Woodgate, W; Armston, JD; Disney, M; Jones, SD; Suarez, L; Hill, MJ; Wilkes, P; Woodgate, W; Armston, JD; Disney, M; Jones, SD; Suarez, L; Hill, MJ; Wilkes, P; Soto-Berelov, M; - view fewer (2016) Quantifying the impact of woody material on leaf area index estimation from hemispherical photography using 3D canopy simulations. Agricultural and Forest Meteorology , 226 pp. 1-12. 10.1016/j.agrformet.2016.05.009.

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Abstract

Estimating the proportion of woody-to-total plant material ‘α’ is an essential step to convert Plant Area Index ‘PAI’ estimates into Leaf Area Index ‘LAI’. α has also been shown to have a significant impact on the passive optical remote sensing signal for retrieval of biophysical parameters in forests, woodlands, and savannas. However, benchmarked indirect α retrieval methods are lacking and thus it is common for this pivotal correction to be ignored. In this paper we validate an α retrieval method using a 3D radiative transfer simulation framework, enabling the retrieval method to be benchmarked against a known and precise model truth. The 3D framework consists of a representative and highly detailed 3D explicit Eucalypt forest reconstructed from field measurements. The 3D structure is coupled with a 3D scattering model to enable simulation of remote sensing instruments. The retrieval method utilises classified hemispherical photography ‘HP’, but is applicable to all ground-based optical instruments that can separate leaf and woody elements. The method is applicable to evergreen forests and thus independent of the estimation of PAI or LAI. The unknown degree of mutual shading or occlusion of leaf and woody elements was traditionally a key impediment to the operational use of this method and was therefore closely examined. The indirect α method utilising classified HP imagery agreed on average to within 0.01 α of the reference (αref = 0.37). In addition, the method demonstrated robustness to a range of LAI, stem density, and stem distribution values, matching to within ±0.05 α of the reference. Angular dependence on indirect α retrieval was also found; where the entire HP image (180° FOV) was needed to produce the most accurate estimate. Conversely, the classified narrow view zenith angle range around 55−60° zenith also provided an α estimate matching the reference. At this narrow zenith angle the method is insensitive to leaf angle distribution. As such, careful consideration of zenith angle range utilised from the instrument is recommended. The results demonstrate the method’s applicability for accurate indirect estimation of α in single-storey forest types. The simple and efficient method can be used to convert estimates of PAI into LAI from a variety of optical ground-based instruments. Quantitative α estimates can and should be used to aid interpretation of the remote sensing signal from satellite imagery, which has been shown to be sensitive to the proportion and spatial distribution of woody canopy materials.

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