SEARCH · Engineering Papers

Results for “Forest”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 973 records · Page 54

All sources NASA NTRS DOE OSTI

NASA NTRS2007

Emissions from Forest Fires near Mexico City

The emissions of NOx (defined as NO (nitric oxide) + NO2 (nitrogen dioxide)) and hydrogen cyanide (HCN), per unit amount of fuel burned, from fires in the pine forests that dominate the mountains surrounding Mexico City (MC) are about 2 times higher than normally observed for forest burning. The ammonia (NH3) emissions are about average for forest burning. The upper limit for the mass ratio of NOX to volatile organic compounds (VOC) for these MC-area mountain fires was approximately 0.38, which is similar to the NOx/VOC ratio in the MC urban area emissions inventory of 0.34, but much larger than the NOx/VOC ratio for tropical forest fires in Brazil (approximately 0.068). The nitrogen enrichment in the fire emissions may be due to deposition of nitrogen-containing pollutants in the outflow from the MC urban area. This effect may occur worldwide wherever biomass burning coexists with large urban areas (e.g. the tropics, southeastern US, Los Angeles Basin). The molar emission ratio of HCN to carbon monoxide (CO) for the mountain fires was 0.012 +/- 0.007, which is 2-9 times higher than widely used literature values for biomass burning. The ambient molar ratio HCN/CO in the MC-area outflow is about 0.003 +/- 0.0003. Thus, if only mountain fires emit significant amounts of HCN, these fires may be contributing about 25% of the CO production in the MCarea (approximately 98-100 W and 19-20 N). Comparing the PM10/CO and PM2.5/CO mass ratios in the MC Metropolitan Area emission inventory (0.01 15 and 0.0037) to the PM1/CO mass ratio for the mountain fires (0.133) then suggests that these fires could produce as much as approximately 79-92% of the primary fine particle mass generated in the MC-area. Considering both the uncertainty in the HCN/CO ratios and secondary aerosol formation in the urban and fire emissions implies that about 50 +/- 30% of the "aged" fine particle mass in the March 2006 MC-area outflow could be from these fires.

Yokelson, R.↗

NASA NTRS2010

Use of NASA Satellite Data to Improve Coastal Cypress Forest Management

Problem: Information gaps exist regarding health status and location of cypress forests in coastal Louisiana (LA). Such information is needed to aid coastal forest conservation and restoration programs. Approach to Issue Mitigation: Use NASA data to revise cypress forest cover type maps. Landsat and ASTER data. Use NASA data to identify and track cypress forest change. Landsat, ASTER, and MODIS data. Work with partners and end-users to transfer useful products and technology.

Spurce, Joseph↗

NASA NTRS2010

Resilience of Alaska's Boreal Forest to Climatic Change

This paper assesses the resilience of Alaska s boreal forest system to rapid climatic change. Recent warming is associated with reduced growth of dominant tree species, plant disease and insect outbreaks, warming and thawing of permafrost, drying of lakes, increased wildfire extent, increased postfire recruitment of deciduous trees, and reduced safety of hunters traveling on river ice. These changes have modified key structural features, feedbacks, and interactions in the boreal forest, including reduced effects of upland permafrost on regional hydrology, expansion of boreal forest into tundra, and amplification of climate warming because of reduced albedo (shorter winter season) and carbon release from wildfires. Other temperature-sensitive processes for which no trends have been detected include composition of plant and microbial communities, long-term landscape-scale change in carbon stocks, stream discharge, mammalian population dynamics, and river access and subsistence opportunities for rural indigenous communities. Projections of continued warming suggest that Alaska s boreal forest will undergo significant functional and structural changes within the next few decades that are unprecedented in the last 6000 years. The impact of these social ecological changes will depend in part on the extent of landscape reorganization between uplands and lowlands and on policies regulating subsistence opportunities for rural communities.

