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Elijah Ramsey III

Publications and source records attributed to Elijah Ramsey III.

At least 19 recordsLinked to original sources
USGS2011

Hyperspectral remote sensing of wetland vegetation

Wetlands proportionally exert a higher influence on biogeochemical fluxes among the land, the atmosphere, and hydrologic systems than their 1% worldwide occurrence suggests [1]. Although their frequency of occurrence is low and their importance is high, wetlands continue to face high detrimental pressures from natural and human-induced forces [2]. Remote sensing offers the single best source of timely, synoptic wetland status and trends information at a variety of spatial and temporal scales [3].

Book chapter↗
USGS2010

Mapping the onset and progression of marsh dieback

Along the Gulf of Mexico (GOM) coasts, vast wetlands inject valuable nutrients and suspended and dissolved materials into the coastal ocean. Juncus roemerianus (black needlerush) wetlands, dominating coastlines in the northeastern GOM, transition to the Spartina alternifl ora (smooth cordgrass) coastline of Louisiana. Mixed marsh and mangrove barrier island systems occupy the southeastern and southwestern GOM [1,2].

Louisiana↗
USGS2008

Conveying multiple, complex themes and classes for natural resource assessments

Two methods were used to convey the spatial association between a classified forested landscape, the distribution of a hurricane impact, and the subsequent recovery of the habitat from the storm. The first method used a constant hue matrix with varying intensity to visually represent combinations of impact and recovery magnitudes. The second combined two colors of constant hue to represent the impact and recovery succession. Maps produced using either method generally simulated known impact and recovery spatial distributions. In the constant hue representation with varying intensity, the combination of impact and recovery could not be uniquely represented in all cases and the relationship was confused between the map and legend color. In the two color representation, however, a definite link existed between the map and legend color and the impact and recovery magnitudes. A drawback to this approach over the constant hue approach was that a separate map had to be used to represent each forest type and its associated impact and recovery covariation. The two color combination, however, provided improved contrast and uniquely defined the link between map and legend colors, and ultimately, a unique impact and recovery combination. In addition, the two color combination produced the highest conveyance of spatial information related to the covariation of forest type, impact, and recovery.

Louisiana↗
USGS2005

Remote sensing of coastal environments

Coastal ecosystems are transitional environments that are sensitively balanced between open water and upland landscapes. Worldwide, they exhibit extreme variations in areal extent, spatial complexity, and temporal variability. Sustaining these ecosystems requires the ability to monitor their biophysical features and controlling processes at high spatial and temporal resolutions but within a holistic context. Remote sensing is the only tool that can economically measure these features and processes over large areas at appropriate resolutions. Consequently, it offers the only holistic approach to understanding the variable forces shaping the dynamic coastal landscape. Remote sensing must be able to adjust to these spatially and temporally changing conditions and also be able to discriminate subtle differences in these systems. As a result, remote sensing of coastal ecosystems is a complex undertaking that needs to incorporate not only the ability to define the observable hydrologic and vegetation features, but also the scale of measurement.

Book chapter↗
USGS2005

Leaf optical property changes associated with the occurrence of Spartina alterniflora dieback in Coastal Louisiana related to remote sensing mapping

In order to provide a remote sensing solution that would detect both the initial onset and monitor the early, as well as, the later stages of impact progression, changes in live leaf optical properties were compared along transects spanning impacted coastal Louisiana marsh sites. Green and red edge reflectance trends generally represented the early stages and fairly well the later stages of dieback progression, while blue and red reflectance and absorption trends represented the later stages of marsh impact that were most closely related to visible signs of marsh impact. Leaf reflectance in the near infrared (NIR) was not compatible with visual reflectance trends and did not co-vary with derived indicators of leaf water content, and thereby, water stress. Predicted from reflectance ratios, carotene tended to remain constant or increase relative to chlorophyll following noted changes in stressed plants at the two least impacted sites, while the pigments co-varied at the two most impacted sites. As an operational solution most amenable for satellite remote sensing, the NIR /red ratio followed blue and red reflectance trends while the NIR /green ratio mimicked the green and red edge reflectance trends indicating impact onset and progression, as well as, generally portraying blue and red reflectance trends indicating later stages of impact. The NIR/ green ratio magnitude and range generally increased from the most to least impacted site providing a convenient method to detect dieback onset and monitor dieback progression. This research demonstrated that remote sensing mapping at these sites could offer a more accurate perception of dieback severity distribution than offered by determinations relying on visible indicators of marsh changes.

Louisiana↗
USGS2004

Light attenuation profiling as an indicator of structural changes in coastal marshes

To best respond to natural and human-induced stresses, resource managers and researchers require remote sensing techniques that can map the biophysical characteristics of natural resources on regional and local scales. The implementation of advanced measurement techniques would provide significant improvements in the quantity, quality, and timeliness of biophysical data useful in understanding the sensitivity of vegetation communities to external influences. In turn, this biophysical data would provide resource planners with a rational decision-making system for resource allocation and response action development planning.

