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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 343 records · Page 19

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NASA NTRS2019

Alternative Vegetation States in Tropical Forests and Savannas: The Search for Consistent Signals in Diverse Remote Sensing Data

Globally, the spatial distribution of vegetation is governed primarily by climatological factors (rainfall and temperature, seasonality, and inter-annual variability). The local distribution of vegetation, however, depends on local edaphic conditions (soils and topography) and disturbances (fire, herbivory, and anthropogenic activities). Abrupt spatial or temporal changes in vegetation distribution can occur if there are positive (i.e., amplifying) feedbacks favoring certain vegetation states under otherwise similar climatic and edaphic conditions. Previous studies in the tropical savannas of Africa and other continents using the MODerate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous fields (VCF) satellite data product have focused on discontinuities in the distribution of tree cover at different rainfall levels, with bimodal distributions (e.g., concentrations of high and low tree cover) interpreted as alternative vegetation states. Such observed bimodalities over large spatial extents may not be evidence for alternate states, as they may include regions that have different edaphic conditions and disturbance histories. In this study, we conduct a systematic multi-scale analysis of diverse MODIS data streams to quantify the presence and spatial consistency of alternative vegetation states in Sub-Saharan Africa. The analysis is based on the premise that major discontinuities in vegetation structure should also manifest as consistent spatial patterns in a range of remote sensing data streams, including, for example, albedo and land surface temperature (LST). Our results confirm previous observations of bimodal and multimodal distributions of estimated tree cover in the MODIS VCF. However, strong disagreements in the location of multimodality between VCF and other data streams were observed at 1 km scale. Results suggest that the observed distribution of VCF over vast spatial extents are multimodal, not because of local-scale feedbacks and emergent bifurcations (the definition of alternative states), but likely because of other factors including regional scale differences in woody dynamics associated with edaphic, disturbance, and/or anthropogenic processes. These results suggest the need for more in-depth consideration of bifurcation mechanisms and thus the likely spatial and temporal scales at which alternative states driven by different positive feedback processes should manifest.

Savanna↗

NASA NTRS2008

Parallel Computing for the Computed-Tomography Imaging Spectrometer

This software computes the tomographic reconstruction of spatial-spectral data from raw detector images of the Computed-Tomography Imaging Spectrometer (CTIS), which enables transient-level, multi-spectral imaging by capturing spatial and spectral information in a single snapshot.

Lee, Seungwon↗

NASA NTRS1989

The effect of spatial resolution upon texture-based cloud field classifications

The loss of cloud-classification accuracy as a function of spatial resolution is assessed by investigating the variation of textural measures as a function of spatial resolution. Landsat MSS imagery is progressively averaged to produce degraded imagery of 1/8-km, 1/4-km, 1/2-km, and 1-km spatial resolution, and textural measures are computed from the Gray Level Difference Vector (GLDV) approach described by Chen et al. (1989). It is found that the classification accuracies obtained using the 1/8-km spatial resolution data are similar to those obtained using the full-resolution (1/16 km) texture measures, indicating that there is no advantage in using even higher spatial resolution 30-m Landsat Thematic Mapper and 10-m SPOT imagery for cloud classification.

Welch, R. M.↗

NASA NTRS1994

Evolution of upwelling fronts off the coast of Portugal

We have analyzed the spatial and temporal variability of chlorophyll in the Atlantic Ocean off the Portugal coast using satellite imagery from 1979 to 1986 in conjunction with wind data. The spatial patterns in the imagery show the typical inshore-offshore and east-west gradients, while the temporal patterns show seasonal high winter values and low summer values. In the satellite imagery for the period 1979-1986, stable mesoscale and large scale patterns recurred despite interannual differences in absolute satellite-derived pigment concentrations.

