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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
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Estimating Temperature Retrieval Accuracy Associated With Thermal Band Spatial Resolution Requirements for Center Pivot Irrigation Monitoring and Management

This study explores the use of synthetic thermal center pivot irrigation scenes to estimate temperature retrieval accuracy for thermal remote sensed data, such as data acquired from current and proposed Landsat-like thermal systems. Center pivot irrigation is a common practice in the western United States and in other parts of the world where water resources are scarce. Wide-area ET (evapotranspiration) estimates and reliable water management decisions depend on accurate temperature information retrieval from remotely sensed data. Spatial resolution, sensor noise, and the temperature step between a field and its surrounding area impose limits on the ability to retrieve temperature information. Spatial resolution is an interrelationship between GSD (ground sample distance) and a measure of image sharpness, such as edge response or edge slope. Edge response and edge slope are intuitive, and direct measures of spatial resolution are easier to visualize and estimate than the more common Modulation Transfer Function or Point Spread Function. For these reasons, recent data specifications, such as those for the LDCM (Landsat Data Continuity Mission), have used GSD and edge response to specify spatial resolution. For this study, we have defined a 400-800 m diameter center pivot irrigation area with a large 25 K temperature step associated with a 300 K well-watered field surrounded by an infinite 325 K dry area. In this context, we defined the benchmark problem as an easily modeled, highly common stressing case. By parametrically varying GSD (30-240 m) and edge slope, we determined the number of pixels and field area fraction that meet a given temperature accuracy estimate for 400-m, 600-m, and 800-m diameter field sizes. Results of this project will help assess the utility of proposed specifications for the LDCM and other future thermal remote sensing missions and for water resource management.

Ryan, Robert E.↗
NASA NTRS2006

Verification and Validation of NASA-Supported Enhancements to the Near Real Time Harmful Algal Blooms Observing System (HABSOS)

This report discusses verification and validation (V&V) assessment of Moderate Resolution Imaging Spectroradiometer (MODIS) ocean data products contributed by the Naval Research Laboratory (NRL) and Applied Coherent Technologies (ACT) Corporation to National Oceanic Atmospheric Administration s (NOAA) Near Real Time (NRT) Harmful Algal Blooms Observing System (HABSOS). HABSOS is a maturing decision support tool (DST) used by NOAA and its partners involved with coastal and public health management.

Spruce, Joseph P.↗
NASA NTRS2005

Techniques for Producing Coastal Land Water Masks from Landsat and Other Multispectral Satellite Data

Coastal erosion and land loss continue to threaten many areas in the United States. Landsat data has been used to monitor regional coastal change since the 1970's. Many techniques can be used to produce coastal land water masks, including image classification and density slicing of individual bands or of band ratios. Band ratios used in land water detection include several variations of the Normalized Difference Water Index (NDWI). This poster discusses a study that compares land water masks computed from unsupervised Landsat image classification with masks from density-sliced band ratios and from the Landsat TM band 5. The greater New Orleans area is imployed in this study, due to its abundance of coastal habitats and ist vulnerability to coastal land loss. Image classification produced the best results based on visual comparison to higher resolution satellite and aerial image displays. However, density-sliced NDWI imagery from either near infrared (NIR) and blue bands or from NIR and green bands also produced more effective land water masks than imagery from the density-sliced Landsat TM band 5. NDWI based on NIR and green bands is noteworthy because it allows land water masks to be generated form multispectral satellite sensors without a blue band (e.g., ASTER and Landsat MSS). NDWI techniques also have potential for producing land water masks from coarser scaled satellite data, such as MODIS.

Spruce, Joe↗
NASA NTRS2007

Evaluation of a Potential for Enhancing the Decision Support System of the Interagency Modeling and Atmospheric Assessment Center with NASA Earth Science Research Results

NASA's objective for the Applied Sciences Program of the Science Mission Directorate is to expand and accelerate the realization of economic and societal benefits from Earth science, information, and technology. This objective is accomplished by using a systems approach to facilitate the incorporation of Earth observations and predictions into the decision-support tools used by partner organizations to provide essential services to society. The services include management of forest fires, coastal zones, agriculture, weather prediction, hazard mitigation, aviation safety, and homeland security. In this way, NASA's long-term research programs yield near-term, practical benefits to society. The Applied Sciences Program relies heavily on forging partnerships with other Federal agencies to accomplish its objectives. NASA chooses to partner with agencies that have existing connections with end-users, information infrastructure already in place, and decision support systems that can be enhanced by the Earth science information that NASA is uniquely poised to provide (NASA, 2004).

