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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Oregon Wildfires: Integrating ECOSTRESS to Map & Analyze Vegetation Moisture for Wildfire Modeling

Wildfire season in the western USA is starting earlier and gaining in intensity. The Bootleg Fire in Southern Oregon began on July 6th, 2021, and burned over 1675 km2 before it was fully contained on August 15th, 2021. Evapotranspiration (ET) is one indicator of vegetation moisture and there is interest in using high-resolution ET products from ECOsystem and Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) in future wildfire modeling. In partnership with the Pacific Northwest National Laboratory and US Forest Service, the team examined ECOSTRESS ET for the two years before the Bootleg Fire and assessed the relationship between ET, topography, and vegetation. Remotely sensed data from Shuttle Radar Topography Mission (SRTM) and Global Ecosystem Dynamics Investigation (GEDI) along with ancillary data from the National Land Cover Database (NLCD) and Landscape Fire Resource Management Planning Tools (LANDFIRE) were incorporated. The team examined data in relation to soil burn severity from the Burned Area Emergency Response (BAER) program. From ET median composites for April 1st – July 5th, 2021 and 2019, the Bootleg Fire area showed a 7 mm/day decrease in ET and a relative 75% decrease in ET between 2019 and 2021. Approximately 6% of the Bootleg Fire area was identified as having a high soil burn severity and these areas were found predominantly in the evergreen forest land cover class and northward facing slopes with a mean ET decrease of 3 mm/day between 2019 and 2021. The team also analyzed ECOSTRESS Water Use Efficiency products as an additional vegetation moisture indicator of pre-fire conditions in the study area. The end products will allow the partners to assess if higher resolution vegetation moisture datasets from ECOSTRESS will improve wildfire modeling for other susceptible areas.

Brenna Hatch↗
NASA NTRS1993

Mapping of taiga forest units using AIRSAR data and/or optical data, and retrieval of forest parameters

A maximum a posteriori Bayesian classifier for multifrequency polarimetric SAR data is used to perform a supervised classification of forest types in the floodplains of Alaska. The image classes include white spruce, balsam poplar, black spruce, alder, non-forests, and open water. The authors investigate the effect on classification accuracy of changing environmental conditions, and of frequency and polarization of the signal. The highest classification accuracy (86 percent correctly classified forest pixels, and 91 percent overall) is obtained combining L- and C-band frequencies fully polarimetric on a date where the forest is just recovering from flooding. The forest map compares favorably with a vegetation map assembled from digitized aerial photos which took five years for completion, and address the state of the forest in 1978, ignoring subsequent fires, changes in the course of the river, clear-cutting of trees, and tree growth. HV-polarization is the most useful polarization at L- and C-band for classification. C-band VV (ERS-1 mode) and L-band HH (J-ERS-1 mode) alone or combined yield unsatisfactory classification accuracies. Additional data acquired in the winter season during thawed and frozen days yield classification accuracies respectively 20 percent and 30 percent lower due to a greater confusion between conifers and deciduous trees. Data acquired at the peak of flooding in May 1991 also yield classification accuracies 10 percent lower because of dominant trunk-ground interactions which mask out finer differences in radar backscatter between tree species. Combination of several of these dates does not improve classification accuracy. For comparison, panchromatic optical data acquired by SPOT in the summer season of 1991 are used to classify the same area. The classification accuracy (78 percent for the forest types and 90 percent if open water is included) is lower than that obtained with AIRSAR although conifers and deciduous trees are better separated due to the presence of leaves on the deciduous trees. Optical data do not separate black spruce and white spruce as well as SAR data, cannot separate alder from balsam poplar, and are of course limited by the frequent cloud cover in the polar regions. Yet, combining SPOT and AIRSAR offers better chances to identify vegetation types independent of ground truth information using a combination of NDVI indexes from SPOT, biomass numbers from AIRSAR, and a segmentation map from either one.

Rignot, Eric↗
NASA NTRS1976

A LANDSAT study of ephemeral and perennial rangeland vegetation and soils

The author has identified the following significant results. Several methods of computer processing were applied to LANDSAT data for mapping vegetation characteristics of perennial rangeland in Montana and ephemeral rangeland in Arizona. The choice of optimal processing technique was dependent on prescribed mapping and site condition. Single channel level slicing and ratioing of channels were used for simple enhancement. Predictive models for mapping percent vegetation cover based on data from field spectra and LANDSAT data were generated by multiple linear regression of six unique LANDSAT spectral ratios. Ratio gating logic and maximum likelihood classification were applied successfully to recognize plant communities in Montana. Maximum likelihood classification did little to improve recognition of terrain features when compared to a single channel density slice in sparsely vegetated Arizona. LANDSAT was found to be more sensitive to differences between plant communities based on percentages of vigorous vegetation than to actual physical or spectral differences among plant species.

