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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Water availability modulates maximum canopy heights of low-elevation Amazonian second-growth forests

Tropical second-growth forests of the Amazon sequester large amounts of carbon and are important carbon sinks, contributing substantially to climate change mitigation, biodiversity conservation, and providing crucial ecosystem services. Deforestation due to selective logging and shifting cultivation is expanding second-growth forest areas in tropical forest regions, which if well managed, regenerate rapidly over time. Maximum forest canopy height is an important metric of biomass and carbon accumulation in second-growth forests and is strongly influenced by water availability. The water limitation hypothesis explains the positive influence of water availability on maximum tree heights and has been examined and demonstrated at a small-scale using field data, and at a global scale, with limited accuracy, using remote sensing data in tropical ecosystems. However, this hypothesis concerning maximum canopy height has not been much studied at regional and national scales for tropical second-growth forests. In this study, we leveraged NASA GEDI spaceborne lidar data across the Brazilian Amazon and derived second-growth forest relative height metrics for delineating the influence of water availability, second-growth forest age, and topographic elevation on maximum canopy height. Water availability was found to significantly influence the maximum canopy height of second-growth forest trees, of age range from 30 to 35 years, at elevations less than 500 m and maximum precipitation thresholds of 1500 mm. Our results indicate that changing precipitation patterns or increased drought conditions under different climate change regimes could impact forest structure, plant communities, ecosystem functioning, and carbon sequestration capabilities of tropical second-growth forests in the Amazon.

Carbon sequestration↗
NASA NTRS2015

Structural Dynamics of Tropical Moist Forest Gaps

Gap phase dynamics are the dominant mode of forest turnover in tropical forests. However, gap processes are infrequently studied at the landscape scale. Airborne lidar data offer detailed information on three-dimensional forest structure, providing a means to characterize fine-scale (1 m) processes in tropical forests over large areas. Lidar-based estimates of forest structure (top down) differ from traditional field measurements (bottom up), and necessitate clear-cut definitions unencumbered by the wisdom of a field observer. We offer a new definition of a forest gap that is driven by forest dynamics and consistent with precise ranging measurements from airborne lidar data and tall, multi-layered tropical forest structure. We used 1000 ha of multi-temporal lidar data (2008, 2012) at two sites, the Tapajos National Forest and Ducke Reserve, to study gap dynamics in the Brazilian Amazon. Here, we identified dynamic gaps as contiguous areas of significant growth, that correspond to areas greater than 10 sq m, with height less than 10 m. Applying the dynamic definition at both sites, we found over twice as much area in gap at Tapajos National Forest (4.8%) as compared to Ducke Reserve (2.0%). On average, gaps were smaller at Ducke Reserve and closed slightly more rapidly, with estimated height gains of 1.2 m y-1 versus 1.1 m y-1 at Tapajos. At the Tapajos site, height growth in gap centers was greater than the average height gain in gaps (1.3 m y-1 versus 1.1 m y-1). Rates of height growth between lidar acquisitions reflect the interplay between gap edge mortality, horizontal ingrowth and gap size at the two sites. We estimated that approximately 10% of gap area closed via horizontal ingrowth at Ducke Reserve as opposed to 6% at Tapajos National Forest. Height loss (interpreted as repeat damage and/or mortality) and horizontal ingrowth accounted for similar proportions of gap area at Ducke Reserve (13% and 10%, respectively). At Tapajos, height loss had a much stronger signal (23% versus 6%) within gaps. Both sites demonstrate limited gap contagiousness defined by an increase in the likelihood of mortality in the immediate vicinity ((is) approximately 6 m) of existing gaps.

