Fernando D. B. Espirito-Santo

Estimates of forest canopy height and aboveground biomass using ICESat

Exchange of carbon between forests and the atmosphere is a vital component of the global carbon cycle. Satellite laser altimetry has a unique capability for estimating forest canopy height, which has a direct and increasingly well understood relationship to aboveground carbon storage. While the Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud and land Elevation Satellite (ICESat) has collected an unparalleled dataset of lidar waveforms over terrestrial targets, processing of ICESat data to estimate forest height is complicated by the pulse broadening associated with large-footprint, waveform-sampling lidar. We combined ICESat waveforms and ancillary topography from the Shuttle Radar Topography Mission to estimate maximum forest height in three ecosystems; tropical broadleaf forests in Brazil, temperate broadleaf forests in Tennessee, and temperate needleleaf forests in Oregon. Final models for each site explained between 59% and 68% of variance in field-measured forest canopy height (RMSE between 4.85 and 12.66 m). In addition, ICESat-derived heights for the Brazilian plots were correlated with field-estimates of aboveground biomass (r(2) = 73%, RMSE = 58.3 Mgha(-1)).

Size and frequency of natural forest disturbances and the Amazon forest carbon balance

Forest inventory studies in the Amazon indicate a large terrestrial carbon sink. However, field plots may fail to represent forest mortality processes at landscape-scales of tropical forests. Here we characterize the frequency distribution of disturbance events in natural forests from 0.01 ha to 2,651 ha size throughout Amazonia using a novel combination of forest inventory, airborne lidar and satellite remote sensing data. We find that small-scale mortality events are responsible for aboveground biomass losses of ~1.7 Pg C y−1 over the entire Amazon region. We also find that intermediate-scale disturbances account for losses of ~0.2 Pg C y−1, and that the largest-scale disturbances as a result of blow-downs only account for losses of ~0.004 Pg C y−1. Simulation of growth and mortality indicates that even when all carbon losses from intermediate and large-scale disturbances are considered, these are outweighed by the net biomass accumulation by tree growth, supporting the inference of an Amazon carbon sink.

Spatial validation of the collection 4 MODIS LAI product in eastern Amazonia

This paper reports on the validation of the Collection 4 MODIS leaf area index (LAI) product over the Tapajo/spl acute/s region, eastern Amazonia. The validation site is enclosed in tile h12v09 of the MODIS LAI product. The methodology to assess MODIS LAI accuracy included two main steps: (1) a multiple regression analysis for the generation of LAI surfaces, based on the relationships between field data and remote sensing information from the Enhanced Thematic Mapper Plus sensor, and between field data and topographic information from a digital elevation model; (2) the direct comparison of these LAI surfaces with the MODIS LAI surfaces. The analysis indicated that MODIS LAI is significantly overestimated for the Tapajo/spl acute/s region by a factor of 1.18. No relationships between MODIS LAI and the validation surfaces were found. These results are indicative of a predominance of LAI retrievals by the backup algorithm, which is overcompensating LAI values at the saturation domain. The overgeneralization of the land cover layer (MOD12Q1) can be a source of uncertainties for the lookup table parameterization. Further validation efforts must be carried out over Amazonia for a quantitative quality assessment of the MODIS LAI surfaces in order to improve its accuracy.

Gap formation and carbon cycling in the Brazilian Amazon: measurement using high-resolution optical remote sensing and studies in large forest plots

