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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Measurements of soil and canopy exchange rates in the Amazon rain forest using Rn-222

Measurements were taken of the emission of Rn-222 from Amazon forest rocks and soils and used as a tracer of ventilation of the forest canopy layer at night. It was determined that the greatest resistance to transfer of trace gases from the soil to the atmosphere lies in the soil air space. Profiles of Rn-222 and CO2 showed steepest concentration gradients in the layer between 0 and 3 m above soil surface. Aerodynamic resistances calculated for this layer from Rn-222 and CO2 varied from 1.6 to 18 s/cm, with greater resistance during the afternoon than at night. The resistance to exchange with air from the entire 41 m layer below the canopy averaged 4.8 s/cm during 13 nights of CO2 profiles. The calculated average time to flush the layer below 41 m is 5.5 hr, and it is concluded that this indicates that significant exchange occurs despite nocturnal stratification.

Trumbore, S. E.↗
NASA NTRS1981

Off-nadir antenna bias correction using Amazon rain forest sigma deg data

The radar response from the Amazon rain forest was studied to determine the suitability of this region for use as a standard target to calibrate a scatterometer like that proposed for the National Ocean Satellite System (NOSS). Backscattering observations made by the SEASAT-1 scatterometer system show the Amazon rain forest to be a homogeneous, azimuthally-isotropic, radar target which is insensitive to polarization. The variation with angle of incidence may be adequately modeled as sigma deg (dB) = alpha theta + beta with typical values for the incidence-angle coefficient from 0.07 dB deg to 0.15 dB/deg. A small diurnal effect occurs, with measurements at sunrise being 0.5 dB to 1 dB higher than the rest of the day. Maximum likelihood estimation algorithms are presented which permit determination of relative bias and true pointing angle for each beam. Specific implementation of these algorithms for the proposed NOSS scatterometer system is also discussed.

Birrer, I. J.↗
NASA NTRS2016

Morton et al. Reply

Multiple mechanisms could lead to up-regulation of dry-season photosynthesis in Amazon forests, including canopy phenology and illumination geometry. We specifically tested two mechanisms for phenology-driven changes in Amazon forests during dry-season months, and the combined evidence from passive optical and lidar satellite data was incompatible with large net changes in canopy leaf area or leaf reflectance suggested by previous studies. We therefore hypothesized that seasonal changes in the fraction of sunlit and shaded canopies, one aspect of bidirectional reflectance effects in Moderate Resolution Imaging Spectroradiometer (MODIS) data, could alter light availability for dry-season photosynthesis and the photosynthetic capacity of Amazon forests without large net changes in canopy composition. Subsequent work supports the hypothesis that seasonal changes in illumination geometry and diffuse light regulate light saturation in Amazon forests. These studies clarify the physical mechanisms that govern light availability in Amazon forests from seasonal variability in direct and diffuse illumination. Previously, in the debate over light limitation of Amazon forest productivity, seasonal changes in the distribution of light within complex Amazon forest canopies were confounded with dry-season increases in total incoming photosynthetically active radiation. In the accompanying Comment, Saleska et al. do not fully account for this confounding effect of forest structure on photosynthetic capacity.

Morton, Douglas C.↗
NASA NTRS1994

Amazon Rain Forest Classification Using J-ERS-1 SAR Data

The Amazon rain forest is a region of the earth that is undergoing rapid change. Man-made disturbance, such as clear cutting for agriculture or mining, is altering the rain forest ecosystem. For many parts of the rain forest, seasonal changes from the wet to the dry season are also significant. Changes in the seasonal cycle of flooding and draining can cause significant alterations in the forest ecosystem.Because much of the Amazon basin is regularly covered by thick clouds, optical and infrared coverage from the LANDSAT and SPOT satellites is sporadic. Imaging radar offers a much better potential for regular monitoring of changes in this region. In particular, the J-ERS-1 satellite carries an L-band HH SAR system, which via an on-board tape recorder, can collect data from almost anywhere on the globe at any time of year.In this paper, we show how J-ERS-1 radar images can be used to accurately classify different forest types (i.e., forest, hill forest, flooded forest), disturbed areas such as clear cuts and urban areas, and river courses in the Amazon basin. J-ERS-1 data has also shown significant differences between the dry and wet season, indicating a strong potential for monitoring seasonal change. The algorithm used to classify J-ERS-1 data is a standard maximum-likelihood classifier, using the radar image local mean and standard deviation of texture as input. Rivers and clear cuts are detected using edge detection and region-growing algorithms. Since this classifier is intended to operate successfully on data taken over the entire Amazon, several options are available to enable the user to modify the algorithm to suit a particular image.

