Comparison of the Noise Robustness of FVC Retrieval Algorithms Based on Linear Mixture Models

Abstract

The fraction of vegetation cover (FVC) is often estimated by unmixing a linear mixture model (LMM) to assess the horizontal spread of vegetation within a pixel based on a remotely sensed reflectance spectrum. The LMM-based algorithm produces results that can vary to a certain degree, depending on the model assumptions. For example, the robustness of the results depends on the presence of errors in the measured reflectance spectra. The objective of this study was to derive a factor that could be used to assess the robustness of LMM-based algorithms under a two-endmember assumption. The factor was derived from the analytical relationship between FVC values determined according to several previously described algorithms. The factor depended on the target spectra, endmember spectra, and choice of the spectral vegetation index. Numerical simulations were conducted to demonstrate the dependence and usefulness of the technique in terms of robustness against the measurement noise.

Tri-Camera High-Speed Videogrammetry for Three-Dimensional Measurement of Laminated Rubber Bearings Based on the Large-Scale Shaking Table

“…In contrast to a point or a line object with two degrees of freedom (DOF), a circular target which provides five DOFs can ensure the robustness of target detection and tracking, and thus has been widely used in many close range photogrammetric applications [24,30]. Much effort has been made towards the ellipse detection algorithms such as Template Matching (TM), Hough transform, Wavelet transform, geometry symmetry and ellipse geometric attributes [31][32][33][34]. The most commonly used Hough Transform method for ellipse detection [35] is fairly robust when detecting an ellipse.…”

Influences of band-correlated noise on FVC by VI-isoline based LMM: characteristic behavior of propagated error

“…[4][5][6][7][8] The objective is to clarify the mechanism of error propagation from target spectrum and endmember spectra to FVC value. In this study, we use an LMM with the two-band VI as a constraint, called VI-isoline based LMM.…”

Soil isoline equations in the red–NIR reflectance subspace describe a heterogeneous canopy

“…This study attempts to do this using a parameter called the fraction of vegetation cover (FVC). 4,9,[32][33][34][35] This paper describes the derivation of the soil isoline equations with consideration for the FVC. The objectives of this study are (1) to derive the soil isoline equations without truncating the polynomials; (2) to approximate the derived isoline equations for the sake of practicality by truncating the higher-order terms to obtain an analytical form of the red and NIR reflectance relationships under conditions of a constant soil reflectance spectrum; and (3) to validate the derived results by conducting a set of numerical experiments using a radiative transfer model to describe the coupling between the leaf and canopy layer system.…”

“…In general, knowledge of the relationship between two reflectances (isoline) plays an important role in an analysis of the performance of a retrieval algorithm. [9][10][11] In the field of remote land sensing, vegetation isolines 12 have been accepted as fundamental to VI equation models, especially given the uncertainties that can result from parameters unrelated to vegetation. Variations in the soil brightness beneath a canopy can significantly disrupt *Address all correspondence to: Hiroki Yoshioka, E-mail: yoshioka@ist.aichi-pu.ac.jp the VI, and such variations have attracted significant attention over time.…”