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  • Other Sources  (1,552)
  • Earth Resources and Remote Sensing  (1,549)
  • LUNAR AND PLANETARY EXPLORATION
  • 2015-2019  (1,549)
  • 1960-1964  (3)
  • 1
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    Mars biological analysis by gas chromatography (1963)
    In:  Other Sources
    Details
    Publication Date: 2011-08-17
    Keywords: LUNAR AND PLANETARY EXPLORATION
    Type: N. Am. Aviation Proc. of the 12th Lunar and Planetary Exploration Colloq., Vol. 3, No. 2; p 29-36
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  • 2
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    Simple vidicon microscopy (1963)
    In:  Other Sources
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    Publication Date: 2011-08-17
    Keywords: LUNAR AND PLANETARY EXPLORATION
    Type: N. Am. Aviation Proc. of the 12th Lunar and Planetary Exploration Colloq., Vol. 3, No. 2; p 47-48
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  • 3
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    NCA-LDAS Land Analysis: Development and Performance of a Multisensor, Multivariate Land Data Assimilation System for the National Climate Assessment (2018)
    In:  CASI
    Details
    Publication Date: 2019-03-13
    Description: This article describes one of the first successful examples of multisensor, multivariate land data assimilation, encompassing a large suite of soil moisture, snow depth, snow cover and irrigation intensity environmental data records (EDRs) from Scanning Multi-channel Mi-crowave Radiometer (SMMR), the Special Sensor Microwave Imager (SSM/I), the Advanced Scatterometer (ASCAT), the Moderate-Resolution Imaging Spectroradiometer (MODIS), the Advanced Microwave Scanning Radiometer (AMSR-E and AMSR2), the Soil Moisture Ocean Salinity (SMOS) mission and the Soil Moisture Active Passive (SMAP) mission. The analysis is performed using the NASA Land Information System (LIS) as an enabling tool for the U.S. National Climate Assessment (NCA). The performance of NCA Land Data Assimilation System (NCA-LDAS) is evaluated by comparing to a number of hydrological reference data products. Results indicate that multivariate assimilation provides systematic improvements in simulated soil moisture and snow depth, with marginal effects on the accuracy of simulated streamow and ET. An important conclusion is that across all evaluated variables, assimilation of data from increasingly more modern sensors (e.g. SMOS, SMAP, AMSR2, ASCAT) produces more skillful results than assimilation of data from older sensors (e.g. SMMR, SSM/I, AMSR-E). The evaluation also indicates high skill of NCA-LDAS when compared with other LSM products. Further, drought indicators based on NCA-LDAS output suggest a trend of longer and more severe droughts over parts of Western U.S. during 1979-2015, particularly in the Southwestern U.S., consistent with the trends from the US drought monitor, albeit for a shorter 2000-2015 time period.
    Keywords: Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN54682 , Journal of Hydrometeorology (ISSN 1525-755X ) (e-ISSN 1525-7541)
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  • 4
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    Landsat's Enduring Legacy: Pioneering Global Land Observations from Space (2017)
    In:  CASI
    Details
    Publication Date: 2018-03-10
    Description: It is our hope that the "Landsat Legacy" story will appeal to a broader audience than just those who use Landsat data on a regular basis. In an era when ready access to images and data from Earth-observing satellites is routine, it is hard to believe that only a few decades ago this was not the case. As the world's first digital land-observing satellite program, Landsat missions laid the foundation for modern space-based Earth observation and blazed the trail in the new field of quantitative remote sensing.
    Keywords: Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN48821
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  • 5
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    Quantifying Boreal Forest Structure and Composition Using UAV Structure from Motion (2018)
    In:  CASI
    Details
    Publication Date: 2019-05-10
    Description: The vast extent and inaccessibility of boreal forest ecosystems are barriers to routine monitoring of forest structure and composition. In this research, we bridge the scale gap between intensive but sparse plot measurements and extensive remote sensing studies by collecting forest inventory variables at the plot scale using an unmanned aerial vehicle (UAV) and a structure from motion (SfM) approach. At 20 Forest Inventory and Analysis (FIA) subplots in interior Alaska, we acquired overlapping imagery and generated dense, 3D, RGB (red, green, blue) point clouds. We used these data to model forest type at the individual crown scale as well as subplot-scale tree density (TD), basal area (BA), and aboveground biomass (AGB). We achieved 85% cross-validation accuracy for five species at the crown level. Classification accuracy was maximized using three variables representing crown height, form, and color. Consistent with previous UAV-based studies, SfM point cloud data generated robust models of TD (r(sup 2) = 0.91), BA (r(sup 2) = 0.79), and AGB (r(sup 2) = 0.92), using a mix of plot- and crown-scale information. Precise estimation of TD required either segment counts or species information to differentiate black spruce from mixed white spruce plots. The accuracy of species-specific estimates of TD, BA, and AGB at the plot scale was somewhat variable, ranging from accurate estimates of black spruce TD (+/1%) and aspen BA (2%) to misallocation of aspen AGB (+118%) and white spruce AGB (50%). These results convey the potential utility of SfM data for forest type discrimination in FIA plots and the remaining challenges to develop classification approaches for species-specific estimates at the plot scale that are more robust to segmentation error.
