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At least 127 records · Page 7

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↗

Ecosystem Carbon Emissions from 2015 Forest Fires in Interior Alaska

In the summer of 2015, hundreds of wildfires burned across the state of Alaska, and consumed more than 1.6 million ha of boreal forest and wetlands in the Yukon-Koyukuk region. Mapping of 113 large wildfires using Landsat satellite images from before and after 2015 indicated that nearly 60% of this area was burned at moderate-to-high severity levels. Field measurements near the town of Tanana on the Yukon River were carried out in July of 2017 in both unburned and 2015 burned forested areas (nearly adjacent to one-another) to visually verify locations of different Landsat burn severity classes (low, moderate, or high). Results: Field measurements indicated that the loss of surface organic layers in boreal ecosystem fires is a major factor determining post-fire soil temperature changes, depth of thawing, and carbon losses from the mineral topsoil layer. Measurements in forest sites showed that soil temperature profiles to 30 cm depth at burned forest sites increased by an average of 8o - 10o C compared to unburned forest sites. Sampling and laboratory analysis indicated a 65% reduction in soil carbon content and a 58% reduction in soil nitrogen content in severely burned sample sites compared to soil mineral samples from nearby unburned spruce forests. Conclusions: Combined with nearly unprecedented forest areas severely burned in the Interior region of Alaska in 2015, total ecosystem fire emission of carbon to the atmosphere exceeded most previous estimates for the state.

Ecosystem↗

Regional Application of an Ecosystem Production Model for Studies of Biogeochemistry in the...

The degree to which primary production, soil carbon, and trace gas fluxes in tropical forests of the Amazon are limited by moisture availability and other environmental factors was examined using an ecosystem modeling application for the country of Brazil. A regional geographic information system (GIS) serves as the data source of climate drivers, satellite images, land cover, and soil properties for input to the NASA Ames-CASA (Carnegie-Ames-Stanford Approach) model over a 8-km grid resolution. Simulation results supports the hypothesis that net primary production (NPP) is limited by cloud interception of solar radiation over the humid northwestern portion of the region. Peak annual rates for NPP of nearly 1.4 kg C m-2yr -1are localized in the seasonally dry eastern Amazon in areas that we assume are primarily deep-rooted evergreen forest cover. Regional effects of forest conversion on NPP and soil carbon content are indicated in the model results, especially in seasonally dry areas. Comparison of model flux predictions along selected eco-climatic transects reveal moisture, soil, and land use controls on gradients of ecosystem production and soil trace gas emissions (CO2, N2O, and NO). These results are used to formulate a series of research hypotheses for testing in the next phase of regional modeling, which includes recalibration of the light-use efficiency term in CASA using field measurements of NPP, and refinements of vegetation index and soil property (texture and potential rooting depth) maps for the region.

Potter, C. S.↗

Application of ERTS-1 data to analysis of agricultural crops and forests in Michigan

The results reported are based on analysis of ERTS Frame 1033-15580 collected over southwestern Lower Michigan on August 25, 1972. Major agricultural crops such as corn and soybeans were approaching maturity at this data and forest canopies were dense. Extensive ground truth information was gathered by detailed field study of test strips. This detailed information was supplemented over larger areas by interpretation of RB-57 and C-47 photography and MSS imagery. Recognition processing of ERTS-1 MSS data was carried out on a digital computer. Fields and forest stands were selected as training sets and test areas. Aerial imagery was essential for locating the positions of these selected areas on ERTS digital tapes. The recognition process was successful for each type of vegetation which had a dense green canopy such as forests, corn, and soybeans. Bare soil was also recognizable as a category.

