Mapping Forest Background Reflectance in a Boreal Region Using Multiangle Compact Airborne Spectrographic Imager Data

Forest background, consisting of understory, moss, litter, and soil, contributes significantly to optical remote sensing signals from forests in the boreal region. In this paper, we present results of background reflectance retrieval from multiangle high-resolution Compact Airborne Spectrographic Imager sensor data over a boreal forest area near Sudbury, ON, Canada. Modifications of the background by white and black plastic sheets at two sites provide two extreme limits for the development and testing of an algorithm for retrieving the background information from multiangle data. Measured background reflectances in red and near-infrared bands at six sites in the vicinity of these modified sites are used to validate the algorithm. We also explore the effect of uncertainties in the input forest structural parameters on this retrieval. The results document: 1) capability of the algorithm to retrieve meaningful background reflectance values for various forest stand conditions, particularly in the low to intermediate canopy density range; 2) the effect of background bidirectional reflectance distribution function on retrieved values; 3) performance of the algorithm using data with different cross angle values; and 4) verification of the internal consistency of the geometric-optical 4-Scale model used. The results provide an important platform for the operational estimation of the vegetation background reflectance from the bidirectional reflections observed by the Multiangle Imaging Spectroradiometer instrument.

[1]  Ranga B. Myneni,et al.  Assessing the information content of multiangle satellite data for mapping biomes: I. Statistical analysis , 2002 .

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

[3]  S. Sandmeier,et al.  Structure Analysis and Classification of Boreal Forests Using Airborne Hyperspectral Brdf Data from Asas Imagery and Processing Techniques Have Also Been Used Potential for Combining Both High Spectral Resolution And , 2022 .

[4]  Jing M. Chen,et al.  Mapping forest background reflectivity over North America with Multi-angle Imaging SpectroRadiometer (MISR) data , 2009 .

[5]  Miina Rautiainen,et al.  Retrieval of leaf area index for a coniferous forest by inverting a forest reflectance model , 2005 .

[6]  Michael D. King,et al.  Airborne spectral measurements of surface anisotropy during SCAR‐B , 1998 .

[7]  John R. Miller,et al.  Four-Scale Linear Model for Anisotropic Reflectance (FLAIR) for plant canopies. I. Model description and partial validation , 2001, IEEE Trans. Geosci. Remote. Sens..

[8]  J. Heiskanen Tree cover and height estimation in the Fennoscandian tundra-taiga transition zone using multiangular MISR data , 2006 .

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

[10]  D. Roberts,et al.  Mapping tree and shrub leaf area indices in an ombrotrophic peatland through multiple endmember spectral unmixing , 2007 .

[11]  Jerzy Neyman,et al.  On a New Class of "Contagious" Distributions, Applicable in Entomology and Bacteriology , 1939 .

[12]  Karl Staenz,et al.  Defining shaded spectra by model inversion for spectral unmixing of hyperspectral datasets - theory and preliminary application , 2002, IEEE International Geoscience and Remote Sensing Symposium.

[13]  Miina Rautiainen,et al.  Application of photon recollision probability in coniferous canopy reflectance simulations , 2005 .

[14]  M. Rautiainen,et al.  BRDF measurement of understory vegetation in pine forests: dwarf shrubs, lichen, and moss , 2005 .

[15]  Wenge Ni,et al.  A Coupled Vegetation-Soil Bidirectional Reflectance Model for a Semiarid Landscape , 2000 .

[16]  A. Kuusk,et al.  A Directional Multispectral Forest Reflectance Model , 2000 .

[17]  D. Randall,et al.  A Revised Land Surface Parameterization (SiB2) for Atmospheric GCMS. Part I: Model Formulation , 1996 .

[18]  Klaus I. Itten,et al.  A field goniometer system (FIGOS) for acquisition of hyperspectral BRDF data , 1999, IEEE Trans. Geosci. Remote. Sens..

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

[20]  John R. Miller,et al.  Scaling-up and model inversion methods with narrowband optical indices for chlorophyll content estimation in closed forest canopies with hyperspectral data , 2001, IEEE Trans. Geosci. Remote. Sens..

[21]  John S. Iiames,et al.  Leaf Area Index (LAI) Change Detection Analysis on Loblolly Pine (Pinus taeda) Following Complete Understory Removal , 2008 .

[22]  Sylvain G. Leblanc,et al.  Investigation of directional reflectance in boreal forests with an improved four-scale model and airborne POLDER data , 1999, IEEE Trans. Geosci. Remote. Sens..

[23]  A. Strahler,et al.  Recent advances in geometrical optical modelling and its applications , 2000 .

[24]  Eleonora P. Zege,et al.  Reflective properties of natural snow: approximate asymptotic theory versus in situ measurements , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[25]  P. Crill,et al.  Spectral reflectance measurements of boreal wetland and forest mosses , 1997 .

[26]  T. Eck,et al.  Characterization of the reflectance anisotropy of three boreal forest canopies in spring-summer , 1999 .

[27]  Y. Knyazikhin,et al.  Validation and intercomparison of global Leaf Area Index products derived from remote sensing data , 2008 .

[28]  John R. Miller,et al.  Four-scale linear model for anisotropic reflectance (FLAIR) for plant canopies. II. validation and inversion with CASI POLDER, and PARABOLA data at BOREAS , 2002, IEEE Trans. Geosci. Remote. Sens..

