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All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Multispectral color photography for mineral exploration by the remote sensing of biogeochemical anomalies

Selected band multispectral photography was evaluated as a mineral exploration tool by detecting stress on trees caused by underground mineralization. Ground truth consisted of two test sites in the Prescott National Forest within which the mineralization had been established by a drilling program. Species of trees were categorized as background, intermediate, and anomalous based upon where they grew with respect to this underlying mineralization. Soil geochemistry and the metal content of ashed samples of the trees were studied in relation to the inferred locus of mineralization. Computer analysis of the reflectance spectra of mineralized trees confirmed that the relative percent reflectance differences of trees growing in anomalous areas was less than that of the same tree species growing in background areas.

Yost, E.↗
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 NTRS2017

The Use of Sun Elevation Angle for Stereogrammetric Boreal Forest Height in Open Canopies

Stereogrammetry applied to globally available high resolution spaceborne imagery (HRSI; less than 5 m spatial resolution) yields fine-scaled digital surface models (DSMs) of elevation. These DSMs may represent elevations that range from the ground to the vegetation canopy surface, are produced from stereoscopic image pairs (stereo pairs) that have a variety of acquisition characteristics, and have been coupled with lidar data of forest structure and ground surface elevation to examine forest height. This work explores surface elevations from HRSI DSMs derived from two types of acquisitions in open canopy forests. We (1) apply an automated mass-production stereogrammetry workflow to along-track HRSI stereo pairs, (2) identify multiple spatially coincident DSMs whose stereo pairs were acquired under different solar geometry, (3) vertically co-register these DSMs using coincident spaceborne lidar footprints (from ICESat-GLAS) as reference, and(4) examine differences in surface elevations between the reference lidar and the co-registered HRSI DSMs associated with two general types of acquisitions (DSM types) from different sun elevation angles. We find that these DSM types, distinguished by sun elevation angle at the time of stereo pair acquisition, are associated with different surface elevations estimated from automated stereogrammetry in open canopy forests. For DSM values with corresponding reference ground surface elevation from spaceborne lidar footprints in open canopy northern Siberian Larix forests with slopes less than10, our results show that HRSI DSM acquired with sun elevation angles greater than 35deg and less than 25deg (during snow-free conditions) produced characteristic and consistently distinct distributions of elevation differences from reference lidar. The former include DSMs of near-ground surfaces with root mean square errors less than 0.68 m relative to lidar. The latter, particularly those with angles less than 10deg, show distributions with larger differences from lidar that are associated with open canopy forests whose vegetation surface elevations are captured. Terrain aspect did not have a strong effect on the distribution of vegetation surfaces. Using the two DSM types together, the distribution of DSM-differenced heights in forests (6.0 m, sigma = 1.4 m) was consistent with the distribution of plot-level mean tree heights (6.5m, sigma = 1.2 m). We conclude that the variation in sun elevation angle at time of stereo pair acquisition can create illumination conditions conducive for capturing elevations of surfaces either near the ground or associated with vegetation canopy. Knowledge of HRSI acquisition solar geometry and snow cover can be used to understand and combine stereogrammetric surface elevation estimates to co-register rand difference overlapping DSMs, providing a means to map forest height at fine scales, resolving the vertical structure of groups of trees from spaceborne platforms in open canopy forests.