Chapin, F. S., III↗

NASA NTRS2010

Alaska's Changing Fire Regime - Implications for the Vulnerability of Its Boreal Forests

A synthesis was carried out to examine Alaska s boreal forest fire regime. During the 2000s, an average of 767 000 ha/year burned, 50% higher than in any previous decade since the 1940s. Over the past 60 years, there was a decrease in the number of lightning-ignited fires, an increase in extreme lightning-ignited fire events, an increase in human-ignited fires, and a decrease in the number of extreme human-ignited fire events. The fraction of area burned from humanignited fires fell from 26% for the 1950s and 1960s to 5% for the 1990s and 2000s, a result from the change in fire policy that gave the highest suppression priorities to fire events that occurred near human settlements. The amount of area burned during late-season fires increased over the past two decades. Deeper burning of surface organic layers in black spruce (Picea mariana (Mill.) BSP) forests occurred during late-growing-season fires and on more well-drained sites. These trends all point to black spruce forests becoming increasingly vulnerable to the combined changes of key characteristics of Alaska s fire regime, except on poorly drained sites, which are resistant to deep burning. The implications of these fire regime changes to the vulnerability and resilience of Alaska s boreal forests and land and fire management are discussed.

Kasischke, E. S.↗

NASA NTRS2010

Complex Spatial Structure in a Population of Didymopanax pittieri, A Tree of Wind-Exposed Lower Montane Rain Forest

Didymopanax pittieri is a common shade-intolerant tree colonizing treefall gaps in the elfin forests on windswept ridgecrests in the lower montane rain forests of the Cordillera de Tilarain, Costa Rica. All D. pittieri taller than > 0.5 m in a 5.2-ha elfin forested portion of a gridded study watershed in the Monteverde Cloud Forest Preserve were located, mapped, and measured. This local population of D. pittieri is spatially inhomogeneous, in that density increases with increasing wind exposure; D. pittieri are more abundant near ridge crests than lower on windward slopes. The important and ubiquitous phenomenon of spatial inhomogeneity in population density is addressed and corrected for in spatial analyses by the application of the inhomogeneous version of Ripley's K. The spatial patterns of four size classes of D. pittieri (<5 cm dbh, 5-10 cm dbh, 10-20 cm dbh, and> 20 cm dbh) were investigated. Within the large-scale trend in density driven by wind exposure, D. pittieri saplings are clumped at the scale of treefall gaps and at the scale of patches of aggregated gaps. D. pittieri 5-10 cm dbh are randomly distributed, apparently due to competitive thinning of sapling clumps during the early stages of gap-phase regeneration. D. pittieri larger than 10 cm dbh are overdispersed at a scale larger than that of patches of gaps. Natural disturbance can influence the distribution of shade intolerant tree populations at several different spatial scales, and can have discordant effects at different life history stages.

Lawton, Robert M.↗

NASA NTRS2011

Measuring Effective Leaf Area Index, Foliage Profile, and Stand Height in New England Forest Stands Using a Full-Waveform Ground-Based Lidar

Effective leaf area index (LAI) retrievals from a scanning, ground-based, near-infrared (1064 nm) lidar that digitizes the full return waveform, the Echidna Validation Instrument (EVI), are in good agreement with those obtained from both hemispherical photography and the Li-Cor LAI-2000 Plant Canopy Analyzer. We conducted trials at 28 plots within six stands of hardwoods and conifers of varying height and stocking densities at Harvard Forest, Massachusetts, Bartlett Experimental Forest, New Hampshire, and Howland Experimental Forest, Maine, in July 2007. Effective LAI values retrieved by four methods, which ranged from 3.42 to 5.25 depending on the site and method, were not significantly different ( b0.1 among four methods). The LAI values also matched published values well. Foliage profiles (leaf area with height) retrieved from the lidar scans, although not independently validated, were consistent with stand structure as observed and as measured by conventional methods. Canopy mean top height, as determined from the foliage profiles, deviated from mean RH100 values obtained from the Lidar Vegetation Imaging Sensor (LVIS) airborne large-footprint lidar system at 27 plots by .0.91 m with RMSE=2.04 m, documenting the ability of the EVI to retrieve stand height. The Echidna Validation Instrument is the first realization of the Echidna lidar concept, devised by Australia's Commonwealth Scientific and Industrial Research Organization (CSIRO), for measuring forest structure using full-waveform, ground-based, scanning lidar.