Blonski, Slawomir↗
NASA NTRS2007

A Rapidly Prototyped Vegetation Dryness Index Evaluated for Wildfire Risk Assessment at Stennis Space Center

MVDI, which effectively involves the differencing of NDMI and NDVI, appears to display increased noise that is consistent with a differencing technique. This effect masks finer variations in vegetation moisture, preventing MVDI from fulfilling the requirement of giving decision makers insight into spatial variation of fire risk. MVDI shows dependencies on land cover and phenology which also argue against its use as a fire risk proxy in an area of diverse and fragmented land covers. The conclusion of the rapid prototyping effort is that MVDI should not be implemented for SSC decision support.

Ross, Kenton↗
NASA NTRS2007

Assessing Hurricane Katrina Vegetation Damage at Stennis Space Center using IKONOS Image Classification Techniques

Hurricane Katrina hit southwestern Mississippi on August 29, 2005, at 9:45 a.m. CDT as a category 3 storm with surges up to approx. 9 m and sustained winds of approx. 120 mph. The hurricane's wind, rain, and flooding devastated several coastal towns, from New Orleans through Mobile. The storm also caused significant damage to infrastructure and vegetation of NASA's SSC (Stennis Space Center). Storm recovery at SSC involved not only repairs of critical infrastructure but also forest damage mitigation (via timber harvests and control burns to reduce fire risk). This presentation discusses an effort to use commercially available high spatial resolution multispectral IKONOS data for vegetation damage assessment, based on data collected over SSC on September 2, 2005.

Spruce, Joseph P.↗
NASA NTRS2007

Assessing Potential of VIIRS Data for Contribution to a Forest Threat Early Warning System

This viewgraph presentation reviews the contributions by the Rapid Prototyping Capability (RPC) towards using Visible Infrared Imager / Radiometer Suite (VIIRS) data in assessing the damage to forests. The Healthy Forest Restoration Act of 2003 mandates development of national Early Warning System (EWS) for forest threat monitoring and mitigation. NASA Stennis is working with the US Forest Service to develop needed components of this EWS. The use of MODIS data for monitoring forest disturbance at broad regional scales is a componet of this program. This RPC experiment was initiated to assess potential of the MODIS follow-on, VIIRS, for monitoring forest disturbance at broad scales and thereby contributing to the EWS. This presentation reviews the potential use of the VIIRS to examine the damage to forests caused by gyspy moths in the West Virginia and Virginia area.

Spruce, Joseph P.↗
NASA NTRS2007

Coral Reef Early Warning System (CREWS) RPC Experiment

This viewgraph document reviews the background, objectives, methodology, validation, and present status of the Coral Reef Early Warning System (CREWS) Rapid Prototyping Capability (RPC) experiment. The potential NASA contribution to CREWS Decision Support Tool (DST) centers on remotely sensed imagery products.

Estep, Leland↗
NASA NTRS2007

Use of AIRS, OMI, MLS, and TES Data in Assessing Forest Ecosystem Exposure to Ozone

Ground-level ozone at high levels poses health threats to exposed flora and fauna, including negative impacts to human health. While concern is common regarding depletion of ozone in the stratosphere, portions of the urban and rural United States periodically have high ambient levels of tropospheric ozone on the ground. Ozone pollution can cause a variety of impacts to susceptible vegetation (e.g., Ponderosa and Jeffrey pine species in the southwestern United States), such as stunted growth, alteration of growth form, needle or leaf chlorosis, and impaired ability to withstand drought-induced water stress. In addition, Southern Californian forests with high ozone exposures have been recently subject to multiyear droughts that have led to extensive forest overstory mortality from insect outbreaks and increased incidence of wildfires. Residual forests in these impacted areas may be more vulnerable to high ozone exposures and to other forest threats than ever before. NASA sensors collect a wealth of atmospheric data that have been used recently for mapping and monitoring regional tropospheric ozone levels. AIRS (Atmospheric Infrared Sounder), OMI (Ozone Monitoring Instrument), MLS (Microwave Limb Sounder), and TES (Tropospheric Emission Spectrometer) data could be used to assess forest ecosystem exposure to ozone. Such NASA data hold promise for providing better or at least complementary synoptic information on ground-level ozone levels that Federal agency partners can use to assess forest health trends and to mitigate the threats as needed in compliance with Federal laws and mandates. NASA data products on ozone concentrations may be able to aid applications of DSTs (decision support tools) adopted by the USDA FS (U.S. Department of Agriculture Forest Service) and by the NPS (National Park Service), such as the Ozone Calculator, in which ground ozone estimates are employed to assess ozone impacts to forested vegetation.

