Tropentag, October 5 - 7, 2004 in Berlin "Rural Poverty Reduction through Research for Development and Transformation"

GIS and Farming System Analysis

¹Humboldt-Universität zu Berlin, Development Planning and Project Management, Germany
²Humboldt-Universität zu Berlin, Agricultural Economics and Social Sciences, Germany

Abstract

Rural project analysis demands a precise local socio-economic and agro-ecological assessment for extended regions. GIS allows combining local data with remote sensing for agro-ecological land-use modelling over broad areas. Farm system analysis supplies socioeconomic indicators at local and at regional level. Local data is included as quantitative and qualitative constraint. Joining both sources in a spatial database enables to spatially model the farming system. Quantification is possible of both, the socio-economic performance of the individual farming unit as a component of a farming system as well as its reciprocal influence with the natural environment. In the present case study the socioeconomic and ecological performance of a farming system is evaluated for the Guacurari District in Misiones, Northern Argentina. The Guacurari District delimitates a variegated environment of tropical forest, alternating with mate-tea plantations, livestock fields and annual crops. The farming units present an average size of 50\,ha, ranging from 5 ha to 300\,ha. Spatial analysis shows that only the largest farms, cattle producers, represent a homogeneous physical environment. The spatial distribution of the individual farming units shows that middle-size farms are located on the most suitable soils. There is no distinction per classes in respect to the distance to the urban centres. Smaller units are concentrated along the main roads. Rural schools are distributed evenly in the district, from which follows that 60% are accessible mainly for the middle to larger units. The agricultural area averages 50% of the available farming area; for the smallest units this figure is only 10%. Extensive lines of production, mate-tea and cattle, provide the highest total agricultural income. In coincidence with this result, total farm income is closely related to agricultural area. Per hectare profit is higher in intermediate classes, with higher incidence of intensive land use activities. GIS-Farming system analysis is able to characterise a region down to the level of the individual farming unit. The natural environment and its interaction with the farming units is spatially quantified. Farmland use is precisely characterised at the field level. The livelihood of rural population is accurate evaluated through socioeconomic indicators.

Keywords: Annual crop, Argentina, farm income, farming area, farming system analysis, gross margin

Contact Address: Amalia Nahír Díaz Lacava, Humboldt-Universität zu Berlin, Development Planning and Project Management, Private address: Kiefernweg 28, 53127 Bonn, Germany, e-mail: adlrdc-bonn.de