Safir, G. R.↗

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

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

Quay, Paul↗

The relationship between surface temperature and a spectral vegetation index of a tallgrass prairie - Effects of burning and other landscape controls

Site-to-site variability in the relation between remotely-sensed surface temperatures (Ts) and the normalized difference spectral vegetation index (NDVI) of a tallgrass prairie was investigated. The primary objective was to determine whether the proportion of burnt/unburnt area within a sub-scene affected the Ts-NDVI regression slope (SL). Regression analyses confirmed that burn treatments, particularly on steep slopes, were responsible for most of the observed variability in SL while soil moisture content and the forested areas also had a significant effect on SL.

Hope, A. S.↗

BOREAS TGB-5 Biogenic Soil Emissions of NO and N2O

The BOReal Ecosystem-Atmosphere Study Trace Gas Biogeochemistry (BOREAS TGB)-5 team made several measurements of trace gas concentrations and fluxes at various NSA sites. This data set contains biogenic soil emissions of nitric oxide and nitrous oxide that were measured over a wide range of spatial and temporal site parameters. Since very little is known about biogenic soil emissions of nitric oxide and nitrous oxide from the boreal forest, the goal of the measurements was to characterize the biogenic soil fluxes of nitric oxide and nitrous oxide from black spruce and jack pine areas in the boreal forest. The diurnal variation and monthly variation of the emissions was examined as well as the impact of wetting through natural or artificial means. Temporally, the data cover mid-August 1993, June to August 1994, and mid-July 1995. The data are provided in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884).

Levine, J. S.↗

Canadian Experiment for Soil Moisture in 2010 (CanEX-SM10): Overview and Preliminary Results

The Canadian Experiment for Soil Moisture in 2010 (CanEx-SM10) was carried out in Saskatchewan, Canada from 31 May to 16 June, 2010. Its main objective was to contribute to Soil Moisture and Ocean salinity (SMOS) mission validation and the pre-launch assessment of Soil Moisture and Active and Passive (SMAP) mission. During CanEx-SM10, SMOS data as well as other passive and active microwave measurements were collected by both airborne and satellite platforms. Ground-based measurements of soil (moisture, temperature, roughness, bulk density) and vegetation characteristics (Leaf Area Index, biomass, vegetation height) were conducted close in time to the airborne and satellite acquisitions. Besides, two ground-based in situ networks provided continuous measurements of meteorological conditions and soil moisture and soil temperature profiles. Two sites, each covering 33 km x 71 km (about two SMOS pixels) were selected in agricultural and boreal forested areas in order to provide contrasting soil and vegetation conditions. This paper describes the measurement strategy, provides an overview of the data sets and presents preliminary results. Over the agricultural area, the airborne L-band brightness temperatures matched up well with the SMOS data. The Radio frequency interference (RFI) observed in both SMOS and the airborne L-band radiometer data exhibited spatial and temporal variability and polarization dependency. The temporal evolution of SMOS soil moisture product matched that observed with the ground data, but the absolute soil moisture estimates did not meet the accuracy requirements (0.04 m3/m3) of the SMOS mission. AMSR-E soil moisture estimates are more closely correlated with measured soil moisture.

Magagi, Ramata↗

Estimating forest productivity with Thematic Mapper and biogeographical data

Spectral data from the Landsat Thematic Mapper (TM) on three forest exosystems (the southern Illinois, the Great Smoky Mountains regions in Tennessee and North Carolina, and the central Adirondack Mountains in New York) were used in conjunction with ground-collected measures of forest productivity and such information as the area's slope, aspect, elevation, and soil and vegetation types, to develop models of regional forest productivity. It is shown that the models developed may be used to estimate the productivity of a region with a high degree of confidence, but that the reliability of single-pixel estimates is poor. The characteristics of a given ecosystem determine which spectral values are most closely related to forest productivity. Thus, mid-IR, NIR, and visible bands are most significant in Illinois and New York, while the thermal band is relatively more important in the Smokies.

