Quantifying Forest Biomass Carbon Stocks From Space

Rodríguez-Veiga, Pedro; Wheeler, James; Louis, Valentin; Tansey, Kevin; Balzter, Heiko

doi:10.1007/s40725-017-0052-5

Cited by 99 publications

(69 citation statements)

References 120 publications

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“…Although relationships between retrieved forest parameters and biomass have been demonstrated, their correlations vary in regions and are sometimes poor [119]. A full exploration of the relationships between forest biomass and its related parameters at different spatial resolutions as well as the associated factors influencing these relationships should be performed.…”

Section: Data Sources For Forest Agb Mappingmentioning

confidence: 99%

A Review of Regional and Global Gridded Forest Biomass Datasets

2019

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Forest biomass quantification is essential to the global carbon cycle and climate studies. Many studies have estimated forest biomass from a variety of data sources, and consequently generated some regional and global maps. However, these forest biomass maps are not well known and evaluated. In this paper, we reviewed an extensive list of currently available forest biomass maps. For each map, we briefly introduced the data sources, the algorithms used, and the associated uncertainties. Large-scale biomass datasets were compared across Europe, the conterminous United States, Southeast Asia, tropical Africa and South America. Results showed that these forest biomass datasets were almost entirely inconsistent, particularly in woody savannas and savannas across these regions. The uncertainties in biomass maps could be from a variety of sources including the chosen allometric equations used to calculate field data, the choice and quality of remotely sensed data, as well as the algorithms to map forest biomass or extrapolation techniques, but these uncertainties have not been fully quantified. We suggested the future directions for generating more accurate large-scale forest biomass maps should concentrate on the compilation of field biomass data, novel approaches of forest biomass mapping, and comprehensively addressing the accuracy of generated biomass maps.

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Section: Data Sources For Forest Agb Mappingmentioning

confidence: 99%

A Review of Regional and Global Gridded Forest Biomass Datasets

2019

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“…Knowledge about the status and changes of forest structural parameters is important for the assessment of forest carbon stocks for national forest inventories in the context of reducing emissions from deforestation and forest degradation (REDD) and as a base input for the estimation of the forest above-ground biomass (AGB) which represents a key component in global carbon cycle models. Remote sensing has proven to be the most effective means to monitor the extent and qualitative as well as quantitative parameters of forests across wide areas from regional to global level [2,3]. In terms of the global carbon cycle, AGB is the most important forest variable.…”

Section: Introductionmentioning

confidence: 99%

“…and ranging (LiDAR), and synthetic aperture radar (SAR) data. A comprehensive summary of studies that aim at quantifying forest biomass from satellite sensors was compiled by [3]. AGB estimates from optical remote sensing data mostly rely on vegetation indices that parameterize the photosynthetic activity of vegetation.…”

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confidence: 99%

Sensitivity of Bistatic TanDEM-X Data to Stand Structural Parameters in Temperate Forests

et al. 2019

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Synthetic aperture radar (SAR) satellite data provide a valuable means for the large-scale and long-term monitoring of structural components of forest stands. The potential of TanDEM-X interferometric SAR (InSAR) for the assessment of forest structural properties has been widely verified. However, present studies are mostly restricted to homogeneous forests and do not account for stratification in assessing model performance. A systematic sensitivity analysis of the TanDEM-X SAR signal to forest structural parameters was carried out with emphasis on different strata of forest stands (location of the study site, forest type, and development stage). Forest structure was parameterized by forest height metrics and stem volume. Results show that X-band volume coherence is highly sensitive to the forest canopy. Volume scattering within the canopy is dependent on the vertical heterogeneity of the forest stand. In general, TanDEM-X coherence is more sensitive to forest vertical structure compared to backscatter. The relations between TanDEM-X volume coherence and forest structural properties were significant at the level of a single test site as well as across sites in temperate forests in Germany. Forest type does not affect the overall relationship between the SAR signal and the forests' vertical structure. The prediction of forest structural parameters based on the outcome of the sensitivity analysis yielded model accuracies between 15% (relative root mean square error) for Lorey's height and 32% for stem volume. The global database of single-polarized bistatic TanDEM-X data provides an important source for mapping structural parameters in temperate forests at large scale, irrespective of forest type. and ranging (LiDAR), and synthetic aperture radar (SAR) data. A comprehensive summary of studies that aim at quantifying forest biomass from satellite sensors was compiled by [3]. AGB estimates from optical remote sensing data mostly rely on vegetation indices that parameterize the photosynthetic activity of vegetation. They imply a relationship between the foliage and the total AGB of a vegetation stand, which is further used to estimate AGB. Since the major part of AGB in forests is composed of non-photosynthetic (woody) components, such approaches imply high uncertainties. The major challenge in AGB mapping from optical data is the saturation of the signal after canopy closure which especially hampers the estimation of high-level AGB [4]. However, recent studies confirmed the general ability of optical systems like Landsat to map AGB at biomass levels around 70 Mg/ha [5].The saturation problem can be overcome by sensors, which are able to penetrate through the canopy and interact with the forest constituents. For instance, LiDAR and interferometric SAR (InSAR) systems generally provide the necessary technique because they are able to penetrate the canopy of a forest and deliver information about the vertical structure of a forest stand. LiDAR data produce high-accuracy canopy height models (CHM) but the main drawback ...

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“…We suggest therefore that RS techniques, which involve considerable methodological complexity, may not be the best option for project level AGB predictions. Cost of technology and expertise, signal saturation issues, modelling procedures, pixel sizes, temporal coverage of imaginary, errors in geo-location and different sources of RS and plot-level AGB data, are often mentioned as drawbacks in the use of RS for AGB estimation (Mitchard 2015, Wells et al 2017, Rodríguez-Veiga et al 2017.…”

Section: Discussionmentioning

confidence: 99%

Connecting the dots : modeling the efects of topography on carbon stocks to promote efficiency in local REDD+ planning

Melgoza¹,

Ángel²

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Tropical forests are of global concern in the context of climate change. This is because forests can both emit carbon dioxide (CO2), an important greenhouse gas (GHG), and sequester it in the biomass of trees. The ability of a given type of forest to hold stocks of carbon is strongly influenced both by topography of the landscape and by the human uses that are present. Topography is not just indicated in the literature as a template within the landscape that defines the patterns of density biomass, but also as a driving factor of human uses. While altitude, slope and terrain convexity, among others, show a relationship with biomass patterns, human activities such as shifting cultivation, grazing and extraction of

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Quantifying Forest Biomass Carbon Stocks From Space

Cited by 99 publications

References 120 publications

A Review of Regional and Global Gridded Forest Biomass Datasets

A Review of Regional and Global Gridded Forest Biomass Datasets

Sensitivity of Bistatic TanDEM-X Data to Stand Structural Parameters in Temperate Forests

Connecting the dots : modeling the efects of topography on carbon stocks to promote efficiency in local REDD+ planning

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