Age dependence of forest reflectance: Analysis of main driving factors

Abstract As an analogy to forest yield tables, successional trajectories of forest reflectance can be established. Examples of such deterministic reflectance age trajectories for common northern temperate forest types in Estonia have been derived from airborne reflectance measurements and simulated by a forest reflectance model. In the simulations, the yield tables were used as input data. The primary controls on the reflectance age course are: changes in canopy closure, tree-storey leaf-area index, species composition, and background reflectance. In long-term monitoring of forest stands, the effects of sun and view angle and phenology must be considered. Successional reflectance trajectories may further form a basis for a forest inventory and monitoring system. Provided that the problems of normalization of multidate satellite imageries and seasonal signature variation are solved, the reflectance change of a particular forest stand may be compared to the change predicted by established reflectance successional trajectories. In case of normal forest development, the measured reflectance changes must be close to those predicted. Some kinds of the disturbance-type forest changes (e.g., extensive thinning due to damage) are detectable by optical methods.

[1]  F. J. Ahern,et al.  Forestry information content of Thematic Mapper data , 1986 .

[2]  Tiit Nilson,et al.  Successional reflectance trajectories in northern temperate forests , 1993 .

[3]  E. Mälkönen Annual primary production and nutrient cycle in a birch stand. , 1977 .

[4]  Eero Nikinmaa,et al.  Analyses of the growth of Scots pine: matching structure with function. , 1992 .

[5]  Gautam Badhwar,et al.  Spectral Characterization of Biophysical Characterstics in a Boreal Forest: Relationship between Thematic Mapper Band Reflectance and Leaf Area Index for Aspen , 1986, IEEE Transactions on Geoscience and Remote Sensing.

[6]  Darrel L. Williams A comparison of spectral reflectance properties at the needle, branch, and canopy level for selected Conifer species , 1991 .

[7]  J. Otterman,et al.  Albedo of a Forest Modeled as a Plane with Dense Protrusions , 1984 .

[8]  S. Running,et al.  The seasonality of AVHRR data of temperate coniferous forests - Relationship with leaf area index , 1990 .

[9]  Steven A. Sader,et al.  RGB-NDVI colour composites for visualizing forest change dynamics , 1992 .

[10]  Tiit Nilson,et al.  A forest canopy reflectance model and a test case , 1991 .

[11]  S. Goetz,et al.  Large-Scale Patterns of Forest Succession as Determined by Remote Sensing , 1991 .

[12]  B. Koch,et al.  Spectroradiometer measurements in the laboratory and in the field to analyse the influence of different damage symptoms on the reflection spectra of forest trees , 1990 .

[13]  L. Marklund,et al.  Biomass functions for pine, spruce and birch in Sweden , 1988 .

[14]  Paul J. Curran,et al.  Factors affecting the remotely sensed response of coniferous forest plantations , 1993 .

[15]  R. Kauth,et al.  The tasselled cap - A graphic description of the spectral-temporal development of agricultural crops as seen by Landsat , 1976 .