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Petr Lukeš Miina Rautiainen Pauline Stenberg Zbyněk Malenovský 《International Journal of Applied Earth Observation and Geoinformation》2011
The spectral invariants theory presents an alternative approach for modeling canopy scattering in remote sensing applications. The theory is particularly appealing in the case of coniferous forests, which typically display grouped structures and require computationally intensive calculation to account for the geometric arrangement of their canopies. However, the validity of the spectral invariants theory should be tested with empirical data sets from different vegetation types. In this paper, we evaluate a method to retrieve two canopy spectral invariants, the recollision probability and the escape factor, for a coniferous forest using imaging spectroscopy data from multiangular CHRIS PROBA and NADIR-view AISA Eagle sensors. Our results indicated that in coniferous canopies the spectral invariants theory performs well in the near infrared spectral range. In the visible range, on the other hand, the spectral invariants theory may not be useful. Secondly, our study suggested that retrieval of the escape factor could be used as a new method to describe the BRDF of a canopy. 相似文献
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C. Comas L. Mehtätalo J. Miina 《Stochastic Environmental Research and Risk Assessment (SERRA)》2013,27(7):1673-1681
We analysed the space–time structure of two spatially explicit forest data sets considering the associated growth function for each tree obtained from the annual radial growth measured from increment cores bored at breast height. We used a new second order formulation based on the mark correlation function, the functional mark correlation function, to analyse spatial pattern involving functions to each spatial location. A decomposition of individual growth function into spatial and non-spatial components was considered and only the spatial components were analysed. Our results confirm the usefulness of these new approach compared with other well-established spatial statistical tools such as the mark correlation function. In particular, the functional mark correlation function of the spatial and temporal components of tree growth determines the space–time structure of tree development regardless of the non-spatial components contained in this function. Moreover, this explicit temporal analysis detects space–time interaction effects that are not evident when analysing the spatial distribution of cumulative growth measures such as the tree basal area. 相似文献
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Janne Heiskanen Miina Rautiainen Lauri Korhonen Matti Mõttus Pauline Stenberg 《International Journal of Applied Earth Observation and Geoinformation》2011
Spectral invariants provide a novel approach for characterizing canopy structure in forest reflectance models and for mapping biophysical variables using satellite images. We applied a photon recollision probability (p) based forest reflectance model (PARAS) to retrieve leaf area index (LAI) from fine resolution SPOT HRVIR and Landsat ETM+ satellite data. First, PARAS was parameterized using an extensive database of LAI-2000 measurements from five conifer-dominated boreal forest sites in Finland, and mixtures of field-measured forest understory spectra. The selected vegetation indices (e.g. reduced simple ratio, RSR), neural networks and kNN method were used to retrieve effective LAI (Le) based on reflectance model simulations. For comparison, we established empirical vegetation index-LAI regression models for our study sites. The empirical RSR–Le regression performed best when applied to an independent test site in southern Finland [RMSE 0.57 (24.2%)]. However, the difference to the best reflectance model based retrievals produced by neural networks was only marginal [RMSE 0.59 (25.1%)]. According to this study, the PARAS model provides a simple and flexible modelling tool for calibrating algorithms for LAI retrieval in conifer-dominated boreal forests. The advantage of PARAS is that it directly uses field measurements to parameterize canopy structure (LAI-2000, hemispherical photographs) and optical properties of foliage and understory. 相似文献
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