Sakari Tuominen , Markus Haakana

Landsat TM imagery and high altitude aerial photographs in estimation of forest characteristics

Tuominen S., Haakana M. (2005). Landsat TM imagery and high altitude aerial photographs in estimation of forest characteristics. Silva Fennica vol. 39 no. 4 article id 367. https://doi.org/10.14214/sf.367

Abstract

Satellite sensor data have traditionally been used in multi-source forest inventory for estimating forest characteristics. Their advantages generally are large geographic coverage and large spectral range. Another remote sensing data source for forest inventories offering a large geographic coverage is high altitude aerial photography. In high altitude aerial photographs the spectral range is very narrow but the spatial resolution is high. This allows the extraction of texture features for forest inventory purposes. In this study we utilized a Landsat 7 ETM satellite image, a photo mosaic composed of high altitude panchromatic aerial photographs, and a combination of the aforementioned in estimating forest attributes for an area covering approximately 281 000 ha in Forestry Centre Häme-Uusimaa in Southern Finland. Sample plots of 9th National Forest Inventory (NFI9) were used as field data. In the estimation, 6 Landsat 7 ETM image channels were used. For aerial photographs, 4 image channels were composed from the spectral averages and texture features. In combining both data sources, 6 Landsat channels and 3 aerial image texture channels were selected for the analysis. The accuracy of forest estimates based on the Landsat image was better than that of estimates based on high altitude aerial photographs. On the other hand, using the combination of Landsat ETM spectral features and textural features on high altitude aerial photographs improved the estimation accuracy of most forest attributes.

Keywords
multi-source forest inventory; satellite imagery; high-altitude aerial photographs; image texture

Received 15 November 2004 Accepted 12 October 2005 Published 31 December 2005

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