Paul M Montesano↗
NASA NTRS2000

BOREAS AFM-12 1-km AVHRR Seasonal Land Cover Classification

The Boreal Ecosystem-Atmosphere Study (BOREAS) Airborne Fluxes and Meteorology (AFM)-12 team's efforts focused on regional scale Surface Vegetation and Atmosphere (SVAT) modeling to improve parameterization of the heterogeneous BOREAS landscape for use in larger scale Global Circulation Models (GCMs). This regional land cover data set was developed as part of a multitemporal one-kilometer Advanced Very High Resolution Radiometer (AVHRR) land cover analysis approach that was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. This land cover classification was derived by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly Normalized Difference Vegetation Index (NDVI) image composites (April-September 1992). This regional data set was developed for use by BOREAS investigators, especially those involved in simulation modeling, remote sensing algorithm development, and aircraft flux studies. Based on regional field data verification, this multitemporal one-kilometer AVHRR land cover mapping approach was effective in characterizing the biome-level land cover structure, embedded spatially heterogeneous landscape patterns, and other types of key land cover information of interest to BOREAS modelers.The land cover mosaics in this classification include: (1) wet conifer mosaic (low, medium, and high tree stand density), (2) mixed coniferous-deciduous forest (80% coniferous, codominant, and 80% deciduous), (3) recent visible bum, vegetation regeneration, or rock outcrops-bare ground-sparsely vegetated slow regeneration bum (four classes), (4) open water and grassland marshes, and (5) general agricultural land use/ grasslands (three classes). This land cover mapping approach did not detect small subpixel-scale landscape features such as fens, bogs, and small water bodies. Field observations and comparisons with Landsat Thematic Mapper (TM) suggest a minimum effective resolution of these land cover classes in the range of three to four kilometers, in part, because of the daily to monthly compositing process. In general, potential accuracy limitations are mitigated by the use of conservative parameterization rules such as aggregation of predominant land cover classes within minimum horizontal grid cell sizes of ten kilometers. The AFM-12 one-kilometer AVHRR seasonal land cover classification data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Steyaert, Lou↗
NASA NTRS2011

Fire Return Interval Within the Northern Boundary of the Larch Forest

Larch (Larix spp.) dominant forests compose a large proportion of the forests of Russia (i.e., about 40% of forested areas). These forests range from the Yenisei ridge on the west to the Pacific Ocean on the east, and from Lake Baikal on the south to the 73rd parallel in the north. Larch stands comprise the world s northern most forest at Ary-Mas (72 deg 28' N, 102 deg 15' E). Larch dominated forests occupy about 70% of the permafrost areas in Siberia. Larch forms high closure stands as well as open forests, and is found mainly over permafrost, where other tree species barely survive. Wildfires are typical for this territory with the majority occurring as ground fires due to low crown closure. Due to the thin active layer in permafrost soils and a dense lichen-moss cover, ground fires may cause stand mortality. The vast areas of larch-dominant forests is generally considered as a "carbon sink"; however, positive long-term temperature trends at higher latitudes are expected to result in an increase of fire frequency, and thus may convert this area to a source for greenhouse gases. There are recent observations regarding the increase of fire frequency within non-protected territories. Surprisingly, there are few publications on fire chronoseqences for the huge forested territory between the Ural Mountains and the Pacific Ocean. Also there is a general understanding that bimodal (late spring -- early summer and late summer-beginning of fall) fire seasonal distribution in the south becomes uni-modal (late spring -- early summer) in the north. The purpose of this study is to investigate the wildfire history at the northern edge of the zone of larch dominance.

Kharuk, V. I.↗
NASA NTRS1989

Relationships between multipolarized radar backscatter and slash pine stand parameters

Multipolarized L-band (24.5 cm) aircraft radar data was obtained for a primarily forested area in northern Florida. Based on the results of previous studies by Hoffer and Hussin (1989), a swath of medium incidence angle (35-25 deg) data was defined. Three groups of slash pine stands were located in the data: 4- to 17-year-old plantations, 18- to 48-year-old plantations, and 16- to 53-year-old natural stands. Stand data obtained from the forest-products companies operating in the area include age, tree height, diameter-at-breast height, basal area, volume (cords/acre), and density (trees/acre). Each of these stand parameters were compared to each of the four polarizations (HH, VV, VH, and HV) of the radar data for each group of stands. Statistically significant relationships were found between the radar backscatter and the forest stand parameters only for the 4- to 17-year-old slash pine plantation stands. In general, the cross-polarized radar backscatter was more highly correlated with the various stand parameters than the like-polarized backscatter, and the VV-polarized data were more highly correlated than the HH-polarized data.

