Elijah W. Ramsey

Oil detection in a coastal marsh with polarimetric Synthetic Aperture Radar (SAR)

The National Aeronautics and Space Administration’s airborne Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) was deployed in June 2010 in response to the Deepwater Horizon oil spill in the Gulf of Mexico. UAVSAR is a fully polarimetric L-band Synthetic Aperture Radar (SAR) sensor for obtaining data at high spatial resolutions. Starting a month prior to the UAVSAR collections, visual observations confirmed oil impacts along shorelines within northeastern Barataria Bay waters in eastern coastal Louisiana. UAVSAR data along several flight lines over Barataria Bay were collected on 23 June 2010, including the repeat flight line for which data were collected in June 2009. Our analysis of calibrated single-look complex data for these flight lines shows that structural damage of shoreline marsh accompanied by oil occurrence manifested as anomalous features not evident in pre-spill data. Freeman-Durden (FD) and Cloude-Pottier (CP) decompositions of the polarimetric data and Wishart classifications seeded with the FD and CP classes also highlighted these nearshore features as a change in dominant scattering mechanism. All decompositions and classifications also identify a class of interior marshes that reproduce the spatially extensive changes in backscatter indicated by the pre- and post-spill comparison of multi-polarization radar backscatter data. FD and CP decompositions reveal that those changes indicate a transform of dominant scatter from primarily surface or volumetric to double or even bounce. Given supportive evidence that oil-polluted waters penetrated into the interior marshes, it is reasonable that these backscatter changes correspond with oil exposure; however, multiple factors prevent unambiguous determination of whether UAVSAR detected oil in interior marshes.

Forest impact estimated with NOAA AVHRR and Landsat TM data related to an empirical hurricane wind-field distribution

Abstract An empirical model was used to relate forest type and hurricane-impact distribution with wind speed and duration to explain the variation of hurricane damage among forest types along the Atchafalaya River basin of coastal Louisiana. Forest-type distribution was derived from Landsat Thematic Mapper image data, hurricane-impact distribution from a suite of transformed advanced very high resolution radiometer images, and wind speed and duration from a wind-field model. The empirical model explained 73%, 84%, and 87% of the impact variances for open, hardwood, and cypress–tupelo forests, respectively. These results showed that the estimated impact for each forest type was highly related to the duration and speed of extreme winds associated with Hurricane Andrew in 1992. The wind-field model projected that the highest wind speeds were in the southern basin, dominated by cypress–tupelo and open forests, while lower wind speeds were in the northern basin, dominated by hardwood forests. This evidence could explain why, on average, the impact to cypress–tupelos was more severe than to hardwoods, even though cypress–tupelos are less susceptible to wind damage. Further, examination of the relative importance of wind speed in explaining the impact severity to each forest type showed that the impact to hardwood forests was mainly related to tropical-depression to tropical-storm force wind speeds. Impacts to cypress–tupelo and open forests (a mixture of willows and cypress–tupelo) were broadly related to tropical-storm force wind speeds and by wind speeds near and somewhat in excess of hurricane force. Decoupling the importance of duration from speed in explaining the impact severity to the forests could not be fully realized. Most evidence, however, hinted that impact severity was positively related to higher durations at critical wind speeds. Wind-speed intervals, which were important in explaining the impact severity on hardwoods, showed that higher durations, but not the highest wind speeds, were concentrated in the northern basin, dominated by hardwoods. The extreme impacts associated with the cypress–tupelo forests in the southeast corner of the basin intersected the highest durations as well as the highest wind speeds.

Generation and validation of characteristic spectra from EO1 Hyperion image data for detecting the occurrence of the invasive species, Chinese tallow

