Estimating Savanna Clumping Index Using Hemispherical Photographs Integrated with High Resolution Remote Sensing Images

In contrast to herbaceous canopies and forests, savannas are grassland ecosystems with sparsely distributed individual trees, so the canopy is spatially heterogeneous and open, whereas the woody cover in savannas, e.g., tree cover, adversely affects ecosystem structures and functions. Studies have shown that the dynamics of canopy structure are related to available water, climate, and human activities in the form of porosity, leaf area index (LAI), and clumping index (CI). Therefore, it is important to identify the biophysical parameters of savanna ecosystems, and undertake practical actions for savanna conservation and management. The canopy openness presents a challenge for evaluating canopy LAI and other biophysical parameters, as most remotely sensed methods were developed for homogeneous and closed canopies. Clumping index is a key variable that can represent the clumping effect from spatial distribution patterns of components within a canopy. However, it is a difficult task to measure the clumping index of the moderate resolution savanna pixels directly using optical instruments, such as the Tracing Radiation and Architecture of Canopies, LAI-2000 Canopy Analyzer, or digital hemispherical photography. This paper proposed a new method using hemispherical photographs combined with high resolution remote sensing images to estimate the clumping index of savanna canopies. The effects of single tree LAI, crown density, and herbaceous layer on the clumping index of savanna pixels were also evaluated. The proposed method effectively calculated the clumping index of moderate resolution pixels. The clumping indices of two study regions located in Ejina Banner and Weichang were compared with the clumping index product over China’s landmass.

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

[2]  Bowei Yan,et al.  Analysis of the pattern of potential woody cover in Texas savanna , 2016, Int. J. Appl. Earth Obs. Geoinformation.

[3]  Jan Pisek,et al.  Estimation of foliage clumping from the LAI-2000 Plant Canopy Analyzer: effect of view caps , 2014, Trees.

[4]  R. Lacaze,et al.  Multi-angular optical remote sensing for assessing vegetation structure and carbon absorption , 2003 .

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

[6]  S. Leblanc.  Correction to the plant canopy gap-size analysis theory used by the Tracing Radiation and Architecture of Canopies instrument. , 2002, Applied optics.

[7]  Raoul Lemeur,et al.  A critical review of light models for estimating the shortwave radiation regime of plant canopies , 1974 .

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

[9]  J. Chen,et al.  Defining leaf area index for non‐flat leaves , 1992 .

[10]  A. Gonsamo,et al.  The computation of foliage clumping index using hemispherical photography , 2009 .

[11]  Kelly K. Caylor,et al.  Determinants of woody cover in African savannas , 2005, Nature.

[12]  Robert W. Pearcy,et al.  Exploitation of environmental heterogeneity by plants: ecophysiological processes above- and belowground , 1994 .

[13]  Guy R. McPherson,et al.  Ecology and Management of North American Savannas , 1998 .

[14]  R. Lacaze,et al.  Expanding global mapping of the foliage clumping index with multi-angular POLDER three measurements: Evaluation and topographic compensation , 2010 .

[15]  F. Woodward,et al.  What controls South African vegetation — climate or fire? , 2003 .

[16]  J. Chen.  Optically-based methods for measuring seasonal variation of leaf area index in boreal conifer stands , 1996 .

[17]  Robert J. Scholes,et al.  Canopy structure in savannas along a moisture gradient on Kalahari sands , 2004 .

[18]  Youngryel Ryu,et al.  Interannual variability of evapotranspiration and energy exchange over an annual grassland in California , 2008 .

[19]  Lars Eklundh,et al.  Estimation of absorbed PAR across Scandinavia from satellite measurements. Part II: Modeling and evaluating the fractional absorption , 2007 .

[20]  Niall P. Hanan,et al.  Tree–grass coexistence in savannas revisited – insights from an examination of assumptions and mechanisms invoked in existing models , 2004 .

[21]  Gérard Dedieu,et al.  Estimation of leaf area and clumping indexes of crops with hemispherical photographs , 2008 .

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

[23]  K. Moffett,et al.  Remote Sens , 2015 .

[24]  Rong Wang,et al.  Inter- and intra-annual variations of clumping index derived from the MODIS BRDF product , 2016, Int. J. Appl. Earth Obs. Geoinformation.

[25]  Andrea Cutini,et al.  Estimation of canopy properties in deciduous forests with digital hemispherical and cover photography , 2013 .

