CIFOR-ICRAF s’attaque aux défis et aux opportunités locales tout en apportant des solutions aux problèmes mondiaux concernant les forêts, les paysages, les populations et la planète.

Nous fournissons des preuves et des solutions concrètes pour transformer l’utilisation des terres et la production alimentaire : conserver et restaurer les écosystèmes, répondre aux crises mondiales du climat, de la malnutrition, de la biodiversité et de la désertification. En bref, nous améliorons la vie des populations.

CIFOR-ICRAF publie chaque année plus de 750 publications sur l’agroforesterie, les forêts et le changement climatique, la restauration des paysages, les droits, la politique forestière et bien d’autres sujets encore, et ce dans plusieurs langues. .

CIFOR-ICRAF s’attaque aux défis et aux opportunités locales tout en apportant des solutions aux problèmes mondiaux concernant les forêts, les paysages, les populations et la planète.

Nous fournissons des preuves et des solutions concrètes pour transformer l’utilisation des terres et la production alimentaire : conserver et restaurer les écosystèmes, répondre aux crises mondiales du climat, de la malnutrition, de la biodiversité et de la désertification. En bref, nous améliorons la vie des populations.

CIFOR–ICRAF publishes over 750 publications every year on agroforestry, forests and climate change, landscape restoration, rights, forest policy and much more – in multiple languages.

CIFOR–ICRAF addresses local challenges and opportunities while providing solutions to global problems for forests, landscapes, people and the planet.

We deliver actionable evidence and solutions to transform how land is used and how food is produced: conserving and restoring ecosystems, responding to the global climate, malnutrition, biodiversity and desertification crises. In short, improving people’s lives.

Remote sensing approach for spatial planning of land management interventions in West African Savannas

Exporter la citation

Forest management, agroforestry and tree planting are some of the key approaches to sustainable rural development, and climate change adaptation and mitigation in West African savannas. However, the planning of land management interventions is hindered by the lack of information at relevant spatial resolution. We examined predictive models for mapping various tree, soil and species diversity attributes with a comparison of RapidEye and Landsat imagery. The field data was collected in the vicinity of the community-managed forest in southern Burkina Faso, where the main environmental threats are agricultural expansion and fuelwood extraction. The modelling was done using Random Forest algorithm. According to our results, tree crown cover and correlated attributes, such as basal area and tree species richness, were predicted most accurately. High spatial resolution RapidEye imagery provided the best accuracy but difference to medium resolution Landsat imagery was negligible for most attributes. Burn scar masked Landsat time series performed similar to dry season single date Landsat imagery, but the former avoids image selection and mosaicking, and could be less sensitive to artifacts due to the burn scars. The presented approach provides valuable information on important tree, soil and species diversity attributes for spatial planning of land management interventions. © 2017 Elsevier Ltd

DOI:
https://doi.org/10.1016/j.jaridenv.2016.12.006
Score Altmetric:
Dimensions Nombre de citations:

Publications connexes