Global sensitivity analysis of the radiative transfer model

Remote sensing (RS) provides operational monitoring of terrestrial vegetation. For optical RS, vegetation information is generally derived from surface reflectance (ρ). More generally, vegetation indices (VIs) are built on the basis of ρ as proxies for vegetation traits. At canopy level, ρ can be affected by a variety of factors, including leaf constituents, canopy structure, background reflectivity, and sun-sensor geometry. Consequently, VIs are mixtures of different information. In this study, a global sensitivity analysis (GSA) is made for several commonly used satellite-derived VIs in order to better understand the application of these VIs at large scales. The sensitivities of VIs to different parameters are analyzed on the basis of PROSPECT-SAIL (PROSAIL) radiative transfer model simulations, which apply for homogeneous canopies, and random forest (RF) learning. Specifically, combined factors such as canopy chlorophyll content (CCC) and canopy water content (CWC) are introduced in the RF-based GSA. We find that for most VIs, the leaf area index is the most influential factor, while the broad-band sensor-derived enhanced VI (EVI) exhibits a strong sensitivity to CCC, and the universal normalized VI (UNVI) is sensitive to CWC. The potential and uncertainty for the application of all the considered VIs are analyzed according to the GSA results. The results can help to improve the use of VIs in different contexts, and the RF-based GSA method can be further applied in more sophisticated situations.

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FLiES-SIF ver. 1.0: Three-dimensional radiative transfer model for estimating solar induced fluorescence

10.5194/gmd-2020-19 ◽

2020 ◽

Cited By ~ 1

Author(s):

Yuma Sakai ◽

Hideki Kobayashi ◽

Tomomichi Kato

Keyword(s):

Sensitivity Analysis ◽

Chlorophyll Fluorescence ◽

Radiative Transfer ◽

Three Dimensional ◽

Radiative Transfer Model ◽

Model Description ◽

Transfer Model ◽

Plant Canopy ◽

Parallel Layer ◽

Leaf Level

Abstract. Global terrestrial ecosystems control the atmospheric CO2 concentration through gross primary production (GPP) and ecosystem respiration processes. Chlorophyll fluorescence is one of the energy release pathways of excess incident lights in the photosynthetic process. Over the last ten years, extensive studies have been revealed that canopy scale sun-induced chlorophyll fluorescence (SIF), which potentially provides a direct pathway to link leaf level photosynthesis to global GPP, can be observed from satellites. SIF is used to infer photosynthetic capacity of plant canopy, however, it is not clear how the leaf-level SIF emission contributes to the top of canopy directional SIF. Plant canopy radiative transfer models are the useful tools to understand the causality of directional canopy SIF. One dimensional (1-D) plane parallel layer models (e.g. the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model) have been widely used and are useful to understand the general mechanisms behind the temporal and seasonal variations in SIF. However, due to the lack of complexity of the actual canopy structures, three dimensional models (3-D) have a potential to delineate the realistic directional canopy SIFs. Forest Light Environmental Simulator for SIF (FLiES-SIF) version 1.0 is the 3-D Monte Carlo plant canopy radiative transfer model to understand the biological and physical mechanisms behind the SIF emission from complex forest canopies. In this model description paper, we focused on the model formulation and simulation schemes, and showed some sensitivity analysis against several major variables such as view angle and leaf area index (LAI). The simulation results show that SIF increases with LAI then saturated at LAI > 2–4 depending on the spectral wavelength. The sensitivity analysis also shows that simulated SIF radiation may decrease with LAI at higher LAI domain (LAI > 5). These phenomena are seen in certain sun and view angle conditions. This type of non-linear and non-monotonic SIF behavior to LAI is also related to spatial forest structure patterns. FLiES-SIF version 1.0 can be used to quantify the canopy SIF in various view angles including the contribution of multiple scattering which is the important component in the near infrared domain. The potential use of the model is to standardize the satellite SIF by correcting the bi-directional effect. This step will contribute to the improvement of the GPP estimation accuracy through SIF.

