An assessment study of three indirect methods for estimating leaf area density and leaf area index of individual trees

Wei, Shanshan; Yin, Tiangang; Dissegna, Maria Angela; Whittle, Andrew J.; Ow, Genevieve; Yusof, Mohamed Lokman Mohd; Lauret, Nicolas; Gastellu-Etchegorry, Jean-Philippe

doi:10.1016/j.agrformet.2020.108101

Cited by 44 publications

(25 citation statements)

References 106 publications

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“…These precautions are made to ease the distinction between the sky and the background of interest (trees) within the photos. Then, the protocol of measurement for an isolated tree originally comes from the device user manual (www.licor.com accessed on 20 January 2021) and the theory of [70], and it has already been later put into application in [71]. Due to the strong geometrical irregularities of the tree crown on a horizontal plane, a cap of 90 • is usually chosen to mask the field of view of the fisheye lens [71].…”

Section: Appendix A2 Lai-2000 Measurements To Compute Pai and Ala For Both The Linden And Magnoliamentioning

confidence: 99%

“…Then, the protocol of measurement for an isolated tree originally comes from the device user manual (www.licor.com accessed on 20 January 2021) and the theory of [70], and it has already been later put into application in [71]. Due to the strong geometrical irregularities of the tree crown on a horizontal plane, a cap of 90 • is usually chosen to mask the field of view of the fisheye lens [71]. This induces a ground measurement sampling of 8 photos, more precisely four reading pairs of photos to be taken at the four cardinal orientations, as illustrated in Figure A1a.…”

Section: Appendix A2 Lai-2000 Measurements To Compute Pai and Ala For Both The Linden And Magnoliamentioning

confidence: 99%

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Impact of Tree Crown Transmittance on Surface Reflectance Retrieval in the Shade for High Spatial Resolution Imaging Spectroscopy: A Simulation Analysis Based on Tree Modeling Scenarios

et al. 2021

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With the advancement of high spatial resolution imaging spectroscopy, an accurate surface reflectance retrieval is needed to derive relevant physical variables for land cover mapping, soil, and vegetation monitoring. One challenge is to deal with tree shadows using atmospheric correction models if the tree crown transmittance Tc is not properly taken into account. This requires knowledge of the complex radiation mechanisms that occur in tree crowns, which can be provided by coupling the physical modeling of canopy radiative transfer codes (here DART) and the 3D representations of trees. First in this study, a sensitivity analysis carried out on DART simulations with an empirical 3D tree model led to a statistical regression predicting Tc from the tree leaf area index (LAI) and the solar zenith angle with good performances (RMSE ≤ 4.3% and R2 ≥ 0.91 for LAI ≤ 4 m2.m-2). Secondly, more realistic 3D voxel-grid tree models derived from terrestrial LiDAR measurements over two trees were considered. The comparison of DART-simulated Tc from these models with the previous predicted Tc over 0.4–2.5 µm showed three main sources of inaccuracy quoted in order of importance: 1) the global tree geometry shape (mean bias up to 21.5%), 2) the transmittance fraction associated to multiple scattering, Tscat (maximum bias up to 13%), and 3) the degree of realism of the tree representation (mean bias up to 7.5%). Results showed that neglecting Tc leads to very inaccurate reflectance retrieval (mean bias > 0.04), particularly if the background reflectance is high, and in the near and shortwave infrared – NIR and SWIR – due to Tscat. The transmittance fraction associated to the non-intercepted transmitted light, Tdir, can reach up to 95% in the SWIR, and Tscat up to 20% in the NIR. Their spatial contributions computed in the tree shadow have a maximum dispersion of 27% and 8% respectively. Investigating how to approximate Tdir and Tscat spectral and spatial variability along with the most appropriate tree 3D modeling is crucial to improve reflectance retrieval in tree shadows when using atmospheric correction models.

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Section: Appendix A2 Lai-2000 Measurements To Compute Pai and Ala For Both The Linden And Magnoliamentioning

confidence: 99%

Section: Appendix A2 Lai-2000 Measurements To Compute Pai and Ala For Both The Linden And Magnoliamentioning

confidence: 99%

Impact of Tree Crown Transmittance on Surface Reflectance Retrieval in the Shade for High Spatial Resolution Imaging Spectroscopy: A Simulation Analysis Based on Tree Modeling Scenarios

et al. 2021

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“…3D radiative transferer models play an important role in assessing the uncertainty of field measurement methods [60] and were even believed to be the only means to find the proper measurement strategy for field-based validation campaigns [54]. The five fAPAR estimation schemes explored by Widlowski using the 3D radiative transfer model were only based on vertical flux [54].…”

Section: The Uncertainty Of Using Fipar As a Proxy For Faparmentioning

confidence: 99%

Comparison of Absorbed and Intercepted Fractions of PAR for Individual Trees Based on Radiative Transfer Model Simulations

