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
More filters
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
More filters
Journal ArticleDOI
Impact of spatial variability of tropical forest structure on radar estimation of aboveground biomass
TL;DR: In this article, the authors used forest inventory plots in old growth, secondary succession, and forest plantations at the La Selva Biological Station in Costa Rica to examine the spatial variability of tropical forest structure and its impact on the L-band and P-band polarimetric radar estimation of AGB at multiple spatial scales.
Journal ArticleDOI
Total carbon stocks in a tropical forest landscape of the Porce region, Colombia
Carlos A. Sierra,Carlos A. Sierra,Jorge I. del Valle,Sergio A. Orrego,Sergio A. Orrego,Flavio Moreno,Mark E. Harmon,Mauricio Zapata,Gabriel J. Colorado,María A. Herrera,Wilson Lara,David E. Restrepo,Lina Berrouet,Lina María Loaiza,John F. Benjumea +14 more
TL;DR: In this article, carbon stocks in live aboveground and belowground biomass, necromass, and soils were measured in a heterogeneous landscape composed of secondary and primary forests. And the authors concluded that estimates of aboveground biomass largely underestimate total carbon stocks.
Journal ArticleDOI
Synthesis of remote sensing approaches for forest carbon estimation: reporting to the Kyoto Protocol
TL;DR: In this paper, a quantitative assessment of remote sensing approaches for land cover discrimination to monitor deforestation and above-ground forest carbon stocks estimation is presented, focusing on the requirements specific to the UK.
Journal ArticleDOI
Imputation of single-tree attributes using airborne laser scanning-based height, intensity, and alpha shape metrics
TL;DR: In this paper, the authors used the k-Most Similar Neighbor (k-MSN) and the Random Forest (RF) methods for the simultaneous estimation of species, diameter at breast height (DBH), height and stem volume using airborne laser scanning (ALS) data.
Journal ArticleDOI
Evaluating uncertainty in mapping forest carbon with airborne LiDAR
TL;DR: In this paper, the authors used a 50-ha plot with mapped trees, allowing an assessment of LiDAR prediction errors at multiple spatial resolutions, and they found that errors scaled approximately as expected, declining by 38% (compared to 40% predicted from theory) from 0.36-to 1-ha resolution.