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  • Earth Resources and Remote Sensing  (740)
  • Management
  • 2020-2022
  • 2000-2004  (742)
  • 2004  (201)
  • 2000  (541)
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  • 2020-2022
  • 2000-2004  (742)
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  • 1
    Publication Date: 2019-08-28
    Description: Below is the 1st year progress report for NAG5-13435 "New Retrieval Algorithms for Geophysical Products from GLI and MODIS Data". Activity on this project has been coordinated with our NASA DB project NAG5-9604. For your convenience, this report has six sections and an Appendix. Sections I - III discuss specific activities undertaken during the past year to analyze/use MODIS data. Section IV formally states our intention to no longer pursue any research using JAXA's (formerly NASDA's) GLI instrument which catastrophically failed very early after launch (also see the Appendix). Section V provides some indications of directions for second year activities based on our January 2004 telephone discussions and email exchanges. A brief summary is given in Section VI.
    Keywords: Earth Resources and Remote Sensing
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  • 2
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    In:  CASI
    Publication Date: 2019-08-28
    Description: This document is concentrates on a couple of the missions where the Spacelab hardware was used to do Earth science. The Atmospheric Laboratory for Applications and Science (ATLAS) series of missions and the Lidar in-Space Technology Experiment (LITE) mission, the ATLAS being a series of three Shuttle missions that were very much Spacelab missions, are described. A little bit about the history, what the missions were, some of the instruments that were on them, and results are given.
    Keywords: Earth Resources and Remote Sensing
    Type: The Spacelab Accomplishments Forum; 67-90; NASA/CP-2000-210332
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  • 3
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    In:  Other Sources
    Publication Date: 2019-08-26
    Description: An assessment of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) laboratory and in-flight uniformity is presented in this Slide presentation. The ideal uniform system is described, being a system where every spectrum is intercomparable to every other spectrum. Two types of failures to achieve this uniformity are described. Graphs showing measured spectral upwelling radiance, the expanded spectral convolution, the radiometric error from spectral error, the results from the hyperion Arizaro calibration experiment and a AVIRIS cross-track uniformity are among those presented. The reasons why uniformity matters are presented.
    Keywords: Earth Resources and Remote Sensing
    Type: AVIRIS Workshop; May 24, 2005 - May 27, 2005; California; United States
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  • 4
    Publication Date: 2019-08-17
    Description: The overall goal of this research is to examine the feasibility of applying a newly developed diagnostic model of soil water evaporation to large land areas using remotely sensed input parameters. The model estimates the rate of soil evaporation during periods when it is limited by the net transport resulting from competing effects of capillary rise and drainage. The critical soil hydraulic properties are implicitly estimated via the intensity and duration of the first stage (energy limited) evaporation, removing a major obstacle in the remote estimation of evaporation over large areas. This duration, or 'time to drying' (t(sub d)) is revealed through three signatures detectable in time series of remote sensing variables. The first is a break in soil albedo that occurs as a small vapor transmission zone develops near the surface. The second is a break in either surface to air temperature differences or in the diurnal surface temperature range, both of which indicate increased sensible heat flux (and/or storage) required to balance the decrease in latent heat flux. The third is a break in the temporal pattern of near surface soil moisture. Soil moisture tends to decrease rapidly during stage I drying (as water is removed from storage), and then become more or less constant during soil limited, or 'stage II' drying (as water is merely transmitted from deeper soil storage). The research tasks address: (1) improvements in model structure, including extensions to transpiration and aggregation over spatially variable soil and topographic landscape attributes; and (2) applications of the model using remotely sensed input parameters.
