Mapping forest canopy nitrogen content by inversion of coupled leaf-canopy radiative transfer models from airborne hyperspectral imagery

Wang, Zhihui; Skidmore, Andrew K.; Darvishzadeh, Roshanak

doi:10.1016/j.agrformet.2018.02.010

Cited by 83 publications

(60 citation statements)

References 111 publications

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“…Porder, Asner, & Vitousek, 2005), but also because the empirical functions are typically overfitted to the data considered in the respective study (Verrelst et al, 2015). Alternative to regressions, mechanistic radiative transfer models (RTMs) could be used in the future to avoid this problem, but research on RTM inversion to retrieve nutrient concentrations at the canopy level is still in its infancy (Wang, Skidmore, et al, 2018; but see Porder et al, 2005).…”

Section: Soil or Plant Data To Assess Nutrient Status?mentioning

confidence: 99%

Towards comparable assessment of the soil nutrient status across scales—Review and development of nutrient metrics

Sundert

Radujković

Cools

et al. 2019

Global Change Biology

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Nutrient availability influences virtually every aspect of an ecosystem, and is a critical modifier of ecosystem responses to global change. Although this crucial role of nutrient availability in regulating ecosystem structure and functioning has been widely acknowledged, nutrients are still often neglected in observational and experimental synthesis studies due to difficulties in comparing the nutrient status across sites. In the current study, we explain different nutrient‐related concepts and discuss the potential of soil‐, plant‐ and remote sensing‐based metrics to compare the nutrient status across space. Based on our review and additional analyses on a dataset of European, managed temperate and boreal forests (ICP [International Co‐operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests] Forests dataset), we conclude that the use of plant‐ and remote sensing‐based metrics that rely on tissue stoichiometry is limited due to their strong dependence on species identity. The potential use of other plant‐based metrics such as Ellenberg indicator values and plant‐functional traits is also discussed. We conclude from our analyses and review that soil‐based metrics have the highest potential for successful intersite comparison of the nutrient status. As an example, we used and adjusted a soil‐based metric, previously developed for conifer forests across Sweden, against the same ICP Forests data. We suggest that this adjusted and further adaptable metric, which included the organic carbon concentration in the upper 20 cm of the soil (including the organic fermentation‐humus [FH] layer), the C:N ratio and pHCaCl2 of the FH layer, can be used as a complementary tool along with other indicators of nutrient availability, to compare the background nutrient status across temperate and boreal forests dominated by spruce, pine or beech. Future collection and provision of harmonized soil data from observational and experimental sites is crucial for further testing and adjusting the metric.

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Section: Soil or Plant Data To Assess Nutrient Status?mentioning

confidence: 99%

Towards comparable assessment of the soil nutrient status across scales—Review and development of nutrient metrics

Sundert

Radujković

Cools

et al. 2019

Global Change Biology

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“…Since the overestimation seemed to be solely defined by the slope of the regression line, the water absorption Applied to PROSAIL spectra ( Figure 4b) the R 2 -results (0.68) are significantly lower and although model results correspond to LUT C w -values, both regression residuals and intercept do not show a systematic bias. However, within the created LUT, several parameter combinations can be considered unrealistic [63], masking or flattening the water signal due to model parameter related interference with the shape of the 970 nm absorption band. The resulting outliers and overall spread of modelled C w -values render the PROSAIL LUT unsuitable for further calibration of the model.…”

Section: Using Prospect For Calibration Of the Pwr Modelmentioning

confidence: 99%

“…Hereby, two issues interact: first, the 4SAIL model assumes a horizontally homogenous canopy, which may not be valid for complex canopy architectures and clumped vegetation through, e.g., formation in rows [65][66][67]. Second, unrealistic parameter combinations may occur in LUTs [63]. Both issues may unfavorably affect modelled reflectance in the 970 nm domain, reducing the predictive power of C w for water content information (R 2 = 0.57; Figure 4b) and rendering the PROSAIL LUT unsuitable for calibration of the presented PWR model.…”

Section: Inversion Of the Beer-lambert Law For Water Content Retrievalmentioning

confidence: 99%

Physically-Based Retrieval of Canopy Equivalent Water Thickness Using Hyperspectral Data

