scholarly journals Detailed reconstruction of trees from terrestrial laser scans for remote sensing and radiative transfer modelling applications

2021 ◽  
Author(s):  
Růžena Janoutová ◽  
Lucie Homolová ◽  
Jan Novotný ◽  
Barbora Navrátilová ◽  
Miroslav Pikl ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Tree Species ◽  
Laser Scanning ◽  
Sensitivity Analyses ◽  
Leaf Angle ◽  
Fluorescence Signal ◽  
Canopy Reflectance ◽  
Angle Distribution ◽  
Forest Species ◽  
Transfer Modelling

Abstract This study presents a method for three-dimensional (3D) reconstruction of forest tree species that are, for instance, required for simulations of 3D canopies in radiative transfer modelling. We selected three forest species of different architecture: Norway spruce (Picea abies) and European beech (Fagus sylvatica), representatives of European production forests, and white peppermint (Eucalyptus pulchella), a common forest species of Tasmania. Each species has a specific crown structure and foliage distribution. Our algorithm for 3D model construction of a single tree is based on terrestrial laser scanning (TLS) and ancillary field measurements of leaf angle distribution, percentage of current-year and older leaves, and other parameters that could not be derived from TLS data. The algorithm comprises four main steps: i) segmentation of a TLS tree point cloud separating wooden parts from foliage, ii) reconstruction of wooden parts (trunks and branches) from TLS data, iii) biologically genuine distribution of foliage within the tree crown, and iv) separation of foliage into two age categories (for spruce trees only). The reconstructed 3D models of the tree species were used to build virtual forest scenes in the DART model and to simulate canopy optical signals, specifically: angularly anisotropic top-of-canopy reflectance (for retrieval of leaf biochemical compounds from nadir canopy reflectance signatures captured in airborne imaging spectroscopy data) and solar-induced chlorophyll fluorescence signal (for experimentally unfeasible sensitivity analyses).

scholarly journals Radiative transfer modelling reveals why canopy reflectance follows function

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Teja Kattenborn ◽  
Sebastian Schmidtlein
Keyword(s):  
Radiative Transfer ◽  
Canopy Reflectance ◽  
Transfer Modelling

scholarly journals Evaluation of the FluorWPS Model and Study of the Parameter Sensitivity for Simulating Solar-Induced Chlorophyll Fluorescence

2021 ◽  
Vol 13 (6) ◽  
pp. 1091
Author(s):  
Chiming Tong ◽  
Yunfei Bao ◽  
Feng Zhao ◽  
Chongrui Fan ◽  
Zhenjiang Li ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Radiative Transfer ◽  
High Performance ◽  
Forest Canopy ◽  
Structural Parameters ◽  
Coefficient Of Determination ◽  
Leaf Angle ◽  
Angle Distribution ◽  
Structural Factors ◽  
Area Index

Solar-induced chlorophyll fluorescence (SIF) has been used as an indicator for the photosynthetic activity of vegetation at regional and global scales. Canopy structure affects the radiative transfer process of SIF within canopy and causes the angular-dependencies of SIF. A common solution for interpreting these effects is the use of physically-based radiative transfer models. As a first step, a comprehensive evaluation of the three-dimensional (3D) radiative transfers is needed using ground truth biological and hyperspectral remote sensing measurements. Due to the complexity of forest modeling, few studies have systematically investigated the effect of canopy structural factors and sun-target-viewing geometry on SIF. In this study, we evaluated the capability of the Fluorescence model with the Weighted Photon Spread method (FluorWPS) to simulate at-sensor radiance and SIF at the top of canopy, and identified the influence of the canopy structural factors and sun-target-viewing geometry on the magnitude and directional response of SIF in deciduous forests. To evaluate the model, a 3D forest scene was first constructed from Goddard’s LiDAR Hyperspectral and Thermal (G-LiHT) LiDAR data. The reliability of the reconstructed scene was confirmed by comparing the calculated leaf area index with the measured ones from the scene, which resulted in a relative error of 3.5%. Then, the performance of FluorWPS was evaluated by comparing the simulated at-sensor radiance spectra with the spectra measured from the DUAL and FLUO spectrometer of HyPlant. The radiance spectra simulated by FluorWPS agreed well with the measured spectra by the two high-performance imaging spectrometers, with a coefficient of determination (R2) of 0.998 and 0.926, respectively. SIF simulated by the FluorWPS model agreed well with the values of the DART model. Furthermore, a sensitivity analysis was conducted to assess the effect of the canopy structural parameters and sun-target-viewing geometry on SIF. The maximum difference of the total SIF can be as large as 45% and 47% at the wavelengths of 685 nm and 740 nm for different foliage area volume densities (FAVDs), and 48% and 46% for fractional vegetation covers (FVCs), respectively. Leaf angle distribution has a markedly influence on the magnitude of SIF, with a ratio of emission part to SIF range from 0.48 to 0.72. SIF from the grass layer under the tree contributed 10%+ more to the top of canopy SIF even for a dense forest canopy (FAVD = 3.5 m−1, FVC = 76%). The red SIF at the wavelength of 685 nm had a similar shape to the far-red SIF at a wavelength of 740 nm but with higher variability in varying illumination conditions. The integration of the FluorWPS model and LiDAR modeling can greatly improve the interpretation of SIF at different scales and angular configurations.

