The verification of LANDSAT data in the geographical analysis of wetlands in west Tennessee

The reliability of LANDSAT imagery as a medium for identifying, delimiting, monitoring, measuring, and mapping wetlands in west Tennessee was assessed to verify LANDSAT as an accurate, efficient cartographic tool that could be employed by a wide range of users to study wetland dynamics. The verification procedure was based on the visual interpretation and measurement of multispectral imagery. The accuracy testing procedure was predicated on surrogate ground truth data gleaned from medium altitude imagery of the wetlands. Fourteen sites or case study areas were selected from individual 9 x 9 inch photo frames on the aerial photography. These sites were then used as data control calibration parameters for assessing the cartography accuracy of the LANDSAT imagery. An analysis of results obtained from the verification tests indicated that 1:250,000 scale LANDSAT data were the most reliable scale of imagery for visually mapping and measuring wetlands using the area grid technique. The mean areal percentage of accuracy was 93.54 percent (real) and 96.93 percent (absolute). As a test of accuracy, the LANDSAT 1:250,000 scale overall wetland measurements were compared with an area cell mensuration of the swamplands from 1:130,000 scale color infrared U-2 aircraft imagery. The comparative totals substantiated the results from the LANDSAT verification procedure

The verification of LANDSAT data in the geographical analysis of wetlands in western Tennessee

There are no author-identified significant results in this report

Application of High-Resolution Thermal Infrared Remote Sensing and GIS to Assess the Urban Heat Island Effect

Day and night airborne thermal infrared image data at 5 m spatial resolution acquired with the 15-channel (0.45 micron - 12.2 micron) Advanced Thermal and Land Applications Sensor (ATLAS) over Alabama, Huntsville on 7 September, 1994 were used to study changes in the thermal signatures of urban land cover types between day and night. Thermal channel number 13 (9.6 micron - 10.2 micron) data with the best noise-equivalent temperature change (NEAT) of 0.25 C after atmospheric corrections and temperature calibration were selected for use in this analysis. This research also examined the relation between land cover irradiance and vegetation amount, using the Normalized Difference Vegetation Index (NDVI), obtained by ratioing the difference and the sum of the red (channel number 3: 0.60-0.63 micron) and reflected infrared (channel number 6: 0.76-0.90 micron) ATLAS data. Based on the mean radiance values, standard deviations, and NDVI extracted from 351 pairs of polygons of day and night channel number 13 images for the city of Huntsville, a spatial model of warming and cooling characteristics of commercial, residential, agricultural, vegetation, and water features was developed using a GIS approach. There is a strong negative correlation between NDVI and irradiance of residential, agricultural, and vacant/transitional land cover types, indicating that the irradiance of a land cover type is greatly influenced by the amount of vegetation present. The predominance of forests, agricultural, and residential uses associated with varying degrees of tree cover showed great contrasts with commercial and services land cover types in the center of the city, and favors the development of urban heat islands. The high-resolution thermal infrared images match the complexity of the urban environment, and are capable of characterizing accurately the urban land cover types for the spatial modeling of the urban heat island effect using a GIS approach

Application of remote sensing to state and regional problems

The author has identified the following significant results. The Lowndes County data base is essentially complete with 18 primary variables and 16 proximity variables encoded into the geo-information system. The single purpose, decision tree classifier is now operational. Signatures for the thematic extraction of strip mines from LANDSAT Digital data were obtained by employing both supervised and nonsupervised procedures. Dry, blowing sand areas of beach were also identified from the LANDSAT data. The primary procedure was the analysis of analog data on the I2S signal slicer

Application of remote sensing to state and regional problems

There are no author-identified significant results in this report

Hypersonic heat transfer and anisotropic visualization with a higher order discontinuous Galerkin finite element method

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2006.Includes bibliographical references (leaves 83-89).Higher order discretizations of the Navier-Stokes equations promise greater accuracy than conventional computational aerodynamics methods. In particular, the discontinuous Galerkin (DG) finite element method has O(hP+l) design accuracy and allows for subcell resolution of shocks. This work furthers the DG finite element method in two ways. First, it demonstrates the results of DG when used to predict heat transfer to a cylinder in a hypersonic flow. The strong shock is captured with a Laplacian artificial viscosity term. On average, the results are in agreement with an existing hypersonic benchmark. Second, this work improves the visualization of the higher order polynomial solutions generated by DG with an adaptive display algorithm. The new algorithm results in more efficient displays of higher order solutions, including the hypersonic flow solutions generated here.by Douglas J. Quattrochi.S.M

Synegies Between Visible/Near-Infrared Imaging Spectrometry and the Thermal Infrared in an Urban Environment: An Evaluation of the Hyperspectral Infrared Imager (HYSPIRI) Mission