et al. 2018

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Quantitative equivalent water thickness on canopy level (EWT canopy ) is an important land surface variable and retrieving EWT canopy from remote sensing has been targeted by many studies. However, the effect of radiative penetration into the canopy has not been fully understood. Therefore, in this study the Beer-Lambert law is applied to inversely determine water content information in the 930 to 1060 nm range of canopy reflectance from measured winter wheat and corn spectra collected in 2015, 2017, and 2018. The spectral model was calibrated using a look-up-table (LUT) of 50,000 PROSPECT spectra. Internal model validation was performed using two leaf optical properties datasets (LOPEX93 and ANGERS). Destructive in-situ measurements of water content were collected separately for leaves, stalks, and fruits. Correlation between measured and modelled water content was most promising for leaves and ears in case of wheat, reaching coefficients of determination (R 2 ) up to 0.72 and relative RMSE (rRMSE) of 26% and in case of corn for the leaf fraction only (R 2 = 0.86, rRMSE = 23%). These findings indicate that, depending on the crop type and its structure, different parts of the canopy are observed by optical sensors. The results from the Munich-North-Isar test sites indicated that plant compartment specific EWT canopy allows us to deduce more information about the physical meaning of model results than from equivalent water thickness on leaf level (EWT) which is upscaled to canopy water content (CWC) by multiplication of the leaf area index (LAI). Therefore, it is suggested to collect EWT canopy data and corresponding reflectance for different crop types over the entire growing cycle. Nevertheless, the calibrated model proved to be transferable in time and space and thus can be applied for fast and effective retrieval of EWT canopy in the scope of future hyperspectral satellite missions.

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“…Some studies have adopted similar models to estimate

{V normalc}_{\max}^{25}

of leaves (Barnes et al, ; Dechant et al, ) and canopies (Serbin et al, ), considering that nitrogen content is a strong indicator of

{V normalc}_{\max}^{25}

(Kattge, Knorr, Raddatz, & Wirth, ; Walker et al, ). However, these empirical models are mostly only reliable in site‐specific studies (Wang, Skidmore, Darvishzadeh, & Wang, ) and face some challenges when extrapolated to broad spatial scales because of the difficulty in separating the spectral signature of nitrogen, a nonpigment constituent, from overlapping and covarying signatures of other biochemical constituents of vegetation within different landscapes (Kokaly, Asner, Ollinger, Martin, & Wessman, ). Solar‐induced fluorescence (SIF; 650–800 nm) is another remotely sensed indicator that has been used to derive

{V normalc}_{\max}^{25}

(Zhang et al, ; Zhang, Guanter, Joiner, Song, & Guan, ), considering the widely reported tight correlation between SIF and leaf photosynthesis (Yang et al, ) or GPP (Frankenberg et al, ; Guanter et al, ; Li, Xiao, & He, ).…”

Section: Introductionmentioning

confidence: 99%

Improved estimates of global terrestrial photosynthesis using information on leaf chlorophyll content

Luo

Croft

Chen

et al. 2019

Global Change Biology

117

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The terrestrial biosphere plays a critical role in mitigating climate change by absorbing anthropogenic CO2 emissions through photosynthesis. The rate of photosynthesis is determined jointly by environmental variables and the intrinsic photosynthetic capacity of plants (i.e. maximum carboxylation rate; Vnormalcmax25). A lack of an effective means to derive spatially and temporally explicit Vnormalcmax25 has long hampered efforts towards estimating global photosynthesis accurately. Recent work suggests that leaf chlorophyll content (Chlleaf) is strongly related to Vnormalcmax25, since Chlleaf and Vnormalcmax25 are both correlated with photosynthetic nitrogen content. We used medium resolution satellite images to derive spatially and temporally explicit Chlleaf, which we then used to parameterize Vnormalcmax25 within a terrestrial biosphere model. Modelled photosynthesis estimates were evaluated against measured photosynthesis at 124 eddy covariance sites. The inclusion of Chlleaf in a terrestrial biosphere model improved the spatial and temporal variability of photosynthesis estimates, reducing biases at eddy covariance sites by 8% on average, with the largest improvements occurring for croplands (21% bias reduction) and deciduous forests (15% bias reduction). At the global scale, the inclusion of Chlleaf reduced terrestrial photosynthesis estimates by 9 PgC/year and improved the correlations with a reconstructed solar‐induced fluorescence product and a gridded photosynthesis product upscaled from tower measurements. We found positive impacts of Chlleaf on modelled photosynthesis for deciduous forests, croplands, grasslands, savannas and wetlands, but mixed impacts for shrublands and evergreen broadleaf forests and negative impacts for evergreen needleleaf forests and mixed forests. Our results highlight the potential of Chlleaf to reduce the uncertainty of global photosynthesis but identify challenges for incorporating Chlleaf in future terrestrial biosphere models.

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Mapping forest canopy nitrogen content by inversion of coupled leaf-canopy radiative transfer models from airborne hyperspectral imagery

Cited by 83 publications

References 111 publications

Towards comparable assessment of the soil nutrient status across scales—Review and development of nutrient metrics

Towards comparable assessment of the soil nutrient status across scales—Review and development of nutrient metrics

Physically-Based Retrieval of Canopy Equivalent Water Thickness Using Hyperspectral Data

Improved estimates of global terrestrial photosynthesis using information on leaf chlorophyll content

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