This review attempts, from a critical perspective, to put 25 years of satellite remote sensing research into the context of forestry planning. It is limited to temperate and boreal regions and to remote sensing in the visible and near infra‐red spectra. It is structured as follows: firstly, the forestry planning problem is defined and information requirements are identified; secondly, the attempts to use satellite remote sensing as an information source for forestry planning are reviewed, divided into the topics inventory and monitoring; and, finally, the methods for extracting forest information from satellite images are re‐examined, and their inherent limitations and methodological weaknesses are discussed. It is concluded that satellite images seldom contain enough information to support the decision process in applied forestry. Although regional level applications may be useful, few successful and reliable applications for local forest inventory, planning or damage monitoring have evolved. Stratificat...

Satellite remote sensing for forestry planning—A review

Application of detailed ground information to vegetation mapping with high spatial resolution digital imagery

Trembling aspen is the most important deciduous species in the North American boreal forest for which methods are needed to consistently map and monitor insect defoliation patterns to assess impacts on aspen health and productivity. The loss of foliage due to insect defoliation results in changes to leaf area index (ΔLAI) that were studied from both field and satellite image data for a large aspen tortrix (Choristoneura conflictana (Wlk.)) outbreak in boreal forest aspen stands in northern Alberta. Field estimates of defoliation for stands undergoing various levels of defoliation severity and both allometric and optical LAI-2000 measurements of leaf area index were collected and related to Landsat enhanced thematic mapper plus (ETM+) image data representing before- and after-defoliation events. This study was undertaken as part of the Climate Change Impact on the Productivity and Health of Aspen (CIPHA) research initiative that is taking place in western Canada. Field estimates of ΔLAI followed defoliatio...

Relating aspen defoliation to changes in leaf area derived from field and satellite remote sensing data

Aerial photographs have been and continue to be the most frequently used remote sensing data source in forestry, particularly in natural resource assessment, inventory, and monitoring (Gillis and Leckie 1993; Hall and Fent 1996; Caylor 2000). Their use in operational forestry was anticipated to decrease as technological advances improved in the capabilities of new airborne and satellite sensors. The incentives were obvious. Within a growing digital arena, an increasing array of both geographic information system (GIS) and image processing system capabilities exist to integrate and analyze digital image data. Digital remote sensing systems tend to offer data with higher radiometric and spectral resolution capabilities than their aerial photo counterparts, and it is often in a format ready for analysis without costly scanning as in the case of the photograph. Despite predictions that digital cameras will eliminate the need for aerial photography and film scanner technologies, no such system has yet been able to match their spatial resolution, data storage or hardcopy output capabilities (Hinz and Heier 2000; Gruber and Leberl 2001). For example, a single 230 x 230 mm aerial photograph at a scale of 1:20,000 scanned at a resolution of 10 micrometres would have a pixel size representing 0.20 m on the ground and require about 450 megabytes of storage, an awesone amount of information contained within a single analogue photograph. Thus, there are advantages and disadvantages when comparing digital systems with aerial photography.

The Roles of Aerial Photographs in Forestry Remote Sensing Image Analysis

Individual tree crowns were automatically located in aerial electro-optical sensor images of a forested scene in Ontario, Canada. The images have pixels with a ground dimension of 36 cm. A model of the appearance of individual tree crowns in a single channel of the image data was used to generate a set of templates. The model has parameters for size, shape, and projected one-sided leaf area density distribution, which are evaluated according to the expected range of values for the scene. Knowledge of the scene illumination and sensing geometry is also incorporated into the model. Tree crown locations were derived from the locations of plausible linear relationships between the templates and the sensed images, as determined with a weighted least-squares straight line regression analysis. The weighting was used to accommodate crown margin irregularity. The procedure successfully located 57% of the trees in a 548 member ground-surveyed sample representing a wide range of species, sizes, and growing situations. Success was defined by a one-to-one spatial relationship between computed crown extents and reference locations. The success rate increased to 73% when only 224 trees that had almost no physical contact with their neighbors were considered. The commission error rate was estimated to be 23%.© (1994) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Model-based approach to automatically locating tree crowns in high spatial resolution images

This paper reviews the current capability of digital remote sensing technology to satisfy the information requirements of forest managers. The discussion is organized with regard.to forest management information requirements rather than along technological lines. The promise of new airborne technologies to provide more detailed information is also discussed in the context of the information requirements, together with examples of encouraging results.

D.G. Leckie

Papers

Digital remote sensing for forestry: Requirements and capabilities, today and tomorrow