The FarmTreeTool provides context-specific, tailormade output, based on a clearly defined agroforestry system. For each assignment a broad array of input data is collected to quantify the defined system. The whole process involves a semi-structured 4-step working method:

Project definition

Clients define the farming scenarios to be analysed and compared and validate this with the DIBcoop team. For landscape-scale projects, land cover classes and appropriate landscape restoration options are defined.

Data collection

Input data is derived from field data, FarmTree’s own database, external databases, and scientific and grey literature. Data is stored in several interrelated datasets so quantitative projections can be made.

Data processing & output generation

The FarmTree team runs the data through the model and generates agro-ecological and economic outputs and performance indicators. Model calibration is done if projections seem unrealistic.

Report writing

The FarmTree team interprets and analyses the output in accordance with the clients’ requirements.