Background: The dynamics of gaps plays a role in the regimes of tree mortality, production of coarse woody debris (CWD) and the variability of light in the forest understory. Aims: To quantify the area affected by, and the carbon fluxes associated with, natural gap-phase disturbances in a tropical lowland evergreen rain forest by use of ground measurements and high-resolution satellite images. Methods: We surveyed two large forest inventory plots of 114 and 53 ha of the Tapajós National Forest (TNF) in the Brazilian Amazon during 2008 and 2009, respectively. We mapped all gaps and collected data on light availability, CWD stocks and tree mortality in the field. Gap location, canopy openness (CO) and leaf area index (LAI) estimated in the field were compared with two IKONOS–2 high-resolution satellite images acquired at approximately the time of the field measurements. Results: In the two large plots (167 ha total area) we found 96 gaps. The gaps represented 1.42% of the total area and gaps <1-year-old accounted for 0.81% of the plot area. In TNF, the production of CWD in recent gaps was 0.76 Mg C ha−1 year−1 and the mean tree mortality was 2.38 stems ha−1 year−1. The area of gaps estimated using thresholds of light intensity measured by remote sensing optical instruments was twice as large as the gap areas measured on the ground. We found no significant correlation between spectral remote sensing images and CO or LAI, probably due to the high degree of shadow in the high-resolution satellite images. Conclusions: We present the first statistics of CWD production based on gap size in the tropical forest literature. Tree mortality and CWD flux and the forest floor light environment were closely related to gap area. However, less than 30% of the annual tree mortality and CWD flux was associated with gaps, and gaps were difficult to detect using remote sensing methods because of the high proportion of shadow in the images. These results highlight the need for permanent plots in long-term carbon studies.

Correction to “Estimates of forest canopy height and aboveground biomass using ICESat”

[1] Exchange of carbon between forests and the atmosphere is a vital component of the global carbon cycle. Satellite laser altimetry has a unique capability for estimating forest canopy height, which has a direct and increasingly well understood relationship to aboveground carbon storage. While the Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud and land Elevation Satellite (ICESat) has collected an unparalleled dataset of lidar waveforms over terrestrial targets, processing of ICESat data to estimate forest height is complicated by the pulse broadening associated with large-footprint, waveform-sampling lidar. We combined ICESat waveforms and ancillary topography from the Shuttle Radar Topography Mission to estimate maximum forest height in three ecosystems; tropical broadleaf forests in Brazil, temperate broadleaf forests in Tennessee, and temperate needleleaf forests in Oregon. Final models for each site explained between 59% and 68% of variance in field-measured forest canopy height (RMSE between 4.85 and 12.66 m). In addition, ICESat-derived heights for the Brazilian plots were correlated with field-estimates of aboveground biomass (r = 73%, RMSE = 58.3 Mgha ). Citation: Lefsky, M. A., D. J. Harding, M. Keller, W. B. Cohen, C. C. Carabajal, F. Del Bom Espirito-Santo, M. O. Hunter, and R. de Oliveira Jr. (2005), Estimates of forest canopy height and aboveground biomass using ICESat, Geophys. Res. Lett., 32, L22S02, doi:10.1029/2005GL023971.

Quantifying immediate carbon emissions from El Niño-mediated wildfires in humid tropical forests

Wildfires produce substantial CO2 emissions in the humid tropics during El Niño-mediated extreme droughts, and these emissions are expected to increase in coming decades. Immediate carbon emissions from uncontrolled wildfires in human-modified tropical forests can be considerable owing to high necromass fuel loads. Yet, data on necromass combustion during wildfires are severely lacking. Here, we evaluated necromass carbon stocks before and after the 2015–2016 El Niño in Amazonian forests distributed along a gradient of prior human disturbance. We then used Landsat-derived burn scars to extrapolate regional immediate wildfire CO2 emissions during the 2015–2016 El Niño. Before the El Niño, necromass stocks varied significantly with respect to prior disturbance and were largest in undisturbed primary forests (30.2 ± 2.1 Mg ha−1, mean ± s.e.) and smallest in secondary forests (15.6 ± 3.0 Mg ha−1). However, neither prior disturbance nor our proxy of fire intensity (median char height) explained necromass losses due to wildfires. In our 6.5 million hectare (6.5 Mha) study region, almost 1 Mha of primary (disturbed and undisturbed) and 20 000 ha of secondary forest burned during the 2015–2016 El Niño. Covering less than 0.2% of Brazilian Amazonia, these wildfires resulted in expected immediate CO2 emissions of approximately 30 Tg, three to four times greater than comparable estimates from global fire emissions databases. Uncontrolled understorey wildfires in humid tropical forests during extreme droughts are a large and poorly quantified source of CO2 emissions. This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications’.