    Keywords: Earth Resources and Remote Sensing
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  • 5
    Publication Date: 2019-08-17
    Description: Parameters describing the vertical structure of forests, for example tree height, height-to-base-of-live-crown, underlying topography, and leaf area density, bear on land-surface, biogeochemical, and climate modeling efforts. Single, fixed-baseline interferometric synthetic aperture radar (INSAR) normalized cross-correlations constitute two observations from which to estimate forest vertical structure parameters: Cross-correlation amplitude and phase. Multialtitude INSAR observations increase the effective number of baselines potentially enabling the estimation of a larger set of vertical-structure parameters. Polarimetry and polarimetric interferometry can further extend the observation set. This paper describes the first acquisition of multialtitude INSAR for the purpose of estimating the parameters describing a vegetated land surface. These data were collected over ponderosa pine in central Oregon near longitude and latitude -121 37 25 and 44 29 56. The JPL interferometric TOPSAR system was flown at the standard 8-km altitude, and also at 4-km and 2-km altitudes, in a race track. A reference line including the above coordinates was maintained at 35 deg for both the north-east heading and the return southwest heading, at all altitudes. In addition to the three altitudes for interferometry, one line was flown with full zero-baseline polarimetry at the 8-km altitude. A preliminary analysis of part of the data collected suggests that they are consistent with one of two physical models describing the vegetation: 1) a single-layer, randomly oriented forest volume with a very strong ground return or 2) a multilayered randomly oriented volume; a homogeneous, single-layer model with no ground return cannot account for the multialtitude correlation amplitudes. Below the inconsistency of the data with a single-layer model is followed by analysis scenarios which include either the ground or a layered structure. The ground returns suggested by this preliminary analysis seem too strong to be plausible, but parameters describing a two-layer compare reasonably well to a field-measured probability distribution of tree heights in the area.
    Keywords: Earth Resources and Remote Sensing
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  • 6
    Publication Date: 2019-08-17
    Description: The purpose of this project has been to develop and enhance the HITRAN molecular spectroscopic database and associated software to support the observational programs of the Earth Observing System (EOS). Emphasis has been on the EOS projects: the Atmospheric Infrared Sounder (AIRS), the High-Resolution Dynamics Limb Sounder (HIRDLS), Measurements of Pollution in the Troposphere (MOPITT), the Tropospheric Emission Spectrometer (TES), and the Stratospheric Aerosol and Gas Experiment (SAGE III). The HITRAN program is also involved in the Ozone Monitoring Experiment (OMI). The data requirements of these programs in terms of spectroscopy are varied with respect to constituents being observed, required remote-sensing parameters, and spectral coverage. A general requisite is for additional spectral parameters and improvements to existing molecular bands sufficient for the simulation of the observations leading to retrieval of the atmospheric state. In addition, cross-section data for heavier molecular species must be expanded and made amenable to modeling in remote sensing. The effort in the project also includes developing software and distribution to make access, manipulation, and use of HITRAN functional to the EOS program.
    Keywords: Earth Resources and Remote Sensing
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  • 7
    Publication Date: 2019-08-17
    Description: The Autonomous Sciencecraft Experiment (ASE) has been selected for flight demonstration by NASAs New Millennium Program (NMP) as part of the Space Technology 6 (ST6) mission. NASA has identified the development of an autonomously operating spacecraft as a necessity for an expanded program of missions exploring the Solar System. The versatile ASE spacecraft command and control software, image formation software, and science processing software will be uploaded to the Earth Observer 1 (EO-1) spacecraft in early 2004 to detect surface modification related to volcanism, ice formation and retreat, and flooding.
