Method for determination of stand attributes and a computer...

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Reexamination Certificate

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C033SDIG002, C356S004010

Reexamination Certificate

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06792684

ABSTRACT:

The invention relates to a method for forest inventory and the determination of stand attributes. With the aid of the method, stand attributes of trees, sample plots and larger forest areas can be measured by measuring and deriving the most important characteristics of individual trees. The invention also relates to a computer program to carry out the method.
PRESENT STATE OF ART
Conventional forest inventory is mostly based on field measurements. E.g. forest inventory at stand level, in which the forest is first divided into almost homogeneous forest units (typically 1-3 hectares in size), is presently based on plot measurements and subjective ocular inventory. Aerial photographs and orthophotos (aerial photos rectified to map projection) are typically used in delineation of stand boundaries and determination of the walking route in the forest However, stand attributes, such as the volume (m
3
/ha), the basal area (m
2
/ha, depicts the cross-sectional area per hectare at the height of 1.3 m), mean height (m), other density type characteristics, tree species, age, and development class, are determined by measurements and assessments carried out in forests. This work has been tried to been made more effective by increasing the level of automation, e.g. by field computers and by more automatic measurement equipment (e.g. patent Fl 101016 B). In forest inventory at stand level, tree and stand attributes are calculated by plotwise information carried out in the same stand and by ocular estimation. In addition to standwise forest inventory, plotwise forest inventory, measurements of single trees, and estimation of larger areas, such as whole nations or parts of them, are carried out.
Remote sensing methods (measurement of target properties without any physical contact) have been studied for a long time as an alternative and future method for the traditional field inventory work. At large area forest inventory, promising results have been obtained by using satellite imagery (e.g.
Tomppo E.
1991.
Satellite image
-
based national forest inventory of Finland. International Archives of Photogrammetry and Remote Sensing.
28: 419-424). In such methods, field-measured plotwise data are typically used as a teaching data set and the satellite image is used to generalize this carefully corrected field data for the whole image. A prerequisite for a successful solution for small areas is that features (channels, ratio of channels and the like) from the satellite image that correlates strongly with stand attributes collected at plot level have to be found. Thus, the method is capable for large area forest inventory. By improving the quality of remote sensing data sources, by taking into account airborne data acquisitions, the accuracy of remote sensing based estimates can be improved. Despite this, the accuracy required in standwise forest inventory (about 15% error tolerated, R. Päivinen, A Pussinen, and E. Tomppo, 1993, “Assessment of boreal forest stands using field assessment and remote sensing”,
Proceedings of Earsel
1993
Conference “Operationalization of Remote Sensing”, ITC Enshedene, The Netherlands,
19-23 Apr., 1993, 8p.) has not been obtained by the use of remote sensing methods.
As an example, the standwise forest inventory in Finland by forestry organizations is performed totally by field work and the national forest inventory is carried out with the help of satellite imagery (such as using Landsat TM images with 30 m spatial resolution). A rather extensive description of accuracy obtained with various remote sensing data sources are depicted in the publications (J. Hyyppä, Hyyppä, H., Inkinen, M., Engdahl, M., Linko, S. and Zhu, Y-H., 1998.
Accuracy of different remote sensing data sources in the retrieval of forest stand attributes. Proceedings of the First International Conference on Geospatial Information in Agriculture and Forestry.
Lake Buena Vista, Fla., USA, 1-3 Jun. 1998, Volume I, pp. 370377, and J. Hyyppä, Hyyppä, H., Inkinen, M, Engdahl, M., Linko, S., Zhu, Y-H., 1999a, Accuracy comparison of various remote sensing data sources in the retrieval of forest stand attributes,
Journal of Forest Ecology and Management
(in press)). The applicant of this patent proposal does not know any remote sensing-based forest inventory method that would satisfy the accuracy requirements of standwise forest inventory;
Another type of a method for stem attribute estimation of a forest plot is depicted in the Finnish patent 101016 B. The method registers optically all trees within a defined radius from a selected center. You can e.g. use the AccuRange 3000-LIR laser rangefinder, the accuracy of which is one 65535
th
of 360° or a pulse detector. The registration is carried out by a rotation measurement unit in such a way that the tangent is calculated as the difference in the absolute angular rotation from the discontinuity parts occurring at both sides of the stems. The method (Finnish patent 101016 B) can be used to automate conventional collection of plotwise data but it requires work done in forest and it is rather slow (one rotation takes 1 to 6 minutes, so that the computer would have time to transfer the measurement data). The method is also inventory based on diameter measurements at horizontal level. The major problem with the method depicted in Fl patent 101016 B is that it is so slow that it is suitable only for collecting small amounts of sample from the whole stand.
Previously, aircraft and helicopters have been used to measure forest canopy height with lasers and microwave radars. These earlier measurements were based on measurements of cross-sectional areas of forests (along the flight direction, the height of the stand was measured from the area illuminated with the laser or the radar). Examples of such studies are e.g. R. Nelson, Krabill, W. B., and Maclean, G. A. 1984,
“Determining forest canopy characteristics using airborne laser data”, Remote Sensing Environment,
15:201-212, and J. Hyyppä, Hallikainen, M., 1996.
Applicability of airborne profiling radar to forest inventory. Remote Sensing Environment,
57: 39-57. Individual trees were not analyzed in these studies, since the images were two-dimensional cross-sections. With these measurements, the tree height was obtained and other attributes derived from that by using regression formulas. The volume estimation errors were at the best about 26.5%, which is not enough for operational use.
Nässet (e.g. E. Nässet,
“Determination of mean tree height of forest stands using airborne laser scanner data”, ISPR J. Photogramm. Remote Sensing,
52, pp. 49-56, 1997.) was able to produce equally distributed samples from the forest using laser scanning, but the estimation of stand characteristics was performed by using statistical methods in a similar way as the previous profiling measurements. As an example, the mean tree height estimate was calculated by taking minimum and maximum heights of laser data within a certain window size.
In year 1999, Hyyppä et al. (J. Hyyppä, Hyyppä, H., Samberg, A., 1999,
Assessing Forest Stand Attributes by Laser Scanner, Laser Radar Technology and Applications IV, Proceedings of SPIE,
3707, 57-69.) demonstrated that it is possible to measure the height of dominant trees by using high pulse rate laser scanner. In this study, volume estimation based on height samples was tested by using a similar approach as previous profiling measurements conducted with lasers and radars. Additionally, a virtual reality tree height model produced with laser scanner was presented in this study. In this work, individual trees were not segmented or recognized and neither any other stand attributes or individual trees.
Also Gunilla Borgefors et al. (Gunilla Borgefors, Tomas Brandberg, Fredrik Walter “
Forest parameter extraction from airborne sensors”, APRS, Vol.
32, Part3-2WS, “
Automatic Extraction of GIS Objects from Digital Imaging”, München
8-10 Sep. 1999, pp. 151-158) have proposed the use of laser data for stand attribute retrieval. In the publication, the stem number and the crown size is defined f

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