Chinese tallow (Triadica sebifera) is an invasive tree that is spreading throughout the south‐eastern United States and now into the west, and in many places causing extensive change to native habitat and associated wildlife. Detecting and mapping the relative distribution of this species is important to its control and eradication. To map the relative distribution of Chinese tallow within a south‐western Louisiana coastal wetland to upland environment, Earth Observing 1 (EO1) satellite Hyperion sensor hyperspectral image data were combined with a subpixel extraction method that modelled characteristic spectra from the image data without requiring a priori characteristic spectra. Because of the low percentage occurrences of Chinese tallow and high spectral covariation in the environment, unique validation and verification methods were implemented, relying on simultaneous collection of field canopy reflectance spectra and subsequent classification of canopy compositions. The subpixel extraction method produced five characteristic spectra, which we further refined to four that adequately represented the field spectra, as well as the Hyperion imaged canopy reflectance datasets. Characteristic spectra were designated as senescing foliage, cypress‐tupelo trees, and trees without leaves; shadows and green vegetation; senescing Chinese tallow with yellow leaves and yellowing foliage; and senescing Chinese tallow with red leaves (‘red tallow’). About 81% (n = 34) of the field and 78% (n = 33) of the Hyperion imaged characteristic spectra associated with ‘red tallow’ were explained by the compositions generated in the field slide classifications.

Using multiple-polarization L-band radar to monitor marsh burn recovery

Aircraft L-band VV-, HH-, and VH-polarizations were examined as tools for monitoring burn recovery in a coastal marsh. Significant relationships were observed between time-since-burn (difference between burn and image collection dates; 550-900 days after burn) and returns related to all polarizations. As marsh burn recovery progressed, VV returns decreased while HH and VH returns increased. Radar returns extracted from control sites adjacent to each burn-simulated nonburn marsh and were not individually or in combination significantly related to the time-since-burn. Normalized by the control data, VH-polarization explained up to 83% of the total variations. Overall, the L-band multipolarization radars estimated time-since-burn within /spl plusmn/59 to /spl plusmn/92 days.

Satellite Optical and Radar Data Used to Track Wetland Forest Impact and Short-Term Recovery from Hurricane Katrina

Satellite Landsat Thematic Mapper (TM) and RADARSAT-1 (radar) satellite image data collected before and after the landfall of Hurricane Katrina in the Pearl River Wildlife Management Area on the Louisiana-Mississippi border, USA, were applied to the study of forested wetland impact and recovery. We documented the overall similarity in the radar and optical satellite mapping of impact and recovery patterns and highlighted some unique differences that could be used to provide consistent and relevant ecological monitoring. Satellite optical data transformed to a canopy foliage index (CFI) indicated a dramatic decrease in canopy cover immediately after the storm, which then recovered rapidly in the Taxodium distichum (baldcypress) and Nyssa aquatica (water tupelo) forest. Although CFI levels in early October indicated rapid foliage recovery, the abnormally high radar responses associated with the cypress forest suggested a persistent poststorm difference in canopy structure. Impact and recovery mapping results showed that even though cypress forests experienced very high wind speeds, damage was largely limited to foliage loss. Bottomland hardwoods, experiencing progressively lower wind speeds further inland, suffered impacts ranging from increased occurrences of downed trees in the south to partial foliage loss in the north. In addition, bottomland hardwood impact and recovery patterns suggested that impact severity was associated with a difference in stand structure possibly related to environmental conditions that were not revealed in the prehurricane 25-m optical and radar image analyses.

Multiple Baseline Radar Interferometry Applied to Coastal Land Cover Classification and Change Analyses

ERS-1 and ERS-2 SAR data were collected in tandem over a four-month period and used to generate interferometric coherence, phase, and intensity products that we compared to a classified land cover coastal map of Big Bend, Florida. Forests displayed the highest intensity, and marshes the lowest. The intensity for fresh marsh and forests progressively shifted while saline marsh intensity variance distribution changed with the season. Intensity variability suggested instability between temporal comparisons. Forests, especially hardwoods, displayed lower coherences and marshes higher. Only marshes retained coherence after 70 days. Coherence was more responsive to land cover class than intensity and provided discrimination in winter. Phase distributions helped reveal variation in vegetation structure, identify broad land cover classes and unique within-class variations, and estimate water-level changes.

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.