Structural Dynamics of Tropical Moist Forest Gaps↗
DOE OSTI2026

Optimizing Cryo-Focused Pyrolysis GC/MS for Tracing Soil Organic Matter Across Diverse Ecosystems

The cycling of organic matter in terrestrial soils and sediments is central to a range of biogeochemical processes that regulate nutrient cycling, crop productivity, trace gas emissions, and contaminant transport. Pyrolysis-gas chromatography/mass spectrometry (py-GC/MS) is a powerful tool for characterizing bulk soil organic matter (SOM) at the molecular level. In this study, we used a cryo-focused py-GC/MS system to analyze soil samples from seven diverse ecosystems: vernal pool, prairie pothole, temperate forest, tropical forest, tundra, wildfire-affected boreal forest, and grassland. We addressed a key bottleneck in molecular-level SOM characterization by developing an automated data analysis pipeline to optimize py-GC/MS and complementary evolved gas analysis/mass spectrometry (EGA/MS) methods, incorporating advanced tools for peak deconvolution, developing a custom compound class library, and implementing fragmentation spectrum-based molecular networking for the first time. This improved workflow was applied to soil samples from all seven ecosystems, including multiple depths and density fractions. Our findings demonstrate that ecosystem type plays a dominant role in shaping compositional differences in SOM. We also identified trends in the source of SOM compounds (e.g., microbial vs plantderived) across soil depth and density fractions, which are critical for understanding persistence and turnover of SOM. Our molecular networking analysis indicated that although many compounds are widespread across ecosystems, others are restricted to specific environments, such as wetlands. This underscores the utility of molecular-level data in elucidating the complexity of SOM composition and the environmental drivers that shape it. Such molecular-level insights can deepen our knowledge of biogeochemical SOM cycles.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1995

On the potential of long wavelength imaging radars for mapping vegetation types and woody biomass in tropical rain forests

In the tropical rain forests of Manu, in Peru, where forest biomass ranges from 4 kg/sq m in young forest succession up to 100 kg/sq m in old, undisturbed floodplain stands, the P-band polarimetric radar data gathered in June of 1993 by the AIRSAR (Airborne Synthetic Aperture Radar) instrument separate most major vegetation formations and also perform better than expected in estimating woody biomass. The worldwide need for large scale, updated biomass estimates, achieved with a uniformly applied method, as well as reliable maps of land cover, justifies a more in-depth exploration of long wavelength imaging radar applications for tropical forests inventories.

Rignot, Eric J.↗
NASA NTRS1982

Vegetation survey in Amazonia using LANDSAT data

Automatic Image-100 analysis of LANDSAT data was performed using the MAXVER classification algorithm. In the pilot area, four vegetation units were mapped automatically in addition to the areas occupied for agricultural activities. The Image-100 classified results together with a soil map and information from RADAR images, permitted the establishment of the final legend with six classes: semi-deciduous tropical forest; low land evergreen tropical forest; secondary vegetation; tropical forest of humid areas, predominant pastureland and flood plains. Two water types were identified based on their sediments indicating different geological and geomorphological aspects.

