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NASA NTRS2003

The Okhotsk Sea Kashevarov Bank Polynya: Its Dependence on Diurnal and Fortnightly Tides and its Initial Formation

Open water areas within the sea ice (polynyas) are sources of intense heat exchange between the ocean and the atmosphere. In this paper, we used microwave and visible/infrared satellite data together with a sea ice model to investigate the polynya opening mechanisms. The satellite data and the model show significant agreement and prove that tides play an active role in the polynya dynamics.

Martin, Seelye↗
NASA NTRS2001

Band-Moment Compression of AVIRIS Hyperspectral Data and its Use in the Detection of Vegetation Stress

A remote sensing campaign was conducted over a U.S. Department of Agriculture test farm at Shelton, Nebraska. An experimental field was set off in plots that were differentially treated with anhydrous ammonia. Four replicates of 0-kg/ha to 200-kg/ha plots, in 50-kg/ha increments, were set out in a random block design. Low-altitude (GSD of 3 m) Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral data were collected over the site in 224 bands. Simultaneously, ground data were collected to support the airborne imagery. In an effort to reduce data load while maintaining or enhancing algorithm performance for vegetation stress detection, band-moment compression and analysis was applied to the AVIRIS image cube. The results indicated that band-moment techniques compress the AVIRIS dataset significantly while retaining the capability of detecting environmentally induced vegetation stress.

Estep, L.↗
NASA NTRS2004

Remote Sensing of the Haughton Impact Structure (HIS): A Terrestrial Proof of Concept for Using the Remote Sensing of Martian Craters as a Probe of Subsurface Composition

Impact cratering is the most widespread geological process in the Solar System. Impact craters can provide 'windows' into the subsurfaces of planetary bodies through excavation and uplift. By utilizing remote methods in the visible and near infrared (VNIR; 0.4-1.4 micron), short-wavelength infrared (SWIR; 1.4-2.5 micron) and thermal infrared (TIR 7-14 micron), subsurface mineral compositions may be identified and mapped via impact craters. Complex craters in particular, expose minerals from both the shallow and deep-seated subsurface, which may be identified spectroscopically. Complex craters have morphological features such as central peaks or peak rings, which are composed of relatively coherent lithologies tapped from deep-seated crustal components. While near-surface crustal components can be observed as coherent rocks uplifted and exposed in the rim and the crater walls, and from the ejecta deposits. Only two previously published studies using this approach have been successful on large planetary bodies. Tompkins and Pieters utilized ultraviolet and VNIR from Clementine to characterize near- and deep-subsurface materials in and around lunar craters. The work of Ramsey and Wright was the first remote spectroscopic study to successfully identify near-subsurface materials in the ejecta and crater wall of a terrestrial impact structure, namely Meteor Crater. Here we present early results of a third such study, a remote spectroscopy evaluation of the Haughton impact structure (HIS). The purpose of this study is to serve as terrestrial proof of concept that remote visible/infrared spectroscopic methods in this case, analysis of LANDSAT 7 ETM+ and ASTER data of the well-preserved HIS can be utilized in deciphering the subsurface composition of planetary crusts. This technique is particularly promising for Mars were limited tectonic uplift and ubiquitous dust-mantling offer few opportunities to access subsurface information.

Tornabene, L. L.↗
NASA NTRS2003

Merging Ocean Color Data From Multiple Missions

Oceanic phytoplankton may play an important role in the cycling of carbon on the Earth, through the uptake of carbon dioxide in the process of photosynthesis. Although they are ubiquitous in the global oceans, their abundances and dynamics are difficult to estimate, primarily due to the vast spatial extent of the oceans and the short time scales over which their abundances can change. Consequently, the effects of oceanic phytoplankton on biogeochemical cycling, climate change, and fisheries are not well known. In response to the potential importance of phytoplankton in the global carbon cycle and the lack of comprehensive data, NASA and the international community have established high priority satellite missions designed to acquire and produce high quality ocean color data (Table 6.1). Ten of the missions are routine global observational missions: the Ocean Color and Temperature Sensor (OCTS), the Polarization and Directionality of the Earth's Reflectances sensor (POLDER), Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectrometer-AM (MODIS-AM), Medium Resolution Imaging Spectrometer (MERIS), Global Imager (GLI), MODIS-PM, Super-GLI (S-GLI), and the Visible/Infrared Imager and Radiometer Suite (VIIRS) on the NPOESS Preparatory Project (NPP) and the National Polar-orbiting Operational Environmental Satellite System (NPOESS). In addition, there are several other missions capable of providing ocean color data on smaller scales. Most of these missions contain the spectral band complement considered necessary to derive oceanic chlorophyll concentrations and other related parameters. Many contain additional bands that can provide important ancillary information about the optical and biological state of the oceans.

