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At least 73 records · Page 4

Use of IKONOS Data for Mapping Cultural Resources of Stennis Space Center, Mississippi

Cultural resource surveys are important for compliance with Federal and State law. Stennis Space Center (SSC) in Mississippi is researching, developing, and validating remote sensing and Geographical Information System (GIS) methods for aiding cultural resource assessments on the center's own land. The suitability of IKONOS satellite imagery for georeferencing scanned historic maps is examined in this viewgraph presentation. IKONOS data can be used to map historic buildings and farmland in Gainsville, MS, and plan archaeological surveys.

Spruce, Joseph P.↗

Use of GPR Surveys in Historical Archaeology Studies at Gainesville Mississippi

Ground Penetrating Radar (GPR) was used in recent surveys to acquire subsurface geophysical data for historic sites at Gainesville, Mississippi, a town abandoned in 1962 with the building of the John C. Stennis Space Center. Prior to GPR data collection, a 20- by 20-meter grid was established using UTM map projection and GPS for locating cell corners. Lines of GPR data were then collected every 25 centimeters. The images were then processed, and coregistered to georeferenced aerial and satellite imagery. This procedure is enabling analysts to assess the GPR imagery more effectively in a geospatial context. Field validation of anomalies created by known subsurface features from both recent and historic sources is allowing soil attributes, such as variations in Relative Dielectric Permittivity, to be tested more accurately. Additional work is assessing how GPR data can be effectively combined with other forms of remote sensing to direct archaeological surveys and excavations.

Goodwin, Ben↗

Low Altitude AVIRIS Data for Mapping Landform Types on West Ship Island, Mississippi

A chain of barrier islands provides protection against hurricanes and severe storms along the southern and southeastern shores of the Unites States. Barrier island landform types can be spectrally similar and as small as a few meters across, making highly detailed maps difficult to produce. To determine whether high-resolution airborne hyperspectral imagery could provide detailed maps of barrier island landform types, we used low-altitude hyperspectral and multispectral imagery to map surface environments of West Ship Island, Mississippi. We employed 3.4 meter AVIRIS hyperspectral imagery acquired in July 1999 and 0.5 meter ADAR multispectral data acquired in November 1997. The data were co-registered to digital ortho aerial imagery, and the AVIRIS data was scaled to ground reflectance using ATREM software. Unsupervised classification of AVIRIS and ADAR data proceeded using ISODATA clustering techniques. The resulting landform maps were field-checked and compared to aerial photography and digital elevation maps. Preliminary analyses indicated that the AVIRIS classification mapped more landform types, while the ADAR-based map enabled smaller patches to be identified. Used together, these maps provided a means to assess landform distributions of West Ship Island before and after Hurricane Georges. Classification accuracy is being assessed through photo-interpretation and field surveys of sample areas selected with stratified random sampling.

Spruce, Joseph↗

Relationship between the Fluorescence Lifetime of Chlorophyll 'a' and Primary Productivity within the Mississippi River Plume and Adjacent Shelf Region

In situ measurements of chlorophyll fluorescence intensity have been widely used to estimate phytoplankton biomass. However, because the fluorescence quantum yield of chlorophyll a in vivo can be highly variable, measurements of chlorophyll fluorescence intensity cannot be directly correlated with phytoplankton biomass and do not provide information on the physiological state of the phytoplankton under study. Conversely, lifetime-based measurements of chlorophyll fluorescence provide a framework in which photosynthetic rates of phytoplankton can be analyzed according to phytoplankton physiology. Along with the measurement of primary production and ambient nutrient concentrations within the Mississippi River plume in the northern Gulf of Mexico, phytoplankton fluorescence lifetimes were measured using a Fluorescence Lifetime Phytoplankton Analyzer (developed under a NASA Small Business Innovative Research contract to Ciencia, Inc.). Variability of fluorescence lifetimes within the plume can be used as a background from which to interpret variations in the maximum quantum yield of photochemistry. The extent to which nutrient and effluent loading in this dynamic coastal area affect the photosynthetic performance of phytoplankton will be presented as a function of phytoplankton fluorescence lifetimes.

Hall, Callie↗

Bio-Optical Properties and Ocean Color Algorithms for Coastal Waters Influenced by the Mississippi River During a Cold Front Passage

During the passage of a cold front in March 2002, bio-optical properties examined in coastal waters impacted by the Mississippi River indicated westward advective flows and increasing river discharge containing a larger nonalgal particle content contributed significantly to surface optical variability. A comparison of seasonal data from three cruises indicated spectral models of absorption and scattering to be generally consistent with other coastal environments, while their parameterization in terms of chlorophyll a concentration (Chl) showed seasonal variability. The exponential slope of the colored dissolved organic matter (CDOM) averaged 0.0161 plus or minus 0.00054 per nanometer, and for nonalgal absorption it averaged 0.011 per nanometer with deviations from general trends observed due to anomalous water properties. Although the phytoplankton specific absorption coefficients varied over a wide range (0.02 to 0.1 square meters (mg Chl) sup -1)) being higher in offshore surface waters, values of phytoplankton absorption spectra at the SeaWiFS wavebands were highly correlated to modeled values. The normalized scattering spectral shapes and the mean spectrum were in agreement to observations in other coastal waters, while the backscattering ratios were on average lower in phytoplankton dominated surface waters (0.0101 plus or minus 0.002) and higher in near-bottom waters (0.0191 plus or minus 0.0045) with low Chl. Average percent differences in remote sensing reflectance R (sub rs) derived form modeled and in-eater radiometric measurements were highest in the blue wavebands (52%) and at sampling stations with a ore stratified water column. Estimates of Chl and CDOM absorption derived from SeaWiFS images generated using regional empirical algorithms were highly correlated to in situ data.

