A digital model of pattern and productivity in an agroforestry landscape.

摘要

Agroforestry, is an approach to land use which offers much promise in addressing many of the interrelated problems associated with rural development and land degradation. (Scherr, 1992, Nair, 1993). This research incorporates remotely sensed agroforestry landscape information within a computerized model that relates spatial structure at the field and landscape scale to maize production. Remote sensing, cartographic modeling as well as landscape ecological theory and methods of analysis figure prominently in the work. The study area is in the coffee zone on the southern footslopes of Mount Kenya.;Findings indicate that the spatial measures that were undertaken at the landscape scale do not explain enough crop variability to be statistically significant. Rather, it is far better explained at the individual field level. Here it was demonstrated that distance from shelter plantings is inversely and curvilinearly related to crop vigor as measured by the relationship between the Near Infra Red and Red wavelengths. Findings indicate that the positive effects of trees in the study landscape are limited to within 25 meters of the canopy. An optimum hedgerow interdistance of 40 meters is suggested in order to maximize crop vigor.;The impact of both the existing conditions as well as two possible alternatives are evaluated for their total landscape wide impacts on maize yields and wood production. It was determined that removal of existing hedgerows (50% percent of all the trees in the area) by a disturbance such as a pest outbreak would cause a 5% reduction in maize production. A second alternative, which identified underutilized planting niches throughout the landscape, is predicted to result in a modest increase in maize production and a doubling a wood products.;The research tests the hypotheses that: There is a correlation between landscape and field structure and crop production. Specifically, it is hypothesized that spatial configuration at the field scale, (e.g. patch size, shape and adjacency relationships etc.) as well as at the landscape scale, (density of trees and hedgerows) can be significantly correlated with productivity. The central hypothesis is that spatial variability across the landscape, at scales both at and beyond that of the field, can explain a significant amount of the variability in yields. In order to carry out the work, a recent innovation in remote sensing, the Compact Airborne Spectrographic Imager (CASI), has been used in the project. The CASI was used to acquire a detailed digital image of the site at a high spatial resolution (1.75 meter pixel size). Six spectrally narrow width bands were acquired with the purpose of determining chlorophyll density as well as crop type and vigor.