Identifying Crop Leaf Angle Distribution Based on Two-Temporal and Bidirectional Canopy Reflectance

2006 ◽  
Vol 44 (12) ◽  
pp. 3601-3609 ◽  
Author(s):  
Wenjiang Huang ◽  
Zheng Niu ◽  
Jihua Wang ◽  
Liangyun Liu ◽  
Chunjiang Zhao ◽  
...  
Keyword(s):  
Leaf Angle ◽  
Canopy Reflectance ◽  
Angle Distribution ◽  
Leaf Angle Distribution

scholarly journals Retrieving Corn Canopy Leaf Area Index from Multitemporal Landsat Imagery and Terrestrial LiDAR Data

2019 ◽  
Vol 11 (5) ◽  
pp. 572 ◽  
Author(s):  
Wei Su ◽  
Jianxi Huang ◽  
Desheng Liu ◽  
Mingzheng Zhang
Keyword(s):  
Laser Scanning ◽  
Landsat Imagery ◽  
Terrestrial Laser Scanning ◽  
Distribution Functions ◽  
Leaf Angle ◽  
Angle Distribution ◽  
Area Index ◽  
Leaf Angle Distribution ◽  
Modis Lai

Leaf angle is a critical structural parameter for retrieving canopy leaf area index (LAI) using the PROSAIL model. However, the traditional method using default leaf angle distribution in the PROSAIL model does not capture the phenological dynamics of canopy growth. This study presents a LAI retrieval method for corn canopies using PROSAIL model with leaf angle distribution functions referred from terrestrial laser scanning points at four phenological stages during the growing season. Specifically, four inferred maximum-probability leaf angles were used in the Campbell ellipsoid leaf angle distribution function of PROSAIL. A Lookup table (LUT) is generated by running the PROSAIL model with inferred leaf angles, and the cost function is minimized to retrieve LAI. The results show that the leaf angle distribution functions are different for the corn plants at different phenological growing stages, and the incorporation of derived specific corn leaf angle distribution functions distribute the improvement of LAI retrieval using the PROSAIL model. This validation is done using in-situ LAI measurements and MODIS LAI in Baoding City, Hebei Province, China, and compared with the LAI retrieved using default leaf angle distribution function at the same time. The root-mean-square error (RMSE) between the retrieved LAI on 4 September 2014, using the modified PROSAIL model and the in-situ measured LAI was 0.31 m2/m2, with a strong and significant correlation (R2 = 0.82, residual range = 0 to 0.6 m2/m2, p < 0.001). Comparatively, the accuracy of LAI retrieved results using default leaf angle distribution is lower, the RMSE of which is 0.56 with R2 = 0.76 and residual range = 0 to 1.0 m2/m2, p < 0.001. This validation reveals that the introduction of inferred leaf angle distributions from TLS data points can improve the LAI retrieval accuracy using the PROSAIL model. Moreover, the comparations of LAI retrieval results on 10 July, 26 July, 19 August and 4 September with default and inferred corn leaf angle distribution functions are all compared with MODIS LAI products in the whole study area. This validation reveals that improvement exists in a wide spatial range and temporal range. All the comparisons demonstrate the potential of the modified PROSAIL model for retrieving corn canopy LAI from Landsat imagery by inferring leaf orientation from terrestrial laser scanning data.

scholarly journals Bi-Hemispherical Canopy Reflectance Model with Surface Heterogeneity Effects for the Estimation of LAI and fAPAR from MODIS White-Sky Spectral Albedo Data

2021 ◽  
Vol 13 (10) ◽  
pp. 1976
Author(s):  
Wouter Verhoef
Keyword(s):  
Optical Properties ◽  
Material Properties ◽  
Land Surface ◽  
Spatial Coherence ◽  
Surface Heterogeneity ◽  
Leaf Angle ◽  
Canopy Reflectance ◽  
Angle Distribution ◽  
Area Index ◽  
Leaf Canopy

Bi-hemispherical reflectance (BHR), in the land surface research community also known as “white-sky albedo”, is independent of the directions of incidence and viewing. For vegetation canopies, it is also nearly independent of the leaf angle distribution, and therefore it can be considered an optical quantity that is only dependent on material properties. For the combination leaf canopy and soil background, the most influential material properties are the canopy LAI (leaf area index), optical properties of the leaves, and soil brightness. When the leaf and soil optical properties are known or assumed, one may estimate the canopy LAI from its white-sky spectral albedo. This is also because a simple two-stream radiative transfer (RT) model is available for the BHR of the leaf canopy and soil combination. In this contribution, crown clumping and lateral linear mixing effects are incorporated in this model. A new procedure to estimate soil brightness is introduced here, even under a moderate layer of green vegetation. The procedure uses the red and NIR spectral bands. A MODIS white-sky albedo product at a spatial resolution of 0.05° is used as a sample input to derive global maps of LAI, soil brightness, and fAPAR at the local moments of minimum and maximum NDVI over a 20-year period. These maps show a high degree of spatial coherence and demonstrate the possible utility of products that can be generated with little effort by using a direct LUT technique.