Gregg, Watson W.↗
NASA NTRS2004

Studying the Diurnal Cycle of Convection Using a TRMM-Calibrated Infrared Rain Algorithm

The development of a satellite infrared (IR) technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall on a global scale is presented. The Convective-Stratiform Technique (CST), calibrated by coincident, physically retrieved rain rates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), is applied over the global tropics. The technique makes use of the IR data from the TRMM Visible/Infrared Scanner (VIRS) before application to global geosynchronous satellite data. The calibrated CST technique has the advantages of high spatial resolution (4 km), filtering of non-raining cirrus clouds, and the stratification of the rainfall into its convective and stratiform components, the last being important for the calculation of vertical profiles of latent heating. The diurnal cycle of rainfall, as well as the division between convective and stratiform rainfall will be presented. The technique is validated using available data sets and compared to other global rainfall products such as Global Precipitation Climatology Project (GPCP) IR product, calibrated with TRMM Microwave Imager (TMI) data. Results from five years of PR data will show the global-tropical partitioning of convective and stratiform rainfall.

Negri, Andrew J.↗
NASA NTRS2005

Studying the Diurnal Cycle of Convection Using a TRMM-Calibrated Infrared Rain Algorithm

The development of a satellite infrared (IR) technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall on a global scale is presented. The Convective-Stratiform Technique (CST), calibrated by coincident, physically retrieved rain rates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), is applied over the global tropics. The technique makes use of the IR data from the TRMM Visible/Infrared Scanner (VIRS) before application to global geosynchronous satellite data. The calibrated CST technique has the advantages of high spatial resolution (4 km), filtering of nonraining cirrus clouds, and the stratification of the rainfall into its convective and stratiform components, the last being important for the calculation of vertical profiles of latent heating. The diurnal cycle of rainfall, as well as the division between convective and Stratiform rainfall will be presented. The technique is validated using available data sets and compared to other global rainfall products such as Global Precipitation Climatology Project (GPCP) IR product, calibrated with TRMM Microwave Imager (TMI) data. Results from five years of PR data will show the global-tropical partitioning of convective and stratiform rainfall.

Negri, Andrew J.↗
NASA NTRS2004

Retrieval of Marine Water Constituents Using Atmospherically Corrected AVIRIS Hyperspectral Data

This paper reports on the validation of bio-optical models in estuarine and nearshore (case 2) waters of New Jersey-New York to retrieve accurate water-leaving radiance spectra and chlorophyll concentration from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imaging spectrometer data. MODTRAN-4 was applied to remove the effects of the atmosphere so as to infer the water-leaving radiance. The study area - Hudson/Raritan of New York and New Jersey (Figure 1) is an extremely complex estuarine system where tidal and wind-driven currents are modified by freshwater discharges from the Hudson, Raritan, Hackensack, and Passaic rivers. Over the last century, the estuarine water quality has degraded in part due to eutrophication, which has disrupted the preexisting natural balance, resulting in phytoplankton blooms of both increased frequency and intensity, increasing oxygen demand, and leading to episodes of hypoxia. As the end result, a thematic map of chlorophyll-a concentration was generated using an atmospherically corrected AVIRIS ratio image. This thematic map serves as an indication of phytoplankton concentration. Such maps are important input into the geographic information system (GIS) for use as a management tool for monitoring water resources.

Bagheri, Sima↗
NASA NTRS1996

Mapping Chaparral in the Santa Monica Mountatins Using Multiple Endmember Spectral Mixture Models

From Intro: A study was initiated in the Santa Monica Mountains to investigate the use of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)for providing improved maps of chaparral coupled with direct estimates of canopy attributes (eg. biomass, leaf area, fuel load)...Analysis focused on AVIRIS data collected on October 19, 1994.

AVIRIS chaparral California chaparral California w↗
NASA NTRS1996

Estimation of Biomass Fire Temperature and Areal Extent from Calibrated AVIRIS Spectra

This paper describes an approach to derive a range of biomass fire parameters from spectra measured by NASA's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). AVIRIS measures images of the upwelling spectral radiance from 400 to 2500 nm at 10nm intervals. Images are measured of 11 by up to 100 km with 20 by 20 m spatial resolution.