Source record↗

NASA NTRS2000

BOREAS ECMWF 6-Hour Analysis and Forecast Data

In cooperation with BOREAS atmospheric research efforts, the ECMWF agreed to provide BOREAS with a customized subset of its 6-hourly forecast data. This data set contains parameters from three ECMWF data products in GRIB format: Surface and Diagnostic Fields, Supplemental Fields, and Extension Data. Sample software and information are provided to assist in reading the data files. Temporally, the atmospheric parameters are available for the four main synoptic hours of 00, 06, 12, and 18 UTC from 1994 to 1996. Spatially, the data are stored in a 0.5- by 0.5-degree latitude/longitude grid. To cover the entire BOREAS study area, the grid extends from 48 to 62 degrees latitude and -92 to -114 degrees longitude. The data are stored in binary data representation known as FM 92 GRIB. Due to the complexity of the content and format of this data set, users are advised to read Sections 6, 7, 8, and 14 before using data. Based on agreements between BOREAS and ECMWF, users may legally obtain and use these data only by having a set of the BOREAS CD-ROMs that contain the data. Possession or use of these data under any other circumstance is prohibited. See Sections 11.3 and 20.4 for details.

Viterbo, Pedro↗

NASA NTRS2003

Flood warnings, flood disaster assessments, and flood hazard reduction : the roles of orbital remote sensing

Orbital remote sensing is now poised to make three fundamental contributions towards reducing the detrimental effects of extreme floods. Effective Flood warning requires frequent (near-daily) radar observation of the Earth's surface through cloud cover. In contrast, both optical and radar wavelengths will increasingly be used for disaster assessment and hazard reduction. These latter tasks are accomplished, in part, by accurate mapping of flooded lands and commonly over periods of several days or more. We use radar scatterometer data from QuikSCAT to detect changes in surface water area and with a full global coverage every 2.5 days. Also, MODIS, RADARSAT, and other higher spatial resolution data are used for flood mapping and other flood measurements. These records are preserved in a global flood hazard atlas at http://www.dartmouth.edu/-floods/Atlas.html.

Shabaneh, Tamer B.↗

NASA NTRS1999

Validation of Satellite Retrieved Land Surface Variables

The effective use of satellite observations of the land surface is limited by the lack of high spatial resolution ground data sets for validation of satellite products. Recent large scale field experiments include FIFE, HAPEX-Sahel and BOREAS which provide us with data sets that have large spatial coverage and long time coverage. It is the objective of this paper to characterize the difference between the satellite estimates and the ground observations. This study and others along similar lines will help us in utilization of satellite retrieved data in large scale modeling studies.

Lakshmi, Venkataraman↗

NASA NTRS1999

Validation of Satellite Retrieved Land Surface Variables

Lakshmi, Venkataraman↗

NASA NTRS2005

Stennis Space Center Verification & Validation Capabilities

Scientists within NASA s Applied Sciences Directorate have developed a well-characterized remote sensing Verification & Validation (V&V) site at the John C. Stennis Space Center (SSC). This site enables the in-flight characterization of satellite and airborne high spatial and moderate resolution remote sensing systems and their products. The smaller scale of the newer high resolution remote sensing systems allows scientists to characterize geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the techniques used to characterize data from the earlier, coarser spatial resolution systems. Scientists are also using the SSC V&V site to characterize thermal infrared systems and active lidar systems. SSC employs geodetic targets, edge targets, radiometric tarps, atmospheric monitoring equipment, and thermal calibration ponds to characterize remote sensing data products. The SSC Instrument Validation Lab is a key component of the V&V capability and is used to calibrate field instrumentation and to provide National Institute of Standards and Technology traceability. This poster presents a description of the SSC characterization capabilities and examples of calibration data.

Pagnutti, Mary↗

NASA NTRS1990

Cloud cover analysis with Arctic Advanced Very High Resolution Radiometer data. II - Classification with spectral and textural measures

The spectral and textural characteristics of polar clouds and surfaces for a 7-day summer series of AVHRR data in two Arctic locations are examined, and the results used in the development of a cloud classification procedure for polar satellite data. Since spatial coherence and texture sensitivity tests indicate that a joint spectral-textural analysis based on the same cell size is inappropriate, cloud detection with AVHRR data and surface identification with passive microwave data are first done on the pixel level as described by Key and Barry (1989). Next, cloud patterns within 250-sq-km regions are described, then the spectral and local textural characteristics of cloud patterns in the image are determined and each cloud pixel is classified by statistical methods. Results indicate that both spectral and textural features can be utilized in the classification of cloudy pixels, although spectral features are most useful for the discrimination between cloud classes.