    Keywords: Earth Resources and Remote Sensing
    Type: Lunar and Planetary Science XXXV: Image Processing and Earth Observations; LPI-Contrib-1197
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  • 8
    Publication Date: 2019-08-17
    Description: The expanded remotely sensed data space consisting of coincident radar backscatter and optical reflectance data provides for a more complete description of the Earth surface. This is especially useful where many parameters are needed to describe a certain scene, such as in the presence of dense and complex-structured vegetation or where there is considerable underlying topography. The goal of this paper is to use a combination of radar and optical data to develop a methodology for parameter classification for dense and hilly forests, and further, class-specific parameter estimation. The area to be used in this study is the H. J. Andrews Forest in Oregon, one of the Long-Term Ecological Research (LTER) sites in the US. This area consists of various dense old-growth conifer stands, and contains significant topographic relief. The Andrews forest has been the subject of many ecological studies over several decades, resulting in an abundance of ground measurements. Recently, biomass and leaf-area index (LAI) values for approximately 30 reference stands have also become available which span a large range of those parameters. The remote sensing data types to be used are the C-, L-, and P-band polarimetric radar data from the JPL airborne SAR (AIRSAR), the C-band single-polarization data from the JPL topographic SAR (TOPSAR), and the Thematic Mapper (TM) data from Landsat, all acquired in late April 1998. The total number of useful independent data channels from the AIRSAR is 15 (three frequencies, each with three unique polarizations and amplitude and phase of the like-polarized correlation), from the TOPSAR is 2 (amplitude and phase of the interferometric correlation), and from the TM is 6 (the thermal band is not used). The range pixel spacing of the AIRSAR is 3.3m for C- and L-bands and 6.6m for P-band. The TOPSAR pixel spacing is 10m, and the TM pixel size is 30m. To achieve parameter classification, first a number of parameters are defined which are of interest to ecologists for forest process modeling. These parameters include total biomass, leaf biomass, LAI, and tree height. The remote sensing data from radar and TM are used to formulate a multivariate analysis problem given the ground measurements of the parameters. Each class of each parameter is defined by a probability density function (pdf), the spread of which defines the range of that class. High classification accuracy results from situations in which little overlap occurs between pdfs. Classification results provide the basis for the future work of class-specific parameter estimation using radar and optical data. This work was performed in part by the Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, and in part by the NASA Ames Research Center, Moffett Field, CA, both under contract from the National Aeronautics and Space Administration.
    Keywords: Earth Resources and Remote Sensing
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  • 9
    Publication Date: 2019-08-17
    Description: The Ocean Color Temperature Scanner (OCTS) onboard the Advanced Earth Observation Satellite (ADEOS) was launched on August 17, 1996. Calibration of OCTS is required for use of the on-orbit measured data for retrieval of physical properties of the ocean. In the solar reflected portion of the electromagnetic spectrum, OCTS measures images with nominally 700-m spatial resolution through eight multispectral bands. The objective of this research was to establish the absolute radiometric calibration of OCTS on orbit through an underflight by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). AVIRIS is a NASA earth-observing imaging spectrometer designed, built and operated by the Jet Propulsion Laboratory (JPL). AVIRIS acquires data from 20-km altitude on a NASA ER-2 aircraft, above most of the Earth's atmosphere. AVIRIS measures the solar reflected spectrum from 370 nm to 2500 nm through 224 contiguous spectral channels. The full width at half maximum (FWHM) of the spectral channels is nominally 10-nm. AVIRIS spectra are acquired as images of 11 km by up to 800 km extent with 20-m spatial resolution. The high spectral resolution of AVIRIS data allows direct convolution to the spectral response functions of the eight multispectral bands of OCTS. The high spatial resolution of AVIRIS data allows for spatial re-sampling of the data to match the ADEOS sensors spatial resolution. In addition, the AVIRIS high spatial resolution allows assessment of the scaling effects due to environmental factors of thin cirrus clouds, sub-pixel cloud cover, white caps, ocean foam, sun-glint, and bright-target adjacency. The platform navigation information recorded by AVIRIS allows calculation of the position and observation geometry of each spectrum for matching to the OCTS measurement. AVIRIS is rigorously characterized and calibrated in the laboratory prior to and following the flight season. The stability and repeatability of AVIRIS calibration have been validated through an extensive series of inflight calibration experiments. In the OCTS portion of the spectrum, using pre-and post-flight runway calibrations of AVIRIS coupled with the on-board calibrator an absolute calibration accuracy of better than 3% spectral, 2% radiometric and 5% spatial has been achieved. An analogous satellite underflight calibration experiment was performed with AVIRIS and the Optical Sensor (OPS) onboard the Japanese Earth Resources Satellite (JERS).
    Keywords: Earth Resources and Remote Sensing
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  • 10
    Publication Date: 2019-08-17
    Description: The Colorado Geological Survey and the co-authors of this paper were awarded one of 15 NASA Broad Agency Announcement (BAA) grants in 2001. The project focuses on the use of hyperspectral remote sensing to map acid-generating minerals that affect water quality within a watershed, and to identify the relative contributions of natural and anthropogenic sources to that drainage. A further objective is to define the most cost-effective remote sensing instrument configuration for this application.
    Keywords: Earth Resources and Remote Sensing
    Type: Proceedings of the 12th JPL Airborne Earth Science Workshop; JPL-Publ-04-6
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