Biomass AVRIS biomass fire smoke cloud aerosol and↗
NASA NTRS2001

Radiometric comparison of AVIRIS and SeaWIFS 1997-2000

The objective of this project is to calibrate and validate the on orbit radiometric characteristics of SeaWIFS with underflights of NASA's calibrated Airborne Visible/Infrared Imaging Spectrometer.

AVIRIS calibration ground truth↗
NASA NTRS2003

Derivative Analysis of AVIRIS Data for Crop Stress Detection

Low-altitude Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral imagery of a cornfield in Nebraska was used to determine whether derivative analysis methods provided enhanced plant stress detection compared with narrow-band ratios. The field was divided into 20 plots representing 4 replicates each of 5 nitrogen (N) fertilization treatments that ranged from 0 to 200 kg N/ha in 50 kg/ha increments. The imagery yielded a 3 m ground pixel size for 224 spectral bands. Derivative analysis provided no advantage in stress detection compared with the performance of narrow-band indices derived from the literature. This result was attributed to a high leaf area index at the time of overflight (LAI approx. equal to 5 to 6t) and the high signal-to-noise character of the narrow AVIRIS bands.

Estep, Lee↗
NASA NTRS2006

Remote Sensing Time Series Product Tool

The TSPT (Time Series Product Tool) software was custom-designed for NASA to rapidly create and display single-band and band-combination time series, such as NDVI (Normalized Difference Vegetation Index) images, for wide-area crop surveillance and for other time-critical applications. The TSPT, developed in MATLAB, allows users to create and display various MODIS (Moderate Resolution Imaging Spectroradiometer) or simulated VIIRS (Visible/Infrared Imager Radiometer Suite) products as single images, as time series plots at a selected location, or as temporally processed image videos. Manually creating these types of products is extremely labor intensive; however, the TSPT development tool makes the process simplified and efficient. MODIS is ideal for monitoring large crop areas because of its wide swath (2330 km), its relatively small ground sample distance (250 m), and its high temporal revisit time (twice daily). Furthermore, because MODIS imagery is acquired daily, rapid changes in vegetative health can potentially be detected. The new TSPT technology provides users with the ability to temporally process high-revisit-rate satellite imagery, such as that acquired from MODIS and from its successor, the VIIRS. The TSPT features the important capability of fusing data from both MODIS instruments onboard the Terra and Aqua satellites, which drastically improves cloud statistics. With the TSPT, MODIS metadata is used to find and optionally remove bad and suspect data. Noise removal and temporal processing techniques allow users to create low-noise time series plots and image videos and to select settings and thresholds that tailor particular output products. The TSPT GUI (graphical user interface) provides an interactive environment for crafting what-if scenarios by enabling a user to repeat product generation using different settings and thresholds. The TSPT Application Programming Interface provides more fine-tuned control of product generation, allowing experienced programmers to bypass the GUI and to create more user-specific output products, such as comparison time plots or images. This type of time series analysis tool for remotely sensed imagery could be the basis of a large-area vegetation surveillance system. The TSPT has been used to generate NDVI time series over growing seasons in California and Argentina and for hurricane events, such as Hurricane Katrina.

Predos, Don↗
NASA NTRS2006

The Critical Need for Continued Data Collection and Development of Future Thermal Satellite Sensors

There is a rich and long history of thermal infrared (TIR) remote sensing data for multidisciplinary Earth science research. The continuity of TIR data collection, however, is now in jeopardy given there are no planned future Earth observing TIR remote sensing satellite systems with moderately high spatial resolutions to replace those currently in orbit on NASA's Terra suite of sensors. This session will convene researchers who have actively worked in the field of TIR remote sensing to present results that elucidate the importance of thermal remote sensing to the wider Earth science research community. Additionally, this session will also exist as a forum for presenting concepts and ideas for new thermal sensing systems with high spatial resolutions for future Earth science satellite missions, as opposed to planned systems such as the Visible/Infrared Imager/Radiometer (VIIRS) suite of sensors on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) that will collect TIR data at very coarse spatial resolutions.

Quattrochi, Dale A.↗
NASA NTRS2006

VIIRS Product Aggregation and Packaging

Areas where the end-users can help define the Visible/Infrared Imager Radiometer Suite (VIIRS) products distributed by NOAA include: temporal aggregation, band packaging, and gelolocation packaging. Proposals in these areas are presented along with background information, advantages and disadvantates of each proposal. The proposals are based on experience with NASA EOS missions and programs (MODIS and SeaWIFS).

Wolfe, Robert↗
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

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

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.↗