Journal ArticleDOI
A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems
TLDR
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.Abstract:
Remote sensing-based methods of aboveground biomass (AGB) estimation in forest ecosystems have gained increased attention, and substantial research has been conducted in the past three decades. This paper provides 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 from remote sensing data, identification of proper algorithms to develop biomass estimation models, and uncertainty analysis to refine the estimation procedure. Additionally, we discuss the impacts of scales on biomass estimation performance and describe a general biomass estimation procedure. Although optical sensor and radar data have been primary sources for AGB estimation, data saturation is an important factor resulting in estimation uncertainty. LIght Detection and Ranging (lidar) can remove data saturation, but limited availability of lidar data prevents its extensive application. This...read more
Citations
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Journal ArticleDOI
Determining diagnostic indicators for fine-scale short vegetation aboveground biomass inversion using a HVRU-based analysis approach
TL;DR: Wang et al. as discussed by the authors extended the AGB inversion researches on short vegetation species at a relatively fine scale using a homogenous vegetation response unit (HVRU)-oriented analysis approach, and explored a convenient scheme to determine diagnostic indicators.
Journal ArticleDOI
Above ground biomass estimation from UAV high resolution RGB images and LiDAR data in a pine forest in Southern Italy
Mauro Maesano,Giovanni Santopuoli,FV Moresi,Giorgio Matteucci,Bruno Lasserre,Gabriele Scarascia Mugnozza +5 more
TL;DR: In this article , a low-cost AGB estimation method was adopted using a commercial fixed-wing drone equipped with an RGB camera, combined with the canopy information derived by LiDAR and validated by field data.
Journal ArticleDOI
Combining Multi-Dimensional SAR Parameters to Improve RVoG Model for Coniferous Forest Height Inversion Using ALOS-2 Data
Rula Sa,Yonghui Nei,Wenyi Fan +2 more
TL;DR: In this article , the extinction coefficient changes with height caused by the inhomogeneous distribution of scatterers in heterogeneous forests and uses the InSAR phase center height histogram and Gaussian function to fit the normalized extinction coefficient curve so as to reflect the vertical structure of the heterogeneous forest.
Journal ArticleDOI
Remote sensing for cost-effective blue carbon accounting
Martino E. Malerba,Micheli Duarte de Paula Costa,Daniel A. Friess,L. Schuster,Mary Young,David Lagomasino,Oscar Serrano,Sharyn Hickey,Paul H. York,Michael Rasheed,Jonathan S. Lefcheck,Ben Radford,Trisha B. Atwood,Daniel Ierodiaconou,Peter I. Macreadie +14 more
TL;DR: In this paper , the authors present a unified roadmap for applying remote sensing technologies to develop cost-effective carbon inventories for blue carbon ecosystems from local to global scales, from both local and global scales.
References
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Journal ArticleDOI
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Assessing the accuracy of remotely sensed data : principles and practices
Russell G. Congalton,Kass Green +1 more
TL;DR: This chapter discusses Accuracy Assessment, which examines the impact of sample design on cost, statistical Validity, and measuring Variability in the context of data collection and analysis.