1742 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 48, NO. 4, APRIL 2010 Improving Clumping and LAI Algorithms Based on Multiangle Airborne Imagery and Ground Measurements Anita Simic, Jing M. Chen, James R. Freemantle, John R. Miller, and Jan Pisek Abstract—Measurements at more than one angle capture the directional anisotropy of solar radiance reflected from vegetated surfaces. According to our recent research, we propose that the best two view angles for vegetation structural mapping are the following: 1) the hotspot, where the Sun and view directions coincide, and 2) the darkspot, where the sensor sees the maximum amount of vegetation structural shadows. The Normalized Differ- ence between Hotspot and Darkspot (NDHD), an angular index generated from Compact Airborne Spectrographic Imager (CASI) data, is found to be highly correlated with the field-measured foliage clumping index. The foliage clumping index characterizes the nonrandomness in the spatial distribution pattern of leaves. It is of comparable importance as the leaf area index (LAI) for quantifying radiation interception and distribution in plant canopies, and it also affects estimated LAI mapping using remote sensing data. As the clumping index can vary considerably within a cover type, it is highly desirable to map its spatial distribution for various ecological applications. We have generated clumping index maps based on the previous algorithms and empirical re- lationships between field-measured Ω and CASI-derived NDHD. Through intensive validation using field data, we demonstrate that the combination of the hotspot and darkspot reflectances has the strongest response to changes in vegetation structure. Two crown structural characteristics, namely, crown height and within-crown density, are major factors that impact the NDHD and clump- ing index difference between the mature and young (regrowth) coniferous forests. The study area is located near Sudbury in the northern Ontario, Canada. Index Terms—Clumping index, Compact Airborne Spectro- graphic Imager (CASI), darkspot, hotspot, leaf area index (LAI), multiangle, Normalized Difference between Hotspot and Darkspot (NDHD). I. I NTRODUCTION C HARACTERIZED by various levels of structural organi- zation, vegetation presents a real challenge for the remote sensing community. Leaves in plant canopies, particularly in forests and shrubs, are generally highly clumped. Leaves are more overlapped vertically than the random case because of canopy structures such as crowns, whirls, branches, and shoots. Manuscript received December 31, 2008; revised June 3, 2009. First pub- lished November 10, 2009; current version published March 24, 2010. This work was supported by the Canadian Space Agency. A. Simic, J. M. Chen, and J. Pisek are with the Department of Geography, University of Toronto, Toronto, ON M5S 3G3, Canada (e-mail: simica@ geog.utoronto.ca). J. R. Freemantle and J. R. Miller are with the Department of Earth and Space Science and Engineering, York University, Toronto, ON M3J 1P3, Canada. Digital Object Identifier 10.1109/TGRS.2009.2033383 This clumping decreases the proportion of sunlit leaves and increases shaded leaves at all Sun angles, thus affecting the interaction of radiation with vegetation, plant growth, and carbon cycle. The foliage clumping index (Ω) characterizes the spatial dis- tribution pattern of leaves. It is particularly useful for estimating radiation interception and distribution in plant canopies, and it is of comparable importance as leaf area index (LAI) for carbon/water cycle modeling [1], [2]. The clumping index is a function of the architectural properties of trees such as stem density and crown size [3], [4]. It serves as a correction factor to the effective LAI (L e ) to obtain the true LAI [3]. Optical instruments, such as LAI-2000, measure canopy gap fractions from the penetration of light at various angles and then convert these measurements into LAI under the assumption of a random spatial distribution of leaves, resulting in L e rather than LAI. Although the total absorbed radiation by the canopy is accurate when L e is used, the distribution of absorbed radiation in the canopy is distorted. If L e is assumed to be the true LAI, the amount of shaded leaf area is underestimated [2]. The propor- tion of shaded and sunlit leaves varies greatly with the clumping index. When introduced into an ecological model, the foliage clumping index caused the estimation of daily canopy photo- synthesis to differ by about 20% for a black spruce site [1]. Kurcharik et al. [3] found that accounting for the clumping in the aspen stand results in a scaled canopy assimilation that is 39% larger than in the case of random distribution. As the clumping index can vary considerably within a cover type, it is highly desirable to map its spatial distribution for various ecological applications [2]. The need to derive the shaded fraction of leaves triggered the use of multiangle remote sensing. Based on the relationship of field data of the bidirectional reflectance distribution function (BRDF), Deering et al. [5] found that forest canopy structure is related to its BRDF. Rapid developments in remote sensing technologies over the last two decades inspired scientists to probe into the relationships between biophysical and structural parameters of a vegetation canopy and multiangular remote sensing data. The acquisition of measurements at more than one angle captures the directional anisotropy of solar radiance reflected from vegetation surfaces. With the advent of the PO- Larization and Directionality of Earth Reflectances (POLDER) instrument, the observations of the hotspot have become more available. Data from the POLDER sensor onboard the ADEOS-1 platform have the ability to measure the same ground 0196-2892/$26.00 © 2009 IEEE Authorized licensed use limited to: University of Tartu IEL Trial. Downloaded on March 31,2010 at 14:56:22 EDT from IEEE Xplore. Restrictions apply.