Abstract

The article deals with the results of a statistical analysis reflecting tendencies (trends) of the relationship between spectral characteristics of taiga forests, indicators of the morphological structure of forest canopy and illumination of the territory. The study was carried out on the example of the model forest territory of the Priangarskiy taiga region of Eastern Siberia (Krasnoyarsk krai) using historical data (forest inventory 1992, Landsat 5 TM 16.06.1989) and the digital elevation model. This article describes a method for determining the quantitative indicator of morphological structure of forest canopy based on taxation data, and the authors propose to subdivide the morphological structure into high complexity, medium complexity, and relatively simple. As a result of the research, dependences of average values of spectral brightness in near and short-wave infrared channels of a Landsat 5 TM image for dark-coniferous, light-coniferous and deciduous forests from the degree of complexity of the forest-canopy structure are received. A high level of variance and maximum brightness average values are marked in green moss (hilocominosa) dark-coniferous and various-grass (larioherbosa) dark-coniferous forests and light-coniferous forests with a complex structure of canopy. The parvifoliate forests are characterized by high values of brightness in stands with a relatively simple structure of the canopy and by a small variance in brightness of any degree of the structure of the canopy complexity. The increase in brightness for the lit slopes in comparison with shaded ones in all stands with a difficult morphological canopy structure is revealed. However, the brightness values of the lit and shaded slopes do not differ for stands with a medium complexity of the structure. It is noted that, in addition to the indicator of the forest-canopy structure, the possible impact on increasing the variance of spectral brightness for the taxation plot has a variability of the slope ratio of “microslopes” inside the forest plot if it exceeds 60%.

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