Persson, Henrik
(2016).
Estimation of boreal forest attributes from very high resolution pleiades data.
Remote sensing. 8
:9
, 1-19
[Journal article]
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- Published Version
Available under License Creative Commons Attribution. 5MB |
Official URL: http://dx.doi.org/10.3390/rs8090736
Abstract
In this study, the potential of using very high resolution Pleiades imagery to estimate a number of common forest attributes for 10-m plots in boreal forest was examined, when a high-resolution terrain model was available. The explanatory variables were derived from three processing alternatives. Height metrics were extracted from image matching of the images acquired from different incidence angles. Spectral derivatives were derived by performing principal component analysis of the spectral bands and lastly, second order textural metrics were extracted from a gray-level co-occurrence matrix, computed with an 11 x 11 pixels moving window. The analysis took place at two Swedish test sites, Krycklan and Remningstorp, containing boreal and hemi-boreal forest. The lowest RMSE was estimated with 1.4 m (7.7%) for Lorey's mean height, 1.7 m (10%) for airborne laser scanning height percentile 90, 5.1 m(2)ha(-1) (22%) for basal area, 66 m(3)ha(-1) (27%) for stem volume, and 26 tonsha(-1) (26%) for above-ground biomass, respectively. It was found that the image-matched height metrics were most important in all models, and that the spectral and textural metrics contained similar information. Nevertheless, the best estimations were obtained when all three explanatory sources were used. To conclude, image-matched height metrics should be prioritised over spectral metrics when estimation of forest attributes is concerned.
Authors/Creators: | Persson, Henrik | ||||
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Title: | Estimation of boreal forest attributes from very high resolution pleiades data | ||||
Series/Journal: | Remote sensing (2072-4292) | ||||
Year of publishing : | 2016 | ||||
Volume: | 8 | ||||
Number: | 9 | ||||
Page range: | 1-19 | ||||
Number of Pages: | 19 | ||||
Publisher: | MDPI | ||||
ISSN: | 2072-4292 | ||||
Language: | English | ||||
Publication Type: | Journal article | ||||
Refereed: | Yes | ||||
Article category: | Scientific peer reviewed | ||||
Version: | Published version | ||||
Copyright: | Creative Commons: Attribution 4.0 | ||||
Full Text Status: | Public | ||||
Agris subject categories.: | K Forestry > K01 Forestry - General aspects | ||||
Subjects: | (A) Swedish standard research categories 2011 > 2 Engineering and Technology > 207 Environmental Engineering > Remote Sensing (A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 401 Agricultural, Forestry and Fisheries > Forest Science | ||||
Keywords: | canopy, image matching, forestry, Pleiades, biomass, VHR | ||||
URN:NBN: | urn:nbn:se:slu:epsilon-e-3961 | ||||
Permanent URL: | http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-e-3961 | ||||
Additional ID: |
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ID Code: | 14057 | ||||
Faculty: | S - Faculty of Forest Sciences | ||||
Department: | (S) > Dept. of Forest Resource Management (NL, NJ) > Dept. of Forest Resource Management | ||||
Deposited By: | SLUpub Connector | ||||
Deposited On: | 20 Feb 2017 09:09 | ||||
Metadata Last Modified: | 09 Sep 2020 14:17 |
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