Zhao, Feng↗

NASA NTRS2012

Lidar Remote Sensing of Forests: New Instruments and Modeling Capabilities

Lidar instruments provide scientists with the unique opportunity to characterize the 3D structure of forest ecosystems. This information allows us to estimate properties such as wood volume, biomass density, stocking density, canopy cover, and leaf area. Structural information also can be used as drivers for photosynthesis and ecosystem demography models to predict forest growth and carbon sequestration. All lidars use time-in-flight measurements to compute accurate ranging measurements; however, there is a wide range of instruments and data types that are currently available, and instrument technology continues to advance at a rapid pace. This seminar will present new technologies that are in use and under development at NASA for airborne and space-based missions. Opportunities for instrument and data fusion will also be discussed, as Dr. Cook is the PI for G-LiHT, Goddard's LiDAR, Hyperspectral, and Thermal airborne imager. Lastly, this talk will introduce radiative transfer models that can simulate interactions between laser light and forest canopies. Developing modeling capabilities is important for providing continuity between observations made with different lidars, and to assist the design of new instruments. Dr. Bruce Cook is a research scientist in NASA's Biospheric Sciences Laboratory at Goddard Space Flight Center, and has more than 25 years of experience conducting research on ecosystem processes, soil biogeochemistry, and exchange of carbon, water vapor and energy between the terrestrial biosphere and atmosphere. His research interests include the combined use of lidar, hyperspectral, and thermal data for characterizing ecosystem form and function. He is Deputy Project Scientist for the Landsat Data Continuity Mission (LDCM); Project Manager for NASA s Carbon Monitoring System (CMS) pilot project for local-scale forest biomass; and PI of Goddard's LiDAR, Hyperspectral, and Thermal (G-LiHT) airborne imager.

Cook, Bruce D.↗

NASA NTRS2013

Recent Efforts to Improve the Near Real Time Forest Disturbance Monitoring Capabilities of the ForWarn System

This presentation discusses the development of anew method for computing NDVI temporal composites from near real time eMODIS data This research is being conducted to improve forest change products used in the ForWarn system for monitoring regional forest disturbances in the United States. ForWarn provides nation-wide NDVI-based forest disturbance detection products that are refreshed every 8 days. Current eMODIS and historical MOD13 24 day NDVI data are used to compute the disturbance detection products. The eMODIS 24 day NDVI data re-aggregated from 7 day NDVI products. The 24 day eMODIS NDVIs are generally cloud free, but do not necessarily use the freshest quality data. To shorten the disturbance detection time, a method has been developed that performs adaptive length/maximum value compositing of eMODIS NDVI, along with cloud and shadow "noise" mitigation. Tests indicate that this method can reduce detection rates by 8-16 days for known recent disturbance events, depending on the cloud frequencies and disturbance type. The noise mitigation in these tests, though imperfect, helped to improve quality of the resulting NDVI and forest change products.

Spruce, Joseph↗

NASA NTRS2014

Satellite Data Aid Monitoring of Nation's Forests

The USDA Forest Service’s Asheville, North Carolina-based Eastern Forest Environmental Threat Assessment Center and Prineville, Oregon-based Western Wildlands Environmental Threat Assessment Center partnered with Stennis Space Center and other agencies to create an early warning system to identify, characterize, and track disturbances from potential forest threats. The result was ForWarn, which is now being used by federal and state forest and natural resource managers.

Source record↗

NASA NTRS2012

Interpretation of Variations in Modis-Measured Greenness Levels of Amazon Forests During 2000 to 2009

This work investigates variations in satellite-measured greenness of Amazon forests using ten years of NASA Moderate Resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) data. Corruption of optical remote sensing data with clouds and aerosols is prevalent in this region; filtering corrupted data causes spatial sampling constraints, as well as reducing the record length, which introduces large biases in estimates of greenness anomalies. The EVI data, analyzed in multiple ways and taking into account EVI accuracy, consistently show a pattern of negligible changes in the greenness levels of forests both in the area affected by drought in 2005 and outside it. Small random patches of anomalous greening and browning-especially prominent in 2009-appear in all ten years, irrespective of contemporaneous variations in precipitation, but with no persistence over time. The fact that over 90% of the EVI anomalies are insignificantly small-within the envelope of error (95% confidence interval) in EVI-warrants cautious interpretation of these results: there were no changes in the greenness of these forests, or if there were changes, the EVI data failed to capture these either because the constituent reflectances were saturated or the moderate resolution precluded viewing small-scale variations. This suggests a need for more accurate and spatially resolved synoptic views from satellite data and corroborating comprehensive ground sampling to understand the greenness dynamics of these forests.