Book chapter↗
USGS1998

Resource management of forested wetlands: Hurricane impact and recovery mapped by combining Landsat TM and NOAA AVHRR data

A temporal suite of NOAA Advanced Very High Resolution Radiometer (AVHRR) images, transformed into a vegetation biomass indicator, was combined with a single-date classification of Landsat Thematic Mapper (TM) to map the association between forest type and hurricane effects. Hurricane effects to the forested wetland included an abrupt decrease and subsequent increase in biomass. The decrease was associated with hurricane impact and the increase with an abnormal bloom in vegetation in the impacted areas. Impact severity was estimated by differencing the biomass maps before and immediately (3 days) after the hurricane. Recovery magnitude was estimated by differencing the biomass maps from immediately (3 days) after and shortly (1.5 months) after the hurricane. Regions of dominantly hardwoods suffering high to moderate impacts and of dominantly cypress-tupelos suffering low impacts identified in this study corroborated findings of earlier studies. Conversely, areas not reported in previous studies as affected were identified, and these areas showed a reverse relationship, i.e., highly impacted cypresstupelo and low or moderately impacted hardwoods. Additionally, generated proportions of hardwood, cypress-tupelo, and open (mixed) forests per each 1-km pixel (impact and recovery maps) suggest that regions containing higher percentages of cypress-tupelos were more likely to have sustained higher impacts. Visual examination of the impact map revealed a spatial covariation between increased impact magnitudes and river corridors dominated by open forest. This spatial association was corroborated by examining changes in the percentage of open forest per 1-km impact pixel; the percentage of open forest peaked at moderate to high impacts. The distribution of recovery supported the impact spatial distribution; however, the magnitudes of the two indicators of hurricane effects were not always spatially dependent. Converse to univariate statistics describing a11 forested area within the basin, higher recoveries tended to be related to higher percentages of hardwoods. Lower recoveries, on the other hand, tended to be related to forests with nearly equal percentages of hardwoods and cypress-tupelo.

Louisiana↗
USGS1997

Comparison of Landsat Thematic Mapper and high resolution photography to Identify change in complex coastal wetlands

Landsat Thematic Mapper (TM) images were used to generate pre- and post- hurricane classifications of a complex wetland environment in southern Louisiana. Accuracies were estimated as 77% and 81.5% for the pre- and post- classifications that included water, emergent vegetation, floating vegetation, and mud flats. From the two classifications, areas of emergent vegetation loss were identified. The classifications and change map were compared to similar output generated from high resolution color infrared photography. The comparison showed spatial scale of the sensor was the most important factor in separation of classes in this type of wetland environment. Classifications derived by using the TM images provided good class separation when one class dominated more extensive areas (>30 m), but not when mixtures of wetland types were on the same order as the TM sensor spatial resolution. Boundary pixel mixtures were problematic, however problems also occurred in areas of fairly continuous canopies containing small pockets of water and floating vegetation, and in areas of degrading marsh. Both areas were predominately misclassified as emergent vegetation. In the case of change detection, loss of emergent vegetation occurring as small pockets was not identified, whereas loss of degraded marsh was identified but the spatial continuity and extent overemphasized. In combination, these misclassifications resulted in the TM change analysis overpredicting emergent vegetation loss by about 40%.

Louisiana↗
USGS1995

Modeling mangrove canopy reflectance using a light interaction model and an optimization technique

At 20 sites, incorporating mixtures of black, red, and white mangroves, canopy reflectance spectra were derived from high resolution spectral data taken from a helicopter platform. Canopy characteristics were predicted from the canopy reflectance spectra by using measured and estimated data as inputs into a light-canopy interaction model within a optimization routine. Pertinent to average conditions typifying the area and time of the study, the light-canopy interaction model accomplished two goals. Using the model as a predictor, a sensitivity analysis suggested that little error in modelling the near nadir view canopy reflectance (R cv ) would result from assuming an average soil reflectance of about 0.1, at leaf area index (LAI) values above 2, at near infrared (NIR) leaf reflectances higher than about 0.45. and at sun elevation angles >40 o . Moderate errors could result from assuming a spherical leaf angel distribution (LAD), and relatively high errors could result from errors in estimating visible leaf reflectances (and NIR leaf reflectances <0.45) and percent skylight. Differences between canopy hemispherical reflectance (R c ) and R cv were dominated by percent skylight variation, while differences between R c and R cv were moderate to slight at a sun elevation above 20 o to 30 o , a near spherical LAD, a soil reflectance near 0.1, a LAI up to 4, and a NIR leaf reflectance less than 0.7. Simulated canopy reflectance spectra were close predictors of obtained spectra, with R 2 values >0.97. Mean predicted LAI values were 2.6±0.86 (mean ±1 standard deviation) and were highly related to LAI values derived from field measurements. Seventy-eight percent of the modelled LAI variance was predicted by a normalized difference vegetation index transform of the field canopy spectra data. Predicted LAD values had a near spherical mean value, while the mean difference between input (estimated from laboratory measurements) and predicted leaf reflectances was nearly zero.

Florida↗