Bentley, R. G., Jr.↗
NASA NTRS1973

Water Resources

Uses of ERTS-1 imagery and data for water resources surveys and management are summarized. Areas discussed are: (1) land use and geology; (2) flood plain and flood inundation mapping; (3) snow cover mapping; (4) glacier observations; (5) data collection systems; (6) surface waters; (7) wetlands mapping; (8) water quality; (9) soil mapping; (10) phreatophyte and riparian vegetation mapping; and (11) evapotranspiration.

Salomonson, V. V.↗
NASA NTRS2001

Modeling and Prediction of Wildfire Hazard in Southern California, Integration of Models with Imaging Spectrometry

Large urban wildfires throughout southern California have caused billions of dollars of damage and significant loss of life over the last few decades. Rapid urban growth along the wildland interface, high fuel loads and a potential increase in the frequency of large fires due to climatic change suggest that the problem will worsen in the future. Improved fire spread prediction and reduced uncertainty in assessing fire hazard would be significant, both economically and socially. Current problems in the modeling of fire spread include the role of plant community differences, spatial heterogeneity in fuels and spatio-temporal changes in fuels. In this research, we evaluated the potential of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Airborne Synthetic Aperture Radar (AIRSAR) data for providing improved maps of wildfire fuel properties. Analysis concentrated in two areas of Southern California, the Santa Monica Mountains and Santa Barbara Front Range. Wildfire fuel information can be divided into four basic categories: fuel type, fuel load (live green and woody biomass), fuel moisture and fuel condition (live vs senesced fuels). To map fuel type, AVIRIS data were used to map vegetation species using Multiple Endmember Spectral Mixture Analysis (MESMA) and Binary Decision Trees. Green live biomass and canopy moisture were mapped using AVIRIS through analysis of the 980 nm liquid water absorption feature and compared to alternate measures of moisture and field measurements. Woody biomass was mapped using L and P band cross polarimetric data acquired in 1998 and 1999. Fuel condition was mapped using spectral mixture analysis to map green vegetation (green leaves), nonphotosynthetic vegetation (NPV; stems, wood and litter), shade and soil. Summaries describing the potential of hyperspectral and SAR data for fuel mapping are provided by Roberts et al. and Dennison et al. To utilize remotely sensed data to assess fire hazard, fuel-type maps were translated into standard fuel models accessible to the FARSITE fire spread simulator. The FARSITE model and BEHAVE are considered industry standards for fire behavior analysis. Anderson level fuels map, generated using a binary decision tree classifier are available for multiple dates in the Santa Monica Mountains and at least one date for Santa Barbara. Fuel maps that will fill in the areas between Santa Barbara and the Santa Monica Mountains study sites are in progress, as part of a NASA Regional Earth Science Application Center, the Southern California Wildfire Hazard Center. Species-level maps, were supplied to fire managing agencies (Los Angeles County Fire, California Department of Forestry). Research results were published extensively in the refereed and non-refereed literature. Educational outreach included funding of several graduate students, undergraduate intern training and an article featured in the California Alliance for Minorities Program (CAMP) Quarterly Journal.

Roberts, Dar A.↗
NASA NTRS1991

Remote sensing and landslide hazard assessment

Remotely acquired multispectral data are used to improve landslide hazard assessments at all scales of investigation. A vegetation map produced from automated interpretation of TM data is used in a GIS context to explore the effect of vegetation type on debris flow occurrence in preparation for inclusion in debris flow hazard modeling. Spectral vegetation indices map spatial patterns of grass senescence which are found to be correlated with soil thickness variations on hillslopes. Grassland senescence is delayed over deeper, wetter soils that are likely debris flow source areas. Prediction of actual soil depths using vegetation indices may be possible up to some limiting depth greater than the grass rooting zone. On forested earthflows, the slow slide movement disrupts the overhead timber canopy, exposes understory vegetation and soils, and alters site spectral characteristics. Both spectral and textural measures from broad band multispectral data are successful at detecting an earthflow within an undisturbed old-growth forest.