MODIS↗

NASA NTRS2013

Taking Stock of Circumboreal Forest Carbon With Ground Measurements, Airborne and Spaceborne LiDAR

The boreal forest accounts for one-third of global forests, but remains largely inaccessible to ground-based measurements and monitoring. It contains large quantities of carbon in its vegetation and soils, and research suggests that it will be subject to increasingly severe climate-driven disturbance. We employ a suite of ground-, airborne- and space-based measurement techniques to derive the first satellite LiDAR-based estimates of aboveground carbon for the entire circumboreal forest biome. Incorporating these inventory techniques with uncertainty analysis, we estimate total aboveground carbon of 38 +/- 3.1 Pg. This boreal forest carbon is mostly concentrated from 50 to 55degN in eastern Canada and from 55 to 60degN in eastern Eurasia. Both of these regions are expected to warm >3 C by 2100, and monitoring the effects of warming on these stocks is important to understanding its future carbon balance. Our maps establish a baseline for future quantification of circumboreal carbon and the described technique should provide a robust method for future monitoring of the spatial and temporal changes of the aboveground carbon content.

Biomass↗

NASA NTRS2013

Forest Structure Characterization Using JPL's UAVSAR Multi-Baseline Polarimetric SAR Interferometry and Tomography

This paper concerns forest remote sensing using JPL's multi-baseline polarimetric interferometric UAVSAR data. It presents exemplary results and analyzes the possibilities and limitations of using SAR Tomography and Polarimetric SAR Interferometry (PolInSAR) techniques for the estimation of forest structure. Performance and error indicators for the applicability and reliability of the used multi-baseline (MB) multi-temporal (MT) PolInSAR random volume over ground (RVoG) model are discussed. Experimental results are presented based on JPL's L-band repeat-pass polarimetric interferometric UAVSAR data over temperate and tropical forest biomes in the Harvard Forest, Massachusetts, and in the La Amistad Park, Panama and Costa Rica. The results are partially compared with ground field measurements and with air-borne LVIS lidar data.

UAVSAR (Uninhabited Aerial Vehicle SAR)↗

NASA NTRS2013

Forest Structure Characterization Using Jpl's UAVSAR Multi-Baseline Polarimetric SAR Interferometry and Tomography

remote sensing↗

NASA NTRS2015

Mapping Species Composition of Forests and Tree Plantations in Northeastern Costa Rica with an Integration of Hyperspectral and Multitemporal Landsat Imagery

An efficient means to map tree plantations is needed to detect tropical land use change and evaluate reforestation projects. To analyze recent tree plantation expansion in northeastern Costa Rica, we examined the potential of combining moderate-resolution hyperspectral imagery (2005 HyMap mosaic) with multitemporal, multispectral data (Landsat) to accurately classify (1) general forest types and (2) tree plantations by species composition. Following a linear discriminant analysis to reduce data dimensionality, we compared four Random Forest classification models: hyperspectral data (HD) alone; HD plus interannual spectral metrics; HD plus a multitemporal forest regrowth classification; and all three models combined. The fourth, combined model achieved overall accuracy of 88.5%. Adding multitemporal data significantly improved classification accuracy (p less than 0.0001) of all forest types, although the effect on tree plantation accuracy was modest. The hyperspectral data alone classified six species of tree plantations with 75% to 93% producer's accuracy; adding multitemporal spectral data increased accuracy only for two species with dense canopies. Non-native tree species had higher classification accuracy overall and made up the majority of tree plantations in this landscape. Our results indicate that combining occasionally acquired hyperspectral data with widely available multitemporal satellite imagery enhances mapping and monitoring of reforestation in tropical landscapes.

hyperspectral fusion↗

NASA NTRS2015

High-Resolution Forest Canopy Height Estimation in an African Blue Carbon Ecosystem

Mangrove forests are one of the most productive and carbon dense ecosystems that are only found at tidally inundated coastal areas. Forest canopy height is an important measure for modeling carbon and biomass dynamics, as well as land cover change. By taking advantage of the flat terrain and dense canopy cover, the present study derived digital surface models (DSMs) using stereophotogrammetric techniques on high-resolution spaceborne imagery (HRSI) for southern Mozambique. A mean-weighted ground surface elevation factor was subtracted from the HRSI DSM to accurately estimate the canopy height in mangrove forests in southern Mozambique. The mean and H100 tree height measured in both the field and with the digital canopy model provided the most accurate results with a vertical error of 1.18-1.84 m, respectively. Distinct patterns were identified in the HRSI canopy height map that could not be discerned from coarse shuttle radar topography mission canopy maps even though the mode and distribution of canopy heights were similar over the same area. Through further investigation, HRSI DSMs have the potential of providing a new type of three-dimensional dataset that could serve as calibration/validation data for other DSMs generated from spaceborne datasets with much larger global coverage. HSRI DSMs could be used in lieu of Lidar acquisitions for canopy height and forest biomass estimation, and be combined with passive optical data to improve land cover classifications.