Spruce, Joseph P.↗
NASA NTRS2007

Simulated NASA Satellite Data Products for the NOAA Integrated Coral Reef Observation Network/Coral Reef Early Warning System

This RPC (Rapid Prototyping Capability) experiment will demonstrate the use of VIIRS (Visible/Infrared Imager/Radiometer Suite) and LDCM (Landsat Data Continuity Mission) sensor data as significant input to the NOAA (National Oceanic and Atmospheric Administration) ICON/ CREWS (Integrated Coral Reef Observation System/Coral Reef Early Warning System). The project affects the Coastal Management Program Element of the Applied Sciences Program.

Estep, Leland↗
NASA NTRS2007

Regional Sediment Management Experiment Using the Visible/Infrared Imager/Radiometer Suite and the Landsat Data Continuity Mission Sensor

The central aim of this RPC (Rapid Prototyping Capability) experiment is to demonstrate the use of VIIRS (Visible/Infrared Imager/ Radiometer Suite and LDCM (Landsat Data Continuity Mission) sensors as key input to the RSM (Regional Sediment Management) GIS (geographic information system) DSS (Decision Support System). The project affects the Coastal Management National Application.

Estep, Leland↗
NASA NTRS2007

Coral Reef Remote Sensing using Simulated VIIRS and LDCM Imagery

The Rapid Prototyping Capability (RPC) node at NASA Stennis Space Center, MS, was used to simulate NASA next-generation sensor imagery over well-known coral reef areas: Looe Key, FL, and Kaneohe Bay, HI. The objective was to assess the degree to which next-generation sensor systems the Visible/Infrared Imager/Radiometer Suite (VIIRS) and the Landsat Data Continuity Mission (LDCM) might provide key input to the National Oceanographic and Atmospheric Administration (NOAA) Integrated Coral Observing Network (ICON)/Coral Reef Early Warning System (CREWS) Decision Support Tool (DST). The DST data layers produced from the simulated imagery concerned water quality and benthic classification map layers. The water optical parameters of interest were chlorophyll (Chl) and the absorption coefficient (a). The input imagery used by the RPC for simulation included spaceborne (Hyperion) and airborne (AVIRIS) hyperspectral data. Specific field data to complement and aid in validation of the overflight data was used when available. The results of the experiment show that the next-generation sensor systems are capable of providing valuable data layer resources to NOAA's ICON/CREWS DST.

Estep, Leland↗
NASA NTRS2007

Assessing Hurricane Katrina Damage to the Mississippi Gulf Coast Using IKONOS Imagery

Hurricane Katrina hit southwestern Mississippi on August 29, 2005, at 10 a.m. CDT as a category 3 event with storm surges up to approximately 9 m and sustained winds of approximately 120 mph. The hurricane ravaged several coastal towns, destroying or severely damaging hundreds of homes. Hurricand Katrina deposited millions of tons of debris and caused severe damage to coastal forests. In response, several Federal agencies have been using a broad range of remotely sensed data (e.g., IKONOS) to aid damage assessment and disaster recovery efforts. This presentation discusses an effort to use IKONOS data for damage assessment, based on data collected over southwestern coastal Mississippi on September 2, 2005.

Spruce, Joseph P.↗
NASA NTRS2007

Potential of VIIRS Data for Regional Monitoring of Gypsy Moth Defoliation: Implications for Forest Threat Early Warning System

