Assessing the potential for leaf-off LiDAR data to model canopy closure in temperate deciduous forests Jason R. Parent ⇑ , John C. Volin Department of Natural Resources and the Environment, University of Connecticut, 1376 Storrs Road, U-4087, Storrs, CT 06269-4087, USA article info Article history: Received 27 February 2014 Received in revised form 13 June 2014 Accepted 13 June 2014 Keywords: LiDAR Leaf-off Canopy closure Canopy openness Canopy density Canopy height model Hemispherical photograph abstract Estimates of canopy closure have many important uses in forest management and ecological research. Field measurements, however, are typically not practical to acquire over expansive areas or for large numbers of locations. This problem has been addressed, in recent years, through the use of airborne light detection and ranging (LiDAR) technology which has proven effective in modeling canopy closure remotely. The techniques developed to use LiDAR for this purpose have been designed and evaluated for datasets acquired during leaf-on conditions. However, a large number of LiDAR datasets are acquired during leaf-off conditions since their primary purpose is to generate bare-earth Digital Elevation Models. In this paper, we develop and evaluate techniques for leveraging small-footprint leaf-off LiDAR data to model leaf-on canopy closure in temperate deciduous forests. We evaluate three techniques for modeling canopy closure: (1) the canopy-to-total-return-ratio (CTRR), (2) the canopy-to-total-pixel-ratio (CTPR), and (3) the hemispherical-viewshed (HV). The first technique has been used widely, in various forms, and has been shown to be effective with leaf-on LiDAR datasets. The CTRR technique that we tested uses the first-return LiDAR data only. The latter two techniques are new con- tributions that we develop and present in this paper. These techniques use Canopy Height Models (CHM) to detect significant gaps in the forest canopy which are of primary importance in estimating closure. The techniques we tested each showed good promise for predicting canopy closure using leaf-off LiDAR data with the CTPR and HV models having particularly high correlations with closure estimates from hemi- spherical photographs. The CTRR model had performance on par with results from previous studies that used leaf-on LiDAR, although, with leaf-off data the model tended to be negatively biased with respect to species having simple and compound leaf types and positively biased for coniferous species. The CTPR and HV models also showed some slight negative biases for compound-leaf species. The biases for the CTPR and HV models were mitigated when the CHM data were smoothed to fill in small gaps. The CHM-based models were robust to changes in the CHM model resolution which suggests that these methods may be applicable to a variety of small-footprint LiDAR datasets. In this research, the new CTPR and HV methods showed a strong ability to predict canopy closure using leaf-off data, however, future work will be needed to test the applicability of the models to variations in LiDAR datasets, forest types, and topography. Ó 2014 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved. 1. Introduction Measurements of canopy structure have important uses in ecological research and in forest management. Canopy structure strongly influences ecological processes in the forest understory by affecting light availability and microclimate which are domi- nant factors in plant growth and survival (Canham et al., 1994; Pacala et al., 1994). Canopy closure is one metric that is commonly used in characterizing canopy structure and is defined as the proportion of the sky hemisphere obscured by vegetation when viewed from a single point (Jennings et al., 1999). 1 This metric can be used to estimate light penetration into the forest understory and is an indicator of forest canopy density (Canham et al., 1990; Lieffers et al., 1999; Englund et al., 2000). Canopy closure is http://dx.doi.org/10.1016/j.isprsjprs.2014.06.009 0924-2716/Ó 2014 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved. ⇑ Corresponding author. Tel.: +1 860 486 2840; fax: +1 860 486 5408. E-mail addresses: jason.parent@uconn.edu (J.R. Parent), john.volin@uconn.edu (J.C. Volin). 1 As other authors have noted, there remains confusion in the literature regarding the terms canopy closure, canopy cover, fractional cover, etc. These issues have been addressed in the literature (e.g. see Jennings et al., 1999) and are beyond the scope of this paper. We have carefully evaluated all studies cited in this paper to ensure that they are applicable to our research on canopy closure as defined in Jennings et al., (1999). ISPRS Journal of Photogrammetry and Remote Sensing 95 (2014) 134–145 Contents lists available at ScienceDirect ISPRS Journal of Photogrammetry and Remote Sensing journal homepage: www.elsevier.com/locate/isprsjprs