Parada, N. D. J.↗
DOE OSTI2025

Thermal stress in degraded forests in the Brazilian Amazon Arc of Deforestation

Understanding thermal stress in tropical forests has taken on new urgency in light of accelerating climate change and expansion of deforestation and forest degradation. Degraded tropical forests in particular may be approaching critical temperature thresholds even more rapidly than intact forests, with implications for tree survival and ecosystem recovery. We investigate thermal stress in degraded tropical forests within the Brazilian Amazon Arc of Deforestation. Using land surface temperature data from the ECOsystem Spaceborne Thermal Radiometer Experiment on the international Space Station (ECOSTRESS), we compared canopy temperatures of intact, selectively logged, and burned forests in Feliz Natal, Mato Grosso, Brazil. Upper canopy temperatures in previously burned forests were 4.1% higher (mean = 36.5 °C) and 50.9% more variable compared to intact and logged forests, which showed remarkably similar temperature distributions (means of 34.9 °C and 35.1 °C, respectively). Modeled leaf temperature distributions based on canopy temperature measurements from one of the warmest days in a 2 year dry season record indicated that 87% of leaves in the warmest burned forest patches exceeded the temperature threshold where respiration surpasses photosynthesis, compared to approximately 72%–74% in intact and logged forests, respectively, in the same time period. After controlling for environmental factors, burned forests were predicted to be 2.6 °C warmer on average [1.39 °C–3.96 °C, 95% credible interval] than intact forests across a 5–40 m canopy height range. Burned forests showed modest thermal recovery over time, with temperatures decreasing by approximately 1.2 °C over a 30 year recovery period. In contrast, logged forests showed minimal thermal differences from intact forests (−0.353 on average, [−1.125–0.274, 95% credible interval]) and negligible change (0.15 °C) over the same timeframe. While the absolute probabilities of exceeding damaging thermal thresholds remain low across all forest types under current climate conditions, the probability of leaves exceeding temperatures that cause permanent leaf damage was ten times higher in burned forests, with implications for the future of burned forest regeneration in water-limited regions of the Amazon basin. In particular, the combination of higher mean temperatures, greater temperature variability, and more frequent exposure to damaging thermal thresholds implies that burned tropical forests will experience substantially higher mortality rates and slower biomass recovery compared to intact and selectively logged forests, especially in water-limited regions where trees cannot rely on evaporative cooling to moderate canopy temperatures.

Brazilian Amazon Arc of Deforestation↗
NASA NTRS2012

Contrasting Patterns of Damage and Recovery in Logged Amazon Forests From Small Footprint LiDAR Data

Tropical forests ecosystems respond dynamically to climate variability and disturbances on time scales of minutes to millennia. To date, our knowledge of disturbance and recovery processes in tropical forests is derived almost exclusively from networks of forest inventory plots. These plots typically sample small areas (less than or equal to 1 ha) in conservation units that are protected from logging and fire. Amazon forests with frequent disturbances from human activity remain under-studied. Ongoing negotiations on REDD+ (Reducing Emissions from Deforestation and Forest Degradation plus enhancing forest carbon stocks) have placed additional emphasis on identifying degraded forests and quantifying changing carbon stocks in both degraded and intact tropical forests. We evaluated patterns of forest disturbance and recovery at four -1000 ha sites in the Brazilian Amazon using small footprint LiDAR data and coincident field measurements. Large area coverage with airborne LiDAR data in 2011-2012 included logged and unmanaged areas in Cotriguacu (Mato Grosso), Fiona do Jamari (Rondonia), and Floresta Estadual do Antimary (Acre), and unmanaged forest within Reserva Ducke (Amazonas). Logging infrastructure (skid trails, log decks, and roads) was identified using LiDAR returns from understory vegetation and validated based on field data. At each logged site, canopy gaps from logging activity and LiDAR metrics of canopy heights were used to quantify differences in forest structure between logged and unlogged areas. Contrasting patterns of harvesting operations and canopy damages at the three logged sites reflect different levels of pre-harvest planning (i.e., informal logging compared to state or national logging concessions), harvest intensity, and site conditions. Finally, we used multi-temporal LiDAR data from two sites, Reserva Ducke (2009, 2012) and Antimary (2010, 2011), to evaluate gap phase dynamics in unmanaged forest areas. The rates and patterns of canopy gap formation at these sites illustrate potential issues for separating logging damages from natural forest disturbances over longer time scales. Multi-temporal airborne LiDAR data and coincident field measurements provide complementary perspectives on disturbance and recovery processes in intact and degraded Amazon forests. Compared to forest inventory plots, the large size of each individual site permitted analyses of landscape-scale processes that would require extremely high investments to study using traditional forest inventory methods.

