Digital enhancement as an aid to detecting patterns of vegetation stress using medium-scale aerial photography

Abstract

The application of image processing algorithms, originally developed for satellite image analysis, has been shown to improve pattern recognition of environmental change and vegetation stress with medium-scale aerial photography. Image enhancement helps to identify subtle features and spatial patterns embedded in a digitized air photo transparency that might otherwise escape visual identification. Our procedure combines visual interpretation with computer-aided image enhancement, including Normalized Difference Vegetation Index (NDVI) and supervised and unsupervised classification. The motiviation for the application of these techniques came from the need to provide a multi-season record of environmental changes in the immediate vicinity of power generation facilities. The procedure involves simple, on-call, acquisition of colour infrared and colour aerial photography that can be electronically enhanced and evaluated, resulting in accurate, timely, and cost-efficient information on vegetation changes related to land management, weather, diseases, insects, or other environmental stressors.