Cook, Elizabeth A.↗

Haiti Agriculture II: Evaluating the Success of Reforestation Practices in Haiti

The Caribbean country of Haiti has an extensive history of deforestation and environmental degradation stemming from French colonization. Over the past 33 years, the Haiti Reforestation Partnership (HRP) and their partners, Comprehensive Development Program (CODEP), have planted approximately 15.52 million trees. However, these efforts lacked scientific guidance to ensure successful forest stand survival. The NASA DEVELOP team partnered with the HRP to create a habitat suitability model (HSM) by using PlanetScope and Sentinel-2 Multispectral Instrument (MSI) imagery. The team also incorporated Landsat 8 and 9 OLI surface temperature, Centre National de L’Information Geo-Spatiale (CNIGS) Airborne Lidar, and ancillary datasets to analyze areas suitable for future reforestation efforts. The habitat model suggested locations with higher forest stand survival based on topography, soil health, climate, and feasibility to access suggested locations. We confirmed the HSM through a cross-analyzation of high enhanced vegetation index (EVI) values. Areas with lower EVI values and higher suitability based on the HSM were suggested for future planting as they lack well-established forest stands but have optimal conditions for growth. Through the creation of the HSM, the team provided the HRP with static maps of high suitability, a 3D printed elevation model, and a guidebook for animators. Additionally, the team provided a structured video highlighting the HRP’s efforts. Effective reforestation and better forest stand survival would help to achieve the goal of securing community food security. This would also serve as a guide to expand planting efforts into other locations and communities.

Kelli Roberts↗

Patterns of Canopy and Surface Layer Consumption in a Boreal Forest Fire from Repeat Airborne Lidar

Fire in the boreal region is the dominant agent of forest disturbance with direct impacts on ecosystem structure, carbon cycling, and global climate. Global and biome-scale impacts are mediated by burn severity, measured as loss of forest canopy and consumption of the soil organic layer. To date, knowledge of the spatial variability in burn severity has been limited by sparse field sampling and moderate resolution satellite data. Here, we used pre- and post-fire airborne lidar data to directly estimate changes in canopy vertical structure and surface elevation for a 2005 boreal forest fire on Alaskas Kenai Peninsula. We found that both canopy and surface losses were strongly linked to pre-fire species composition and exhibited important fine-scale spatial variability at sub-30m resolution. The fractional reduction in canopy volume ranged from 0.61 in lowland black spruce stands to 0.27 in mixed white spruce and broad leaf forest. Residual structure largely reflects standing dead trees, highlighting the influence of pre-fire forest structure on delayed carbon losses from above ground biomass, post-fire albedo, and variability in understory light environments. Median loss of surface elevation was highest in lowland black spruce stands (0.18 m) but much lower in mixed stands (0.02 m), consistent with differences in pre-fire organic layer accumulation. Spatially continuous depth-of-burn estimates from repeat lidar measurements provide novel information to constrain carbon emissions from the surface organic layer and may inform related research on post-fire successional trajectories. Spectral measures of burn severity from Landsat were correlated with canopy (r = 0.76) and surface (r = -0.71) removal in black spruce stands but captured less of the spatial variability in fire effects for mixed stands (canopy r = 0.56, surface r = -0.26), underscoring the difficulty in capturing fire effects in heterogeneous boreal forest landscapes using proxy measures of burn severity from Landsat.

Alonzo, Michael↗

Remote detection of soil geochemical anomalies from an aircraft platform - Examples from the Virginia Piedmont

The use of remote-sensing data on forest leaf flush to identify areas with anomalously high soil heavy-metal concentrations is demonstrated using airborne Thematic Mapper Simulator (TMS) leaf-area-index data obtained over two sites in Virginia in spring 1983 and 1984. Mean-reflectance differences, especially in the 760-900-nm and 630-690-nm bands, corresponding to delayed leaf flush are found to be good indicators of higher heavy-metal concentration. Airborne and ground-based canopy-temperature measurements are also shown to be significantly higher in high-heavy-metal areas than in control areas.