Mckean, J.↗
NASA NTRS2011

Vegetation Water Content Mapping in a Diverse Agricultural Landscape: National Airborne Field Experiment 2006

Mapping land cover and vegetation characteristics on a regional scale is critical to soil moisture retrieval using microwave remote sensing. In aircraft-based experiments such as the National Airborne Field Experiment 2006 (NAFE 06), it is challenging to provide accurate high resolution vegetation information, especially on a daily basis. A technique proposed in previous studies was adapted here to the heterogenous conditions encountered in NAFE 06, which included a hydrologically complex landscape consisting of both irrigated and dryland agriculture. Using field vegetation sampling and ground-based reflectance measurements, the knowledge base for relating the Normalized Difference Water Index (NDWI) and the vegetation water content was extended to a greater diversity of agricultural crops, which included dryland and irrigated wheat, alfalfa, and canola. Critical to the generation of vegetation water content maps, the land cover for this region was determined from satellite visible/infrared imagery and ground surveys with an accuracy of 95.5% and a kappa coefficient of 0.95. The vegetation water content was estimated with a root mean square error of 0.33 kg/sq m. The results of this investigation contribute to a more robust database of global vegetation water content observations and demonstrate that the approach can be applied with high accuracy. Keywords: Vegetation, field experimentation, thematic mapper, NDWI, agriculture.

Cosh, Michael H.↗
DOE OSTI2026

Exploring the potential of using L-Band InSAR for the mapping of flooded vegetation in tropical wetlands

Wetlands play a critical role in global water and carbon cycles, yet monitoring their water extent remains difficult, particularly beneath dense vegetation. SAR-based techniques such as backscatter thresholding are limited by complex scattering mechanisms, while fully polarimetric SAR (PolSAR) data capable of detecting doublebounce scattering remain scarce. To address these challenges, this study evaluates the potential of Interferometric SAR (InSAR) for mapping water surfaces beneath vegetation, termed flooded vegetation, using the Atrato floodplain in Colombia as a case study. We develop an automated workflow combining InSAR fringe detection with local phase homogeneity analysis and random sampling of processing parameters to generate probabilistic flooded vegetation maps. Applied to ALOS PALSAR-1 L-band image pairs from 2007–2011, the workflow captures seasonal fluctuations in flooded extent ranging from 500 to 1,500 km2. Compared to other L-band SAR inundation products, the InSAR-based maps identify broader flooded areas, with ~70% agreement in pairwise comparisons. Around 84% of detections align with existing wetland inventories and seasonal changes correspond with regional hydrological indicators, including terrestrial water storage anomalies and water gauge measurements. PolSAR analysis shows that InSAR complements backscatter-based methods by detecting inundation in areas with weak double-bounce signals. These findings suggest that combining InSAR with backscatter-based methods can improve detection of flooded vegetation, which is especially relevant for the upcoming NISAR mission that will offer frequent global L-band observations.

Coastal inundation↗
NASA NTRS1973

Vegetative and geologic mapping of the western Seward Peninsula, Alaska, based on ERTS-1 imagery

ERTS-1 scene 1009-22095 (Western Seward Peninsula, Alaska) has been studied, partly as a training exercise, to evaluate whether direct visual examination of individual and custom color-composite prints can provide new information on the vegetation and geology of this relatively well known area of Alaska. The vegetation analysis reveals seven major vegetation types, only four of which are described on existing vegetation maps. In addition, the ERTS analysis provides greater detail than the existing maps on the areal distribution of vegetation types. The geologic analysis demonstrates that most of the major rock units and geomorphic boundaries shown on the available geologic maps could also be identified on the ERTS data. Several major high-angle faults were observed, but the zones of thrust faults which are much less obvious.

Anderson, J. H.↗
DOE OSTI2020

Sitewide Environmental Impact Statement Site 300 and Arroyo Mocho Lawrence Livermore National Laboratory Alameda and San Joaquin Counties, California (Mid-Term Report)

