ALBERT

Description: In this presentation, we will discuss the development of this large format broadband infrared FPA based on a GaAs/AlGaAs materials system and its performance in quantum efficiency, noise equivalent differential temperature, uniformity, and operability.

Description: We present an analysis of 2.5 years of weekly ozone soundings conducted at a new monitoring station in Paramaribo, Surinam (6 deg N,55 deg W). This is currently one of only three ozone sounding stations in the northern hemisphere (NH) tropics, and the only one in the equatorial Atlantic region. Paramaribo is part of the Southern Hemisphere ADditional Ozone Sounding program (SHADOZ). Due to its position close to the equator, the Inter Tropical Convergence Zone (ITCZ) passes over Paramaribo twice per year, which results in a semi-annual seasonality of many parameters including relative humidity and ozone. The dataset from Paramaribo is used to: (1) evaluate ozone variability relative to precipitation, atmospheric circulation patterns and biomass burning; (2) contrast ozone at the NH equatorial Atlantic with that at nearby southern hemisphere (SH) stations Natal (6 deg S,35 deg W) and Ascension (8 deg S,14 deg W); (3) compare the seasonality of tropospheric ozone with a satellite-derived ozone product: Tropical Tropospheric Ozone Columns from the Modified Residual method (MR-TTOC). We find that Paramaribo is a distinctly Atlantic station. Despite its position north of the equator, it resembles nearby SH stations during most of the year. Transport patterns in the lower and middle troposphere during February and March differ from SH stations, which leads to a seasonality of ozone with two maxima. MR-TTOC over Paramaribo does not match the observed seasonality of ozone due to the use of a SH ozone sonde climatology in the MR method. The Paramaribo ozone record is used to suggest an improvement for northern hemisphere MR-TTOC retrievals. We conclude that station Paramaribo shows unique features in the region, and clearly adds new information to the existing SHADOZ record.

Description: Measurements have been made at L-band and C-band over conifer forests in Virginia to study the response of passive microwave instruments to biomass and soil moisture. A series of aircraft measurements were made in July, August and November, 1999 over relatively homogenous conifer forests of varying biomass. Three radiometers participated in these measurements. These were: 1) the L-band radiometer ESTAR, a horizontally polarized synthetic aperture radiometer which has been used extensively in past measurements of soil moisture; 2) the L-band radiometer SLFMR, a vertically polarized cross-track scanner which has been used successfully in the past for mapping sea surface salinity; and 3) The ACMR, a new C-band radiometer which operates at V- and H-polarization and in the configuration for these experiments did not scan. All three radiometers were flown on the NASA P-3 aircraft based at the Goddard Space Flight Center's Wallops Flight Facility. The ESTAR and SLFMR were mounted in the bomb bay of the P-3 and imaged across track whereas the ACMR was mounted to look aft at 54 degrees up from nadir. Data was collected at altitudes of 915 meters and 457 meters. The forests consisted of relatively homogeneous "managed" stands of conifer located near Waverly, Virginia. This is a relatively flat area about 30 miles southeast of Richmond, VA with numerous stands of trees being grown for the forestry industry. The stands selected for study consisted of areas of regrowth and mature stands of pine. In addition, a small stand of very large trees was observed. Soil moisture sampling was done in each stand during the aircraft over flights. Data was collected on July 7, August 27, November 15 and November 30, 1999. Measurements were made with ESTAR on all days. The ACMR flew on the summer missions and the SLFMR was present only on the August 27 flight. Soil moisture varied from quite dry on July 7 to quite moist on November 30 (which was shortly after a period of rain). The microwave images clearly distinguish between the different forest stands. Research is continuing to seek a quantitative correlation with biomass and surface soil moisture.

Description: To assess the contribution of chlorophyll fluorescence (ChlF) to apparent reflectance (Ra) in the red/far-red, spectra were collected on a C4 agricultural species (corn, Zea Mays L.) under conditions ranging from nitrogen deficiency to excess. A significant contribution of ChlF to Ra was observed, with on average 10-25% at 685nm and 2-6% at 740nm of Ra being due to ChlF. Higher ChlF was consistently measured from the abaxial leaf surface as compared to the adaxial. Using 350-665nm excitation, the study confirms the trends in three ChlF ratios established previously by active F technology, suggesting that the ChlF utility this technology has developed for monitoring vegetation physiological status is likely applicable also under natural solar illumination.

Description: In this paper we present our early analytical results that demonstrated the improvement in the optical communications system performance when adaptive optics techniques are implemented in a high background environment.

