Estimation of local forest attributes by utilizing two-phase sampling and auxiliary data
Tuominen S. (2007). Estimation of local forest attributes by utilizing two-phase sampling and auxiliary data. https://doi.org/10.14214/df.41
Abstract
This thesis examines the feasibility of a forest inventory method based on two-phase sampling in estimating forest attributes at the stand or substand levels for forest management purposes. The method is based on multi-source forest inventory combining auxiliary data consisting of remote sensing imagery or other geographic information and field measurements. Auxiliary data are utilized as first-phase data for covering all inventory units. Various methods were examined for improving the accuracy of the forest estimates. Pre-processing of auxiliary data in the form of correcting the spectral properties of aerial imagery was examined (I), as was the selection of aerial image features for estimating forest attributes (II). Various spatial units were compared for extracting image features in a remote sensing aided forest inventory utilizing very high resolution imagery (III). A number of data sources were combined and different weighting procedures were tested in estimating forest attributes (IV, V). Correction of the spectral properties of aerial images proved to be a straightforward and advantageous method for improving the correlation between the image features and the measured forest attributes. Testing different image features that can be extracted from aerial photographs (and other very high resolution images) showed that the images contain a wealth of relevant information that can be extracted only by utilizing the spatial organization of the image pixel values. Furthermore, careful selection of image features for the inventory task generally gives better results than inputting all extractable features to the estimation procedure. When the spatial units for extracting very high resolution image features were examined, an approach based on image segmentation generally showed advantages compared with a traditional sample plot-based approach. Combining several data sources resulted in more accurate estimates than any of the individual data sources alone. The best combined estimate can be derived by weighting the estimates produced by the individual data sources by the inverse values of their mean square errors. Despite the fact that the plot-level estimation accuracy in two-phase sampling inventory can be improved in many ways, the accuracy of forest estimates based mainly on single-view satellite and aerial imagery is a relatively poor basis for making stand-level management decisions.
Keywords
multi-source forest inventory;
two-phase sampling
Published 7 May 2007
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Available at https://doi.org/10.14214/df.41 | Download PDF
Original articles
Tuominen, S. & Pekkarinen, A. 2004. Local radiometric correction of digital aerial photographs for multi source forest inventory. Remote Sensing of Environment 89: 72-82.
https://doi.org/10.1016/j.rse.2003.10.005
Tuominen, S. & Pekkarinen, A. 2005. Performance of different spectral and textural aerial photograph features in multi-source forest inventory. Remote Sensing of Environment 94(2): 256-268.
https://doi.org/10.1016/j.rse.2004.10.001
Pekkarinen, A. & Tuominen, S. 2003. Stratification of a forest area for multisource forest inventory by means of aerial photographs and image segmentation. In: Corona, P., Köhl, M. & Marchetti, M. (eds.). Advances in forest inventory for sustainable forest management and biodiversity monitoring. Forestry Sciences 76. Kluwer Academic Publishers. pp. 111-123.
Tuominen, S. & Poso, S. 2001. Improving multi-source forest inventory by weighting auxiliary data sources. Silva Fennica 35(2).
https://doi.org/10.14214/sf.596
Tuominen, S., Fish, S. and Poso S. 2003. Combining remote sensing, data from earlier inventories and geostatistical interpolation in multi source forest inventory. Canadian Journal of Forest Research 33, 624-634.
http://pubs.nrc-cnrc.gc.ca/cgi-bin/rp/rp2_tocs_e?cjfr_cjfr4-03_33