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How to perform global sensitivity analysis of a catchment-scale, distributed pesticide transfer model? Application to the PESHMELBA model

10.5194/gmd-2021-425 ◽

2021 ◽

Author(s):

Emilie Rouzies ◽

Claire Lauvernet ◽

Bruno Sudret ◽

Arthur Vidard

Keyword(s):

Water Quality ◽

Sensitivity Analysis ◽

Global Sensitivity Analysis ◽

Transfer Model ◽

Valuable Insight ◽

Catchment Scale ◽

Sobol Indices ◽

Global Sensitivity ◽

Sensitivity Indices ◽

The Impact

Abstract. Pesticide transfers in agricultural catchments are responsible for diffuse but major risks to water quality. Spatialized pesticide transfer models are useful tools to assess the impact of the structure of the landscape on water quality. Before considering using these tools in operational contexts, quantifying their uncertainties is a preliminary necessary step. In this study, we explored how global sensitivity analysis can be applied to the recent PESHMELBA pesticide transfer model to quantify uncertainties on transfer simulations. We set up a virtual catchment based on a real one and we compared different approaches for sensitivity analysis that could handle the specificities of the model: high number of input parameters, limited size of sample due to computational cost and spatialized output. We compared Sobol' indices obtained from Polynomial Chaos Expansion, HSIC dependence measures and feature importance measures obtained from Random Forest surrogate model. Results showed the consistency of the different methods and they highlighted the relevance of Sobol' indices to capture interactions between parameters. Sensitivity indices were first computed for each landscape element (site sensitivity indices). Second, we proposed to aggregate them at the hillslope and the catchment scale in order to get a summary of the model sensitivity and a valuable insight into the model hydrodynamical behaviour. The methodology proposed in this paper may be extended to other modular and distributed hydrological models as there has been a growing interest in these methods in recent years.

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A Global Sensitivity Analysis Toolbox to Quantify Drivers of Vegetation Radiative Transfer Models

Sensitivity Analysis in Earth Observation Modelling ◽

10.1016/b978-0-12-803011-0.00016-1 ◽

2017 ◽

pp. 319-339 ◽

Cited By ~ 2

Author(s):

J. Verrelst ◽

J.P. Rivera

Keyword(s):

Sensitivity Analysis ◽

Radiative Transfer ◽

Global Sensitivity Analysis ◽

Global Sensitivity ◽

Radiative Transfer Models ◽

Transfer Models

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Quantifying the Robustness of Vegetation Indices through Global Sensitivity Analysis of Homogeneous and Forest Leaf-Canopy Radiative Transfer Models

Remote Sensing ◽

10.3390/rs11202418 ◽

2019 ◽

Vol 11 (20) ◽

pp. 2418 ◽

Cited By ~ 6

Author(s):

Pablo Morcillo-Pallarés ◽

Juan Pablo Rivera-Caicedo ◽

Santiago Belda ◽

Charlotte De Grave ◽

Helena Burriel ◽

...

Keyword(s):

Sensitivity Analysis ◽

Radiative Transfer ◽

Global Sensitivity Analysis ◽

Vegetation Indices ◽

Landsat 8 ◽

Global Sensitivity ◽

Radiative Transfer Models ◽

Equivalent Water Thickness ◽

Input Variables ◽

Transfer Models

Vegetation indices (VIs) are widely used in optical remote sensing to estimate biophysical variables of vegetated surfaces. With the advent of spectroscopy technology, spectral bands can be combined in numerous ways to extract the desired information. This resulted in a plethora of proposed indices, designed for a diversity of applications and research purposes. However, it is not always clear whether they are sensitive to the variable of interest while at the same time, responding insensitive to confounding factors. Hence, to be able to quantify the robustness of VIs, a systematic evaluation is needed, thereby introducing a widest possible variety of biochemical and structural heterogeneity. Such exercise can be achieved with coupled leaf and canopy radiative transfer models (RTMs), whereby input variables can virtually simulate any vegetation scenario. With the intention of evaluating multiple VIs in an efficient way, this led us to the development of a global sensitivity analysis (GSA) toolbox dedicated to the analysis of VIs on their sensitivity towards RTM input variables. We identified VIs that are designed to be sensitive towards leaf chlorophyll content (LCC), leaf water content (LWC) and leaf area index (LAI) for common sensors of terrestrial Earth observation satellites: Landsat 8, MODIS, Sentinel-2, Sentinel-3 and the upcoming imaging spectrometer mission EnMAP. The coupled RTMs PROSAIL and PROINFORM were used for simulations of homogeneous and forest canopies respectively. GSA total sensitivity results suggest that LCC-sensitive indices respond most robust: for the great majority of scenarios, chlorophyll a + b content (Cab) drives between 75% and 82% of the indices’ variability. LWC-sensitive indices were most affected by confounding variables such as Cab and LAI, although the equivalent water thickness (Cw) can drive between 25% and 50% of the indices’ variability. Conversely, the majority of LAI-sensitive indices are not only sensitive to LAI but rather to a mixture of structural and biochemical variables.