Limitations and Potential of Satellite Imagery to Monitor Environmental Response to Coastal Flooding

Abstract RAMSEY, E. III; WERLE, D.; SUZUOKI, Y.; RANGOONWALA, A., and LU, Z., 2012. Limitations and potential of satellite imagery to monitor environmental response to coastal flooding. Storm-surge flooding and marsh response throughout the coastal wetlands of Louisiana were mapped using several types of remote sensing data collected before and after Hurricanes Gustav and Ike in 2008. These included synthetic aperture radar (SAR) data obtained from the (1) C-band advance SAR (ASAR) aboard the Environmental Satellite, (2) phased-array type L-band SAR (PALSAR) aboard the Advanced Land Observing Satellite, and (3) optical data obtained from Thematic Mapper (TM) sensor aboard the Land Satellite (Landsat). In estuarine marshes, L-band SAR and C-band ASAR provided accurate flood extent information when depths averaged at least 80 cm, but only L-band SAR provided consistent subcanopy detection when depths averaged 50 cm or less. Low performance of inundation mapping based on C-band ASAR was attributed to an apparent inundation detection limit (>30 cm deep) in tall Spartina alterniflora marshes, a possible canopy collapse of shoreline fresh marsh exposed to repeated storm-surge inundations, wind-roughened water surfaces where water levels reached marsh canopy heights, and relatively high backscatter in the near-range portion of the SAR imagery. A TM-based vegetation index of live biomass indicated that the severity of marsh dieback was linked to differences in dominant species. The severest impacts were not necessarily caused by longer inundation but rather could be caused by repeated exposure of the palustrine marsh to elevated salinity floodwaters. Differential impacts occurred in estuarine marshes. The more brackish marshes on average suffered higher impacts than the more saline marshes, particularly the nearshore coastal marshes occupied by S. alterniflora.

Mapping the invasive species, Chinese tallow, with EO1 satellite Hyperion hyperspectral image data and relating tallow occurrences to a classified Landsat Thematic Mapper land cover map

Our objective was to provide a realistic and accurate representation of the spatial distribution of Chinese tallow (Triadica sebifera) in the Earth Observing 1 (EO1) Hyperion hyperspectral image coverage by using methods designed and tested in previous studies. We transformed, corrected, and normalized Hyperion reflectance image data into composition images with a subpixel extraction model. Composition images were related to green vegetation, senescent foliage and senescing cypress‐tupelo forest, senescing Chinese tallow with red leaves (‘red tallow’), and a composition image that only corresponded slightly to yellowing vegetation. These statistical and visual comparisons confirmed a successful portrayal of landscape features at the time of the Hyperion image collection. These landscape features were amalgamated in the Landsat Thematic Mapper (TM) pixel, thereby preventing the detection of Chinese tallow occurrences in the Landsat TM classification. With the occurrence in percentage of red tallow (as a surrogate for Chinese tallow) per pixel mapped, we were able to link dominant land covers generated with Landsat TM image data to Chinese tallow occurrences as a first step toward determining the sensitivity and susceptibility of various land covers to tallow establishment. Results suggested that the highest occurrences and widest distribution of red tallow were (1) apparent in disturbed or more open canopy woody wetland deciduous forests (including cypress‐tupelo forests), upland woody land evergreen forests (dominantly pines and seedling plantations), and upland woody land deciduous and mixed forests; (2) scattered throughout the fallow fields or located along fence rows separating active and non‐active cultivated and grazing fields, (3) found along levees lining the ubiquitous canals within the marsh and on the cheniers near the coastline; and (4) present within the coastal marsh located on the numerous topographic highs.

Remote sensing and numerical modeling of suspended sediment in Laguna de terminos, Campeche, Mexico

Abstract It is necessary to understand the complex physical processes at work in coastal lagoons in order to manage them effectively. Improved methods of data collection and analysis must be found to provide synoptic, timely hydrodynamic information because of the sheer size of some lagoons and the difficulty of acquiring in situ data (particularly in the tropics). This paper summarizes research to model salinity and suspended sediment distributions in Laguna de Terminos, Mexico, using 1) a coupled hydrodynamic and dispersion model and 2) analysis of two Landsat Thematic Mapper images collected on 25 November 1984 and 24 April 1987. Atmospherically corrected chromaticity data derived from Thematic Mapper data were significantly correlated with modeled total suspended sediment concentrations for the two dates. Comparison between numerically modeled and remotely sensed suspended sediment maps at 1.5× 1.5 km resolution yielded a covariation map useful for identifying areas of discrepancy between the remotely sensed data and model output.