Stem volume estimation in boreal forests using ERS-1/2 coherence and SPOT XS optical data

Citation
Jes. Fransson et al., Stem volume estimation in boreal forests using ERS-1/2 coherence and SPOT XS optical data, INT J REMOT, 22(14), 2001, pp. 2777-2791
Citations number
35
Categorie Soggetti
Earth Sciences
Journal title
INTERNATIONAL JOURNAL OF REMOTE SENSING
ISSN journal
01431161 → ACNP
Volume
22
Issue
14
Year of publication
2001
Pages
2777 - 2791
Database
ISI
SICI code
0143-1161(20010920)22:14<2777:SVEIBF>2.0.ZU;2-G
Abstract
The use of spaceborne synthetic aperture radar (SAR) systems to estimate st em volume and biomass in boreal forests has shown some promising results, b ut with saturation of the radar backscatter at relatively low stem volumes and limited accuracy of stem volume estimation. These limitations have moti vated evaluation of more advanced methods, such as interferometry. The resu lts presented in this study show that ERS interferometry, under favourable conditions, may be used to estimate stem volume at stand level with saturat ion level and accuracy useful for operational forestry management planning in boreal forests. Five interferograms were analysed, covering a test site located in the central part of Sweden with stem volume in the range Of 0-30 5 m(3) ha(-1). The best interferogram showed a linear relationship between stem volume and coherence with a root mean square error (RMSE) of approxima tely 26 m(3) ha(-1), corresponding to 20% of the average stem volume, throu ghout the range of stem volume. No saturation was observed up to the maximu m stem volume. However, the sensitivity of coherence to stem volume varied considerably between the interferograms. Finally, four SPOT XS images were evaluated and compared with the stem volume estimations obtained from the i nterferograms, resulting in a relative RMSE of about 24% of the stem volume , for the best case. The estimation of stem volume using coherence data,was found to be better than optical data for stem volumes exceeding about 110 m(3) ha(-1). The statistical analysis was performed using linear regression models with cross-validation.