The uncertainty of biomass estimates from modeled ICESat-2 returns across a boreal forest gradient

Montesano, P.; Rosette, J.; Sun, Guoqing; North, Peter; Nelson, Ross; Dubayah, Ralph; Ranson, K.J.; Харук, В. И.

doi:10.1016/j.rse.2014.10.029

Cited by 58 publications

(40 citation statements)

References 81 publications

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“…A spaceborne assessment of forest structure from individual active sensors across a gradient of boreal forest structure shows broad ranges of uncertainty at plot scales (Montesano et al, 2014a(Montesano et al, , 2015. These plot-scale studies provide an indication of the scale at which TTE structure changes.…”

Section: A Conceptual Model Of the Tte: Forest Patches Ecotone Formmentioning

confidence: 99%

Spaceborne potential for examining taiga–tundra ecotone form and vulnerability

et al. 2016

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Abstract. In the taiga-tundra ecotone (TTE), site-dependent forest structure characteristics can influence the subtle and heterogeneous structural changes that occur across the broad circumpolar extent. Such changes may be related to ecotone form, described by the horizontal and vertical patterns of forest structure (e.g., tree cover, density, and height) within TTE forest patches, driven by local site conditions, and linked to ecotone dynamics. The unique circumstance of subtle, variable, and widespread vegetation change warrants the application of spaceborne data including high-resolution (< 5 m) spaceborne imagery (HRSI) across broad scales for examining TTE form and predicting dynamics. This study analyzes forest structure at the patch scale in the TTE to provide a means to examine both vertical and horizontal components of ecotone form. We demonstrate the potential of spaceborne data for integrating forest height and density to assess TTE form at the scale of forest patches across the circumpolar biome by (1) mapping forest patches in study sites along the TTE in northern Siberia with a multi-resolution suite of spaceborne data and (2) examining the uncertainty of forest patch height from this suite of data across sites of primarily diffuse TTE forms. Results demonstrate the opportunities for improving patch-scale spaceborne estimates of forest height, the vertical component of TTE form, with HRSI. The distribution of relative maximum height uncertainty based on prediction intervals is centered at ∼ 40 %, constraining the use of height for discerning differences in forest patches. We discuss this uncertainty in light of a conceptual model of general ecotone forms and highlight how the uncertainty of spaceborne estimates of height can contribute to the uncertainty in identifying TTE forms. A focus on reducing the uncertainty of height estimates in forest patches may improve depiction of TTE form, which may help explain variable forest responses in the TTE to climate change and the vulnerability of portions of the TTE to forest structure change.

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Section: A Conceptual Model Of the Tte: Forest Patches Ecotone Formmentioning

confidence: 99%

Spaceborne potential for examining taiga–tundra ecotone form and vulnerability

et al. 2016

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“…However, it is not clear whether the ATLAS sensor will be suitable to estimate canopy height and AGB on forest areas due to concerns on the noise level of the discrete return photon-counting system [143,144]. Additionally, AGB estimation by ATLAS in sparse forests such as the boreal taiga-tundras and savannas will be challenging due to the low sampling rate, the sole use of the green wavelength and the low sensitivity of the sensor to discern differences in AGB at 10 t ha −1 intervals [144,145].…”

Section: Future Scenariomentioning

confidence: 99%

Quantifying Forest Biomass Carbon Stocks From Space

et al. 2017

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Purpose of Review This review presents cutting-edge methods and current and forthcoming satellite remote sensing technologies to map aboveground biomass (AGB). Recent Findings The monitoring of carbon stored in living AGB of forest is of key importance to understand the global carbon cycle and for the functioning of international economic mechanisms aiming to protect and enhance forest carbon stocks. The main challenge of monitoring AGB lies in the difficulty of obtaining field measurements and allometric models in several parts of the world due to geographical remoteness, lack of capacity, data paucity or armed conflicts. Space-borne remote sensing in combination with ground measurements is the most cost-efficient technology to undertake the monitoring of AGB. Summary These approaches face several challenges: lack of ground data for calibration/validation purposes, signal saturation in high AGB, coverage of the sensor, cloud cover persistence or complex signal retrieval due to topography. New space-borne sensors to be launched in the coming years will allow accurate measurements of AGB in high biomass forests (>200 t ha −1 ) for the first time across large areas.

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“…Generally, lidar data and high-resolution images can obtain more accurate AGB prediction results [16,[19][20][21][22][23][24]; however, they are limited in spatial and temporal coverage. To date, Landsat images have been the most commonly used in AGB studies as multi-temporal medium-resolution data (30 m), leveraging the complete spatial coverage of imagery [14,17,25], while coarse resolution MODIS, AVHRR, SPOT-VGT are difficult to use because of the mismatch between field measurements and satellite observations [26,27].…”

Section: Introductionmentioning

confidence: 99%

Quantifying Live Aboveground Biomass and Forest Disturbance of Mountainous Natural and Plantation Forests in Northern Guangdong, China, Based on Multi-Temporal Landsat, PALSAR and Field Plot Data

Shen

Huang

et al. 2016

Remote Sensing

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Spatially explicit knowledge of aboveground biomass (AGB) in large areas is important for accurate carbon accounting and quantifying the effect of forest disturbance on the terrestrial carbon cycle. We estimated AGB from 1990 to 2011 in northern Guangdong, China, based on a spatially explicit dataset derived from six years of national forest inventory (NFI) plots, Landsat time series imagery and Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radars (PALSAR) 25 m mosaic data (2007)(2008)(2009)(2010). Four types of variables were derived for modeling and assessment. The random forest approach was used to seek the optimal variables for mapping and validation. The root mean square error (RMSE) of plot-level validation was between 6.44 and 39.49 (t/ha), the normalized root-mean-square error (NRMSE) was between 7.49% and 19.01% and mean absolute error (MAE) was between 5.06 and 23.84 t/ha. The highest coefficient of determination R 2 of 0.8 and the lowest NRMSE of 7.49% were reported in 2006. A clear increasing trend of mean AGB from the lowest value of 13.58 t/ha to the highest value of 66.25 t/ha was witnessed between 1988 and 2000, while after 2000 there was a fluctuating ascending change, with a peak mean AGB of 67.13 t/ha in 2004. By integrating AGB change with forest disturbance, the trend in disturbance area closely corresponded with the trend in AGB decrease. To determine the driving forces of these changes, the correlation analysis was adopted and exploratory factor analysis (EFA) method was used to find a factor rotation that maximizes this variance and represents the dominant factors of nine climate elements and nine human activities elements affecting the AGB dynamics. Overall, human activities contributed more to short-term AGB dynamics than climate data. Harvesting and human-induced fire in combination with rock desertification and global warming made a strong contribution to AGB changes. This study provides valuable information for the relationships between forest AGB and climate as well as forest disturbance in subtropical zones.

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The uncertainty of biomass estimates from modeled ICESat-2 returns across a boreal forest gradient

Cited by 58 publications

References 81 publications

Spaceborne potential for examining taiga–tundra ecotone form and vulnerability

Spaceborne potential for examining taiga–tundra ecotone form and vulnerability

Quantifying Forest Biomass Carbon Stocks From Space

Quantifying Live Aboveground Biomass and Forest Disturbance of Mountainous Natural and Plantation Forests in Northern Guangdong, China, Based on Multi-Temporal Landsat, PALSAR and Field Plot Data

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