2006AN ANGULAR INDEX TO INDICATE SURFACE HETEROGENEOUS

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AN ANGULAR INDEX TO INDICATE SURFACE HETEROGENEOUS BEHAVIORS FROM MODIS

Ziti Jiao a,b, C.B. Schaaf b , F. Gao c, A.H. Strahler b, X. Li a,b, J. Wang a, J. Liu d a State Key Laboratory of Remote Sensing Science (Beijing Normal University)

b Department of Geography and Environment, Boston University, Boston, MA 02215, USA

c NASA GSFC, Greenbelt and ERT Inc., MD 20771, USA

d I.M. Systems Group, 3401 Bexhill Place, Kensington, Maryland 20895ˈUSA

ABSTRACT An anisotropic flat index (AFX) is among the operational BRDF and albedo products offered in both the V004 and V005 reprocessed versions. We examine this BRDF shape indicator with 20 ground multiangular data sets as well as MODIS satellite samples, and find that the AFX routinely captures the BRDF shape. An AFX < 1.0 indicates a dome shaped anisotropic pattern with prominent backscatter peak reflectances, and strong retro solar view angle (hotspot) maximum reflectances; an AFX = 1.0 approximately indicates a Lambertian surface; and an AFX > 1.0 corresponds to a bowl shaped anisotropy pattern. For green vegetation, the BRDF shape is related to canopy architecture. Therefore, the behavior of the AFX provides an opportunity to infer canopy structure of the surface cover that produces the anisotropic effect.

Index Terms—MODIS, BRDF, Anisotropic Flat Index, BRDF shape indicator, Vegetation structure

1. INTRODUCTION Various efforts have attempted to construct anisotropic indexes from anisotropic reflectance to detect vegetation structural change or distinguish different land cover types. These anisotropic indexes were often classified into reflectance-based indexes and model parameter-based indexes. Sandmeier et al [1] proposed an anisotropic factor (ANIF) and an anisotropic index (ANIX) to explore physical mechanisms of hyperspectral BRDF effect and their relationship to land cover types using typical ground measurements. Roujean et al. [2] established a simple vertical difference vegetation index with isotropic parameters in red and NIR band to produce global maps of vegetation parameters. D’Entremont et al. [3] investigated a normalized difference f-index (NDFI) between volumetric and geometric parameters. Doll et al. [4] however found that the NDFI was not very promising for urban mapping. Gao et al. [5] proposed a structural scattering index (SSI) based on red geometric and NIR volumetric parameter of the

RTLSR BRDF model, and showed that the SSI could be used to distinguish different land cover types or to detect structural changes. A parameter k estimated by the inversion of the RPV model has been used to identify the very probable presence of a structurally heterogeneous surface [6]. Chen et al. [7] and Leblanc et al. [8] have proposed an angular index based on the Normalized Difference between Hotspot and Dark spot (NDHD) and found that the NDHD is linearly related to a foliage clumping index for different vegetation types based on a simulation of four scale BRDF model. Canadian and global clumping index maps were produced with POLDER data based on this linear relationship between NHDH and clumping index. In this paper, we examine an anisotropic flat index, which is defined as simple ratio of the white sky albedo (WSA) to the isotropic parameter as: )(/)()(// /ISOfWSAAFX (1)

By simply deriving from kernel-driven semiempirical BRDF models [9, 10], we can acquire another form of the AFX as follows:

geokisogeovolkisovolHffHffAFX__*)()(*)(

)(1)(

//󰀎/

/󰀎 /

(2)

Where volkH_ and geokH_ are bihemispherical integrals of the

BRDF model RossThick and LiSparse reciprocal kernel, and are precomputed mathematical quantities. Here volkH_ =

0.189184, and geokH_ = -1.377622 respectively. Inspection

of equation (2) indicates that the AFX varies around unit one depending on kernel weights. When volumetric scattering is dominant, the AFX will be greater than one; when the AFX will be less than one, the geometric-optical surface scattering dominates; otherwise they will approximately equal to one representing a Lambertian surface.

2. ANALYSIS WITH GROUND BRDF DATA SETS In this section, we analyze the AFX with 20 ground BRDF data sets. These datasets were collected by numerous

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