At the request of Lawrence Livermore National Security (LLNS), Nomad Ecology (Nomad) conducted sensitive botanical resource surveys, and vegetation mapping and classification of the 7,000-acre Lawrence Livermore National Laboratory (LLNL) Experimental Test Site (Site 300) and 17 acres surrounding the Arroyo Mocho pumping station and the access road to the pumping station (Arroyo Mocho). In addition to surveying for sensitive botanical resources, Nomad also compiled existing rare plant and vegetation data provided by LLNL from past monitoring and environmental impact evaluations. The results of these efforts will provide supporting information for a Site-wide Environmental Impact Statement (SWEIS). These surveys were conducted during the months of April – June, and August 2020. Rare plant surveys were scheduled for February and March 2020; however, February surveys were not initiated because the contract for this work was not finalized, and March surveys were cut short due to the timing of the Covid-19 shelter in place. February and March rare plant surveys are scheduled for 2021; therefore, the rare plant survey results in this report should be considered incomplete until the 2021 surveys are conducted. A total of 10 special status plant species were recorded within Site 300 and Arroyo Mocho. Of these 10, three were not previously recorded within the study areas, and include Hospital Canyon larkspur (Delphinium californicum subsp. interius), Jepson’s woolly sunflower (Eriophyllum jepsonii), and Michael’s rein orchid (Piperia michaelii), which all occur at Arroyo Mocho. Special status plant species known from these two sites total 23 rare plant occurrences (populations), which represent an estimated 50,929 rare plant individuals. This total of all special status plant species breaks down to one occurrence of a federally and/or state listed plant species (98 individuals), six occurrences of California Rare Plant Rank (CRPR) 1 & 2 species (49,010 individuals), and 16 occurrences of CRPR 3 & 4 species (1,821 individuals). A total of 35 vegetation communities were mapped at Site 300, of which 20 are considered Sensitive Natural Communities. A total of nine vegetation communities were mapped at Arroyo Mocho, of which two are considered Sensitive Natural Communities.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1973

Identification, definition and mapping of terrestrial ecosystems in interior Alaska

The author has identified the following significant results. The vegetation map in preparation at the time of the last report was refined and labeled. This map is presented as an indication of the spatial and classificatory detail possible from interpretations of enlarged ERTS-1 color photographs. Using this map, areas covered by the several vegetation types characterized by white spruce were determined by planimetry. A 1:63,360 scale land use map of the Juneau area was drawn. This map incorporates the land use classification system now under development by the U.S. Geological Survey. The ERTS-1 images used in making the Juneau map were used to determine changes in surface area of the terminal zones of advancing and receding glaciers, the Taku, Norris, and Mendenhall. A new 1:63,360 scale land use map of the Bonanza Creek Experimental Forest and vicinity was drawn. Several excellent new sciences of test areas were received from NASA in color-infrared transparency format. These are being used for making photographic prints for analysis and mapping according to procedures outlined in this report.

Anderson, J. H.↗
DOE OSTI2025

A Region-Growing Segmentation Approach to Delineating Timberline from Satellite-Derived Tree Fractional Cover Products

Timberline marks the transitions from continuous forests to sparse forests and tundra landscapes. As the spatial distribution and dynamics of timberline are closely associated with regional energy and carbon balance, mapping timberline is important to a wide range of environmental and ecological studies. However, current timberline delineation approaches remain under-developed. We proposed an automatic timberline delineation method based on a seeded region-growing segmentation technique and satellite-derived products of tree fractional cover. We applied our approach to the West Siberian Plain and Alaska treeline regions as defined by the Circumpolar Arctic Vegetation Map. The results demonstrate the effectiveness of the proposed method for the accurate delineation of the timberlines that spatially align well with very-high-resolution satellite images. Based on the delineated timberlines, we find regional-scale tree encroachment to be not as substantial as previously reported. The proposed approach can be applied to understanding climate-induced forest responses and inform forest management practices.

Circumpolar Arctic Vegetation Map↗
DOE OSTI2021

Final Site 300 Sensitive Botanical Resource Report for the Sitewide Environmental Impact Statement, Lawrence Livermore National Laboratory, Alameda and San Joaquin Counties, California

At the request of Lawrence Livermore National Security (LLNS), Nomad Ecology (Nomad) conducted sensitive botanical resource surveys, and vegetation mapping and classification of the 7,000-acre Lawrence Livermore National Laboratory (LLNL) Experimental Test Site (Site 300). In addition to surveying for sensitive botanical resources, Nomad also compiled existing rare plant and vegetation data provided by LLNL from past monitoring and environmental impact evaluations. The results of these efforts will provide supporting information for a Site-wide Environmental Impact Statement (SWEIS). These surveys were conducted during the months of April-June, and August 2020, and February and March 2021. Rare plant surveys were originally scheduled for February and March 2020; however, February surveys were not initiated because the contract for this work was not finalized, and March surveys were cut short due to the timing of the Covid-19 shelter in place. Therefore, February and March rare plant surveys were conducted in 2021. A total of seven special status plant species were recorded within Site 300. Special status plant species known from the site total 26 rare plant occurrences (populations), which represent an estimated 14,077 rare plant individuals. This total of all special status plant species breaks down to one occurrence of a federally and/or state listed plant species (98 individuals), five occurrences of California Rare Plant Rank (CRPR) 1 & 2 species (11,553 individuals), and 20 occurrences of CRPR 3 & 4 species (2,426 individuals). A total of 35 vegetation communities were mapped at Site 300, of which 20 are considered Sensitive Natural Communities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The impact of forest-controlled snow variability on late-season streamflow varies by climatic region and forest structure

