The decrease of natural forest area in the tropics is alarmingly high as a result of forest over-utilization and land use changes. The reasons are manifold, including increasing demand for forest products and transformation of natural forests into high yield tree or agricultural crops for food, fodder and biofuel. It is a challenge for research and development to develop approaches that contribute to conservation and enhancement of the forest resource and the functions and services that forests provide. Forest transition systems cover wide areas in many tropical regions, in particular where population pressure is high. An example is Jambi Province on Sumatra in Indonesia, where forest transition through deforestation and land conversion has proceeded at a rapid pace, resulting in a land cover dominated by rubber and oil palm plantations, with few remaining forest areas left.

This research is part of Scientific Project B05 (SP B05) of the Collaborative Research Centre 990. SP B05 is on methodological approaches to the assessment of all tree resources in the study areas, focusing on the estimation of above ground biomass and species richness (biodiversity) using an integrated approach of both field sampling and remote sensing. Numerous studies have been done on South East Asian vegetation types for the estimation of above ground biomass and various biomass models for tropical forest have been produced. However, application of these models to specific situations like the one in the CRC990 study area is frequently hampered by a number of uncertainties about the applicability, provenance and precision of these models and the lack of specific reference information. Regarding species richness estimation, there is the expectation that remote sensing may yield valuable information that allows improving the field sample based observations.

This research has the goal to contribute to a landscape level assessment of carbon pools and biodiversity components by integrating ground truth field observations and remote sensing analysis. That integration will allow to spatially regionalize above ground biomass and carbon pools and species richness (biodiversity) over the defined study areas.
Depending on the imagery available, this project will yield input information to other scientific projects. Furthermore, depending on input from other projects, regionalization may also be done for other carbon pools than above ground biomass only (i.e. for soil carbon and below ground biomass).


  • Evaluate the application of biomass models on landscape level in transformation systems, including error analysis.
  • Estimating biomass and species richness for study sites in lowland rainforest, jungle rubber, intensive rubber and oil palm plantations within the study region and optimize the integration of field sampling and remote sensing analysis.
  • Analyze and evaluate the applicability of remote sensing in Jambi Province, in particular with respect to cloud cover, topography and the particular spatial pattern of a transformation landscape.
  • Optimizing field sampling for integration with remote sensing for biomass estimation and estimation of biodiversity components.