Inventorying tree intensification

Inventorying tree intensification to quantify shade/canopy cover variability in multi-strata tropical agroforestry land use(s) - Case of Cocoa Agroforestry in Cameroon

Funding agency: The Special Research Fund (BOF) of Ghent University: Doctoral Grants for Candidates from Developing Countries
Research associate: Frederick N. Numbisi
Promoters: Robert De Wulf, Frieke Vancoillie
Duration: 01/2015 – 12/2018


In the forested south of Cameroon, Cocoa Agroforestry is an important land use and livelihood strategy. A growing demand for Cocoa and by-products has sparked a recent boost in governmental strategies to increase production and national export earnings, through intensifying management and extensive land use. This land use is practised under a multi-strata shade/canopy system; with a contending shade tree management (retention and integration) varying with site characteristics, farm management objectives and farmers’ experience. In such system, shade provision is an important determinant of production capacity and environmental resilience – already evidence as reforestation option in savannah-forest transition of central Cameroon. There are ample reports in literature revealing the economic importance and need of tree integration within the system, while a few studies have been pivotal in ascertaining their ecosystem services (ES) potential as such as biodiversity and carbon storage. Yet lacking is research-based information on shade cover variation with the tree management strategy employed at temporal scale. Such empirical evidence is much needed to support sustainable management and livelihood options.

Measurements from spaceborne Earth Observation satellites offer efficient, less laborious and large-scale assessment of agricultural vegetation. Such measurements have proved successful in assessing tree attributes within savannah or Sahel agroforests, using OBIA approaches. In tropical agroforestry conditions, issues of mixed features/trees and variable clusters of vegetation structures present challenges in multi-strata canopy assessment, and thus require customized image analysis protocols.

Project Objectives

The aim of this research is to explore a remote sensing derived measurement and inventorying of tropical agroforestry, in providing evidence-based guidance to sustainable tree intensification, land use and adapted management planning. In quantifying the ES (Ecosystem service) potential of multi-strata agroforestry system at landscape scale, remote sensing measurements are expected to provide reliable estimates. Multi-resolution and multi-temporal remote sensing data will be processed/fused for delineating tropical agroforest land use. Also, coupling of HR satellite data with in-situ canopy attributes, followed by advanced image analysis (neural network and OBIA) could be effective in reconstructing canopy/shade cover variability from agroforestry plot characteristics.

Specific objectives

  1. Assess the spatio-temporal changes of a forested landscape mosaic in relation to Cocoa agroforestry dynamics
  2. Estimate shade tree dynamics in Cocoa Agroforests, and variability of canopy provision
  3. Ascertain the underlying farmland fragmentation and orientation of tree intensification
  4. Develop evidence-based approach to contribute in municipal management planning