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A Global Sensitivity Analysis of Commonly Used Satellite-Derived Vegetation Indices for Homogeneous Canopies Based on Model Simulation and Random Forest Learning
2019
Remote Sensing
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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) ...
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. ...
J.Verrelst for the contribution of the ARTMO GUI tool.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/rs11212547
fatcat:e4q77uy5xvdmhjbwoodccqf2eq
Improving the Retrieval of Forest Canopy Chlorophyll Content from MERIS Dataset by Introducing the Vegetation Clumping Index
2021
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Overall, it is concluded that include the CI, particularly the approach using forest random regression, have the potential for satellite-based forest CCC mapping at regional and global scales. ...
Firstly, the PROSPECT-D and 4-Scale models were used to simulate forest canopy spectra, and the forest CCCe including CI was found more feasible to be remotely sensed than the CCC. ...
Holly Croft from University of Toronto for her kindly help during the published field data collection. ...
doi:10.1109/jstars.2021.3082621
fatcat:z5644kpn7vbu5m7jorzato2k2e
Remote Sensing-Based Biomass Estimation
[chapter]
2016
Environmental Applications of Remote Sensing
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We present a case study that explores the capability of canopy fraction cover and digital canopy height model (DCHM) for modeling the spatial distribution of the aboveground biomass of two forests, dominated ...
In this chapter, we present a review of different models of spatial distribution of biomass and resources based on remote sensing that are widely used. ...
Regression tree and random forest are a family of tree-based models; in the first one, data are stratified into homogeneous subsets by decreasing the within-class entropy, whereas in the second one, a ...
doi:10.5772/61813
fatcat:olp4nwuqu5dy7dxlmtpzyt4xde
Forest and Crop Leaf Area Index Estimation Using Remote Sensing: Research Trends and Future Directions
2020
Remote Sensing
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Differences in canopy structure result in different sensor types (active or passive), platforms (terrestrial, airborne, or satellite), and models being appropriate for the LAI estimation of forest and ...
The ease of use of empirical models supports these as the preferred choice for forest and crop LAI estimation. ...
Empirical Models The empirical models most commonly used to estimate LAI use spectral reflectance-based parameters [103] , vegetation indices [104] , derived metrics, and machine learning methods. ...
doi:10.3390/rs12182934
fatcat:wh3p2pgq35cizailwwv4wlaqje
Estimation and Mapping of Winter Oilseed Rape LAI from High Spatial Resolution Satellite Data Based on a Hybrid Method
2017
Remote Sensing
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Based on PROSAIL (coupling of PROSPECT and SAIL) simulation datasets, nine vegetation indices (VIs) were analyzed to identify the optimal independent variables for estimating LAI values. ...
Our study indicates that based on the estimation results derived from different datasets, RFR is the optimal modeling algorithm amidst curve fitting and kNN with R 2 > 0.954 and RMSE <0.218. ...
Mansaray assisted in the preparation and revision of the manuscript; Zhenhai Li offered valuable comments on the methods and manuscript; Weiwei Liu and Jiahui Han were involved in the field experiments ...
doi:10.3390/rs9050488
fatcat:s5bh6jiad5gw5np74ispdy5kwi
Linking Land Use and Plant Functional Diversity Patterns in Sabah, Borneo, through Large-Scale Spatially Continuous Sentinel-2 Inference
2022
Land
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Functional traits (leaf water content, chlorophyll-a and -b, and leaf area index) were estimated from Sentinel-2 spectral reflectance using a pre-trained neural network on radiative transfer modeling simulations ...
By linking large-scale patterns of functional diversity as derived from satellite remote sensing to land-use information, this study indicated initial responsiveness to broad human disturbance gradients ...
The analysis was based on repeated PROSAIL simulations with random variations of the trait values while mapping the spectral responses and the correlation between Sentinel-2's spectral bands and trait ...
doi:10.3390/land11040572
fatcat:fp4fih3iujg6dg6al6u5u6d45e
A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems
2014
International Journal of Digital Earth
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This paper provides a survey of current biomass estimation methods using remote sensing data and discusses four critical issuescollection of field-based biomass reference data, extraction and selection ...
This literature survey has indicated the limitations of using single-sensor data for biomass estimation and the importance of integrating multi-sensor/scale remote sensing data to produce accurate estimates ...
Cycling in Forest Ecosystems and Carbon Sequestration at Zhejiang A&F University, and the Center for Global Change and Earth Observations at Michigan State University. ...
doi:10.1080/17538947.2014.990526
fatcat:bkc3syq3pfgzxkawig2pog7i3y
Evaluating SAR-optical sensor fusion for aboveground biomass estimation in a Brazilian tropical forest
2019
Annals of Forest Research
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The aim of the present study is to evaluate the potential of C-band SAR data from the Sentinel-1/2 instruments and machine learning algorithms for the estimation of forest above ground forest biomass ( ...