Key, J.↗

NASA NTRS1992

A catchment scale water balance model for FIFE

A catchment scale water balance model is presented and used to predict evaporation from the King's Creek catchment at the First ISLSCP Field Experiment site on the Konza Prairie, Kansas. The model incorporates spatial variability in topography, soils, and precipitation to compute the land surface hydrologic fluxes. A network of 20 rain gages was employed to measure rainfall across the catchment in the summer of 1987. These data were spatially interpolated and used to drive the model during storm periods. During interstorm periods the model was driven by the estimated potential evaporation, which was calculated using net radiation data collected at site 2. Model-computed evaporation is compared to that observed, both at site 2 (grid location 1916-BRS) and the catchment scale, for the simulation period from June 1 to October 9, 1987.

Famiglietti, J. S.↗

NASA NTRS1995

Hierarchical analysis of spatial pattern and processes of Douglas-fir forests

There has been an increased interest in the quantification of pattern in ecological systems over the past years. This interest is motivated by the desire to construct valid models which extend across many scales. Spatial methods must quantify pattern, discriminate types of pattern, and relate hierarchical phenomena across scales. Wavelet analysis is introduced as a method to identify spatial structure in ecological transect data. The main advantage of the wavelet transform over other methods is its ability to preserve and display hierarchical information while allowing for pattern decomposition. Two applications of wavelet analysis are illustrated, as a means to: (1) quantify known spatial patterns in Douglas-fir forests at several scales, and (2) construct spatially-explicit hypotheses regarding pattern generating mechanisms. Application of the wavelet variance, derived from the wavelet transform, is developed for forest ecosystem analysis to obtain additional insight into spatially-explicit data. Specifically, the resolution capabilities of the wavelet variance are compared to the semi-variogram and Fourier power spectra for the description of spatial data using a set of one-dimensional stationary and non-stationary processes. The wavelet cross-covariance function is derived from the wavelet transform and introduced as a alternative method for the analysis of multivariate spatial data of understory vegetation and canopy in Douglas-fir forests of the western Cascades of Oregon.

Bradshaw, G. A.↗

NASA NTRS1986

Cometary atmospheres: Modeling the spatial distribution of observed neutral radicals

New data for the spatial distribution of cometary C2 are presented. A recompilation of the Haser scale lengths for C2 and CN resolves the previously held anomalous drop of the C2/CN ratio for heliocentric distances larger than 1 AU. Clues to the source of cometary C2 have been found through fitting the sunward-antisunward brightness profiles with the Monte Carlo particle-trajectory model. A source (parent) lifetime of 3.1 x 10,000 seconds is found, and an ejection speed for C2 radicals upon dissociation of the parent(s) of approx. 0.5 km 1/5 is calculated.

Combi, M. R.↗

NASA NTRS2020

High-Resolution Gridded Level 3 Aerosol Optical Depth Data from MODIS

The state-of-art satellite observations of atmospheric aerosols over the last two decades from NASA's MODIS instruments have been extensively utilized in climate change and air quality research and applications. The operational algorithms now produce level 2 aerosol data at varying spatial resolutions (1, 3, and 10 km) and level 3 data at 1 degree. The local and global applications have been benefited from the coarse resolution gridded data sets (i.e., level 3, 1 degree), as it is easier to use since data volume is low and, several online and offline tools are readily available to access and analyze the data with minimal computing resources. At the same time, researchers who require data at much finer spatial scales have to go through a challenging process of obtaining, processing, and analyzing larger volumes of data sets that require high-end computing resources and coding skills. Therefore, we have created a high spatial resolution (HRG, 0.1x0.1 degree) daily and monthly aerosol optical depth (AOD) product by combining two MODIS operational algorithms, namely Deep Blue (DB) and Dark Target (DT). The new HRG AODs meets the accuracy requirements of level 2 AOD data and provide either the same or more spatial coverage on daily and monthly scales. The data sets are provided in daily and monthly files through open Ftp server with python scripts to read and map the data. The reduced data volume with an easy to use format and tools to access the data will encourage more users to utilize the data for research and applications.