Bell, R.↗

Automated image processing of Landsat II digital data for watershed runoff prediction

Digital image processing of Landsat data from a 230 sq km area was examined as a possible means of generating soil cover information for use in the watershed runoff prediction of Kern County, California. The soil cover information included data on brush, grass, pasture lands and forests. A classification accuracy of 94% for the Landsat-based soil cover survey suggested that the technique could be applied to the watershed runoff estimate. However, problems involving the survey of complex mountainous environments may require further attention

Sasso, R. R.↗

Spatial transportability of geobotanical spectral signatures associated with soil geochemical anomalies

Consideration is given to a specific problem of spectral signature extension through examination and comparison of multitemporal spectral data signatures developed over a generalized, along-strike geochemical trend located within eastern deciduous hardwood forest. The spectral geobotanical signatures associated with soil Pb, Cu, and Zn anomalies were examined in south-central Virginia. Spectral discrimination between a training pair of anomalous and control sites within the Mineral district was 100 percent successful. It is concluded that spectral geobotanical signatures serve to identify regions of lowered biomass, lowered vigor, and/or differing species composition.

Bell, R.↗

Completing below-ground carbon budgets for pastures, recovering forests, and mature forests of Amazonia

This progress report covers the following efforts initiated for the year: year-round monthly soil CO2 flux measurements were started in both primary and secondary forests and in managed and degraded pastures; root sorting and weighing has begun and all four ecosystems at Paragominas have been analyzed through samples; regional modeling of soil water dynamics and minimum rooting depth has been done and the RADAMBRASIL soils database has been digitized and a 20 year record of the precipitation for the region has been produced, along with a hydrological ('bucket-tipping') model that will run within a GIS framework; prototype tension lysimeters have been designed and installed in soil pits to begin assessing the importance of DOC as a source of organic matter in deep soils; and many publications, listed in this document, have resulted from this year's research. Two of the papers published are included with this annual report document.

Davidson, Eric A.↗

Okefenokee Water Resources: Using Earth Observations to Assess Hydrologic Changes and Wildfire Risk in the Okefenokee Swamp

The Okefenokee Swamp is a vital ecosystem known for its protection of biodiversity, peatland carbon sinks, and recreational and economic opportunities for local residents. The swamp has experienced several wildfires since the 1990s, and new development along the borders of Okefenokee National Wildlife Refuge (ONWR) threatens to alter hydrologic activity and increase fire frequency. NASA DEVELOP partnered with staff at the ONWR to determine the feasibility of using satellite imagery to assess wildfire risk and map changes in vegetation cover. Using data from NASA satellites Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI), Soil Moisture Active Passive (SMAP) data from the USDA’s Crop Condition and Soil Moisture Analytics Tool (Crop-CASMA), European Space Agency (ESA) Sentinel-1 C-Band Synthetic Aperture Radar (C-SAR), and Sentinel-2 Multispectral Instrument (MSI), the DEVELOP team assessed the relationship between hydrologic change, vegetation cover, and wildfire risk in the swamp. Results showed that the southern portion of ONWR has been burned the most since 1990 and has greater water stability than other areas of the refuge. The team also found that the largest pockets of mature forests remain in the northernmost regions. Soil moisture anomaly readings may serve as an indicator of fire conditions. The team used these results to create a vegetation map, a swamp water visibility time series map, a historical wildfire correlation analysis, and a methodology tutorial. These products will assist the ONWR in making informed management decisions about the future of the Okefenokee Swamp.

Brianne Kendall↗

BOREAS TF-4 CO2 and CH4 Chamber Flux Data from the SSA

The BOREAS TF-4 team measured fluxes of CO2 and CH4 across the soil-air interface in four ages of jack pine forest at the BOREAS SSA during August 1993 to March 1995. Gross and net flux of CO2 and flux of CH4 between soil and air are presented for 24 chamber sites in mature jack pine forest, 20-year-old, 4-year-old, and clear cut areas. The data are stored in tabular ASCII files.

Anderson, Dean↗