Description: The use of hyperspectral data to determine the abundance of constituents in a certain portion of the Earth's surface relies on the capability of imaging spectrometers to provide a large amount of information at each pixel of a certain scene. Today, hyperspectral imaging sensors are capable of generating unprecedented volumes of radiometric data. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), for example, routinely produces image cubes with 224 spectral bands. This undoubtedly opens a wide range of new possibilities, but the analysis of such a massive amount of information is not an easy task. In fact, most of the existing algorithms devoted to analyzing multispectral images are not applicable in the hyperspectral domain, because of the size and high dimensionality of the images. The application of neural networks to perform unsupervised classification of hyperspectral data has been tested by several authors and also by us in some previous work. We have also focused on analyzing the intrinsic capability of neural networks to parallelize the whole hyperspectral unmixing process. The results shown in this work indicate that neural network models are able to find clusters of closely related hyperspectral signatures, and thus can be used as a powerful tool to achieve the desired classification. The present work discusses the possibility of using a Self Organizing neural network to perform unsupervised classification of hyperspectral images. In sections 3 and 4, the topology of the proposed neural network and the training algorithm are respectively described. Section 5 provides the results we have obtained after applying the proposed methodology to real hyperspectral data, described in section 2. Different parameters in the learning stage have been modified in order to obtain a detailed description of their influence on the final results. Finally, in section 6 we provide the conclusions at which we have arrived.

Description: Two fixed-threshold Canada Centre for Remote Sensing and European Space Agency (CCRS and ESA) and three contextual GIGLIO, International Geosphere and Biosphere Project, and Moderate Resolution Imaging Spectroradiometer (GIGLIO, IGBP, and MODIS) algorithms were used for fire detection with Advanced Very High Resolution Radiometer (AVHRR) data acquired over Canada during the 1995 fire season. The CCRS algorithm was developed for the boreal ecosystem, while the other four are for global application. The MODIS algorithm, although developed specifically for use with the MODIS sensor data, was applied to AVHRR in this study for comparative purposes. Fire detection accuracy assessment for the algorithms was based on comparisons with available 1995 burned area ground survey maps covering five Canadian provinces. Overall accuracy estimations in terms of omission (CCRS=46%, ESA=81%, GIGLIO=75%, IGBP=51%, MODIS=81%) and commission (CCRS=0.35%, ESA=0.08%, GIGLIO=0.56%, IGBP=0.75%, MODIS=0.08%) errors over forested areas revealed large differences in performance between the algorithms, with no relevance to type (fixed-threshold or contextual). CCRS performed best in detecting real forest fires, with the least omission error, while ESA and MODIS produced the highest omission error, probably because of their relatively high threshold values designed for global application. The commission error values appear small because the area of pixels falsely identified by each algorithm was expressed as a ratio of the vast unburned forest area. More detailed study shows that most commission errors in all the algorithms were incurred in nonforest agricultural areas, especially on days with very high surface temperatures. The advantage of the high thresholds in ESA and MODIS was that they incurred the least commission errors.

Description: We describe a low energy neutral atom imager suitable for composition measurements Europa and other icy Galilean moons in the Jovian magnetosphere. This instrument employs conversion surface technology and is sensitive to either neutrals converted to negative ions, neutrals converted to positive ions and the positive ions themselves depending on the power supply. On a mission such as the Jupiter Icy Moons Orbiter (JIMO), two back-to-back sensors would be flown with separate power supplies fitted to the neutral atom and iodneutral atom sides. This will allow both remote imaging of 1 eV 〈 E 〈 4 keV neutrals from icy moon surfaces and atmospheres, and in situ measurements of ions at similar energies in the moon ionospheres and Jovian magnetospheric plasma. The instrument provides composition measurements of the neutrals and ions that enter the spectrometer with a mass resolution dependent on the time-of-flight subsystem and capable of resolving molecules. The lower energy neutrals, up to tens of eV, arise from atoms and molecules sputtered off the moon surfaces and out of the moon atmospheres by impacts of more energetic (keV to MeV) ions from the magnetosphere. Direct Simulation Monte Carlo (DSMC) models are used to convert measured neutral abundances to compositional distributions of primary and trace species in the sputtered surfaces and atmospheres. The escaping neutrals can also be detected as ions after photo- or plasma-ionization and pickup. Higher energy, keV neutrals come from charge exchange of magnetospheric ions in the moon atmospheres and provide information on atmospheric structure. At the jovicentric orbits of the icy moons the presence of toroidal gas clouds, as detected at Europa's orbit, provide M e r opportunities to analyze both the composition of neutrals and ions originating from the moon surfaces, and the characteristics of magnetospheric ions interacting with neutral cloud material. Charge exchange of low energy ions near the moons, and directional distributions of the resultant neutrals, allow indirect global mapping of magnetic field structures around the moons. Temporal variation of the magnetic structures can be linked to induced magnetic fields associated with subsurface oceans.