Quantitative forest canopy structure assessment using an inverted geometric‐optical model and up‐scaling

Zeng, Yuan; Schaepman, Michael E.; Wu, Bingfang; Clevers, J.G.P.W.; Bregt, A.K.

doi:10.1080/01431160802395276

Cited by 29 publications

(15 citation statements)

References 37 publications

(40 reference statements)

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“…It reveals that PT is a key factor to determine the canopy reflectance. The previous studies used to combine ZT and ZG as one shadowed component [14], [22]. 6.…”

Section: Comparison With the Observed Canopy Reflectancementioning

confidence: 99%

“…The Li-Strahler model is a pioneer GO model in describing the bidirectional reflectance factor (BRF) of canopy using the area ratios of the four scene components. The model has been widely used for retrieving canopy parameters [14], such as leaf area index (LAI). However, the model may lead uncertainties in BRF modeling because the sunlight and view angles rather than the complex canopy structure are better considered.…”

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confidence: 99%

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GOST2: The Improvement of the Canopy Reflectance Model GOST in Separating the Sunlit and Shaded Leaves

Fan

Liu

2015

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Accurately simulating the area ratios of the sunlit and shaded foliage in multiple-view angles presents a challenge in developing a geometric-optical (GO) model. GOST model by Fan et al.[1] proposed a high computationally demanding ray tracing method on this issue. In order to relax the computational restriction, a new hybrid canopy reflectance model GOST2 based on GOST is developed with a "ray tracing + GO" method, which is used for simulating the area ratios of the sunlit and shaded foliage. GOST2 shows the explicitly physical mechanism and has the capability in modeling the area ratios of the sunlit and shaded foliage on slopes. The area ratios of the four scene components of the five GO models, such as GOST2, GOST, the Li-Strahler model, the four-scale model, and Unified, are quantitatively evaluated. The canopy reflectances by the five GO models and the three-dimensional virtual canopy model are validated by the observed reflectance. It indicates that GOST2 is both reliable and computationally undemanding canopy reflectance model.

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“…It reveals that PT is a key factor to determine the canopy reflectance. The previous studies used to combine ZT and ZG as one shadowed component [14], [22]. 6.…”

Section: Comparison With the Observed Canopy Reflectancementioning

confidence: 99%

mentioning

confidence: 99%

GOST2: The Improvement of the Canopy Reflectance Model GOST in Separating the Sunlit and Shaded Leaves

Fan

Liu

2015

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…Nevertheless, physical models have been used for CC estimation more successfully in other biomes (e.g. Jasinski 1996, Woodcock et al 1997, Zeng et al 2009).…”

Section: Remote Sensingmentioning

confidence: 99%

Estimation of boreal forest canopy cover with ground measurements, statistical models and remote sensing

Korhonen¹

2011

Diss. For.

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“…In general, identifying individual species reliably using satellite-based and aerial imagery is challenging due to the difficulties of choosing and detecting optimal spectral wavelengths to differentiate the target species from others (which may only be possible at certain times of year), and controlling for the effects of vegetation structural characteristics (Chopping, 2011;Kempeneers et al, 2008;Pisek et al, 2011;Zeng et al, 2009) as well as identifying spatial associations between invasive and closely-related native species (Call and Nilsen, 2003). A number of invasive species have also been identified based on the uniqueness in leaf chemistry using both hyperspectral (Asner et al, 2008, Hestir et al, 2008Somers and Asner, 2013b) and multispectral (Becker et al, 2013;Schneider and Fernando, 2010) analyses.…”

Section: Introductionmentioning

confidence: 99%

Potential of remote sensing to predict species invasions

Rocchini

Andreo

Förster

et al. 2015

Progress in Physical Geography: Earth and Environment

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Understanding the causes and effects of species invasions is a priority in ecology and conservation biology. One of the crucial steps in evaluating the impact of invasive species is to map changes in their actual and potential distribution and relative abundance across a wide region over an appropriate time span. While direct and indirect remote sensing approaches have long been used to assess the invasion of plant species, the distribution of invasive animals is mainly based on indirect methods that rely on environmental proxies of conditions suitable for colonization by a particular species. The aim of this article is to review recent efforts in the predictive modelling of the spread of both plant and animal invasive species using remote sensing, and to stimulate debate on the potential use of remote sensing in biological invasion monitoring and forecasting. Specifically, the challenges and drawbacks of remote sensing techniques are discussed in relation to: i) developing species distribution models, and ii) studying life cycle changes and phenological variations. Finally, the paper addresses the open challenges and pitfalls of remote sensing for biological invasion studies including sensor characteristics, upscaling and downscaling in species distribution models, and uncertainty of results.

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Quantitative forest canopy structure assessment using an inverted geometric‐optical model and up‐scaling

Cited by 29 publications

References 37 publications

GOST2: The Improvement of the Canopy Reflectance Model GOST in Separating the Sunlit and Shaded Leaves

GOST2: The Improvement of the Canopy Reflectance Model GOST in Separating the Sunlit and Shaded Leaves

Estimation of boreal forest canopy cover with ground measurements, statistical models and remote sensing

Potential of remote sensing to predict species invasions

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