Forest parameter estimation by means of Monte-Carlo simulations with experimental considerations – Estimation of multiple reflections among trees depending on forest parameters

Ding, Yaliu; Arai, Kohei

doi:10.1016/j.asr.2008.05.010

Cited by 9 publications

(6 citation statements)

References 8 publications

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“…Their study differs because they estimated the multiple scattering as the difference between the measured spectra and the linear combination of endmembers [21], in which the coefficients are estimated by using least square error approach. Ding and Arai [22] suggested that multiple scattering decreases with tree interdistance, and thus increases with tree density, which is similar to the results in the current study. In addition, they recorded the number of photons in multiple scattering rather than the radiance of those photons, which is also similar to the current study.…”

Section: A Discussion Of Resultssupporting

confidence: 92%

“…This simplification seems practically reasonable; however, it has not yet been tested and verified, because separation of the second-order scattering from the total multiple scattering is challenging. Moreover, recent studies have found that multiple scattering depends on the height and shape of vegetation canopies, the distance between vegetation canopies, and the wavelength used [7], [22], [23]. These findings suggest that the contribution of the second-order scattering to the total multiple scattering could change with density and structural parameters of plants, as well as spectral wavelength.…”

Section: Introductionmentioning

confidence: 90%

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Assessment of Multiple Scattering in the Reflectance of Semiarid Shrublands

Jian‐min

Cao

Chen

et al. 2015

IEEE Trans. Geosci. Remote Sensing

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Multiple scattering within a mixed pixel results in a nonlinear effect on the measured spectra in remotely sensed imagery. This study provides a quantitative assessment of multiple scattering in the reflectance of semiarid shrublands and explores its relationship to the characteristics of shrubs (density and height) and imaging parameters (wavelength and viewing angles). Field measurements were conducted at the southern fringe of the Otindag Sandy Land in China. A Monte Carlo ray tracing model, the Forest LIGHT interaction model (FLIGHT), was applied to simulate the multiple scattering results. FLIGHT simulation results were first evaluated against field measurements and then compared with a Landsat-8 OLI image. Results show that: 1) the contribution of multiple scattering to the spectra of a scene increases linearly with the fractional cover of vegetation and crown height; 2) in general, multiple scattering has a stronger effect on the near-infrared (NIR) domain than on the visible bands; 3) shadows significantly strengthen the multiple scattering effect, specifically within the visible bands; and 4) 80 to 100% of the total multiple scattering is caused by the second-order scattering within the visible bands and 60% to 90% within the NIR band. This study helps to improve our understanding of the multiple scattering effect and to select between linear and nonlinear spectral unmixing models to solve the abundances of shrubs and soil in mixed pixels.Index Terms-Multiple scattering effect, nonlinear spectral mixture analysis (NSMA), spectral unmixing, the Forest LIGHT interaction model (FLIGHT).

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Section: A Discussion Of Resultssupporting

confidence: 92%

Section: Introductionmentioning

confidence: 90%

Assessment of Multiple Scattering in the Reflectance of Semiarid Shrublands

Jian‐min

Cao

Chen

et al. 2015

IEEE Trans. Geosci. Remote Sensing

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“…Monteith (1965) observed that when leaves form the canopy, radiation is trapped between the leaves by multiple reflections, and the amount of trapping increases with the irregularity of the surface. Ding and Arai (2009) also found that the multiple reflections were greatly dependent on forest parameters, including the tree inter-distance, species, crown types and crown shapes. In addition, the spectral reflectance of vegetation was also still dependent on the proportion of different components, pigmentation, nutritional status, forest age, colour, water content, among other factors (Roy, 1989).…”

Section: Discussionmentioning

confidence: 94%

Impact of understorey on overstorey leaf area index estimation from optical remote sensing in five forest types in northeastern China

Liu

et al. 2014

Agricultural and Forest Meteorology

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“…Prova disso é que o MMC tem sido uma ferramenta essencial em diversas áreas da ciência, dentre elas: economia [6]; medicina [7]; medicina nuclear [8]; biologia [9]; ecologia [10,11]; física do clima [12]; climatologia [13,14]; engenharias [15,16]; modelagem de colisões veiculares [17][18][19][20].…”

Section: Método De Monte Carlounclassified

Análise probabilística de colisões veiculares pelo método de Monte Carlo

Carvalho¹,

Armigliato²,

Almeida³

et al. 2016

Rev. Bras. Crimin.

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ResumoEste trabalho apresenta um modelo para análise probabilística de perícias de colisão de veículos automotores, apresentando um modelo computacional flexível para avaliação da confiabilidade por simulação Monte Carlo. Os procedimentos desenvolvidos buscaram a representação estatística dos parâmetros ambientais e psicomotores, tais como coeficientes de atrito e ritmo de Reação, em uma simulação, com 10.000 iterações, da confiabilidade em um modelo bidimensional aplicado a um estudo de caso de colisão frontal envolvendo dois veículos de passeio, obtendo intervalos unilaterais e bilaterais para as variáveis estudadas. AbstractThis paper presents a model for probabilistic analysis skills collision of motor vehicles, featuring a flexible computational model for the evaluation of reliability by Monte Carlo simulation. The developed procedures sought statistical representation of environmental and psychomotor parameters such as friction coefficient and reaction rate in a simulation with 10,000 iterations, reliability in a twodimensional model applied to a frontal collision case study involving two vehicles, obtaining unilateral and bilateral ranges for the variables studied.

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Forest parameter estimation by means of Monte-Carlo simulations with experimental considerations – Estimation of multiple reflections among trees depending on forest parameters

Cited by 9 publications

References 8 publications

Assessment of Multiple Scattering in the Reflectance of Semiarid Shrublands

Assessment of Multiple Scattering in the Reflectance of Semiarid Shrublands

Impact of understorey on overstorey leaf area index estimation from optical remote sensing in five forest types in northeastern China

Análise probabilística de colisões veiculares pelo método de Monte Carlo

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