rench {G}uiana, in order to assess whether this information could help defining an ecologically consistent forest typology. {T}o gain insight into both the spatial and temporal heterogeneity of {F}rench {G}uiana's forests, instrumental artefacts affecting the satellite data first had to be addressed. {D}ata used in this study represent the spectral response of forest canopies, and the way in which such data are captured makes them susceptible to the ?bi-directional reflectance distribution function' ({BRDF}). {BRDF} indicates that objects do not reflect light in equal proportions in all directions (isotropically). {T}hus, forest canopies will reflect light anisotropically depending on factors including canopy roughness, leaf optical properties and inclination, and the position of the sun relative to the sensor. {T}he second chapter of this thesis examines how {BRDF} affects the canopy reflectance of forests in {F}rench {G}uiana, and how not correcting for {BRDF} affects spectral classifications of those forests. {W}hen monthly reflectance data corrected for the artefact are examined, these suggest seasonally-occurring changes in forest structure or spectral properties of {F}rench {G}uiana's forests. {T}he third chapter of this thesis thus examines temporal effects of {BRDF}, and used cross-regional comparisons and plot-level radiative transfer modelling to seek to understand the drivers of the monthly variation of the forests' canopy reflectance. {F}or the latter, the {D}iscrete {A}nisotropic {R}adiative {T}ransfer ({DART}) model was used along with aerial laser scanning ({ALS}) observations over different forest structures, indicating that the observed variation in reflectance (and derivatives known as vegetation indices) could not be explained by monthly variations in solar direction. {A}t the regional scale, it was also demonstrated that forests in the {G}uiana {S}hield possess temporal variation distinct from forests in central {A}frica or northern {B}orneo, forests also lying just above the {E}quator. {H}ad the observed temporal variation in vegetation indices been the result of {BRDF}, it would have been expected that the forests in the three zones would have similar patterns of variation, which they did not. {C}entral {A}frican forests appear to have their greening synchronized with rainfall, whereas forests in the {G}uianas appear synchronized with the availability of solar radiation. {F}urther analysis of the vegetation index time-series of observations also indicated that different types of forests in {F}rench {G}uiana possess distinct patterns of temporal variation, suggesting that tropical forest types can be discriminated on the basis of their respective ?temporal signatures.? {T}hat was exploited in the fourth chapter of the thesis, which maps forests in {F}rench {G}uiana based on their combined spatio-temporal canopy reflectance patterns and by so doing presents a novel way of addressing forest typology, based on ecologically meaningful information. {T}he thesis presented demonstrates that it is possible to adequately address remote sensing data artefacts to examine patterns of spatial and temporal variation in tropical forests. {I}t has shown that phenological patterns of tropical rainforests can be deduced from remote sensing data, and that forest types can be mapped based on spatio-temporal canopy reflectance patterns. {I}t is thus an important contribution to understand the ecology of tropical forests in {F}rench {G}uiana and to improve the toolbox of scientists dealing with the identification of spatio-temporal patterns observable in forests at the landscape level.},
  keywords = {{FORET} {DENSE} ; {PHYTOECOLOGIE} ; {PHENOLOGIE} ; {ZONE} {HUMIDE} ; {CANOPEE} {FORESTIERE} ; {TELEDETECTION} {SPATIALE} ; {REFLECTANCE} ; {TRANSFERT} {RADIATIF} ; {VARIATION} {TEMPORELLE} ; {VARIATION} {SAISONNIERE} ; {BIODIVERSITE} ; {SERVICES} {ECOSYSTEMIQUES} ; {GUYANE} {FRANCAISE} ; {ZONE} {TROPICALE}},
  address = {{M}ontpellier},
  publisher = {{A}gro{P}aris{T}ech},
  pages = {138  multigr.},
  year = {2016},
  URL = {https://www.documentation.ird.fr/hor/fdi:010085721},
}