Estimation of LAI with the LiDAR Technology: A Review

Wang, Yao; Fang, Hongliang

doi:10.3390/rs12203457

Cited by 72 publications

(33 citation statements)

References 137 publications

(272 reference statements)

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“…The LiDAR-detected canopy height was based on the return of a laser beam by tree leaves [63]. The canopy height is the height of tree crowns which consists of treetops, branches, and more importantly, tree leaves on tops of the crowns.…”

Section: Discussionmentioning

confidence: 99%

Elevation and Distribution of Freshwater and Sewage Canals Regulate Canopy Structure and Differentiate Hurricane Damages to a Basin Mangrove Forest

Gao

2021

Remote Sensing

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The coastal mangrove forest bears important ecosystem functions and services, including the protection of shorelines and coastal communities. While coastal mangroves often suffer severe damage during storms, understanding the vulnerability and resistance of mangroves to the damage at a landscape scale is crucial for coastal mangrove management and conservation. In September 2017, two consecutive major hurricanes caused tremendous damage to the coastal mangroves in the Caribbean. By utilizing LiDAR data taken before and after the hurricanes in a basin mangrove forest in Northeast Puerto Rico, we analyzed the spatial variation of a canopy structure before the hurricanes and hurricane-induced canopy height reduction and explored possible drivers by means of spatial regressions. Regarding the canopy structure, we found that the pre-hurricane canopy height of the mangrove forest decreased with elevation and distance to the freshwater/sewage canals within the forest, and these two drivers explained 82% of variations in the mangrove canopy height. The model, thus, implies that freshwater and nutrient inputs brought by the canals tend to promote the canopy height, and mangrove trees at lower elevation are especially more advantageous. Similarly, tree densities decreased with the canopy height but increased with the elevation and the distance to the canals. We also found that this mangrove forest suffered on average a 53% canopy height reduction, reflecting mostly heavy crown defoliation and the rupture of branches. The regression, which explains 88% of spatial variation in the canopy height reduction, showed that mangroves with a higher canopy or lower density, or growing in lower elevation, or being closer to the canals suffered more damage. Our findings indicate that delivered freshwater/sewage by means of human-made canals has a strong impact on the canopy structure as well as its resistance to tropical storms. Freshwater and sewage tend to release the salinity stress and nutrient deficit and, thus, to promote the mangrove canopy height. However, the addition of freshwater and nutrients might also increase the risk of mangrove damage during the storms probably because of an altered allometry of assimilates.

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Section: Discussionmentioning

confidence: 99%

Elevation and Distribution of Freshwater and Sewage Canals Regulate Canopy Structure and Differentiate Hurricane Damages to a Basin Mangrove Forest

Gao

2021

Remote Sensing

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“…By applying Beer-Lambert's turbid medium approximation, local transmittance enables estimation of PAD and PAI. Infravoxel clumping may have caused an underestimation of LAI and PAI [77,97]. Qu et al [98] estimated the PAI of a moist tropical forest at Fazenda Cauaxi in the Paragominas Municipality of Pará State, Brazil.…”

Section: Three-dimensional (3d) Forest Reconstructionmentioning

confidence: 99%

Simulating Imaging Spectroscopy in Tropical Forest with 3D Radiative Transfer Modeling