J-ERS-1↗
NASA NTRS2000

Predicting Fire Susceptibility in the Forests of Amazonia

Although fire is the single greatest threat to the ecological integrity of Amazon forests, our ability to predict the occurrence of Amazon forest fires is rudimentary. Part of the difficulty encountered in making such predictions is the remarkable capacity of Amazon forests to tolerate drought by tapping moisture stored in deep soil. These forests can avoid drought-induced leaf shedding by withdrawing moisture to depths of 8 meters and more. Hence, the absorption of deep soil moisture allows these forests to maintain their leaf canopies following droughts of several months duration, thereby maintaining the deep shade and high relative humidity of the forest interior that prevents these ecosystems from burning. But the drought- and fire-avoidance that is conferred by this deep-rooting phenomenon is not unlimited. During successive years of drought, such as those provoked by El Nino episodes, deep soil moisture can be depleted, and drought-induced leaf shedding begins. The goal of this project was to incorporate this knowledge of Amazon forest fire ecology into a predictive model of forest flammability.

Nepstad, Daniel C.↗
NASA NTRS1984

Analysis of normalized radar cross section (sigma-O) signature of Amazon rain forest using SEASAT scatterometer data

The normalized radar cross section (NRCS) signature of the Amazon rain forest was SEASAT scatterometer data. Statistics of the measured (NRCS) values were determined from multiple orbit passes for three local time periods. Plots of mean normalized radar cross section, dB against incidence angle as a function of beam and polarization show that less than 0.3 dB relative bias exists between all beams over a range of incidence angle from 30 deg to 53 deg. The backscattered measurements analyzed show the Amazon rain forest to be relatively homogeneous, azimuthally isotropic and insensitive to polarization. The return from the rain forest target appears relatively consistent and stable, except for the small diurnal variation (0.75 dB) that occurs at sunrise. Because of the relative stability of the rain forest target and the scatterometer instrument, the response of versus incidence angle was able to detect errors in the estimated yaw altitude angle. Also, small instrument gain biases in some of the processing channels were detected. This led to the development of an improved NRCS algorithm, which uses a more accurate method for estimating the system noise power.

Bracalente, E. M.↗
NASA NTRS1989

C-13/C-12 of atmospheric CO2 in the Amazon basin - Forest and river sources

Results are presented of measurements of the CO2 concentrations and C-13/C-12 ratios in CO2 in air samples collected from within the Amazonian rain forest and over the Amazon river between 1982 and 1987. Results indicate the presence of a diurnal cycle in the CO2 concentration and the C-13/C-12 ratio. It was found that the CO2 input to air in the forest was derived from the soil respiration, and the CO2 input to air over the Amazon river was derived from the degassing of CO2 from the river. It was also found that plants growing at heights lower than 7 m assimilate soil-derived CO2 with a low C-13/C-12 ratio.

Quay, Paul↗
NASA NTRS1982

Sigma/deg/ signature of the Amazon rain forest obtained from the Seasat scatterometer

Scatterometer data from Seasat of the Amazon rain forest were examined to determine if the region is suitable to use as a reference for calibration of radars. The consistency of Skylab data viewing the Amazon region prompted the analyses, and the Seasat-A scatterometer system (SASS) gathered data of the same region at varying angles. The instrument employed a 100 W 14.6 GHz signal with the reflected power sampled 61 times during each 1.89 sec measurement period. Doppler filters were used in 15 parallel channels of reception, and represented areas 20 km by 50-70 km. Tests were made of regional and temporal stability of the Amazon area, with five measurement angles averaged at different incidence angles to find the mean deviation, which was found to be less than 0.5 dB. Diurnal effects were confined to early morning, and further tests are recommended to obtain results for an entire year, to develop screening methods for thick clouds and rain, and to determine the deviation more precisely.