[29]  Jan Pisek,et al.  Algorithm for global leaf area index retrieval using satellite imagery , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[30]  Fraser Gemmell,et al.  Testing the Utility of Multi-angle Spectral Data for Reducing the Effects of Background Spectral Variations in Forest Reflectance Model Inversion , 2000 .

[31]  A. Strahler,et al.  Geometric-Optical Modeling of a Conifer Forest Canopy , 1985, IEEE Transactions on Geoscience and Remote Sensing.

[32]  A. Kuusk A two-layer canopy reflectance model , 2001 .

[33]  J. Pisek,et al.  Assessment of a global leaf area index product from SPOT-4 VEGETATION data over selected sites in Canada , 2007 .

[34]  A. Kuusk,et al.  Impact of understory vegetation on forest canopy reflectance and remotely sensed LAI estimates , 2006 .

[35]  C. Bacour,et al.  Variability of biome reflectance directional signatures as seen by POLDER , 2005 .

[36]  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 .

[37]  Debra P. C. Peters,et al.  Remote sensing of woody shrub cover in desert grasslands using MISR with a geometric-optical canopy reflectance model , 2008 .

[38]  S. T. Gower,et al.  Direct and Indirect Estimation of Leaf Area Index, fAPAR, and Net Primary Production of Terrestrial Ecosystems , 1999 .

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

[40]  M. Rautiainen,et al.  Multi-angular reflectance properties of a hemiboreal forest: An analysis using CHRIS PROBA data , 2008 .

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

[42]  Philip Lewis,et al.  3D modelling of forest canopy structure for remote sensing simulations in the optical and microwave domains , 2006 .

[43]  A. Rango,et al.  Mapping shrub abundance in desert grasslands using geometric-optical modeling and multi-angle remote sensing with CHRIS/Proba , 2006 .

[44]  Andres Kuusk,et al.  The performance of foliage mass and crown radius models in forming the input of a forest reflectance model: A test on forest growth sample plots and Landsat 7 ETM+ images , 2007 .

[45]  Frédéric Baret,et al.  Evaluation of the representativeness of networks of sites for the global validation and intercomparison of land biophysical products: proposition of the CEOS-BELMANIP , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[46]  S. Leblanc,et al.  A Shortwave Infrared Modification to the Simple Ratio for LAI Retrieval in Boreal Forests: An Image and Model Analysis , 2000 .

[47]  John R. Miller,et al.  Improving Clumping and LAI Algorithms Based on Multiangle Airborne Imagery and Ground Measurements , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[48]  Sylvain G. Leblanc,et al.  Multiple-scattering scheme useful for geometric optical modeling , 2001, IEEE Trans. Geosci. Remote. Sens..

[49]  Andres Kuusk,et al.  Simulation of the reflectance of ground vegetation in sub-boreal forests , 2004 .

[50]  F. R. Schiebe,et al.  Canopy attributes of desert grassland and transition communities derived from multiangular airborne imagery , 2003 .

[51]  Michel M. Verstraete,et al.  Toward a direct comparison of field and laboratory goniometer measurements , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[52]  A. Rango,et al.  Modelling the reflectance anisotropy of Chihuahuan Desert grass–shrub transition canopy–soil complexes , 2004 .

[53]  Bernard Pinty,et al.  Multi-angle Imaging SpectroRadiometer (MISR) instrument description and experiment overview , 1998, IEEE Trans. Geosci. Remote. Sens..

[54]  Frédéric Baret,et al.  Validation of global moderate-resolution LAI products: a framework proposed within the CEOS land product validation subgroup , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[55]  Jing M. Chen,et al.  Leaf chlorophyll content retrieval from airborne hyperspectral remote sensing imagery , 2008 .

[56]  Miina Rautiainen,et al.  Reduced simple ratio better than NDVI for estimating LAI in Finnish pine and spruce stands , 2004 .

[57]  C. Schaaf,et al.  Relationship of MISR RPV parameters and MODIS BRDF shape indicators to surface vegetation patterns in an Australian tropical savanna , 2008 .

[58]  M. Chopping Terrestrial applications of multiangle remote sensing , 2008 .

[59]  John R. Miller,et al.  Remote Estimation of Crop Chlorophyll Content Using Spectral Indices Derived From Hyperspectral Data , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[60]  S. Running,et al.  Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data , 2002 .

[61]  M. Rautiainen,et al.  Hot spot reflectance signatures of common boreal lichens , 2005 .

[62]  J. Ardö,et al.  Investigating the use of Landsat thematic mapper data for estimation of forest leaf area index in southern Sweden , 2003 .

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

[64]  J. Pisek,et al.  Comparison and validation of MODIS and VEGETATION global LAI products over four BigFoot sites in North America , 2007 .

[65]  S. Ganguly,et al.  Physical interpretation of the correlation between multi‐angle spectral data and canopy height , 2007 .

[66]  Ranga B. Myneni,et al.  Effect of orbital drift and sensor changes on the time series of AVHRR vegetation index data , 2000, IEEE Trans. Geosci. Remote. Sens..

[67]  Ranga B. Myneni,et al.  Assessing the information content of multiangle satellite data for mapping biomes: II. Theory , 2002 .

[68]  Oliver Sonnentag,et al.  Leaf area index measurements at Fluxnet-Canada forest sites , 2006 .