Drought-induced Amazonian wildfires instigate a decadal-scale disruption of forest carbon dynamics

Drought-induced wildfires have increased in frequency and extent over the tropics. Yet, the long-term (greater than 10 years) responses of Amazonian lowland forests to fire disturbance are poorly known. To understand post-fire forest biomass dynamics, and to assess the time required for fire-affected forests to recover to pre-disturbance levels, we combined 16 single with 182 multiple forest census into a unique large-scale and long-term dataset across the Brazilian Amazonia. We quantified biomass, mortality and wood productivity of burned plots along a chronosequence of up to 31 years post-fire and compared to surrounding unburned plots measured simultaneously. Stem mortality and growth were assessed among functional groups. At the plot level, we found that fire-affected forests have biomass levels 24.8 ± 6.9% below the biomass value of unburned control plots after 31 years. This lower biomass state results from the elevated levels of biomass loss through mortality, which is not sufficiently compensated for by wood productivity (incremental growth + recruitment). At the stem level, we found major changes in mortality and growth rates up to 11 years post-fire. The post-fire stem mortality rates exceeded unburned control plots by 680% (i.e. greater than 40 cm diameter at breast height (DBH); 5–8 years since last fire) and 315% (i.e. greater than 0.7 g cm−3 wood density; 0.75–4 years since last fire). Our findings indicate that wildfires in humid tropical forests can significantly reduce forest biomass for decades by enhancing mortality rates of all trees, including large and high wood density trees, which store the largest amount of biomass in old-growth forests. This assessment of stem dynamics, therefore, demonstrates that wildfires slow down or stall the post-fire recovery of Amazonian forests. This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications’.

Combining Landsat ETM+ and terrain data for scaling up leaf area index (LAI) in eastern Amazon: an intercomparison with MODIS product

The general aim of this study was to produce a continuous field of LAI to evaluate the LAI surface (MODIS product) derived from the moderate resolution imaging spectroradiometer (MODIS), for the Tapajos region, eastern Amazonia. Our method consisted in generating regression models combining spectral data derived from Enhanced Thematic Mapper Plus (ETM+) sensor (07/30/2001) and terrain slope and altimetry information extracted from a digital terrain model. The spectral variables considered for this study are reflectance, vegetation indices (NDVI and SR) and fraction images. Using a multiple comparison test, we compared the mean LAI estimated by the three models generated in this study (270 m spatial resolution) with the 8 days LAI composition (08/13/2001) derived from MODIS sensor (1 km spatial resolution) and also with field data. The MODIS LAI surface for the Tapajos region showed a more homogenous surface and little information about land cover and land use when we visually compared with our estimations. This fact occurs due to the 1 km resolution from de MODIS LAI against the 270 m resolution used in our approach. The statistics indicated that the mean LAI derived from MODIS sensor is significantly overestimated (P<0.05) in relation to both field and modeled data. We conclude that the approach employed here is promising for generating LAI surfaces, based on field data, for MODIS LAI validation purposes

Corrigendum: Size and frequency of natural forest disturbances and the Amazon forest carbon balance

Corrigendum: Size and frequency of natural forest disturbances and the Amazon forest carbon balance

Spectral signature of leaves of amazon rainforest tree species

Remote sensing is based on the interaction of electromagnetic radiation with the portion of the electromagnetic radiation that interacts with Earth surface targets. Studies to analyze the spectrum of reflectance of surface targets by sensor systems could be done by terrestrial (laboratory and field), aerial and orbital acquisitions. Consequently, for vegetation studies through remote sensing observations is necessary to know the physiology of the plant studied and the reflectance spectrum, considering that the solar radiation reaches the earths surface and results in three fractions: one part is absorbed, another is reflected and a third part is transmitted. The leaves are the principal absorber of electromagnetic radiation in a canopy and represents the element that more contribute to the signal detected by orbital sensors. The present work has as its main goal the analysis of the spectral signature responses of common species of several forest functional types in a tropical forest area in the Amazon.