A critical mechanism in the demonstration of sustainable forest management is the use of sensitive indicators which provide unambiguous information about the response for the forest to management. These indicators need to be quantifiable, technically sound, scientifically based and ultimately measurable using cost-effective monitoring systems. The BC Ministry of Forests and Range Practices Act (FRPA) Resource Evaluation Program is a long-term commitment by government to identify issues regarding the implementation of forest policies, practices and legislation. The program has identified eleven key resource value indicators defining a range of values including biodiversity, forage, timber, water and wildlife objectives that must be maintained. A common characteristic of these indicators is the need to map and monitor aspects of forest structure at both fine and landscape scales. In reality however, there are challenges involved in both the definition and monitoring of indicators due, in part, to a mismatch in resolution, both in time and space. Aerial photography for example, is often used as a critical dataset for interpretation and mapping; however, in many cases, the data is not ideal because it contains operator bias, is subjective, and is time- and cost-intensive. Additionally, a number of attributes required for the development of these indicators can not be accurately derived from this type of technology. Alternatively, low spatial resolution imagery, such as Landsat Thematic Mapper, often contains more than one type of cover within its 30 m pixel, making it more suitable for broad cover and land use mapping than for providing detailed information on forest structure. In recent years there have been increases in the use of airborne, small footprint LiDAR (Light Distance And Ranging) data and high spatial resolution satellite imagery. These technologies offer the potential to significantly enhance the timeliness, scope, and rigor of forest measurement information available to decision makers. LiDAR technology, in particular, offers a revolutionary and complementary method to assess forest structure by measuring the height of the canopy from aircraft, underlying terrain morphology, and information on the vertical distribution of foliage. LiDAR data has been shown to be highly correlated with structural attributes such as stand diversity, growth stage and crown complexity, and high spatial resolution imagery has been successfully applied to estimate habitat quality, leaf area and species detection.
Coops, Nicholas C.. 2007. Sustainable forestry indicators derived from airborne LiDAR data and high spatial resolution satellite imagery. Forest Investment Account (FIA) - Forest Science Program. Forest Investment Account Report. FIA2007MR280
Topic: FLNRORD Research Program
Keywords: Forest, Investment, Account, (FIA), Sustainable, forestry, British, Columbia
To copy the URL of a document, Right Click on the document title, select "Copy Shortcut/Copy Link", then paste as needed. Only documents available to the public have this feature enabled.