Hussin, Yousif Ali↗
NASA NTRS1974

Interpretation of Pennsylvania agricultural land use from ERTS-1 data

The author has identified the following significant results. To study the complex agricultural patterns in Pennsylvania, a portion of an ERTS scene was selected for detailed analysis. Various photographic products were made and were found to be only of limited value. This necessitated the digital processing of the ERTS data. Using an unsupervised classification procedure, it was possible to delineate the following categories: (1) forest land with a northern aspect, (2) forest land with a southern aspect, (3) valley trees, (4) wheat, (5) corn, (6) alfalfa, grass, pasture, (7) disturbed land, (8) builtup land, (9) strip mines, and (10) water. These land use categories were delineated at a scale of approximately 1:20,000 on the line printer output. Land use delineations were also made using the General Electric IMAGE 100 interactive analysis system.

Mcmurtry, G. J.↗
NASA NTRS1986

Characterization of vegetation by microwave and optical remote sensing

Two series of carefully controlled experiments were conducted. First, plots of important crops (corn, soybeans, and sorghum), prairie grasses (big bluestem, switchgrass, tal fescue, orchardgrass, bromegrass), and forage legumes (alfalfa, red clover, and crown vetch) were manipulated to produce wide ranges of phytomass, leaf area index, and canopy architecture. Second, coniferous forest canopies were simulated using small balsam fir trees grown in large pots of soil and arranged systematically on a large (5 m) platform. Rotating the platform produced many new canopies for frequency and spatial averaging of the backscatter signal. In both series of experiments, backscatter of 5.0 GHz (C-Band) was measured as a function of view angle and polarization. Biophysical measurements included leaf area index, fresh and dry phytomass, water content of canopy elements, canopy height, and soil roughness and moisture content. For a subset of the above plots, additional measurements were acquired to exercise microwave backscatter models. These measurements included size and shape of leaves, stems, and fruit and the probability density function of leaf and stem angles. The relationships of the backscattering coefficients and the biophysical properties of the canopies were evaluated using statistical correlations, analysis of variance, and regression analysis. Results from the corn density and balsam fir experiments are discussed and analyses of data from the other experiments are summarized.

Daughtry, C. S. T.↗
NASA NTRS1988

Shuttle imaging radar A analysis of land use in Amazonia

Over large areas in the tropics, satellite imagery is the principal source of data on the area, current stature, and extent of disturbance of the forests. The information from imagery that covers large areas at low resolution is greatly enhanced when different types of imagery can be compared. The paper presents a comparison of data from Landsat MSS and from the Shuttle Imaging Radar (SIR-A) L band HH polarization data for sites in the Amazon Basin. Results indicate that SIR-A backscatter from the undisturbed forest was lower than that from some disturbed areas and from flooded forests and that SIR-A brightness, increases nonlinearly with the Landsat normalized difference vegetation index. It is hypothesized that the brightest radar returns in southern Amazonia are from newly cleared forests that are littered with standing and fallen tree boles that function as corner reflectors; and that backscatter will diminish from disturbed areas over time as fields are burned repeatedly.