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Emulation of Leaf, Canopy and Atmosphere Radiative Transfer Models for Fast Global Sensitivity Analysis

Remote Sensing ◽

10.3390/rs8080673 ◽

2016 ◽

Vol 8 (8) ◽

pp. 673 ◽

Cited By ~ 33

Author(s):

Jochem Verrelst ◽

Neus Sabater ◽

Juan Rivera ◽

Jordi Muñoz-Marí ◽

Jorge Vicent ◽

...

Keyword(s):

Sensitivity Analysis ◽

Radiative Transfer ◽

Global Sensitivity Analysis ◽

Global Sensitivity ◽

Radiative Transfer Models ◽

Leaf Canopy ◽

Transfer Models

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FLiES-SIF version 1.0: three-dimensional radiative transfer model for estimating solar induced fluorescence

Geoscientific Model Development ◽

10.5194/gmd-13-4041-2020 ◽

2020 ◽

Vol 13 (9) ◽

pp. 4041-4066

Author(s):

Yuma Sakai ◽

Hideki Kobayashi ◽

Tomomichi Kato

Keyword(s):

Sensitivity Analysis ◽

Chlorophyll Fluorescence ◽

Radiative Transfer ◽

Three Dimensional ◽

Radiative Transfer Model ◽

Model Description ◽

Transfer Model ◽

Plant Canopy ◽

Parallel Layer ◽

Leaf Level

Abstract. Global terrestrial ecosystems control the atmospheric CO2 concentration through gross primary production (GPP) and ecosystem respiration processes. Chlorophyll fluorescence is one of the energy release pathways of excess incident light in the photosynthetic process. Over the last 10 years, extensive studies have revealed that canopy-scale Sun-induced chlorophyll fluorescence (SIF), which potentially provides a direct pathway to link leaf-level photosynthesis to global GPP, can be observed from satellites. SIF is used to infer photosynthetic capacity of plant canopy; however, it is not clear how the leaf-level SIF emission contributes to the top-of-canopy directional SIF. Plant canopy radiative transfer models are useful tools to understand the mechanism of anisotropic light interactions such as scattering and absorption in plant canopies. One-dimensional (1-D) plane-parallel layer models (e.g., the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model) have been widely used and are useful to understand the general mechanisms behind the temporal and seasonal variations in SIF. However, a 1-D model does not explain the complexity of the actual canopy structures. Three-dimensional models (3-D) have a potential to delineate the realistic directional canopy SIFs. Forest Light Environmental Simulator for SIF (FLiES-SIF) version 1.0 is a 3-D Monte Carlo plant canopy radiative transfer model to understand the biological and physical mechanisms behind the SIF emission from complex forest canopies. The FLiES-SIF model is coupled with leaf-level fluorescence and a physiology module so that users are able to simulate how the changes in environmental and leaf traits as well as canopy structure affect the observed SIF at the top of the canopy. The FLiES-SIF model was designed as three-dimensional model, yet the entire modules are computationally efficient: FLiES-SIF can be easily run by moderate-level personal computers with lower memory demands and public software. In this model description paper, we focused on the model formulation and simulation schemes, and showed some sensitivity analysis against several major variables such as view angle and leaf area index (LAI). The simulation results show that SIF increases with LAI then saturated at LAI>2–4 depending on the spectral wavelength. The sensitivity analysis also shows that simulated SIF radiation may decrease with LAI at a higher LAI domain (LAI>5). These phenomena are seen in certain Sun and view angle conditions. This type of nonlinear and nonmonotonic SIF behavior towards LAI is also related to spatial forest structure patterns. FLiES-SIF version 1.0 can be used to quantify the canopy SIF in various view angles including the contribution of multiple scattering which is the important component in the near-infrared domain. The potential use of the model is to standardize the satellite SIF by correcting the bidirectional effect. This step will contribute to the improvement of the GPP estimation accuracy through SIF.

Download Full-text