aerosol↗

NASA NTRS2002

Measurement Sets and Sites Commonly Used for Characterization

Scientists at NASA's Earth Science Applications Directorate are creating a well-characterized Verification & Validation (V&V) site at the Stennis Space Center. This site enables the in-flight characterization of remote sensing systems and the data they acquire. The data are predominantly acquired by commercial, high spatial resolution satellite systems, such as IKONOS and QuickBird 2, and airborne systems. The smaller scale of these newer high resolution remote sensing systems allows scientists to characterize the geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the techniques used to characterize data from the earlier, coarser spatial resolution systems. Scientists are also using the SSC V&V site to characterize thermal infrared systems and active LIDAR systems. SSC employs geodetic targets, edge targets, radiometric tarps, and thermal calibration ponds to characterize remote sensing data products. This paper presents a proposed set of required measurements for visible through long-wave infrared remote sensing systems and a description of the Stennis characterization. Other topics discussed include: 1) The use of ancillary atmospheric and solar measurements taken at SSC that support various characterizations; 2) Additional sites used for radiometric, geometric, and spatial characterization in the continental United States; 3) The need for a standardized technique to be adopted by CEOS and other organizations.

Pagnutti, Mary↗

NASA NTRS1993

Direct measurements of tropospheric ozone from TOMS data

In the past year, we have made measurements of the tropospheric total column of ozone during the biomass burning season in Africa (August to October). Fishman et. al. had reported previously that by taking a time average of the low spatial resolution data from TOMS (Total Ozone Mapping Spectrometer) on Nimbus-7 (referred to as the Grid-T data set), during the biomass burning season in Africa, a plume of ozone extends from the East coast of Africa into the Atlantic. In this report, we present an analysis that we have made using the measured TOMS radiances taken from the High Density TOMS data set (referred as the HDT data set), which examines this plume in more detail.

Hudson, Robert D.↗

NASA NTRS1974

Analysis of multispectral signatures and investigation of multi-aspect remote sensing techniques

Two major aspects of remote sensing with multispectral scanners (MSS) are investigated. The first, multispectral signature analysis, includes the effects on classification performance of systematic variations found in the average signals received from various ground covers as well as the prediction of these variations with theoretical models of physical processes. The foremost effects studied are those associated with the time of day airborne MSS data are collected. Six data collection runs made over the same flight line in a period of five hours are analyzed, it is found that the time span significantly affects classification performance. Variations associated with scan angle also are studied. The second major topic of discussion is multi-aspect remote sensing, a new concept in remote sensing with scanners. Here, data are collected on multiple passes by a scanner that can be tilted to scan forward of the aircraft at different angles on different passes. The use of such spatially registered data to achieve improved classification of agricultural scenes is investigated and found promising. Also considered are the possibilities of extracting from multi-aspect data, information on the condition of corn canopies and the stand characteristics of forests.

Malila, W. A.↗

NASA NTRS1976

Machine processing of remotely acquired data

The two major branches of remote sensing are based on image orientation and numerical orientation. Numerically oriented systems tend to involve computers for data analysis. In designing an information-gathering system, the sensor as well as the means of analysis must be well mated to the type of system orientation. Attention is given to sensor types as related to system types, the multispectral approach and pattern recognition, the multispectral scanner as data source, an illustrative example, procedural details in the use of pattern recognition, the speed and cost of data processing, the use of spatial information, and data preprocessing steps.

Landgrebe, D. A.↗