Quantification of shelterbelt characteristics using high-resolution imagery

The Agriculture and Agri-Food Canada Prairie Shelterbelt Program has distributed shelterbelt trees across the Prairie Provinces since 1903 to reduce wind erosion and other environmental benefits such as sequestering carbon and providing habitat for biodiversity. To assess the existence and conditions of shelterbelts on the landscape, visiting individual shelterbelts across each province is costly and time-consuming. High-resolution imagery offers a potentially quick and inexpensive method of identifying shelterbelts and deriving information about them. As resolution of imagery increases, more information can be extracted as ground features are becoming increasingly recognizable. Although shelterbelts could be analyzed across large sections of land, finer resolution comes at a greater price in required time and computing power. Shelterbelts were examined using spectral reflectance from multi-spectral bands and using shape, texture and other relational properties as determined with object-oriented image analysis. Principal components analysis and multiple discriminate analysis were used to identify shelterbelt characters by species. In a selected region, 93 of 97 field shelterbelts (95.8%) were correctly identified from 1:40,000 orthophotos. Spectral reflectance, variance and shape parameters were combined to differentiate among six shelterbelt species compositions.