Morton, D. C.↗
DOE OSTI2026

AmeriFlux FLUXNET-1F MX-Aog Alamos Old-Growth tropical dry forest

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site MX-Aog Alamos Old-Growth tropical dry forest. This is the FLUXNET version of the carbon flux data for the site MX-Aog Alamos Old-Growth tropical dry forest produced by applying the standard ONEFlux (1F) software. Site Description - This tower is located at a patch of remnant old growth tropical dry forest where the dominant vegetation are leguminous trees and a notorious presence of the genus Brusera. The site is at about 18 km from the municipality of Alamos Sonora Mexico within a private ranch managed by the NGO Nature Culture International. The area is also within a federally protected land named “Area de Proteccion de Flora y Fauna Sierra de Alamos Rio-Cuchijaqui" in the catalog of the “Comision Nacional de Areas Naturales Protegidas (CONANP-Mexico)”. The preserved ranch is surrounded by a mosaic of forest patches with different successional stages of tropical dry forest, and some places that are used for local agriculture and livestock. This ecosystem lies in a highly seasonal region under the influence of the North American Monsoon that brings about 70% of the rains from July to September.

Yepez, Enrico A. [Instituto Tecnologico de Sonora]↗
NASA NTRS2019

Biomass-Burning Smoke Heights over the Amazon Observed from Space

We characterise the vertical distribution of biomass-burning emissions across the Amazon during the biomass-burning season (July–November) with an extensive climatology of smoke plumes derived from MISR and MODIS (2005–2012) and CALIOP (2006–2012) observations. Smoke plume heights exhibit substantial variability, spanning a few hundred metres up to 6 km above the terrain. However, the majority of the smoke is located at altitudes below 2.5 km. About 60 % of smoke plumes are observed in drought years, 40 %–50 % at the peak month of the burning season (September) and 94 % over tropical forest and savanna regions, with respect to the total number of smoke plume observations. At the time of the MISR observations (10:00–11:00 LT), the highest plumes are detected over grassland fires (with an averaged maximum plume height of ∼1100 m) and the lowest plumes occur over tropical forest fires (∼800 m). A similar pattern is found later in the day (14:00–15:00 LT) with CALIOP, although at higher altitudes (2300 m grassland vs. 2000 m tropical forest), as CALIOP typically detects smoke at higher altitudes due to its later overpass time, associated with a deeper planetary boundary layer, possibly more energetic fires, and greater sensitivity to thin aerosol layers. On average, 3 %–20 % of the fires inject smoke into the free troposphere; this percentage tends to increase toward the end of the burning season (November: 15 %–40 %). We find a well-defined seasonal cycle between MISR plume heights, MODIS fire radiative power and atmospheric stability across the main biomes of the Amazon, with higher smoke plumes, more intense fires and reduced atmospheric stability conditions toward the end of the burning season. Lower smoke plume heights are detected during drought (800 m) compared to non-drought (1100 m) conditions, in particular over tropical forest and savanna fires. Drought conditions favour understory fires over tropical forest, which tend to produce smouldering combustion and low smoke injection heights. Droughts also seem to favour deeper boundary layers and the percentage of smoke plumes that reach the free troposphere is lower during these dry conditions. Consistent with previous studies, the MISR mid-visible aerosol optical depth demonstrates that smoke makes a significant contribution to the total aerosol loading over the Amazon, which in combination with lower injection heights in drought periods has important implications for air quality. This work highlights the importance of biome type, fire properties and atmospheric and drought conditions for plume dynamics and smoke loading. In addition, our study demonstrates the value of combining observations of MISR and CALIOP constraints on the vertical distribution of smoke from biomass burning over the Amazon.

Gonzalez-Alonso, Laura↗
NASA NTRS2012

Retrieval of Vertical LAI Profiles Over Tropical Rain Forests using Waveform Lidar at La Selva, Costa Rica