Birrer, I. J.↗
NASA NTRS1985

Information for space radar designers: Required dynamic range vs resolution and antenna calibration using the Amazon rain forest

Calibration of the vertical pattern of the antennas for the SEASAT scatterometer was accomplished using the nearly-uniform radar return from the Amazon rain forest. A similar calibration will be attempted for the SIR-B antenna. Thick calibration is important to establish the radiometric calibration across the swath of the SIR-B, and the developed methodology will provide an important tool in the evaluation of future spaceborne imaging radars. This calibration was made by the very-wide-beam SEASAT scatterometer antennas because at 14.65 GHz the scattering coefficient of the rain forest is almost independent of angle of incidence. It is expected that the variation in scattering coefficient for the rain forest across the relatively narrow vertical beam of the SIR-B will be very small; even at L band the forest should be essentially impenetrable for radar signals, the volume scatter from the treetops will predominate as at higher frequencies. The basic research elements include: (1) examination of SIR-B images over the rain forest to establish the variability of the scattering coefficient at finer resolutions than that of the SEASAT scatterometer; (2) analysis of the variability of SIR-B data detected prior to processing for either azimuth compression or; possibly, range compression so that averages over relatively large footprints can be used; (3) processing of data of the form of (2) using algorithms that can recover the vertical pattern of the antenna.

Moore, R. K.↗
NASA NTRS1986

Airborne and spaceborne radar images for geologic and environmental mapping in the Amazon rain forest, Brazil

Spaceborne and airborne radar image of portions of the Middle and Upper Amazon basin in the state of Amazonas and the Territory of Roraima are compared for purposes of geological and environmental mapping. The contrasted illumination geometries and imaging parameters are related to terrain slope and surface roughness characteristics for corresponding areas that were covered by each of the radar imaging systems. Landforms range from deeply dissected mountain and plateau with relief up to 500 m in Roraima, revealing ancient layered rocks through folded residual mountains to deeply beveled pediplain in Amazonas. Geomorphic features provide distinct textural signatures that are characteristic of different rock associations. The principle drainages in the areas covered are the Rio Negro, Rio Branco, and the Rio Japura. Shadowing effects and low radar sensitivity to subtle linear fractures that are aligned parallel or nearly parallel to the direction of radar illumination illustrate the need to obtain multiple coverage with viewing directions about 90 degrees. Perception of standing water and alluvial forest in floodplains varies with incident angle and with season. Multitemporal data sets acquired over periods of years provide an ideal method of monitoring environmental changes.

Ford, John P.↗
NASA NTRS2020

Impacts of Degradation on Water, Energy, and Carbon Cycling of the Amazon Tropical Forests

Selective logging, fragmentation, and understory fires directly degrade forest structure and composition. However, studies addressing the effects of forest degradation on carbon, water, and energy cycles are scarce. Here, we integrate field observations and high‐resolution remote sensing from airborne lidar to provide realistic initial conditions to the Ecosystem Demography Model (ED‐2.2) and investigate how disturbances from forest degradation affect gross primary production (GPP), evapotranspiration (ET), and sensible heat flux (H). We used forest structural information retrieved from airborne lidar samples (13,500 ha) and calibrated with 817 inventory plots (0.25 ha) across precipitation and degradation gradients in the eastern Amazon as initial conditions to ED‐2.2 model. Our results show that the magnitude and seasonality of fluxes were modulated by changes in forest structure caused by degradation. During the dry season and under typical conditions, severely degraded forests (biomass loss ≥66%) experienced water stress with declines in ET (up to 34%) and GPP (up to 35%) and increases of H (up to 43%) and daily mean ground temperatures (up to 6.5°C) relative to intact forests. In contrast, the relative impact of forest degradation on energy, water, and carbon cycles markedly diminishes under extreme, multiyear droughts, as a consequence of severe stress experienced by intact forests. Our results highlight that the water and energy cycles in the Amazon are driven by not only climate and deforestation but also the past disturbance and changes of forest structure from degradation, suggesting a much broader influence of human land use activities on the tropical ecosystems.