D'Sa Eurico J.↗

Assimilation of GRACE Terrestrial Water Storage Data into a Land Surface Model: Results for the Mississippi River Basin

NASA's GRACE mission has the potential to be extremely valuable for water resources applications and global water cycle research. What makes GRACE unique among Earth Science satellite systems is that it is able to monitor variations in water stored in all forms, from snow and surface water to soil moisture to groundwater in the deepest aquifers. However, the space and time resolutions of GRACE observations are coarse. GRACE typically resolves water storage changes over regions the size of Nebraska on a monthly basis, while city-scale, daily observations would be more useful for water management, agriculture, and weather prediction. High resolution numerical (computer) hydrology models have been developed, which predict the fates of water and energy after they strike the land surface as precipitation and sunlight. These are similar to weather and climate forecast models, which simulate atmospheric processes. We integrated the GRACE observations into a hydrology model using an advanced technique called data assimilation. The results were new estimates of groundwater, soil moisture, and snow variations, which combined the veracity of GRACE with the high resolution of the model. We tested the technique over the Mississippi River basin, but it will be even more valuable in parts of the world which lack reliable data on water availability.

Zaitchik, Benjamin F.↗

Modeling the Height of Young Forests Regenerating from Recent Disturbances in Mississippi using Landsat and ICESat data

Many forestry and earth science applications require spatially detailed forest height data sets. Among the various remote sensing technologies, lidar offers the most potential for obtaining reliable height measurement. However, existing and planned spaceborne lidar systems do not have the capability to produce spatially contiguous, fine resolution forest height maps over large areas. This paper describes a Landsat-lidar fusion approach for modeling the height of young forests by integrating historical Landsat observations with lidar data acquired by the Geoscience Laser Altimeter System (GLAS) instrument onboard the Ice, Cloud, and land Elevation (ICESat) satellite. In this approach, "young" forests refer to forests reestablished following recent disturbances mapped using Landsat time-series stacks (LTSS) and a vegetation change tracker (VCT) algorithm. The GLAS lidar data is used to retrieve forest height at sample locations represented by the footprints of the lidar data. These samples are used to establish relationships between lidar-based forest height measurements and LTSS-VCT disturbance products. The height of "young" forest is then mapped based on the derived relationships and the LTSS-VCT disturbance products. This approach was developed and tested over the state of Mississippi. Of the various models evaluated, a regression tree model predicting forest height from age since disturbance and three cumulative indices produced by the LTSS-VCT method yielded the lowest cross validation error. The R(exp 2) and root mean square difference (RMSD) between predicted and GLAS-based height measurements were 0.91 and 1.97 m, respectively. Predictions of this model had much higher errors than indicated by cross validation analysis when evaluated using field plot data collected through the Forest Inventory and Analysis Program of USDA Forest Service. Much of these errors were due to a lack of separation between stand clearing and non-stand clearing disturbances in current LTSS-VCT products and difficulty in deriving reliable forest height measurements using GLAS samples when terrain relief was present within their footprints. In addition, a systematic underestimation of about 5 m by the developed model was also observed, half of which could be explained by forest growth that occurred between field measurement year and model target year. The remaining difference suggests that tree height measurements derived using waveform lidar data could be significantly underestimated, especially for young pine forests. Options for improving the height modeling approach developed in this study were discussed.

Li, Ainong↗

Optimization of a Radiative Transfer Forward Operator for Simulating SMOS Brightness Temperatures over the Upper Mississippi Basin, USA

The Soil Moisture and Ocean Salinity (SMOS) satellite mission is routinely providing global multi-angular observations of brightness temperature (TB) at both horizontal and vertical polarization with a 3-day repeat period. The assimilation of such data into a land surface model (LSM) may improve the skill of operational flood forecasts through an improved estimation of soil moisture (SM). To accommodate for the direct assimilation of the SMOS TB data, the LSM needs to be coupled with a radiative transfer model (RTM), serving as a forward operator for the simulation of multi-angular and multi-polarization top of atmosphere TBs. This study investigates the use of the Variable Infiltration Capacity (VIC) LSM coupled with the Community Microwave Emission Modelling platform (CMEM) for simulating SMOS TB observations over the Upper Mississippi basin, USA. For a period of 2 years (2010-2011), a comparison between SMOS TBs and simulations with literature-based RTM parameters reveals a basin averaged bias of 30K. Therefore, time series of SMOS TB observations are used to investigate ways for mitigating these large biases. Specifically, the study demonstrates the impact of the LSM soil moisture climatology in the magnitude of TB biases. After CDF matching the SM climatology of the LSM to SMOS retrievals, the average bias decreases from 30K to less than 5K. Further improvements can be made through calibration of RTM parameters related to the modeling of surface roughness and vegetation. Consequently, it can be concluded that SM rescaling and RTM optimization are efficient means for mitigating biases and form a necessary preparatory step for data assimilation.

SMOS↗