HRSI↗

NASA NTRS2016

Threats to North American Forests from Southern Pine Beetle with Warming Winters

In coming decades, warmer winters are likely to lift range constraints on many cold-limited forest insects. Recent unprecedented expansion of the southern pine beetle (SPB, Dendroctonus frontalis) into New Jersey, New York, Connecticut, and Massachusetts in concert with warming annual temperature minima highlights the risk that this insect pest poses to the pine forests of the northern United States and Canada under continued climate change. Here we present the first projections of northward expansion in SPB-suitable climates using a statistical bioclimatic range modeling approach and current-generation general circulation model (GCM) output under the RCP 4.5 and 8.5 emissions scenarios. Our results show that by the middle of the 21st century, the climate is likely to be suitable for SPB expansion into vast areas of previously unaffected forests throughout the northeastern United States and into southeastern Canada. This scenario would pose a significant economic and ecological risk to the affected regions, including disruption oflocal ecosystem services, dramatic shifts in forest structure, and threats to native biodiversity.

risk↗

NASA NTRS2020

Gila Water Resources II: Using Earth Observations to Identify Wildfire Impacts on Hydrologic Functions and Recovery in the Gila National Forest

Wildfires have the potential to cause devastating and long-lasting impacts on ecological systems. In the Gila National Forest (Gila NF), wildfire events have occurred with increasing frequency and severity over recent years. These disturbances, such as the historic Whitewater Baldy Complex Fire (2012) and Silver Fire (2013), have raised concerns over post-fire flooding, debris flows, and vegetation recovery. Understanding connections between burn events and ecological functions is crucial for developing effective land management practices within the Gila NF that ensure conservation of the watershed. The Gila Water Resources II team worked in partnership with the US Department of Agriculture (USDA) US Forest Service’s (USFS) Gila National Forest and Region 3. This project provided insight into the influence of wildfires on increased flooding events and determined if restoration efforts in the Gila NF are having a beneficial impact on vegetation regeneration. To understand recovery trends and hydrologic impact in the Gila NF between 2000-2019, this project used Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper Plus, Landsat 8 Operational Land Imager, Global Precipitation Measurement Integrated Multi-satellite Retrievals for GPM precipitation, along with ancillary data from USGS stream gauges and data provided by USDA USFS’s Gila National Forest and Region 3. Based on these data, the team identified burn areas that received restorative treatments and compared Normalized Burn Ratio for different land cover types to better inform land management decisions. Additionally, the team analyzed the relationship between precipitation and streamflow from stream gauges to investigate the impact wildfires have on hydrology within the watershed.

Water Resources↗

NASA NTRSDate not supplied

Capacity Building Engagement for Estimating Forest Stand Height Utilizing the SAR Handbook

Utilizing Synthetic Aperture Radar (SAR) which provides information such as vegetation structure and moisture content, independently of weather conditions is a powerful tool that can be employed to more effectively monitor deforestation and estimate biomass which is of paramount concern, especially in South and Southeast Asia which contain nearly 15% of all tropical forests. SERVIR, a NASA-USAID initiative, works in partnership with regional hubs around the world building capacity through promoting the use of Earth observations and geospatial technologies. The SERVIR Global network and the Silva Carbon program collaboratively developed the SAR Handbook: Comprehensive Methodologies for Forest Monitoring and Biomass Estimation which set out to reduce the barriers associated with leveraging SAR and increase the capacity of researchers and practitioners globally to use SAR for monitoring. In particular, utilizing SAR to estimate Forest Stand Height (FSH) is crucial for greenhouse gas emissions reporting and estimating carbon storage. Programs such as Reducing Emissions from Deforestation and Forest Degradation (REDD) rely on parameters such as these for their monitoring efforts. This talk will showcase the collaborative efforts, emergent geospatial technology leveraged, and capacity building approaches utilized by our team to conduct a South and Southeast Asia focused in-person training event located at SERVIR-Mekong, a SERVIR hub lead by the Asian Disaster Preparedness Center (ADPC) in Bangkok.

AGU↗