Marcos Longo↗
NASA NTRS2021

A Method for Landsat and Sentinel 2 (HLS) BRDF Normalization

The Harmonized Landsat/Sentinel-2 (HLS) project aims to generate a seamless surface reflectance product by combining observations from USGS/NASA Landsat-8 and ESA Sentinel-2 remote sensing satellites. These satellites’ sampling characteristics provide nearly constant observation geometry and low illumination variation through the scene. However, the illumination variation throughout the year impacts the surface reflectance by producing higher values for low solar zenith angles and lower reflectance for large zenith angles. In this work, we present a model to derive the bidirectional reflectance distribution function (BRDF) normalization and apply it to the HLS product at 30m spatial resolution. It is based on the BRDF parameters estimated from the MODerate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product (M{O,Y}D09) at 1 km spatial resolution using the VJB method (Vermote et al., 2009). Unsupervised classification (segmentation) of HLS images is used to disaggregate the BRDF parameters to the HLS spatial resolution and to build a BRDF parameters database at HLS scale. We first test the proposed BRDF normalization for different solar zenith angles over two homogeneous sites, in particular one desert and one Peruvian Amazon forest. The proposed method reduces both the correlation with the solar zenith angle and the coefficient of variation (CV) of the reflectance time series in the red and near infrared bands to 4% in forest and keeps a low CV of 3% to 4% for the deserts. Additionally, we assess the impact of the view zenith angle (VZA) in an area of the Brazilian Amazon forest close to the equator, where impact of the angular variation is stronger because it occurs in the principal plane. The directional reflectance shows a strong dependency with the VZA. The current HLS BRDF correction reduces this dependency but still shows an under-correction, especially in the near infrared, while the proposed method shows no dependency with the view angles. We also evaluate the BRDF parameters using field surface albedo measurements as a reference over seven different sites of the US surface radiation budget observing network (SURFRAD) and five sites of the Australian OzFlux network.

Belen Franch↗
NASA NTRS2004

Dust Transport and Deposition Observed from the Terra-MODIS Space Observations

Meteorological observations, in situ data and satellite images of dust episodes were used already in the 1970s to estimate that 100 tg of dust are transported from Africa over the Atlantic Ocean every year between June and August and deposited in the Atlantic Ocean and the Americas. Desert dust is a main source of nutrients to oceanic biota and the Amazon forest, but deteriorates air quality and caries pathogens as shown for Florida. Dust affects the Earth radiation budget, thus participating in climate change and feedback mechanisms. There is an urgent need for new tools for quantitative evaluation of the dust distribution, transport and deposition. The Terra spacecraft launched at the dawn of the last millennium provides first systematic well calibrated multispectral measurements from the MODIS instrument, for daily global analysis of aerosol. MODIS data are used here to distinguish dust from smoke and maritime aerosols and evaluate the African dust column concentration, transport and deposition. We found that 230+/-80 tg of dust are transported annually from Africa to the Atlantic Ocean, 30 tg return to Africa and Europe, 70 tg reach the Caribbean, 45 tg fertilize the Amazon Basin, 4 times as previous estimates thus explaining a paradox regarding the source of nutrition to the Amazon forest, and 120+/-40 tg are deposited in the Atlantic Ocean. The results are compared favorably with dust transport models for particle radius less than or equal to 12 microns. This study is a first example of quantitative use of MODIS aerosol for a geophysical study.

Kaufman, Y. J.↗
NASA NTRS2004

Dust Transport and Deposition Observed from the Terra-Moderate Image Spectrometer (MODIS) Space Observations