The addition of texture and optical data provided a noticeable improvement (3%) over models with SAR backscatter only. The best model performance was achieved with the Random Tree algorithm. ...
Data acquired with financial support from the US Agency for International Development (USAID) and the US Department of State (USDS) and with technical support from the US Forest Service. ...
doi:10.15287/afr.2018.1267
fatcat:wyuyagd3b5a3vizn5spsg2akk4
Towards scalable estimation of plant functional diversity from Sentinel-2: In-situ validation in a heterogeneous (semi-)natural landscape
2021
Remote Sensing of Environment
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We thank Altino Geraldes, Joao Carlos Azevedo, and the local farmers and foresters in the Montesinho-Nogueira Natura 2000 site for their help and collaboration. ...
Henebry, and the anonymous reviewers for their valuable comments and suggestions that greatly improved the manuscript. This work was supported financially by the Ecology Fund of the Royal L.T. ...
CAB was derived using a protocol based on Lichtenthaler (1987) . ...
doi:10.1016/j.rse.2021.112505
fatcat:fj3vfmetvzf7lg2mayh6iabi6e
Biomass Estimation Using Satellite-Based Data
[chapter]
2021
Forest Biomass - From Trees to Energy
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regression algorithms used (parametric and non-parametric) that contribute to a more robust, practical, and cost-effective approach for forest AGB estimation at different levels. ...
This chapter aims to present different types of predicted variables derived from multi-sources sensors, such as original spectral bands, transformed images, vegetation indices, textural features, and different ...
Acknowledgements This work is funded by the National Funds through FCT -Foundation for Science and Technology under the Project UIDB/05183/2020 and by Programa Operativo de Cooperação Transfronteiriço ...
doi:10.5772/intechopen.93603
fatcat:xdij2dyqwjcyzdfzywikogb3fm
Improved estimates of global terrestrial photosynthesis using information on leaf chlorophyll content
2019
Global Change Biology
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The rate of photosynthesis is determined jointly by environmental variables and the intrinsic photosynthetic capacity of plants (i.e. maximum carboxylation ...
The terrestrial biosphere plays a critical role in mitigating climate change by absorbing anthropogenic CO 2 emissions through photosynthesis. ...
Jane Liu from University of Toronto for the helpful comments on the paper in its thesis format. ...
doi:10.1111/gcb.14624
fatcat:5tchx2c5bnhq5exz75jfmdciqe
Review of Machine Learning Approaches for Biomass and Soil Moisture Retrievals from Remote Sensing Data
2015
Remote Sensing
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) from remote sensing data using machine learning methods. ...
The main objective of this paper is to provide a review of research that is being carried out to retrieve two critically important terrestrial biophysical quantities (vegetation biomass and soil moisture ...
parameters (i.e., vegetation indices, textural features, backscatter) for the development of regression-based retrieval models, • Machine learning algorithms and • Simulation or biophysical models (data ...
doi:10.3390/rs71215841
fatcat:jiktp2klrzfffbzdf2ozbbk2ke
Lidar Boosts 3D Ecological Observations and Modelings: A review and perspective
2020
IEEE Geoscience and Remote Sensing Magazine
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lidar-derived surfaces, hierarchical semantic segmentation based on lidar point clouds, and deep learning-based methods. ...
[271] used a function-structure-plant model to provide in silico experiments for exploring the feasibility of lidar-based phenotype estimation (e.g., a green area index) with machine learning methods ...
doi:10.1109/mgrs.2020.3032713
fatcat:vot6c4ceabectd6xcpgev5duyu
Integration of a Landsat Time-Series of NBR and Hydrological Modeling to Assess Pinus Pinaster Aiton. Forest Defoliation in South-Eastern Spain
2019
Remote Sensing
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between the mortality processes of Pinus pinaster plantations and the hydrological regime, using different spectral indices of vegetation and machine learning algorithms. ...
Random Forest was the most accurate model (R2 = 0.79; RMSE = 0.059), showing a high model performance and prediction. ...
Acknowledgments: The authors thank the Andalusia Department of Agriculture and Environment, which ...
doi:10.3390/rs11192291
fatcat:7ii3wdkpx5e4xi2uizopsqi5vu
Estimation of Forest Aboveground Biomass in Changbai Mountain Region Using ICESat/GLAS and Landsat/TM Data
2017
Remote Sensing
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Lastly, GLAS-derived AGB, in combination with vegetation indices, leaf area index (LAI), canopy closure, and digital elevation model (DEM), were used to drive a data fusion model based on the random forest ...
The relationships between the GLAS-derived maximum canopy height and Landsat-derived LAI were modeled using a linear model, which was based on the assumption that the power law between LAI and the maximum ...
Random Forest is an algorithm based on ensemble techniques for classification and regression analysis [81] . ...
doi:10.3390/rs9070707
fatcat:vxlegf26kvbznbu6iegr53azo4
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