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67 results on '"Dungan, Jennifer L."'

52. Estimation of signal-to-noise - A new procedure applied to AVIRIS data

Author

Curran, Paul J and Dungan, Jennifer L

Subjects
Earth Resources And Remote Sensing
Abstract

To make the best use of narrowband airborne visible/infrared imaging spectrometer (AVIRIS) data, an investigator needs to know the ratio of signal to random variability or noise (signal-to-noise ratio or SNR). The signal is land cover dependent and varies with both wavelength and atmospheric absorption; random noise comprises sensor noise and intrapixel variability (i.e., variability within a pixel). The three existing methods for estimating the SNR are inadequate, since typical laboratory methods inflate while dark current and image methods deflate the SNR. A new procedure is proposed called the geostatistical method. It is based on the removal of periodic noise by notch filtering in the frequency domain and the isolation of sensor noise and intrapixel variability using the semi-variogram. This procedure was applied easily and successfully to five sets of AVIRIS data from the 1987 flying season and could be applied to remotely sensed data from broadband sensors.

Published
1989
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53. Estimating the signal-to-noise ratio of AVIRIS data

Author

Curran, Paul J and Dungan, Jennifer L

Subjects
Earth Resources And Remote Sensing
Abstract

To make the best use of narrowband airborne visible/infrared imaging spectrometer (AVIRIS) data, an investigator needs to know the ratio of signal to random variability or noise (signal-to-noise ratio or SNR). The signal is land cover dependent and varies with both wavelength and atmospheric absorption; random noise comprises sensor noise and intrapixel variability (i.e., variability within a pixel). The three existing methods for estimating the SNR are inadequate, since typical laboratory methods inflate while dark current and image methods deflate the SNR. A new procedure is proposed called the geostatistical method. It is based on the removal of periodic noise by notch filtering in the frequency domain and the isolation of sensor noise and intrapixel variability using the semi-variogram. This procedure was applied easily and successfully to five sets of AVIRIS data from the 1987 flying season and could be applied to remotely sensed data from broadband sensors.

Published
1988

54. Zones of information in the AVIRIS spectra

Author

Curran, Paul J and Dungan, Jennifer L

Subjects
Earth Resources And Remote Sensing
Abstract

To make the best use of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data an investigator needs to know the ratio of signal to random variability or noise (S/N ratio). The signal is land-cover dependent and decreases with both wavelength and atmospheric absorption and random noise comprises sensor noise and intra-pixel variability. The three existing methods for estimating the S/N ratio are inadequate as typical laboratory methods inflate, while dark current and image methods deflate the S/N ratio. We propose a new procedure called the geostatistical method. It is based on the removal of periodic noise by notch filtering in the frequency domain and the isolation of sensor noise and intra-pixel variability using the semi-variogram. This procedure was applied easily and successfully to five sets of AVIRIS data from the 1987 flying season.

Published
1988

60. Application of Geostatistical Simulation to Enhance Satellite Image Products.

Author

Leuangthong, Oy, Deutsch, Clayton V., Hlavka, Christine A., and Dungan, Jennifer L.

Abstract

With the deployment of Earth Observing System (EOS) satellites that provide daily global imagery, there is increasing interest in defining the limitations of the data and derived products due to their coarse spatial resolution. Much of the detail, i.e. small fragments and notches in boundaries, is lost with coarse resolution imagery provided by systems such as the EOS MODerate Resolution Imaging Spectroradiometer (MODIS). Higher spatial resolution data such as the EOS Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Landsat Thematic Mapper and airborne sensor imagery provide more detailed information but are less frequently available. There is, however, both theoretical and analytical evidence that burn scars and other fragmented types of land covers form self-similar or self-affine patterns, that is, patterns that look similar when viewed at widely differing spatial scales. Therefore small features of the patterns should be predictable, at least in a statistical sense, with knowledge about the large features. Recent developments in fractal modeling for characterizing the spatial distribution of undiscovered petroleum deposits are thus applicable to generating simulations of finer resolution satellite image products. We present example EOS products, an analysis to investigate self-similarity and a discussion of simulation approaches. [ABSTRACT FROM AUTHOR]

Published
2005
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64. Satellite-based estimation of surface vapor pressure deficits using MODIS land surface temperature data

Author

Hashimoto, Hirofumi, Dungan, Jennifer L., White, Michael A., Yang, Feihua, Michaelis, Andrew R., Running, Steven W., and Nemani, Ramakrishna R.

Subjects
*REMOTE sensing, *VAPOR pressure, *MODIS (Spectroradiometer), *LINEAR statistical models, *MATHEMATICAL models, *ARID regions, *SOIL moisture, *SATURATION vapor pressure
Abstract

Vapor Pressure Deficit (VPD) is a principle mediator of global terrestrial CO2 uptake and water vapor loss through plant stomata. As such, methods to estimate VPD accurately and efficiently are critical for ecosystem and climate modeling efforts. Based on prior work relating energy partitioning, remotely sensed land surface temperature (LST), and VPD, we developed simple linear models to predict VPD using saturated vapor pressure calculated from MODIS LST at a number of different temporal and spatial resolutions. We developed and assessed the LST–VPD models using three data sets: (1) instantaneous and daytime average ground-based VPD and radiometric temperature from the Soil Moisture Experiments in 2002 (SMEX02); (2) daytime average VPD from AmeriFlux eddy covariance flux tower observations; and (3) estimated daytime average VPD from Global Surface Summary of Day (GSSD) observations. We estimated model parameters for VPD estimation both regionally (MOD11 A2) and globally (MOD11 C2) with RMSE values ranging from .32 to .38 kPa. VPD was overestimated along coastlines and underestimated in arid regions with low vegetation cover. Also, residuals were larger with higher VPDs because of the non-linear function of saturation vapor pressure with LST. Linear relationships were seen at multiple scales and appear useful for estimation purposes within a range of 0 to 2.5 kPa. [Copyright &y& Elsevier]

Published
2008
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66. Residential firewood use

Author

Lipfert, Frederick W., Dungan, Jennifer L., and Bailey, Mark R.

Subjects
Fuelwood -- Environmental aspects, Air pollution -- Environmental aspects, Science and technology, Environmental aspects
Abstract

Residential Firewood Use In their report on the use of residential firewood in the United States, Lipfert and Dungan (1) used the New England Fuelwood Study (2) results in developing [...]

Published
1984

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