Meteorological observations, in situ data and satellite images of dust episodes were used already in the 1970s to estimate that 100 tg of dust are transported from Africa over the Atlantic Ocean every year between June and August and deposited in the Atlantic Ocean and the Americas. Desert dust is a main source of nutrients to oceanic biota and the Amazon forest, but deteriorates air quality and caries pathogens as shown for Florida. Dust affects the Earth radiation budget, thus participating in climate change and feedback mechanisms. There is an urgent need for new tools for quantitative evaluation of the dust distribution, transport and deposition. The Terra spacecraft launched at the dawn of the last millennium provides first systematic well calibrated multispectral measurements from the MODIS instrument, for daily global analysis of aerosol. MODIS data are used here to distinguish dust from smoke and maritime aerosols and evaluate the African dust column concentration, transport and deposition. We found that 230 plus or minus 80 tg of dust are transported annually from Africa to the Atlantic Ocean, 30 tg return to Africa and Europe, 70 tg reach the Caribbean, 45 tg fertilize the Amazon Basin, 4 times as previous estimates thus explaining a paradox regarding the source of nutrition to the Amazon forest, and 120 plus or minus 40 tg are deposited in the Atlantic Ocean. The results are compared favorably with dust transport models for particle radius less than or equal to 12 microns. This study is a first example of quantitative use of MODIS aerosol for a geophysical study.

Kaufman, Y.↗
NASA NTRS2016

Consistency of Vegetation Index Seasonality Across the Amazon Rainforest

Vegetation indices (VIs) calculated from remotely sensed reflectance are widely used tools for characterizing the extent and status of vegetated areas. Recently, however, their capability to monitor the Amazon forest phenology has been intensely scrutinized. In this study, we analyze the consistency of VIs seasonal patterns obtained from two MODIS products: the Collection 5 BRDF product (MCD43) and the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC). The spatio-temporal patterns of the VIs were also compared with field measured leaf litterfall, gross ecosystem productivity and active microwave data. Our results show that significant seasonal patterns are observed in all VIs after the removal of view-illumination effects and cloud contamination. However, we demonstrate inconsistencies in the characteristics of seasonal patterns between different VIs and MODIS products. We demonstrate that differences in the original reflectance band values form a major source of discrepancy between MODIS VI products. The MAIAC atmospheric correction algorithm significantly reduces noise signals in the red and blue bands. Another important source of discrepancy is caused by differences in the availability of clear-sky data, as the MAIAC product allows increased availability of valid pixels in the equatorial Amazon. Finally, differences in VIs seasonal patterns were also caused by MODIS collection 5 calibration degradation. The correlation of remote sensing and field data also varied spatially, leading to different temporal offsets between VIs, active microwave and field measured data. We conclude that recent improvements in the MAIAC product have led to changes in the characteristics of spatio-temporal patterns of VIs seasonality across the Amazon forest, when compared to the MCD43 product. Nevertheless, despite improved quality and reduced uncertainties in the MAIAC product, a robust biophysical interpretation of VIs seasonality is still missing.

MAIAC↗
NASA NTRS2014

Abrupt Increases in Amazonian Tree Mortality Due to Drought-Fire Interactions

Interactions between climate and land-use change may drive widespread degradation of Amazonian forests. High-intensity fires associated with extreme weather events could accelerate this degradation by abruptly increasing tree mortality, but this process remains poorly understood. Here we present, to our knowledge, the first field-based evidence of a tipping point in Amazon forests due to altered fire regimes. Based on results of a large-scale, longterm experiment with annual and triennial burn regimes (B1yr and B3yr, respectively) in the Amazon, we found abrupt increases in fire-induced tree mortality (226 and 462%) during a severe drought event, when fuel loads and air temperatures were substantially higher and relative humidity was lower than long-term averages. This threshold mortality response had a cascading effect, causing sharp declines in canopy cover (23 and 31%) and aboveground live biomass (12 and 30%) and favoring widespread invasion by flammable grasses across the forest edge area (80 and 63%), where fires were most intense (e.g., 220 and 820 kW x m(exp −1)). During the droughts of 2007 and 2010, regional forest fires burned 12 and 5% of southeastern Amazon forests, respectively, compared with less than 1% in nondrought years. These results show that a few extreme drought events, coupled with forest fragmentation and anthropogenic ignition sources, are already causing widespread fire-induced tree mortality and forest degradation across southeastern Amazon forests. Future projections of vegetation responses to climate change across drier portions of the Amazon require more than simulation of global climate forcing alone and must also include interactions of extreme weather events, fire, and land-use change.

MODIS↗