Stone, Thomas A.↗
NASA NTRS2004

Clear-Sky Narrowband Albedo Variations Derived from VIRS and MODIS Data

A critical parameter for detecting clouds and aerosols and for retrieving their microphysical properties is the clear-sky radiance. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the visible (VIS; 0.63 m) and near-infrared (NIR; 1.6 or 2.13 m) channels available on same satellites as the CERES scanners. Another channel often used for cloud and aerosol, and vegetation cover retrievals is the vegetation (VEG; 0.86- m) channel that has been available on the Advanced Very High Resolution Radiometer (AVHRR) for many years. Generally, clear-sky albedo for a given surface type is determined for conditions when the vegetation is either thriving or dormant and free of snow. Snow albedo is typically estimated without considering the underlying surface type. The albedo for a surface blanketed by snow, however, should vary with surface type because the vegetation often emerges from the snow to varying degrees depending on the vertical dimensions of the vegetation. For example, a snowcovered prairie will probably be brighter than a snowcovered forest because the snow typically falls off the trees exposing the darker surfaces while the snow on a grassland at the same temperatures will likely be continuous and, therefore, more reflective. Accounting for the vegetation-induced differences should improve the capabilities for distinguishing snow and clouds over different surface types and facilitate improvements in the accuracy of radiative transfer calculations between the snow-covered surface and the atmosphere, eventually leading to improvements in models of the energy budgets over land. This paper presents a more complete analysis of the CERES spectral clear-sky reflectances to determine the variations in clear-sky top-of-atmosphere (TOA) albedos for both snow-free and snow-covered surfaces for four spectral channels using data from Terra and Aqua.. The results should be valuable for improved cloud retrievals and for modeling radiation fields.

Sun-Mack, Sunny↗
NASA NTRS2013

Comparison of Precision of Biomass Estimates in Regional Field Sample Surveys and Airborne LiDAR-Assisted Surveys in Hedmark County, Norway

Airborne scanning LiDAR (Light Detection and Ranging) has emerged as a promising tool to provide auxiliary data for sample surveys aiming at estimation of above-ground tree biomass (AGB), with potential applications in REDD forest monitoring. For larger geographical regions such as counties, states or nations, it is not feasible to collect airborne LiDAR data continuously ("wall-to-wall") over the entire area of interest. Two-stage cluster survey designs have therefore been demonstrated by which LiDAR data are collected along selected individual flight-lines treated as clusters and with ground plots sampled along these LiDAR swaths. Recently, analytical AGB estimators and associated variance estimators that quantify the sampling variability have been proposed. Empirical studies employing these estimators have shown a seemingly equal or even larger uncertainty of the AGB estimates obtained with extensive use of LiDAR data to support the estimation as compared to pure field-based estimates employing estimators appropriate under simple random sampling (SRS). However, comparison of uncertainty estimates under SRS and sophisticated two-stage designs is complicated by large differences in the designs and assumptions. In this study, probability-based principles to estimation and inference were followed. We assumed designs of a field sample and a LiDAR-assisted survey of Hedmark County (HC) (27,390 km2), Norway, considered to be more comparable than those assumed in previous studies. The field sample consisted of 659 systematically distributed National Forest Inventory (NFI) plots and the airborne scanning LiDAR data were collected along 53 parallel flight-lines flown over the NFI plots. We compared AGB estimates based on the field survey only assuming SRS against corresponding estimates assuming two-phase (double) sampling with LiDAR and employing model-assisted estimators. We also compared AGB estimates based on the field survey only assuming two-stage sampling (the NFI plots being grouped in clusters) against corresponding estimates assuming two-stage sampling with the LiDAR and employing model-assisted estimators. For each of the two comparisons, the standard errors of the AGB estimates were consistently lower for the LiDAR-assisted designs. The overall reduction of the standard errors in the LiDAR-assisted estimation was around 40-60% compared to the pure field survey. We conclude that the previously proposed two-stage model-assisted estimators are inappropriate for surveys with unequal lengths of the LiDAR flight-lines and new estimators are needed. Some options for design of LiDAR-assisted sample surveys under REDD are also discussed, which capitalize on the flexibility offered when the field survey is designed as an integrated part of the overall survey design as opposed to previous LiDAR-assisted sample surveys in the boreal and temperate zones which have been restricted by the current design of an existing NFI.