Wojnowski

Wei

et al. 2021

Remote Sensing

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The fraction of absorbed photosynthetically active radiation (fAPAR) is a key parameter for estimating the gross primary production (GPP) of trees. For continuous, dense forest canopies, fAPAR, is often equated with the intercepted fraction, fIPAR. This assumption is not valid for individual trees in urban environments or parkland settings where the canopy is sparse and there are well-defined tree crown boundaries. Here, the distinction between fAPAR and fIPAR can be strongly influenced by the background and large illumination variations due to multi-scattering and shadows of buildings. This study investigates the radiative budget of PAR bands using a coupled leaf-canopy radiative transfer model (PROSPECT-DART), considering a suite of tropical tree species over a wide range of assumed leaf chlorophyll contents. The analyses simulate hyperspectral images (5 nm bandwidth) of individual tree crowns for the selected background (concrete vs. grass) and illumination conditions. We then use an artificial neural network-based method to partition sunlit vs. shaded leaves within each crown, as the latter have lower fAPAR and fIPAR values. Our results show fAPAR of sunlit leaves decreases with the ratio of diffuse to direct scene irradiance (SKYL), while SKYL has minimal influence for shaded leaves. Both fAPAR and fIPAR decrease at more oblique solar zenith angles (SZA). Higher values of fAPAR and fIPAR occur with concrete backgrounds and the influence of the background is larger at higher diffuse ratio and solar zenith angles. The results show that fIPAR is typically 6–9% higher than fAPAR, and up to 14% higher for sunlit leaves with a concrete background at SKYL = 0. The differences between the fIPAR and fAPAR also depend on the health condition of the leaves, such as chlorophyll content. This study can improve the understanding of urban individual trees fAPAR/fIPAR and facilitate the development of protocols for fAPAR field measurements.

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“…Although both parameters are related to the penetration of light though the canopy, CC includes all sizes of gaps in the field of view (FOV), while canopy cover focuses on the space between crown gaps [11]. From an ecological view, CC is more meaningful for understory light conditions, which can be used to estimate other canopy indices such as leaf area index (LAI) and foliage clumping index [12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Extracting Canopy Closure by the CHM-Based and SHP-Based Methods with a Hemispherical FOV from UAV-LiDAR Data in a Poplar Plantation

Wang

et al. 2021

Remote Sensing

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Canopy closure (CC), a useful biophysical parameter for forest structure, is an important indicator of forest resource and biodiversity. Light Detection and Ranging (LiDAR) data has been widely studied recently for forest ecosystems to obtain the three-dimensional (3D) structure of the forests. The components of the Unmanned Aerial Vehicle LiDAR (UAV-LiDAR) are similar to those of the airborne LiDAR, but with higher pulse density, which reveals more detailed vertical structures. Hemispherical photography (HP) had proven to be an effective method for estimating CC, but it was still time-consuming and limited in large forests. Thus, we used UAV-LiDAR data with a canopy-height-model-based (CHM-based) method and a synthetic-hemispherical-photography-based (SHP-based) method to extract CC from a pure poplar plantation in this study. The performance of the CC extraction methods based on an angular viewpoint was validated by the results of HP. The results showed that the CHM-based method had a high accuracy in a 45° zenith angle range with a 0.5 m pixel size and a larger radius (i.e., k = 2; R2 = 0.751, RMSE = 0.053), and the accuracy declined rapidly in zenith angles of 60° and 75° (R2 = 0.707, 0.490; RMSE = 0.053, 0.066). In addition, the CHM-based method showed an underestimate for leaf-off deciduous trees with low CC. The SHP-based method also had a high accuracy in a 45° zenith angle range, and its accuracy was stable in three zenith angle ranges (R2: 0.688, 0.674, 0.601 and RMSE = 0.059, 0.056, 0.058 for a 45°, 60° and 75° zenith angle range, respectively). There was a similar trend of CC change in HP and SHP results with the zenith angle range increase, but there was no significant change with the zenith angle range increase in the CHM-based method, which revealed that it was insensitive to the changes of angular CC compared to the SHP-based method. However, the accuracy of both methods showed differences in plantations with different ages, which had a slight underestimate for 8-year-old plantations and an overestimate for plantations with 17 and 20 years. Our research provided a reference for CC estimation from a point-based angular viewpoint and for monitoring the understory light conditions of plantations.

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An assessment study of three indirect methods for estimating leaf area density and leaf area index of individual trees

Cited by 44 publications

References 106 publications

Impact of Tree Crown Transmittance on Surface Reflectance Retrieval in the Shade for High Spatial Resolution Imaging Spectroscopy: A Simulation Analysis Based on Tree Modeling Scenarios

Impact of Tree Crown Transmittance on Surface Reflectance Retrieval in the Shade for High Spatial Resolution Imaging Spectroscopy: A Simulation Analysis Based on Tree Modeling Scenarios

Comparison of Absorbed and Intercepted Fractions of PAR for Individual Trees Based on Radiative Transfer Model Simulations

Extracting Canopy Closure by the CHM-Based and SHP-Based Methods with a Hemispherical FOV from UAV-LiDAR Data in a Poplar Plantation

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