This study explores the potential of waveform lidar in mapping the vertical and spatial distributions of leaf area index (LAI) over the tropical rain forest of La Selva Biological Station in Costa Rica. Vertical profiles of LAI were derived at 0.3 m height intervals from the Laser Vegetation Imaging Sensor (LVIS) data using the Geometric Optical and Radiative Transfer (GORT) model. Cumulative LAI profiles obtained from LVIS were validated with data from 55 ground to canopy vertical transects using a modular field tower to destructively sample all vegetation. Our results showed moderate agreement between lidar and field derived LAI (r2=0.42, RMSE=1.91, bias=−0.32), which further improved when differences between lidar and tower footprint scales (r2=0.50, RMSE=1.79, bias=0.27) and distance of field tower from lidar footprint center (r2=0.63, RMSE=1.36, bias=0.0) were accounted for. Next, we mapped the spatial distribution of total LAI across the landscape and analyzed LAI variations over different land cover types. Mean values of total LAI were 1.74, 5.20, 5.41 and 5.62 over open pasture, secondary forests, regeneration forests after selective-logging and old-growth forests respectively. Lastly, we evaluated the sensitivities of our LAI retrieval model to variations in canopy/ground reflectance ratio and to waveform noise such as induced by topographic slopes. We found for both, that the effects were not significant for moderate LAI values (about 4). However model derivations of LAI might be inaccurate in areas of high-slope and high LAI (about 8) if ground return energies are low. This research suggests that large footprint waveform lidar can provide accurate vertical LAI profile estimates that do not saturate even at the high LAI levels in tropical rain forests and may be a useful tool for understanding the light transmittance within these canopies.

Tang, Hao↗
NASA NTRS1989

Tropical deforestation and species endangerment - The role of remote sensing

Initial results of a pilot study to link remotely sensed information on tropical forest loss to field-based information on species endangerment are presented. LANDSAT MSS imagery was used to estimate net forest removal, regrowth, and forest edges in Mabira Forest in Uganda during 15-year period. Although four distinct types of closed tropical forest based on structure of dominance could be recognized on the ground, the types could not be distinguished according to differences in spectral reflectance in the MSS bands; yet the closed tropical forest could be readily distinguished from nonforest vegetation types. It is concluded that the utilization of MSS for this purpose is likely to be most successful when combined with larger-scale resolution imagery, such as TM, SPOT, and aerial photography, as well as existing vegetation maps. Of significant promise, however, is the ability to differentiate disturbance regimes, regrowth, and exterior and interior edges of tropical closed forest by the combined use of MSS imagery and ground data.

Westman, Walter E.↗
NASA NTRS2001

An Integrated Use of Experimental, Modeling and Remote Sensing Techniques to Investigate Carbon and Phosphorus Dynamics in the Humid Tropics

Moist tropical forests comprise one of the world's largest and most diverse biomes, and exchange more carbon, water, and energy with the atmosphere than any other ecosystem. In recent decades, tropical forests have also become one of the globe's most threatened biomes, subjected to exceptionally high rates of deforestation and land degradation. Thus, the importance of and threats to tropical forests are undeniable, yet our understanding of basic ecosystem processes in both intact and disturbed portions of the moist tropics remains poorer than for almost any other major biome. Our approach in this project was to take a multi-scale, multi-tool approach to address two different problems. First, we wanted to test if land-use driven changes in the cycles of probable limiting nutrients in forest systems were a key driver in the frequently observed pattern of declining pasture productivity and carbon stocks. Given the enormous complexity of land use change in the tropics, in which one finds a myriad of different land use types and intensities overlain on varying climates and soil types, we also wanted to see if new remote sensing techniques would allow some novel links between parameters which could be sensed remotely, and key biogeochemical variables which cannot. Second, we addressed to general questions about the role of tropical forests in the global carbon cycle. First, we used a new approach for quantifying and minimizing non-biological artifacts in the NOAA/NASA AVHRR Pathfinder time series of surface reflectance data so that we could address potential links between Amazonian forest dynamics and ENSO cycles. Second, we showed that the disequilibrium in C-13 exchanged between land and atmosphere following tropical deforestation probably has a significant impact on the use of 13-CO2 data to predict regional fluxes in the global carbon cycle.

