Journal ArticleDOI
Above ground biomass estimation in an African tropical forest with lidar and hyperspectral data
Gaia Vaglio Laurin,Gaia Vaglio Laurin,Qi Chen,Jeremy A. Lindsell,David A. Coomes,Fabio Del Frate,Leila Guerriero,Francesco Pirotti,Riccardo Valentini +8 more
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TLDR
In this paper, a Partial Least Square Regression (PLSR) was adopted to cope with multiple inputs and multicollinearity issues; the Variable of Importance in the Projection was calculated to evaluate importance of individual predictors for biomass.Abstract:
The estimation of above ground biomass in forests is critical for carbon cycle modeling and climate change mitigation programs. Small footprint lidar provides accurate biomass estimates, but its application in tropical forests has been limited, particularly in Africa. Hyperspectral data record canopy spectral information that is potentially related to forest biomass. To assess lidar ability to retrieve biomass in an African forest and the usefulness of including hyperspectral information, we modeled biomass using small footprint lidar metrics as well as airborne hyperspectral bands and derived vegetation indexes. Partial Least Square Regression (PLSR) was adopted to cope with multiple inputs and multicollinearity issues; the Variable of Importance in the Projection was calculated to evaluate importance of individual predictors for biomass. Our findings showed that the integration of hyperspectral bands (R2 = 0.70) improved the model based on lidar alone (R2 = 0.64), this encouraging result call for additional research to clarify the possible role of hyperspectral data in tropical regions. Replacing the hyperspectral bands with vegetation indexes resulted in a smaller improvement (R2 = 0.67). Hyperspectral bands had limited predictive power (R2 = 0.36) when used alone. This analysis proves the efficiency of using PLSR with small-footprint lidar and high resolution hyperspectral data in tropical forests for biomass estimation. Results also suggest that high quality ground truth data is crucial for lidar-based AGB estimates in tropical African forests, especially if airborne lidar is used as an intermediate step of upscaling field-measured AGB to a larger area.read more
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Journal ArticleDOI
A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems
TL;DR: A survey of current biomass estimation methods using remote sensing data and discusses four critical issues – collection of field-based biomass reference data, extraction and selection of suitable variables fromRemote sensing data, identification of proper algorithms to develop biomass estimation models, and uncertainty analysis to refine the estimation procedure.
Journal Article
Calibration and validation of hyperspectral indices for the estimation of broadleaved forest leaf chlorophyll content, leaf mass per area, leaf area index and leaf canopy biomass
G. Le Maire,C. François,Kamel Soudani,Daniel Berveiller,Jean-Yves Pontailler,Nathalie Bréda,Hélène Genet,Hendrik Davi,Eric Dufrêne +8 more
TL;DR: In this article, the best vegetation indices (index form and wavelengths) were determined on a generic simulated database to estimate CHL, LMA, LAI and Bleaf in a general way.
Journal ArticleDOI
Importance of sample size, data type and prediction method for remote sensing-based estimations of aboveground forest biomass
Fabian Ewald Fassnacht,Fabian Ewald Fassnacht,Florian Hartig,Hooman Latifi,Christian Berger,Jaime Hernández,Patricio Corvalán,Barbara Koch +7 more
TL;DR: In this article, the influence of the predictor data (sensor) type is the most important factor for the accu- racy of biomass estimates, with LiDAR being preferable to hyperspectral data.
Journal ArticleDOI
Evaluating the utility of the medium-spatial resolution Landsat 8 multispectral sensor in quantifying aboveground biomass in uMgeni catchment, South Africa
Timothy Dube,Onisimo Mutanga +1 more
TL;DR: In this paper, the utility of the newly-launched medium-resolution multispectral Landsat 8 Operational Land Imager (OLI) dataset with a large swath width, in quantifying aboveground biomass (AGB) in a forest plantation was assessed.
Journal ArticleDOI
Estimate of winter-wheat above-ground biomass based on UAV ultrahigh-ground-resolution image textures and vegetation indices
Jibo Yue,Jibo Yue,Jibo Yue,Guijun Yang,Qingjiu Tian,Qingjiu Tian,Haikuan Feng,Kaijian Xu,Kaijian Xu,Chengquan Zhou +9 more
TL;DR: In this paper, the authors evaluated the use of image textures, VIs, and combinations thereof to make multiple temporal estimates and maps of AGB covering three winter-wheat growth stages.
References
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Book
Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach
TL;DR: The second edition of this book is unique in that it focuses on methods for making formal statistical inference from all the models in an a priori set (Multi-Model Inference).
Journal ArticleDOI
PLS-regression: a basic tool of chemometrics
TL;DR: PLS-regression (PLSR) as mentioned in this paper is the PLS approach in its simplest, and in chemistry and technology, most used form (two-block predictive PLS) is a method for relating two data matrices, X and Y, by a linear multivariate model.
Journal ArticleDOI
Partial least-squares regression: a tutorial
Paul Geladi,Bruce R. Kowalski +1 more
TL;DR: In this paper, a tutorial on the Partial Least Squares (PLS) regression method is provided, and an algorithm for a predictive PLS and some practical hints for its use are given.
Journal ArticleDOI
Tree allometry and improved estimation of carbon stocks and balance in tropical forests
Jérôme Chave,C. Andalo,Sandra Brown,Michael A. Cairns,Jeffrey Q. Chambers,Derek Eamus,H. Fölster,François Fromard,Niro Higuchi,T. Kira,J. P. Lescure,Bruce Walker Nelson,H. Ogawa,H. Puig,B. Riera,Takuo Yamakura +15 more
TL;DR: A critical reassessment of the quality and the robustness of these models across tropical forest types, using a large dataset of 2,410 trees ≥ 5 cm diameter, directly harvested in 27 study sites across the tropics, is provided.
Journal ArticleDOI
Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages
Daniel A. Sims,John A. Gamon +1 more
TL;DR: Developing spectral indices for prediction of leaf pigment content that are relatively insensitive to species and leaf structure variation and thus could be applied in larger scale remote-sensing studies without extensive calibration are developed.