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

An algorithm for the estimation of bounds on the emissivity and temperatures from thermal multispectral airborne remotely sensed data

The effective flux incident upon the detectors of a thermal sensor, after it has been corrected for atmospheric effects, is a function of a non-linear combination of the emissivity of the target for that channel and the temperature of the target. The sensor system cannot separate the contribution from the emissivity and the temperature that constitute the flux value. A method that estimates the bounds on these temperatures and emissivities from thermal data is described. This method is then tested with remotely sensed data obtained from NASA's Thermal Infrared Multispectral Scanner (TIMS) - a 6 channel thermal sensor. Since this is an under-determined set of equations i.e. there are 7 unknowns (6 emissivities and 1 temperature) and 6 equations (corresponding to the 6 channel fluxes), there exist theoretically an infinite combination of values of emissivities and temperature that can satisfy these equations. Using some realistic bounds on the emissivities, bounds on the temperature are calculated. These bounds on the temperature are refined to estimate a tighter bound on the emissivity of the source. An error analysis is also carried out to quantitatively determine the extent of uncertainty introduced in the estimate of these parameters. This method is useful only when a realistic set of bounds can be obtained for the emissivities of the data. In the case of water the lower and upper bounds were set at 0.97 and 1.00 respectively. Five flights were flown in succession at altitudes of 2 km (low), 6 km (mid), 12 km (high), and then back again at 6 km and 2 km. The area selected with the Ross Barnett reservoir near Jackson, Mississippi. The mission was flown during the predawn hours of 1 Feb. 1992. Radiosonde data was collected for that duration to profile the characteristics of the atmosphere. Ground truth temperatures using thermometers and radiometers were also obtained over an area of the reservoir. The results of two independent runs of the radiometer data averaged 7.03 plus or minus .70 for the first run and 7.31 plus or minus .88 for the second run. The results of the algorithm yield a temperature of 7.68 for the low altitude data to 8.73 for the high altitude data

Multi-resolution processing for fractal analysis of airborne remotely sensed data

Fractal geometry is increasingly becoming a useful tool for modeling natural phenomenon. As an alternative to Euclidean concepts, fractals allow for a more accurate representation of the nature of complexity in natural boundaries and surfaces. Since they are characterized by self-similarity, an ideal fractal surface is scale-independent; i.e. at different scales a fractal surface looks the same. This is not exactly true for natural surfaces. When viewed at different spatial resolutions parts of natural surfaces look alike in a statistical manner and only for a limited range of scales. Images acquired by NASA's Thermal Infrared Multispectral Scanner are used to compute the fractal dimension as a function of spatial resolution. Three methods are used to determine the fractal dimension - Schelberg's line-divider method, the variogram method, and the triangular prism method. A description of these methods and the results of applying these methods to a remotely-sensed image is also presented. Five flights were flown in succession at altitudes of 2 km (low), 6 km (mid), 12 km (high), and then back again at 6 km and 2 km. The area selected was the Ross Barnett reservoir near Jackson, Mississippi. The mission was flown during the predawn hours of 1 Feb. 1992. Radiosonde data was collected for that duration to profile the characteristics of the atmosphere. This corresponds to 3 different pixel sizes - 5m, 15m, and 30m. After, simulating different spatial sampling intervals within the same image for each of the 3 image sets, the results are cross-correlated to compare the extent of detail and complexity that is obtained when data is taken at lower spatial intervals

Application of remote sensing to state and regional problems

There are no author-identified significant results in this report

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 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

An initial analysis of LANDSAT 4 Thematic Mapper data for the classification of agricultural, forested wetland, and urban land covers

An initial analysis of LANDSAT 4 thematic mapper (TM) data for the delineation and classification of agricultural, forested wetland, and urban land covers was conducted. A study area in Poinsett County, Arkansas was used to evaluate a classification of agricultural lands derived from multitemporal LANDSAT multispectral scanner (MSS) data in comparison with a classification of TM data for the same area. Data over Reelfoot Lake in northwestern Tennessee were utilized to evaluate the TM for delineating forested wetland species. A classification of the study area was assessed for accuracy in discriminating five forested wetland categories. Finally, the TM data were used to identify urban features within a small city. A computer generated classification of Union City, Tennessee was analyzed for accuracy in delineating urban land covers. An evaluation of digitally enhanced TM data using principal components analysis to facilitate photointerpretation of urban features was also performed

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

A Bioinformatics Method Identifies Prominent Off-targeted Transcripts in RNAi Screens

Because off-target effects hamper interpretation and validation of RNAi screens, we developed a bioinformatics method, Genome-wide Enrichment of Seed Sequence matches (GESS), to identify candidate off-targeted transcripts from direct analysis of primary screening data. GESS identified a prominent off-targeted transcript in several screens, including MAD2 in a screen for components of the spindle assembly checkpoint. We demonstrate how incorporation of the results of GESS analysis can enhance the validation rate in RNAi screens