Comparison↗
NASA NTRS2019

Land carbon models underestimate the severity and duration of drought’s impact on plant productivity

The ability to accurately predict ecosystem drought response and recovery is necessary to produce reliable forecasts of land carbon uptake and future climate. Using a suite of models from the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), we assessed modeled net primary productivity (NPP) response to, and recovery from, drought events against a benchmark derived from tree ring observations between 1948 and 2008 across forested regions of the US and Europe. We find short lag times (0–6 months) between climate anomalies and modeled NPP response. Although models accurately simulate the direction of drought legacy effects (i.e. NPP decreases), projected effects are approximately four times shorter and four times weaker than observations suggest. This discrepancy between observed and simulated vegetation recovery from drought reveals a potential critical model deficiency. Since productivity is a crucial component of the land carbon balance, models that underestimate drought recovery time could overestimate predictions of future land carbon sink strength and, consequently, underestimate forecasts of atmospheric CO2.

carbon cycle↗
NASA NTRS1985

Forest discrimination with multipolarization imaging radar

The relations between polarization signatures and biophysical characteristics through a range of different forest environments were investigated using airborne synthetic-aperture (SAR) images acquired at L-band on March 1, 1984 in South Carolina. SAR data acquired in four linear polarization states with 10-m spatial resolution were encoded as color composite images and compared to US Forest Service forest stand data. The most useful correlative forest data were stand basal area, forest age, site condition index, and forest management type. It is found that the multipolarization images discriminate variation in tree density or difference in the amount of understory, but no evidence has been found for discrimination between evergreen and deciduous forest types.

Ford, J. P.↗
NASA NTRS1985

Remote detection of geobotanical anomalies associated with hydrocarbon microseepage

As part of the continuing study of the Lost River, West Virginia NASA/Geosat Test Case Site, an extensive soil gas survey of the site was conducted during the summer of 1983. This soil gas survey has identified an order of magnitude methane, ethane, propane, and butane anomaly that is precisely coincident with the linear maple anomaly reported previously. This and other maple anomalies were previously suggested to be indicative of anaerobic soil conditions associated with hydrocarbon microseepage. In vitro studies support the view that anomalous distributions of native tree species tolerant of anaerobic soil conditions may be useful indicators of methane microseepage in heavily vegetated areas of the United States characterized by deciduous forest cover. Remote sensing systems which allow discrimination and mapping of native tree species and/or species associations will provide the exploration community with a means of identifying vegetation distributional anomalies indicative of microseepage.

Rock, B. N.↗
NASA NTRSDate not supplied

Los Angeles Urban Development Utilizing Nasa Earth Observations to Evaluate the Impact of Tree Coverage on Urban Heat Mitigation

In recent decades, Los Angeles, California has experienced an increase in summer temperatures that has intensified the urban heat island effect. The expansion of developed areas has contributed significantly to this phenomenon by trapping and reradiating heat, posing dangerous health risks to residents. To mitigate this problem, organizations including City Plants and the L.A.’s Office of City Forest Management have implemented initiatives to promote urban greening and tree planting, which help cool down vulnerable communities. In collaboration with these partners, NASA DEVELOP has undertaken a study to investigate the role of trees in urban environments and their effectiveness in reducing local urban heat islands.

Leyla Namazie↗
NASA NTRS2011

Persistent Effects of Fire Severity on Early Successional Forests in Interior Alaska