Townsend, Alan R.↗
NASA NTRS2021

The Role of Fire in Global Forest Loss Dynamics

Fires, among other forms of natural and anthropogenic disturbance, play a central role in regulating the location, composition and biomass of forests. Understanding the role of fire in global forest loss is crucial in constraining land-use change emissions and the global carbon cycle. We analysed the relationship between forest loss and fire at 500 m resolution based on satellite-derived data for the 2003–2018 period. Satellite fire data included burned area and active fire detections, to best account for large and small fires, respectively. We found that, on average, 38 ± 9% (± range) of global forest loss was associated with fire, and this fraction remained relatively stable throughout the study period. However, the fraction of fire-related forest loss varied substantially on a regional basis, and showed statistically significant trends in key tropical forest areas. Decreases in the fraction of fire-related forest loss were found where deforestation peaked early in our study period, including the Amazon and Indonesia while increases were found for tropical forests in Africa. The inclusion of active fire detections accounted for 41%, on average, of the total fire-related forest loss, with larger contributions in small clearings in interior tropical forests and human-dominated landscapes. Comparison to higher-resolution fire data with resolutions of 375 and 20 m indicated that commission errors due to coarse resolution fire data largely balanced out omission errors due to missed small fire detections for regional to continental-scale estimates of fire-related forest loss. Besides an improved understanding of forest dynamics, these findings may help to refine and separate fire-related and non-fire-related land-use change emissions in forested ecosystems.

Dan van Wees↗
NASA NTRS1992

Geographic information system for fusion and analysis of high-resolution remote sensing and ground truth data

We seek to combine high-resolution remotely sensed data with models and ground truth measurements, in the context of a Geographical Information System, integrated with specialized image processing software. We will use this integrated system to analyze the data from two Case Studies, one at a bore Al forest site, the other a tropical forest site. We will assess the information content of the different components of the data, determine the optimum data combinations to study biogeophysical changes in the forest, assess the best way to visualize the results, and validate the models for the forest response to different radar wavelengths/polarizations. During the 1990's, unprecedented amounts of high-resolution images from space of the Earth's surface will become available to the applications scientist from the LANDSAT/TM series, European and Japanese ERS-1 satellites, RADARSAT and SIR-C missions. When the Earth Observation Systems (EOS) program is operational, the amount of data available for a particular site can only increase. The interdisciplinary scientist, seeking to use data from various sensors to study his site of interest, may be faced with massive difficulties in manipulating such large data sets, assessing their information content, determining the optimum combinations of data to study a particular parameter, visualizing his results and validating his model of the surface. The techniques to deal with these problems are also needed to support the analysis of data from NASA's current program of Multi-sensor Airborne Campaigns, which will also generate large volumes of data. In the Case Studies outlined in this proposal, we will have somewhat unique data sets. For the Bonanza Creek Experimental Forest (Case I) calibrated DC-8 SAR data and extensive ground truth measurement are already at our disposal. The data set shows documented evidence to temporal change. The Belize Forest Experiment (Case II) will produce calibrated DC-8 SAR and AVIRIS data, together with extensive measurements on the tropical rain forest itself. The extreme range of these sites, one an Arctic forest, the other a tropical rain forest, has been deliberately chosen to find common problems which can lead to generalized observations and unique problems with data which raise issues for the EOS System.

Freeman, Anthony↗
NASA NTRS1993

Geographic information system for fusion and analysis of high-resolution remote sensing and ground data