    Keywords: Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN66705 , Forests (e-ISSN 1999-4907); 9; 3; 119
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  • 6
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    Advances in Above- and In-Water Radiometry, Volume 3: Hybridspectral Next-Generation Optical Instruments (2018)
    In:  CASI
    Details
    Publication Date: 2019-07-04
    Description: This publication documents the scientific advances associated with new instrument systems and accessories built to improve above- and in-water observations of the apparent optical properties (AOPs) for a diversity of water masses, including optically complex waters. The principal objective is to be prepared for the launch of next-generation ocean color satellites with the most capable commercial off-the-shelf (COTS) instrumentation in the shortest time possible. The technologies described herein are entirely new hybrid sampling capabilities, so as to satisfy the requirements established for next-generation missions. Both above- and in-water instruments are documented with software options for autonomous control of data collection activities as applicable. The instruments were developed for the Hybridspectral Alternative for Remote Profiling of Optical Observations for NASA Satellites (HARPOONS) vicarious calibration project. The state-of-the-art accuracy required for vicarious calibration also led to the development of laboratory instruments to ensure the field observations were within uncertainty requirements. Separate detailed presentations of the individual instruments provide the hardware designs, accompanying software for data acquisition and processing, and examples of the results achieved.
    Keywords: Earth Resources and Remote Sensing
    Type: NASA/TP–2018-219033/VOL. 3 , GSFC-E-DAA-TN68736
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  • 7
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    Improved Tree-Ring Archives Will Support Earth-System Science (2017)
    In:  Other Sources
    Details
    Publication Date: 2019-05-21
    Description: A steep decline in archiving could make large tree-ring datasets irrelevant. But increased spatiotemporal coverage, the addition of novel parameters at sub-annual resolution, and integration with other in situ and remote Earth observations will elevate tree-ring data as an essential component of global-change research.
    Keywords: Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN68143 , Nature Ecology & Evolution (e-ISSN 2397-334X); 1; 8
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  • 8
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    How Universal is the Relationship Between Remotely Sensed Vegetation Indices and Crop Leaf Area Index? A Global Assessment (2016)
    In:  CASI
    Details
    Publication Date: 2019-05-21
    Description: Leaf Area Index (LAI) is a key variable that bridges remote sensing observations to the quantification of agroecosystem processes. In this study, we assessed the universality of the relationships between crop LAI and remotely sensed Vegetation Indices (VIs). We first compiled a global dataset of 1459 in situ quality-controlled crop LAI measurements and collected Landsat satellite images to derive five different VIs including Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), two versions of the Enhanced Vegetation Index (EVI and EVI2), and Green Chlorophyll Index (CI(sub Green)). Based on this dataset, we developed global LAI-VI relationships for each crop type and VI using symbolic regression and Theil-Sen (TS) robust estimator. Results suggest that the global LAI-VI relationships are statistically significant, crop-specific, and mostly non-linear. These relationships explain more than half of the total variance in ground LAI observations (R2 greater than 0.5), and provide LAI estimates with RMSE below 1.2 m2/m2. Among the five VIs, EVI/EVI2 are the most effective, and the crop-specific LAI-EVI and LAI-EVI2 relationships constructed by TS, are robust when tested by three independent validation datasets of varied spatial scales. While the heterogeneity of agricultural landscapes leads to a diverse set of local LAI-VI relationships, the relationships provided here represent global universality on an average basis, allowing the generation of large-scale spatial-explicit LAI maps. This study contributes to the operationalization of large-area crop modeling and, by extension, has relevance to both fundamental and applied agroecosystem research.
    Keywords: Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN40736 , Remote Sensing (e-ISSN 2072-4292); 8; 7; 597
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  • 9
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    Landsat-8 Sensor Characterization and Calibration (2015)
    In:  CASI
    Details
    Publication Date: 2019-05-21
    Description: Landsat-8 was launched on 11 February 2013 with two new Earth Imaging sensors to provide a continued data record with the previous Landsats. For Landsat-8, pushbroom technology was adopted, and the reflective bands and thermal bands were split into two instruments. The Operational Land Imager (OLI) is the reflective band sensor and the Thermal Infrared Sensor (TIRS), the thermal. In addition to these fundamental changes, bands were added, spectral bandpasses were refined, dynamic range and data quantization were improved, and numerous other enhancements were implemented. As in previous Landsat missions, the National Aeronautics and Space Administration (NASA) and United States Geological Survey (USGS) cooperated in the development, launch and operation of the Landsat- 8 mission. One key aspect of this cooperation was in the characterization and calibration of the instruments and their data. This Special Issue documents the efforts of the joint USGS and NASA calibration team and affiliates to characterize the new sensors and their data for the benefit of the scientific and application users of the Landsat archive. A key scientific use of Landsat data is to assess changes in the land-use and land cover of the Earth's surface over the now 43-year record. In order to perform these analyses and avoid confusing sensor changes with Earth surface changes, a solid understanding of the sensors' performance, consistent geolocation and radiometry are essential. Particularly with the significant changes in the Landsat-8 sensors relative to previous Landsat missions, this characterization becomes all the more important.
    Keywords: Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN31254 , Remote Sensing (e-ISSN 2072-4292); 7; 3; 2279-2282
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  • 10
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    Pre-Launch Radiometric Characterization of JPSS-1 VIIRS Thermal Emissive Bands (2016)
    In:  CASI
    Details
    Publication Date: 2019-05-21
    Description: Pre-launch characterization and calibration of the thermal emissive spectral bands on the Joint Polar Satellite System (JPSS-1) Visible Infrared Imaging Radiometer Suite (VIIRS) is critical to ensure high quality data products for environmental and climate data records post-launch. A comprehensive test program was conducted at the Raytheon El Segundo facility in 2013-2014, including extensive environmental testing. This work is focused on the thermal band radiometric performance and stability, including evaluation of a number of sensor performance metrics and estimation of uncertainties. Analysis has shown that JPSS-1 VIIRS thermal bands perform very well in relation to their design specifications, and comparisons to the Suomi National Polar-orbiting Partnership (SNPP) VIIRS instrument have shown their performance to be comparable.
    Keywords: Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN29811 , Remote Sensing (ISSN 2072-4292); 8; 1; 47
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