Previous studies have documented how forests influence snow at fine spatial scales, but none have documented the influence that existing forest-snow variability has on streamflow. Here to test how much forest-controlled snow variability influences streamflow, a tiling parameterization based on classifications from high-resolution (1–3 m) vegetation maps was incorporated into the Distributed Hydrology and Soil Vegetation Model (DHSVM). Within each grid cell (90–150 m), the tiling parameterization simulated forest-snow variability with four independently evolving snowpacks. Each tile had unique radiation conditions to represent conditions underneath the canopy, in exposed areas, and along north- and south-facing forest edges. This tiled parameterization was used to test where and when detailed forest-snow modelling should be considered further and where and when the impacts are too small to be worth the effort. To test this, tiled model simulations of streamflow were compared to non-tiled model simulations in the Sierra Nevada, CA, the Jemez Mountains, NM, and the Eastern Cascades, WA. In Tuolumne, CA, the tiled model simulated little difference in grid cell average SWE, and late-season streamflow decreased by only 3%–4% compared to the non-tiled model. In Jemez, NM, the tiled model decreased late-season streamflow by 18% due to increased sublimation. In Chiwawa, WA, the tiled model increased late-season streamflow by 15% due to high shortwave radiation attenuation and less longwave radiation enhancement from the forest. Furthermore, within the Chiwawa, a substantial silvicultural practice was synthetically implemented to increase the north-facing edge's fractional area. This silvicultural experiment, which used the same fractional forest area in all simulations increased late-season streamflow by 35% compared to tiled model simulations that did not represent forest edges. In conclusion, representing forest-SWE variability had an effect on late-season streamflow in some watersheds but not in others based on the fractional area of the forest edges, forest characteristics, and climate conditions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1973

Identification, definition and mapping of terrestrial ecosystems in interior Alaska

The author has identified the following significant results. Two new, as yet unfinished vegetation maps are presented. These tend further to substantiate the belief that ERTS-1 imagery is a valuable mapping tool. Newly selected scenes show that vegetation interpretations can be refined through use of non-growing season imagery, particularly through the different spectral characteristics of vegetation lacking foliage and through the effect of vegetation structure on apparent snow cover. Scenes now are available for all test area north of the Alaska Range except Mt. McKinley National Park. No support was obtained for the hypothesis that similar interband ratios, from two areas apparently different spectrally because of different sun angles, would indicate similar surface features. However, attempts to test this hypothesis have so far been casual.

Anderson, J. H.↗
NASA NTRS1973

Identification, definition and mapping of terrestrial ecosystems in interior Alaska

The author has identified the following significant results. A reconstituted, simulated color-infrared print, enlarged to a scale of 1:250,000, was used to make a vegetation map of a 3,110 sq km area just west of Fairbanks, Alaska. Information was traced from the print which comprised the southeastern part of ERTS-1 scene 1033-21011. A 1:1,000,000 scale color-infrared transparency of this scene, obtained from NASA, was used along side the print as an aid in recognizing colors, color intensities and blends, and mosaics of different colors. Color units on the transparency and print were identified according to vegetation types using NASA air photos, U.S. Forest Service air photos, and experience of the investigator. Five more or less pure colors were identified and associated with vegetation types. These colors were designated according to their appearances on the print: (1) orange for forest vegetation dominated by broad-leaved trees: (2) gray for forest vegetation dominated by needle-leaved trees; (3) violet for scrub vegetation; (4) light violet denoting herbaceous tundra vegetation; and (5) dull violet for muskeg vegetation. This study has shown, through close examinations of the NASA transparency, that much more detailed vegetation landscape, or ecosystem maps could be produced, if only spectral signatures could be consistently and reliably recognized and transferred to a map of suitable scale.

Anderson, J. H.↗