We seek to combine high-resolution remotely sensed data with models and ground truth measurements, in the context of a Geographical Information System (GIS), integrated with specialized image processing software. We will use this integrated system to analyze the data from two Case Studies, one at a boreal forest site, the other a tropical forest site. We will assess the information content of the different components of the data, determine the optimum data combinations to study biogeophysical changes in the forest, assess the best way to visualize the results, and validate the models for the forest response to different radar wavelengths/polarizations. During the 1990's, unprecedented amounts of high-resolution images from space of the Earth's surface will become available to the applications scientist from the LANDSAT/TM series, European and Japanese ERS-1 satellites, RADARSAT and SIR-C missions. When the Earth Observation Systems (EOS) program is operational, the amount of data available for a particular site can only increase. The interdisciplinary scientist, seeking to use data from various sensors to study his site of interest, may be faced with massive difficulties in manipulating such large data sets, assessing their information content, determining the optimum combinations of data to study a particular parameter, visualizing his results and validating his model of the surface. The techniques to deal with these problems are also needed to support the analysis of data from NASA's current program of Multi-sensor Airborne Campaigns, which will also generate large volumes of data. In the Case Studies outlined in this proposal, we will have somewhat unique data sets. For the Bonanza Creek Experimental Forest (Case 1) calibrated DC-8 SAR (Synthetic Aperture Radar) data and extensive ground truth measurement are already at our disposal. The data set shows documented evidence to temporal change. The Belize Forest Experiment (Case 2) will produce calibrated DC-8 SAR and AVIRIS data, together with extensive measurements on the tropical rain forest itself. The extreme range of these sites, one an Arctic forest, the other a tropical rain forest, has been deliberately chosen to find common problems which can lead to generalized observations and unique problems with data which raise issues for the EOS System.

Freeman, Anthony↗
NASA NTRS2000

Tropical Deforestation in the Bolivian Amazon

Landsat satellite images from the mid-1980s and early 1990s were used to map tropical forest extent and deforestation in approximately 800,000 sq km of Amazonian Bolivia. Forest cover extent, including tropical deciduous forest, totalled 472,000 sq km while the area of natural non-forest formations totalled 298,000 sq km. The area deforested totalled 15,000 sq km in the middle 1980s and 28,800 sq km by the early 1990s. The rate of tropical deforestation in the >1,000 mm/y precipitation forest zone of Bolivia was 2,200 sq km/y from 1985-1986 to 1992-1994. We document a spatially-concentrated "deforestation zone" in Santa Cruz Department where >60% of the Bolivian deforestation is occurring at an accelerating rate in areas of tropical deciduous dry forest.

Tucker, Compton J.↗
NASA NTRS1989

Radar modeling of tropical mangal forest stands

Radar modeling of mangal forest stands in the Sundarbans area of southern Bangladesh is discussed. The modeling uses radar system parameters with forest data on tree height, spacing, biomass, species combinations, and water content (including slightly conductive water) in leaves and trunks of the mangal. For Sundri and Gewa tropical mangal forests, six model components are proposed; the models are required to explain the contributions of various combinations of forest species in the attenuation and scattering of mangal-vegetated nonflooded or flooded surfaces. Statistical data of simulated images have been compared with those of SIR-B images both to refine the modeling procedures and to characterize the model output appropriately. The possibility of delineation of flooded or nonflooded boundaries is discussed.

Wang, Yong↗
NASA NTRS2012

Monitoring Strategies for REDD+: Integrating Field, Airborne, and Satellite Observations of Amazon Forests

Large-scale tropical forest monitoring efforts in support of REDD+ (Reducing Emissions from Deforestation and forest Degradation plus enhancing forest carbon stocks) confront a range of challenges. REDD+ activities typically have short reporting time scales, diverse data needs, and low tolerance for uncertainties. Meeting these challenges will require innovative use of remote sensing data, including integrating data at different spatial and temporal resolutions. The global scientific community is engaged in developing, evaluating, and applying new methods for regional to global scale forest monitoring. Pilot REDD+ activities are underway across the tropics with support from a range of national and international groups, including SilvaCarbon, an interagency effort to coordinate US expertise on forest monitoring and resource management. Early actions on REDD+ have exposed some of the inherent tradeoffs that arise from the use of incomplete or inaccurate data to quantify forest area changes and related carbon emissions. Here, we summarize recent advances in forest monitoring to identify and target the main sources of uncertainty in estimates of forest area changes, aboveground carbon stocks, and Amazon forest carbon emissions.

Morton, Douglas↗