A majority of the human population lives in urban areas and as such, the quality of urban environments is becoming increasingly important to the human population. Furthermore, these areas are major sources of environmental contaminants and sinks of energy and materials. Remote sensing provides an improved understanding of urban areas and their impacts by mapping urban extent, urban composition (vegetation and impervious cover fractions), and urban radiation balance through measures of albedo, emissivity and land surface temperature (LST). Recently, the National Research Council (NRC) completed an assessment of remote sensing needs for the next decade (NRC, 2007), proposing several missions suitable for urban studies, including a visible, near-infrared and shortwave infrared (VSWIR) imaging spectrometer and a multispectral thermal infrared (TIR) instrument called the Hyperspectral Infrared Imagery (HyspIRI). In this talk, we introduce the HyspIRI mission, focusing on potential synergies between VSWIR and TIR data in an urban area. We evaluate potential synergies using an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and MODIS-ASTER (MASTER) image pair acquired over Santa Barbara, United States. AVIRIS data were analyzed at their native spatial resolutions (7.5m VSWIR and 15m TIR), and aggregated 60 m spatial resolution similar to HyspIRI. Surface reflectance was calculated using ACORN and a ground reflectance target to remove atmospheric and sensor artifacts. MASTER data were processed to generate estimates of spectral emissivity and LST using Modtran radiative transfer code and the ASTER Temperature Emissivity Separation algorithm. A spectral library of common urban materials, including urban vegetation, roofs and roads was assembled from combined AVIRIS and field-measured reflectance spectra. LST and emissivity were also retrieved from MASTER and reflectance/emissivity spectra for a subset of urban materials were retrieved from co-located MASTER and AVIRIS pixels. Fractions of Impervious, Soil, Green Vegetation (GV) and Non-photosynthetic Vegetation (NPV), were estimated using Multiple Endmember Spectral Mixture Analysis (MESMA) applied to AVIRIS data at 7.5, 15 and 60 m spatial scales. Surface energy parameters, including albedo, vegetation cover fraction, broadband emissivity and LST were also determined for urban and natural land-cover classes in the region. Fractions were validated using 1m digital photography

MicroRNAs of the mir-17~92 cluster regulate multiple aspects of pancreatic tumor development and progression

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy characterized by resistance to currently employed chemotherapeutic approaches. Members of the mir-17~92 cluster of microRNAs (miRNAs) are upregulated in PDAC, but the precise roles of these miRNAs in PDAC are unknown. Using genetically engineered mouse models, we show that loss of mir-17~92 reduces ERK pathway activation downstream of mutant KRAS and promotes the regression of KRASG12D-driven precursor pancreatic intraepithelial neoplasias (PanINs) and their replacement by normal exocrine tissue. In a PDAC model driven by concomitant KRASG12D expression and Trp53 heterozygosity, mir-17~92 deficiency extended the survival of mice that lacked distant metastasis. Moreover, mir-17~92-deficient PDAC cell lines display reduced invasion activity in transwell assays, form fewer invadopodia rosettes than mir-17~92-competent cell lines and are less able to degrade extracellular matrix. Specific inhibition of miR-19 family miRNAs with antagomirs recapitulates these phenotypes, suggesting that miR-19 family miRNAs are important mediators of PDAC cell invasion. Together these data demonstrate an oncogenic role for mir-17~92 at multiple stages of pancreatic tumorigenesis and progression; specifically, they link this miRNA cluster to ERK pathway activation and precursor lesion maintenance in vivo and identify a novel role for miR-19 family miRNAs in promoting cancer cell invasion

Using Remotely Sensed Data and Hydrologic Models to Evaluate the Effects of Climate Change on Shallow Aquatic Ecosystems in the Mobile Bay, AL Estuary

Coastal systems in the northern Gulf of Mexico, including the Mobile Bay, AL estuary, are subject to increasing pressure from a variety of activities including climate change. Climate changes have a direct effect on the discharge of rivers that drain into Mobile Bay and adjacent coastal water bodies. The outflows change water quality (temperature, salinity, and sediment concentrations) in the shallow aquatic areas and affect ecosystem functioning. Mobile Bay is a vital ecosystem that provides habitat for many species of fauna and flora. Historically, submerged aquatic vegetation (SAV) and seagrasses were found in this area of the northern Gulf of Mexico; however the extent of vegetation has significantly decreased over the last 60 years. The objectives of this research are to determine: how climate changes affect runoff and water quality in the estuary and how these changes will affect habitat suitability for SAV and seagrasses. Our approach is to use watershed and hydrodynamic modeling to evaluate the impact of climate change on shallow water aquatic ecosystems in Mobile Bay and adjacent coastal areas. Remotely sensed Landsat data were used for current land cover land use (LCLU) model input and the data provided by Intergovernmental Panel on Climate Change (IPCC) of the future changes in temperature, precipitation, and sea level rise were used to create the climate scenarios for the 2025 and 2050 model simulations. Project results are being shared with Gulf coast stakeholders through the Gulf of Mexico Data Atlas to benefit coastal policy and climate change adaptation strategies