In regenerating forests,accurate knowledge of tree abundance and spatial distribution is important for evaluating future forest conditions to determine if these conditions are sufficient to meet sustainable forest management objectives.High spatial resolution remote sensing provides a potentially low cost means to obtain this information if efficient and reliable methods for extraction of coniferous crop and deciduous competitor tree information can be developed from imagery acquired in a single campaign.Research to date has made use of high-resolution digital and scanned photography for semi-automated estimation of crop tree spatial density,crown size,and competition abundance.Requirements for image acquisition parameters such as spectral bands,view angle ranges,and scale vary for each of these estimates.In this paper,current image processing capabilities are summarized and a proposed imaging system is presented within the context of a larger sampling methodology for operational monitoring of coniferous forest regeneration.
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