A NASA RPC (Rapid Prototyping Capability) experiment was conducted to assess the potential of VIIRS (Visible/Infrared Imager/Radiometer Suite) data for monitoring non-native gypsy moth (Lymantria dispar) defoliation of forests. This experiment compares defoliation detection products computed from simulated VIIRS and from MODIS (Moderate Resolution Imaging Spectroradiometer) time series products as potential inputs to a forest threat EWS (Early Warning System) being developed for the USFS (USDA Forest Service). Gypsy moth causes extensive defoliation of broadleaved forests in the United States and is specifically identified in the Healthy Forest Restoration Act (HFRA) of 2003. The HFRA mandates development of a national forest threat EWS. This system is being built by the USFS and NASA is aiding integration of needed satellite data products into this system, including MODIS products. This RPC experiment enabled the MODIS follow-on, VIIRS, to be evaluated as a data source for EWS forest monitoring products. The experiment included 1) assessment of MODIS-simulated VIIRS NDVI products, and 2) evaluation of gypsy moth defoliation mapping products from MODIS-simulated VIIRS and from MODIS NDVI time series data. This experiment employed MODIS data collected over the approximately 15 million acre mid-Appalachian Highlands during the annual peak defoliation time frame (approximately June 10 through July 27) during 2000-2006. NASA Stennis Application Research Toolbox software was used to produce MODIS-simulated VIIRS data and NASA Stennis Time Series Product Tool software was employed to process MODIS and MODIS-simulated VIIRS time series data scaled to planetary reflectance. MODIS-simulated VIIRS data was assessed through comparison to Hyperion-simulated VIIRS data using data collected during gypsy moth defoliation. Hyperion-simulated MODIS data showed a high correlation with actual MODIS data (NDVI R2 of 0.877 and RMSE of 0.023). MODIS-simulated VIIRS data for the same date showed moderately high correlation with Hyperion-simulated VIIRS data (NDVI R2 of 0.62 and RMSE of 0.035), even though the datasets were collected about a half an hour apart during changing weather conditions. MODIS products (MOD02, MOD09, and MOD13) and MOD02-simulated VIIRS time series data were used to generate defoliation mapping products based on image classification and image differencing change detection techniques. Accuracy of final defoliation mapping products was assessed by image interpreting over 170 randomly sampled locations found on Landsat and ASTER data in conjunction with defoliation map data from the USFS. The MOD02-simulated VIIRS 400-meter NDVI classification produced a similar overall accuracy (87.28 percent with 0.72 Kappa) to the MOD02 250-meter NDVI classification (86.71 percent with 0.71 Kappa). In addition, the VIIRS 400-meter NDVI, MOD02 250-meter NDVI, and MOD02 500-meter NDVI showed good user and producer accuracies for the defoliated forest class (70 percent) and acceptable Kappa values (0.66). MOD02 and MOD02-simulated VIIRS data both showed promise as data sources for regional monitoring of forest disturbance due to insect defoliation.

Spruce, Joseph P.↗
NASA NTRS2008

Potential of VIIRS Time Series Data for Aiding the USDA Forest Service Early Warning System for Forest Health Threats: A Gypsy Moth Defoliation Case Study

The Healthy Forest Restoration Act of 2003 mandated that a national forest threat Early Warning System (EWS) be developed. The USFS (USDA Forest Service) is currently building this EWS. NASA is helping the USFS to integrate remotely sensed data into the EWS, including MODIS data for monitoring forest disturbance at broad regional scales. This RPC experiment assesses the potential of VIIRS (Visible/Infrared Imager/Radiometer Suite) and MODIS (Moderate Resolution Imaging Spectroradiometer) data for contribution to the EWS. In doing so, the RPC project employed multitemporal simulated VIIRS and MODIS data for detecting and monitoring forest defoliation from the non-native Eurasian gypsy moth (Lymantria despar). Gypsy moth is an invasive species threatening eastern U.S. hardwood forests. It is one of eight major forest insect threats listed in the Healthy Forest Restoration Act of 2003. This RPC experiment is relevant to several nationally important mapping applications, including carbon management, ecological forecasting, coastal management, and disaster management

Spruce, Joseph P.↗
NASA NTRS2008

Coral Reef Remote Sensing Using Simulated VIIRS and LDCM Imagery

The Rapid Prototyping Capability (RPC) node at NASA Stennis Space Center, MS, was used to simulate NASA next-generation sensor imagery over well-known coral reef areas: Looe Key, FL, and Kaneohe Bay, HI. The objective was to assess the degree to which next-generation sensor systems-the Visible/Infrared Imager/Radiometer Suite (VIIRS) and the Landsat Data Continuity Mission (LDCM)- might provide key input to the National Oceanographic and Atmospheric Administration (NOAA) Integrated Coral Observing Network (ICON)/Coral Reef Early Warning System (CREWS) Decision Support Tool (DST). The DST data layers produced from the simulated imagery concerned water quality and benthic classification map layers. The water optical parameters of interest were chlorophyll (Chl) and the absorption coefficient (a). The input imagery used by the RPC for simulation included spaceborne (Hyperion) and airborne (AVIRIS) hyperspectral data. Specific field data to complement and aid in validation of the overflight data was used when available. The results of the experiment show that the next-generation sensor systems are capable of providing valuable data layer resources to NOAA s ICON/CREWS DST.

Estep, Leland↗
NASA NTRS2008

Assessing MODIS-based Products and Techniques for Detecting Gypsy Moth Defoliation

The project showed potential of MODIS and VIIRS time series data for contributing defoliation detection products to the USFS forest threat early warning system. This study yielded the first satellite-based wall-to-wall 2001 gypsy moth defoliation map for the study area. Initial results led to follow-on work to map 2007 gypsy moth defoliation over the eastern United States (in progress). MODIS-based defoliation maps offer promise for aiding aerial sketch maps either in planning surveys and/or adjusting acreage estimates of annual defoliation. More work still needs to be done to assess potential of technology for "now casts"of defoliation.

Spruce, Joseph P.↗