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
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Journal ArticleDOI
Improving Accuracy Estimation of Forest Aboveground Biomass Based on Incorporation of ALOS-2 PALSAR-2 and Sentinel-2A Imagery and Machine Learning: A Case Study of the Hyrcanian Forest Area (Iran)
TL;DR: The results showed that the AGB models derived from the combination of the Sentinel-2A and the ALOS-2 PALSAR-2 data had the highest accuracy, followed by models using the Sentinel -2A dataset and the AlOS- 2 PALSar-2 dataset.
Journal ArticleDOI
Estimating leaf area index and aboveground biomass of grazing pastures using Sentinel-1, Sentinel-2 and Landsat images
Jie Wang,Xiangming Xiao,Rajen Bajgain,Patrick J. Starks,Jean L. Steiner,Russell Doughty,Qing Chang +6 more
TL;DR: In this article, the authors examined the potential of integrating synthetic aperture radar (SAR, Sentinel-1) and optical remote sensing (Landsat-8 and Sentinel-2) data to monitor the conditions of a native pasture and an introduced pasture in Oklahoma, USA.
Journal ArticleDOI
Examining Spectral Reflectance Saturation in Landsat Imagery and Corresponding Solutions to Improve Forest Aboveground Biomass Estimation
TL;DR: The results indicate that pine forest and mixed forest have the highest AGB saturation values and Chinese fir and broadleaf forest have lower saturation values, and bamboo forest and shrub have the lowest saturation values.
Journal ArticleDOI
Remote sensing approaches for monitoring mangrove species, structure, and biomass: Opportunities and challenges
TL;DR: This review provides an overview of the techniques that are currently being used to map various attributes of mangrove, summarizes the studies that have been undertaken since 2010 on a variety of remote sensing applications for monitoring mangroves, and addresses the limitations of these studies.
Journal ArticleDOI
Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics
TL;DR: An overview of the definitions of FH is provided, discussing the drivers, processes, stress and adaptation mechanisms of forest plants, and how to observe FH with RS, and the concept of spectral traits (ST) and spectral trait variations (STV) in the context ofFH monitoring is introduced.
References
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Journal ArticleDOI
Remotely sensed biomass over steep slopes: An evaluation among successional stands of the Atlantic Forest, Brazil
TL;DR: In this paper, the authors investigated how topographical features affect biomass estimation using remotely sensed data and how such estimates can be used in the characterization of successional stands in the Atlantic Rainforest in southeastern Brazil.
Posted ContentDOI
Mapping landscape scale variations of forest structure, biomass, and productivity in Amazonia
Sassan Saatchi,Yadvinder Malhi,Brian R. Zutta,Wolfgang Buermann,Liana O. Anderson,A. M. Araujo,Oliver L. Phillips,Julie Peacock,H. ter Steege,G. Lopez Gonzalez,Timothy R. Baker,L. Arroyo,S. Almeida,Niro Higuchi,Timothy J. Killeen,Abel Monteagudo,David A. Neill,Nigel C. A. Pitman,Adriana Prieto,Rafael de Paiva Salomão,NL Silva,R. Vásquez Martínez,W. Laurance,H. A. Ramírez +23 more
TL;DR: In this article, the authors combine a network of forest inventories with recently developed global data products from satellite observations in modeling the potential distributions of forest structure and productivity in Amazonia and examine how geomorphology, soil, and precipitation control these distributions.
Journal ArticleDOI
Retrieval of tropical forest biomass information from ALOS PALSAR data
TL;DR: In this article, the authors performed regression analysis to estimate above-ground forest biomass using PALSAR backscatter data for natural and planted forests in south-eastern Bangladesh.
Journal ArticleDOI
Imputing Mean Annual Change to Estimate Current Forest Attributes
TL;DR: In this paper, the authors used three nearest neighbor imputation methods to estimate mean annual change of four forest attributes (basal area, stems, volume, and biomass) from paneled forest inventories.
Journal ArticleDOI
National‐scale estimates of forest root biomass carbon stocks and associated carbon fluxes in Canada
TL;DR: In this paper, the contribution of roots to the carbon budget of Canada's 2.3'×'106 km2 managed forests from 1990 to 2008 using the empirical modeling approach of the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) driven by detailed forestry data sets from the National Forest C Monitoring, Accounting and Reporting System.