Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Spatial modelling of benthic cover using remote sensing data in the Aldabra lagoon, western Indian Ocean

Domaine:

geospatialenvironment and energy

Type de record:

datasetmodel
Créateur:
SarTomA H
Hôte:avatar
Spatially explicit ecological modelling was used to predict the distribution of 4 benthic components (live coral, carbonate sand, macroalgae and dead coral) inside the Aldabra lagoon, southern Seychelles, western Indian Ocean. Both classic ordinary least-squares and spatial autoregression techniques were carried out on a field data set of 774 spatially referenced records and 3 satellite remote sensing images to define an empirical relationship between local environmental conditions (water depth and water level variation) and benthic cover. This relationship was then used to generate a synoptic model of the spatial cover and distribution of each benthic component at the landscape (i.e. whole lagoon) scale. Environmental conditions were estimated from satellite remote sensing data (water depth) and using GIS techniques (water level variation). By drawing on species−environment relationships applicable to many lagoons, continuous records of percentage benthic cover were derived for the extensive lagoon (174 km2) at a high measurement level (ratio) for use in conservation and resource management applications. The transition from the ordinary least-squares model to the spatially lagged model was accompanied by a marked growth in predictive power (R2 = 0.25 to 0.79), indicating that neighbourhood context interactions play an important role in determining benthic cover of the Aldabra lagoon.

Visit

figshare.com

Tags

Earth scienceslagoonsensingspatialmodellingwesternindianoceandatabenthic+4

Licenses

Copyright - All rights reserved

Similaires

Linkage between fish functional groups and coral reef benthic habitat composition in the Western Indian OceanRefining Species Distribution Modelling Using Remote Sensing DataModelling the Spatial Distribution of the Anopheles Mosquito for Malaria Risk Zoning Using Remote Sensing and GISRemote Sensing Reveals Lasting Legacies of Land-Use by Small-Scale Foraging Communities in the Southwestern Indian OceanEstimating spatial and temporal variation in ocean surface pCO2 in the Gulf of Mexico using remote sensing and machine learning techniquesModelling coral reef connectivity in the SW Indian Ocean

Linkage between fish functional groups and coral reef benthic habitat composition in the Western Indian Ocean

Benthic habitat composition is a key factor that structures assemblages of coral reef fishes. Howeve

Refining Species Distribution Modelling Using Remote Sensing Data

Refining Species Distribution Modelling Using Remote Sensing Data

Poster presented at the Deep Learning Indaba 2023 by Emily Morris

Modelling the Spatial Distribution of the Anopheles Mosquito for Malaria Risk Zoning Using Remote Sensing and GIS

Remote Sensing and Geographic Information System was used to develop a spatial risk malaria distribu

Remote Sensing Reveals Lasting Legacies of Land-Use by Small-Scale Foraging Communities in the Southwestern Indian Ocean

Archaeologists interested in the evolution of anthropogenic landscapes have productively adopted Nic

Estimating spatial and temporal variation in ocean surface pCO2 in the Gulf of Mexico using remote sensing and machine learning techniques

International audience A satellite-based surface pCO 2 model with good performance is

Modelling coral reef connectivity in the SW Indian Ocean

<p>Coral larvae can be transported over great distances by ocean currents, establishin