Indirect estimates of canopy gap fraction based on the linear conversion of hemispherical photographs Methodology and comparison with standard thresholding techniques

One of the crucial steps in image processing is the thresholding, meaning the image segmentation needed to separate the foreground (canopy) from the background (sky). Due to the plethora of factors affecting image grey levels (lens vignetting, gamma correction, heterogeneity of sky irradiance, etc.), with current thresholding procedures the estimation of canopy gap fraction is rather uncertain. Both manual and automatic segmentation methods are highly dependent on exposure, operator experience or assumptions of thresholding algorithms, and therefore produce rather subjective and non-repeatable results. However, since CCD and CMOS sensors used in digital cameras respond linearly to light, it is nowadays possible to obtain images in which digital numbers are proportional to canopy brightness. For this purpose the standard in-camera logarithmic conversion (gamma correction) has to be replaced with a linear conversion of the sensor analog signal. In this work, the potential of the linear conversion of digital images in the estimation of canopy gap fraction is assessed and discussed, comparing the estimates obtained with digital cameras and with the LI-COR LAI-2000. In addition, the performance of the linear conversion is compared with standard automatic or manual thresholding methods, both in terms of canopy gap fraction and of plant architectural parameters. The ability to acquire hemispherical photographs with digital numbers proportional to radiance opens new possibilities in the analysis of canopy structure and microclimate, with important feedbacks in ecology and remote sensing. In particular, using two synchronized cameras above and below the canopy, it is possible to calculate high-resolution gap fraction data, which provide an accurate and objective estimation of the intercepted radiation and of typical architectural parameters, such as LAI. In addition, the effectiveness of this methodology for the estimation of linear and logarithmic averages of canopy gap fraction, makes this technique an important step forward in the estimation of leaf area index of non-random canopies.

[1]  T. Nilson.  A theoretical analysis of the frequency of gaps in plant stands , 1971 .

[2]  Jing M. Chen,et al.  Determining digital hemispherical photograph exposure for leaf area index estimation , 2005 .

[3]  Tiit Nilson,et al.  Inversion of gap frequency data in forest stands , 1999 .

[4]  Frédéric Baret,et al.  Review of methods for in situ leaf area index determination Part I. Theories, sensors and hemispherical photography , 2004 .

[5]  Jing M. Chen,et al.  Quantifying the effect of canopy architecture on optical measurements of leaf area index using two gap size analysis methods , 1995, IEEE Trans. Geosci. Remote. Sens..

[6]  C. Woodcock,et al.  Evaluation of the MODIS LAI algorithm at a coniferous forest site in Finland , 2004 .

[7]  Francisco de Castro,et al.  The effect of leaf clustering in the interception of light in vegetal canopies: theoretical considerations , 1999 .

[8]  F. Baret,et al.  Review of methods for in situ leaf area index (LAI) determination: Part II. Estimation of LAI, errors and sampling , 2004 .

[9]  T. A. Black,et al.  Characteristics of shortwave and longwave irradiances under a Douglas-fir forest stand , 1991 .

[10]  Roselyne Lacaze,et al.  Retrieval of vegetation clumping index using hot spot signatures measured by POLDER instrument , 2002 .

[11]  J. Hicke,et al.  Global synthesis of leaf area index observations: implications for ecological and remote sensing studies , 2003 .

[12]  G. Russell,et al.  Leaf area index estimates obtained for clumped canopies using hemispherical photography , 1999 .

[13]  Richard A. Fournier,et al.  Integrating clumping effects in forest canopy structure: an assessment through hemispherical photographs , 2003 .

[14]  D. Coombe,et al.  Hemisperical and Woodland Canopy Photography and the Light Climate , 1959 .

[15]  R. Hall,et al.  A comparison of digital and film fisheye photography for analysis of forest canopy structure and gap light transmission , 2001 .

[16]  Sylvain G. Leblanc,et al.  Methodology comparison for canopy structure parameters extraction from digital hemispherical photography in boreal forests , 2005 .

[17]  D. Clark,et al.  Evaluation of digital and film hemispherical photography and spherical densiometry for measuring forest light environments. , 2000 .

[18]  Jing M. Chen,et al.  Canopy architecture and remote sensing of the fraction of photosynthetically active radiation absorbed by boreal conifer forests , 1996, IEEE Trans. Geosci. Remote. Sens..

[19]  A. Kuusk,et al.  Angular distribution of radiation beneath forest canopies using a CCD-radiometer , 2002 .

[20]  Michael Nobis,et al.  Automatic thresholding for hemispherical canopy-photographs based on edge detection , 2005 .

[21]  S. Hale,et al.  Comparison of film and digital hemispherical photography across a wide range of canopy densities , 2002 .

[22]  Sylvain G. Leblanc,et al.  A practical scheme for correcting multiple scattering effects on optical LAI measurements , 2001 .

[23]  Alessandro Cescatti,et al.  Effects of needle clumping in shoots and crowns on the radiative regime of a Norway spruce canopy , 1998 .

[24]  T. Spies,et al.  Evaluating Forest Vegetative Cover with Computerized Analysis of Fisheye Photographs , 1986, Forest Science.

[25]  Andres Kuusk,et al.  Improved algorithm for estimating canopy indices from gap fraction data in forest canopies , 2004 .

[26]  T. W. Ridler,et al.  Picture thresholding using an iterative selection method. , 1978 .

[27]  Craig Macfarlane,et al.  Photographic exposure affects indirect estimation of leaf area in plantations of Eucalyptus globulus Labill. , 2000 .

[28]  Megumi Ishida,et al.  Automatic thresholding for digital hemispherical photography , 2004 .

[29]  Pol Coppin,et al.  Assessment of automatic gap fraction estimation of forests from digital hemispherical photography , 2005 .

[30]  P. Rich.  Characterizing plant canopies with hemispherical photographs. , 1990 .

[31]  Sven Wagner,et al.  Calibration of grey values of hemispherical photographs for image analysis , 1998 .

[32]  Ian T. Young,et al.  Methods for CCD camera characterization , 1994, Electronic Imaging.

[33]  S. T. Gower,et al.  Leaf area index of boreal forests: theory, techniques, and measurements , 1997 .

[34]  A. Lang.  Estimation of leaf area index from transmission of direct sunlight in discontinuous canopies , 1986 .

[35]  Kazukiyo Yamamoto,et al.  Effects of image quality, size and camera type on forest light environment estimates using digital hemispherical photography , 2004 .

[36]  Jb Miller,et al.  A formula for average foliage density , 1967 .

[37]  John M. Norman,et al.  Characterization of radiation regimes in nonrandom forest canopies: theory, measurements, and a simplified modeling approach. , 1999, Tree physiology.