scholarly journals Influence of 3D Spruce Tree Representation on Accuracy of Airborne and Satellite Forest Reflectance Simulated in DART

Forests ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 292 ◽  
Author(s):  
Růžena Janoutová ◽  
Lucie Homolová ◽  
Zbyněk Malenovský ◽  
Jan Hanuš ◽  
Nicolas Lauret ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Radiative Transfer ◽  
High Performance ◽  
Laser Scanning ◽  
Coniferous Forest ◽  
Canopy Structure ◽  
Remote Sensing Data ◽  
Turbid Medium ◽  
Canopy Reflectance ◽  
Simple Tree

Advances in high-performance computer resources and exploitation of high-density terrestrial laser scanning (TLS) data allow for reconstruction of close-to-reality 3D forest scenes for use in canopy radiative transfer models. Consequently, our main objectives were (i) to reconstruct 3D representation of Norway spruce (Picea abies) trees by deriving distribution of woody and foliage elements from TLS and field structure data and (ii) to use the reconstructed 3D spruce representations for evaluation of the effects of canopy structure on forest reflectance simulated in the Discrete Anisotropic Radiative Transfer (DART) model. Data for this study were combined from two spruce research sites located in the mountainous areas of the Czech Republic. The canopy structure effects on simulated top-of-canopy reflectance were evaluated for four scenarios (10 × 10 m scenes with 10 trees), ranging from geometrically simple to highly detailed architectures. First scenario A used predefined simple tree crown shapes filled with a turbid medium with simplified trunks and branches. Other three scenarios used the reconstructed 3D spruce representations with B detailed needle shoots transformed into turbid medium, C with simplified shoots retained as facets, and D with detailed needle shoots retained as facets D. For the first time, we demonstrated the capability of the DART model to simulate reflectance of complex coniferous forest scenes up to the level of a single needle (scenario D). Simulated bidirectional reflectance factors extracted for each scenario were compared with actual airborne hyperspectral and space-borne Sentinel-2 MSI reflectance data. Scenario A yielded the largest differences from the remote sensing observations, mainly in the visible and NIR regions, whereas scenarios B, C, and D produced similar results revealing a good agreement with the remote sensing data. When judging the computational requirements for reflectance simulations in DART, scenario B can be considered as most operational spruce forest representation, because the transformation of 3D shoots in turbid medium reduces considerably the simulation time and hardware requirements.

scholarly journals Simulations of Leaf BSDF Effects on Lidar Waveforms

2020 ◽  
Vol 12 (18) ◽  
pp. 2909
Author(s):  
Benjamin D. Roth ◽  
Adam A. Goodenough ◽  
Scott D. Brown ◽  
Jan A. van Aardt ◽  
M. Grady Saunders ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Radiative Transfer ◽  
Forest Canopy ◽  
Near Infrared ◽  
Difficult Problem ◽  
Leaf Angle ◽  
Lidar Data ◽  
Angle Distribution ◽  
Visible Wavelengths ◽  
Leaf Angle Distribution

Establishing linkages between light detection and ranging (lidar) data, produced from interrogating forest canopies, to the highly complex forest structures, composition, and traits that such forests contain, remains an extremely difficult problem. Radiative transfer models have been developed to help solve this problem and test new sensor platforms in a virtual environment. Many forest canopy studies include the major assumption of isotropic (Lambertian) reflecting and transmitting leaves or non-transmitting leaves. Here, we study when these assumptions may be valid and evaluate their associated impacts/effects on the lidar waveform, as well as its dependence on wavelength, lidar footprint, view angle, and leaf angle distribution (LAD), by using the Digital Imaging and Remote Sensing Image Generation (DIRSIG) remote sensing radiative transfer simulation model. The largest effects of Lambertian assumptions on the waveform are observed at visible wavelengths, small footprints, and oblique interrogation angles relative to the mean leaf angle. For example, a 77% increase in return signal was observed with a configuration of a 550 nm wavelength, 10 cm footprint, and 45° interrogation angle to planophile leaves. These effects are attributed to (i) the bidirectional scattering distribution function (BSDF) becoming almost purely specular in the visible, (ii) small footprints having fewer leaf angles to integrate over, and (iii) oblique angles causing diminished backscatter due to forward scattering. Non-transmitting leaf assumptions have the greatest error for large footprints at near-infrared (NIR) wavelengths. Regardless of leaf angle distribution, all simulations with non-transmitting leaves with a 5 m footprint and 1064 nm wavelength saw around a 15% reduction in return signal. We attribute the signal reduction to the increased multiscatter contribution for larger fields of view, and increased transmission at NIR wavelengths. Armed with the knowledge from this study, researchers will be able to select appropriate sensor configurations to account for or limit BSDF effects in forest lidar data.

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