[26]  Zhen Zhen,et al.  Impact of Tree-Oriented Growth Order in Marker-Controlled Region Growing for Individual Tree Crown Delineation Using Airborne Laser Scanner (ALS) Data , 2014, Remote. Sens..

[27]  Peng Gong,et al.  Modeling radiation and photosynthesis of a heterogeneous savanna woodland landscape with a hierarchy of model complexities , 2007 .

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

[29]  Guy R. McPherson,et al.  Ecology and Management of North American Savannas , 1998 .

[30]  J. Cihlar,et al.  Plant canopy gap-size analysis theory for improving optical measurements of leaf-area index. , 1995, Applied optics.

[31]  Gareth Roberts,et al.  Vegetation structure characteristics and relationships of Kalahari woodlands and savannas , 2004 .

[32]  C. Schaaf,et al.  Characterizing vegetation cover in global savannas with an annual foliage clumping index derived from the MODIS BRDF product , 2011 .

[33]  J. Chen,et al.  Global mapping of foliage clumping index using multi-angular satellite data , 2005 .

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

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

[36]  S. T. Gower,et al.  Characterizing canopy nonrandomness with a multiband vegetation imager (MVI) , 1997 .

[37]  J. Norman,et al.  Instrument for Indirect Measurement of Canopy Architecture , 1991 .

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

[39]  J. Norman,et al.  Photosynthesis in Sitka spruce (Picea sitchensis (Bong.) Carr.). V. Radiation penetration theory and a test case , 1975 .

[40]  A. Strahler,et al.  Global clumping index map derived from the MODIS BRDF product , 2012 .

[41]  S. Leblanc,et al.  Derivation and validation of Canada-wide coarse-resolution leaf area index maps using high-resolution satellite imagery and ground measurements , 2002 .

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

[43]  J. M. Norman,et al.  Photosynthesis in Sitka Spruce (Picea sitchensis (Bong.) Carr.). III. Measurements of Canopy Structure and Interception of Radiation , 1974 .

[44]  C. Woodcock,et al.  Measuring Gap Fraction, Element Clumping Index and LAI in Sierra Forest Stands Using a Full-Waveform Ground-Based Lidar , 2012 .

[45]  Jing M. Chen,et al.  Improved LAI Algorithm Implementation to MODIS Data by Incorporating Background, Topography, and Foliage Clumping Information , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[46]  Craig Macfarlane,et al.  Measurement of Crown Cover and Leaf Area Index Using Digital Cover Photography and Its Application to Remote Sensing , 2009, Remote. Sens..

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

[48]  Hideki Kobayashi,et al.  On the correct estimation of effective leaf area index: does it reveal information on clumping effects? , 2010 .

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

[50]  Serge Collineau,et al.  2 – The Physical Nature of Solar Radiation in Heterogeneous Canopies: Spatial and Temporal Attributes , 1994 .

[51]  Sylvain G. Leblanc,et al.  A four-scale bidirectional reflectance model based on canopy architecture , 1997, IEEE Trans. Geosci. Remote. Sens..

[52]  Frederick C. Meinzer,et al.  Seasonal leaf dynamics across a tree density gradient in a Brazilian savanna , 2005, Oecologia.

[53]  Hongliang Fang,et al.  Intercomparison of clumping index estimates from POLDER, MODIS, and MISR satellite data over reference sites , 2015 .

[54]  N. Ramankutty,et al.  Estimating historical changes in global land cover: Croplands from 1700 to 1992 , 1999 .

[55]  J. Chen,et al.  Retrieving forest background reflectance in a boreal region from Multi-angle Imaging SpectroRadiometer (MISR) data , 2007 .

[56]  John R. Miller,et al.  Mapping Forest Background Reflectance in a Boreal Region Using Multiangle Compact Airborne Spectrographic Imager Data , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[57]  Stephen V. Stehman,et al.  Agent-based region growing for individual tree crown delineation from airborne laser scanning (ALS) data , 2015 .

[58]  Luca Ridolfi,et al.  Tree‐grass coexistence in Savannas: The role of spatial dynamics and climate fluctuations , 1999 .

[59]  Peng Gong,et al.  Foliage Clumping Index Over China's Landmass Retrieved From the MODIS BRDF Parameters Product , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[60]  Roger C. Anderson,et al.  Savannas, Barrens, and Rock Outcrop Plant Communities of North America: Introduction , 1999 .