Estimation of forest stand volume using textural indices of aerial images

Document Type : Research article

Authors

1 Ph.D. student of forest biometry, University of Tarbiat Modares

2 Associate Prof., Faculty of Natural Resources, University of Tarbiat Modares

3 Professor, Faculty of Natural Resources, University of Tehran

Abstract

Because of several radiometric errors, precise estimation of forest stand volume based on spectral indices is not achievable. In contrast to spectral indices, textural indices are more consistent dealing with these errors. In this research, estimation of forest stand volume based on textural indices was studied. For this aim, 150 plots were collected using systematic random design. Green, red and near infra red bands were used. Textural indices included second moment, contrast and homogeneity extract by different window size. Appropriate band, index and window size were chosen by stepwise regression. Based on this analysis, near infra red band, homogeneity index and 31×31 pixel window size were selected. RMSE and bias of estimation was 43 and 2 percent, respectively. Although, estimation accuracy of forest stand volume by textual indices was suitable for mapping purposes, however, its application in forestry operations needs more researches.

Keywords

References

- بی‌نام، 1381. جدول حجم گونه‌های جنگلی شمال کشور. دفتر فنی جنگل‌داری، سازمان جنگلها مراتع و آبخیزداری کشور، 114 صفحه.
- Anttila, P., 2002. Nonparametric estimation of stand volume using spectral and spatial features of aerial photographs and old inventory data. Canadian Journal of Forest Research, 32: 1849-1857.
- Bruniquel-Pinel, V. and Gastellu-Etchegorry, P., 1998. Sensitivity of texture of high resolution images of forest to biophysical and acquisition parameters. Remote Sensing of Environment, 65: 61-85.
- Franco-Lopez, H., Ek, A.R. and Bauer, M.E., 2001. Estimation and mapping of forest density, volume and cover type using the k-nearest neighbors method. Remote Sensing of Environment, 77: 251-274.
- Ge, S., Carruthers, R. and Gong, P., 2006. Texture analysis for mapping Tamarix parviflora using aerial photographs along the Cache Creek, California. Environmental Monitoring and Assessment, 114: 65-83.
- Haralick, R.M., Shanmugm, K. and Dinstein, I., 1973. Textural features for image classification. IEEE Transactions on Systems, Man and Cybernetics, 3 (6): 610-621.
- Holopainen, M. and Wang, G., 1998. The calibration of digitized aerial photographs for forest stratification. International Journal of Remote Sensing, 19 (4): 677-696.
- Hudak, A.T. and Wessman, C.A., 1998. Textural analysis of historical aerial photography to characterize woody plant encroachment in South African Savanna. Remote Sensing of Environment, 66: 317-330.
- Kayitakire, F., Hamel, C. and Defourny, P., 2006. Retrieving forest structure variables based on image texture analysis and IKONOS-2 imagery. Remote Sensing of Environment, 102: 390-401.
- Li, X. and Strahler, A.H., 1992. Geometric-optical bidirectional reflectance modeling of the discrete crown vegetation canopy: Effect of crown shape and mutual shadowing. IEEE Transactions on Geoscience and Remote Sensing, 30: 276-292.
- Maudie, A.J., 1999. Forest inventory classification using aerial image texture in the New Brunswick Acadian Forest Region. M.Sc. Thesis, the University of Calgary, 115 p.
- Pellikka, P., King, D.J. and Leblanc, S.G., 2000. Quantification and reduction of bidirectional effects in aerial CIR imagery of deciduous forest using two reference land surface types. Remote Sensing Reviews, 19 (1–4): 259-291.
- Poso, S., Wang, G. and Tuominen, S., 1999. Weighting alternative estimates when using multi-source auxiliary data for forest inventory. Silva Fennica, 33: 41-50.
- Samal, A., Brandle J.R. and Zhang, D., 2006. Texture as the basis for individual tree identification. Information Sciences, 176: 565-576.
- Tuominen, S. and Pekkarinen, A., 2005. Performance of different spectral and textural aerial photograph features in multi-source forest inventory. Remote Sensing of Environment, 94: 256-268.
- Wiebe, J.A., 1998. Texture estimates of operational forestry parameters, Ph.D. Thesis, University of Calgary, 109 p.
- Wulder, M.A., LeDrew, E.F., Franklin, S.E. and Lavigne, M.B., 1998. Aerial image texture information in the estimation of northern deciduous and mixed wood forest leaf area index (LAI). Remote Sensing of Environment, 64: 64-76.

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