There has been a recent increase in the frequency and extent of wildfires in interior Alaska, and this trend is predicted to continue under a warming climate. Although less well documented, corresponding increases in fire severity are expected. Previous research from boreal forests in Alaska and western Canada indicate that severe fire promotes the recruitment of deciduous tree species and decreases the relative abundance of black spruce (Picea mariana) immediately after fire. Here we extend these observations by (1) examining changes in patterns of aspen and spruce density and biomass that occurred during the first two decades of post-fire succession, and (2) comparing patterns of tree composition in relation to variations in post-fire organic layer depth in four burned black spruce forests in interior Alaska after 10-20 years of succession.Wefound that initial effects of fire severity on recruitment and establishment of aspen and black spruce were maintained by subsequent effects of organic layer depth and initial plant biomass on plant growth during post-fire succession. The proportional contribution of aspen (Populus tremuloides) to total stand biomass remained above 90% during the first and second decades of succession in severely burned sites, while in lightly burned sites the proportional contribution of aspen was reduced due to a 40- fold increase in spruce biomass in these sites. Relationships between organic layer depth and stem density and biomass were consistently negative for aspen, and positive or neutral for black spruce in all four burns. Our results suggest that initial effects of post-fire organic layer depths on deciduous recruitment are likely to translate into a prolonged phase of deciduous dominance during post-fire succession in severely burned stands. This shift in vegetation distribution has important implications for climate-albedo feedbacks, future fire regime, wildlife habitat quality and natural resources for indigenous subsistence activities in interior Alaska.

Shenoy, Aditi↗
NASA NTRS1993

Relating P-band AIRSAR backscatter to forest stand parameters

As part of research on forest ecosystems, the Jet Propulsion Laboratory (JPL) and collaborating research teams have conducted multi-season airborne synthetic aperture radar (AIRSAR) experiments in three forest ecosystems including temperate pine forest (Duke, Forest, North Carolina), boreal forest (Bonanza Creek Experimental Forest, Alaska), and northern mixed hardwood-conifer forest (Michigan Biological Station, Michigan). The major research goals were to improve understanding of the relationships between radar backscatter and phenological variables (e.g. stand density, tree size, etc.), to improve radar backscatter models of tree canopy properties, and to develop a radar-based scheme for monitoring forest phenological changes. In September 1989, AIRSAR backscatter data were acquired over the Duke Forest. As the aboveground biomass of the loblolly pine forest stands at Duke Forest increased, the SAR backscatter at C-, L-, and P-bands increased and saturated at different biomass levels for the C-band, L-band, and P-band data. We only use the P-band backscatter data and ground measurements here to study the relationships between the backscatter and stand density, the backscatter and mean trunk dbh (diameter at breast height) of trees in the stands, and the backscatter and stand basal area.

Wang, Yong↗
NASA NTRS2012

Utilizing NASA Earth Observing System (EOS) Data to Determine Ideal Planting Locations for Wetland Tree Species in St. Bernard Parish, Louisiana

St. Bernard Parish, in southeast Louisiana, is rapidly losing coastal forests and wetlands due to a combination of natural and anthropogenic disturbances (e.g. subsidence, saltwater intrusion, low sedimentation, nutrient deficiency, herbivory, canal dredging, levee construction, spread of invasive species, etc.). After Hurricane Katrina severely impacted the area in 2005, multiple Non-Governmental Organizations (NGOs) have worked not only on rebuilding destroyed dwellings, but on rebuilding the ecosystems that once protected the citizens of St. Bernard Parish. Volunteer groups, NGOs, and government entities often work separately and independently of each other and use different sets of information to choose the best planting sites for coastal forests. Using NASA EOS, NRCS soil surveys, and ancillary road and canal data in conjunction with ground truthing, the team created maps of optimal planting sites for several species of wetland trees to aid in unifying these organizations, who share a common goal, under one plan. The methodology for this project created a comprehensive Geographic Information System (GIS) to help identify suitable planting sites in St. Bernard Parish. This included supplementing existing elevation data using LIDAR data and classifying existing land cover in the study area from ASTER multispectral satellite data. Low altitude AVIRIS hyperspectral imagery was used to assess the health of vegetation over an area near the intersection of the Mississippi River Gulf Outlet Canal (MRGO) and Bayou la Loutre. Historic extent of coastal forests was mapped using aerial photos from USGS collected between 1952 and 1956. The final products demonstrated the utility of combining NASA EOS with other geospatial data in assessing, monitoring, and restoring of coastal ecosystems in Louisiana. This methodology also provides a useful template for other ecological forecasting and coastal restoration applications.

Reahard, Ross↗