Applying LiDAR to Quantify the Plant Area Index Along a Successional Gradient in a Tropical Forest of Thailand

Pimmasarn, Siriruk; Tripathi, Nimisha; Ninsawat, Sarawut; Sasaki, Nophea

doi:10.3390/f11050520

Cited by 8 publications

(5 citation statements)

References 37 publications

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“…These methods also offer the potential to map entire landscapes and regions, and will be the only way to obtain global coverage of tropical forest canopy structure. Remote sensing technologies that provide measures related to canopy structure include active sensors such as radar and lidar [33,[54][55][56], as well as sensors that rely on reflected and transmitted solar radiation such as the MODIS instrument and the Li-Cor LAI-2000. The physical principles behind all of these sensors are well known, and their capacity to indirectly estimate LAI in a variety of environments has been validated.…”

Section: Regularity Of Canopy Physical Structure Across Succession-why?mentioning

confidence: 99%

Physical structure and biological composition of canopies in tropical secondary and old-growth forests

et al. 2021

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The area of tropical secondary forests is increasing rapidly, but data on the physical and biological structure of the canopies of these forests are limited. To obtain such data and to measure the ontogeny of canopy structure during tropical rainforest succession, we studied patch-scale (5 m2) canopy structure in three areas of 18–36 year-old secondary forest in Costa Rica, and compared the results to data from old-growth forest at the same site. All stands were sampled with a stratified random design with complete harvest from ground level to the top of the canopy from a modular portable tower. All canopies were organized into distinct high- and low-leaf-density layers (strata), and multiple strata developed quickly with increasing patch height. The relation of total Leaf Area Index (LAI, leaf area per area of ground) to patch canopy height, the existence of distinct high and low leaf- density layers (strata and free air spaces), the depth and LAI of the canopy strata and free air spaces, and the relation of the number of strata to patch canopy height were remarkably constant across the entire successional gradient. Trees were the most important contributor to LAI at all stages, while contribution of palm LAI increased through succession. We hypothesize that canopy physical structure at the patch scale is driven by light competition and discuss how this hypothesis could be tested. That canopy physical structure was relatively independent of the identity of the species present suggests that canopy physical structure may be conserved even as canopy floristics shift due to changing climate.

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Section: Regularity Of Canopy Physical Structure Across Succession-why?mentioning

confidence: 99%

Physical structure and biological composition of canopies in tropical secondary and old-growth forests

et al. 2021

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“…Here, we used a uniform 1 × 1 × 1 m voxel size matching with the spatial resolution and pixel grid of the imaging spectroscopy acquisition. Some post-processing steps are required to adjust the raw 3D distribution of PAD obtained from AMAPvox [69][70][71][72] and ensure accurate description of horizontal and vertical structure. These adjustments were performed as follows:…”

Section: Definition Of 3d Structure Of the Canopymentioning

confidence: 99%

“…They reported a mean PAI of 6.94 m 2 /m 2 . Another study was conducted by Pimmasarn et al [69] in Khao Yai National Park in central Thailand. They obtained a mean PAI of 8.02 m 2 /m 2 .…”

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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“…Here, we used a uniform 1 x 1 x 1 m voxel size matching with the spatial resolution and pixel grid of the imaging spectroscopy acquisition. Some post-processing steps are required to adjust the raw 3D distribution of PAD obtained from AMAPvox [67][68][69][70] and ensure accurate description of horizontal and vertical structure. These adjustments were performed as follows:…”

Section: Definition Of 3d Structure Of the Canopymentioning

confidence: 99%

“…They reported a mean PAI of 6.94 m²/m². Another study was conducted by Pimmasarn et al [67] in Khao Yai National Park in central Thailand. They obtained a mean PAI of 8.02 m²/m².…”

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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Applying LiDAR to Quantify the Plant Area Index Along a Successional Gradient in a Tropical Forest of Thailand

Cited by 8 publications

References 37 publications

Physical structure and biological composition of canopies in tropical secondary and old-growth forests

Physical structure and biological composition of canopies in tropical secondary and old-growth forests

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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