et al. 2021

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Optical remote sensing can contribute to biodiversity monitoring and species composition mapping in tropical forests. Inferring ecological information from canopy reflectance is complex and data availability suitable to such a task is limiting, which makes simulation tools particularly important in this context. We explored the capability of the 3D radiative transfer model DART (Discrete Anisotropic Radiative Transfer) to simulate top of canopy reflectance acquired with airborne imaging spectroscopy in a complex tropical forest, and to reproduce spectral dissimilarity within and among species, as well as species discrimination based on spectral information. We focused on two factors contributing to these canopy reflectance properties: the horizontal variability in leaf optical properties (LOP) and the fraction of non-photosynthetic vegetation (NPVf). The variability in LOP was induced by changes in leaf pigment content, and defined for each pixel based on a hybrid approach combining radiative transfer modeling and spectral indices. The influence of LOP variability on simulated reflectance was tested by considering variability at species, individual tree crown and pixel level. We incorporated NPVf into simulations following two approaches, either considering NPVf as a part of wood area density in each voxel or using leaf brown pigments. We validated the different scenarios by comparing simulated scenes with experimental airborne imaging spectroscopy using statistical metrics, spectral dissimilarity (within crowns, within species, and among species dissimilarity) and supervised classification for species discrimination. The simulation of NPVf based on leaf brown pigments resulted in the closest match between measured and simulated canopy reflectance. The definition of LOP at pixel level resulted in conservation of the spectral dissimilarity and expected performances for species discrimination. Therefore, we recommend future research on forest biodiversity using physical modeling of remote-sensing data to account for LOP variability within crowns and species. Our simulation framework could contribute to better understanding of performances of species discrimination and the relationship between spectral variations and taxonomic and functional dimensions of biodiversity. This work contributes to the improved integration of physical modeling tools for applications, focusing on remotely sensed monitoring of biodiversity in complex ecosystems, for current sensors, and for the preparation of future multispectral and hyperspectral satellite missions.

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“…By applying Beer-Lambert's turbid medium approximation, local transmittance enables to estimate PAD and PAI. Infravoxel clumping may have caused an underestimation of LAI and PAI [75,94]. Qu et al [95] estimated the PAI of a moist tropical forest at Fazenda Cauaxi in the Paragominas Municipality of Pará State, Brazil.…”

Section: D Forest Reconstructionmentioning

confidence: 99%

Simulating Imaging Spectroscopy in Tropical Forest with 3D Radiative Transfer Modeling

Ebengo¹,

Boissieu²,

Vincent³

et al. 2021

Preprint

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Optical remote sensing can contribute to biodiversity monitoring and species composition mapping in tropical forests. Inferring ecological information from canopy reflectance is complex and data availability suitable to such a task is limiting, which makes simulation tools particularly important in this context. We explored the capability of the 3D radiative transfer model DART to simulate top of canopy reflectance acquired with airborne imaging spectroscopy in complex tropical forest, and to reproduce spectral dissimilarity within and among species, as well as species discrimination based on spectral information. We focused on two factors contributing to these canopy reflectance properties: the horizontal variability in leaf optical properties (LOP) and the fraction of non-photosynthetic vegetation (NPVf). The variability in LOP was induced by changes in leaf pigment content, and defined for each pixel based on a hybrid approach combining radiative transfer modeling and spectral indices. The influence of LOP variability on simulated reflectance was tested by considering variability at species, individual tree crown and pixel level. We incorporated NPVf into simulations following two approaches, either considering NPVf as a part of wood area density in each voxel or using leaf brown pigments. We validated the different scenarios by comparing simulated scenes with experimental airborne imaging spectroscopy using statistical metrics, spectral dissimilarity (within crowns, within species, and among species dissimilarity) and supervised classification for species discrimination. The simulation of NPVf based on leaf brown pigments resulted in the closest match between measured and simulated canopy reflectance. The definition of LOP at pixel level resulted in conservation of the spectral dissimilarity and expected performances for species discrimination. Our simulation framework could contribute to better understand performances for species discrimination and relationship between spectral variations and taxonomic and functional dimensions of biodiversity.

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Estimation of LAI with the LiDAR Technology: A Review

Cited by 72 publications

References 137 publications

Elevation and Distribution of Freshwater and Sewage Canals Regulate Canopy Structure and Differentiate Hurricane Damages to a Basin Mangrove Forest

Elevation and Distribution of Freshwater and Sewage Canals Regulate Canopy Structure and Differentiate Hurricane Damages to a Basin Mangrove Forest

Simulating Imaging Spectroscopy in Tropical Forest with 3D Radiative Transfer Modeling

Simulating Imaging Spectroscopy in Tropical Forest with 3D Radiative Transfer Modeling

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