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At least 649 records · Page 36

Calibration and Characterization of the NASA EOS Terra and Aqua MODIS Instruments

The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument is operating on both of the Terra and Aqua missions within the NASA Earth Observing System (EOS). The Terra MODIS instrument began taking observations in February 2000 and the Aqua MODIS instrument began taking observations in June of 2002 and both continue to operate successfully up to the present time. The MODIS instrument scans the entire Earth every 24 hours at nominal spatial resolutions between 250 and 1000 meters. It has 36 spectral bands spanning the electromagnetic spectrum from the visible wavelengths mar 400 micrometers to the emissive thermal infrared wavelengths at 15 micrometers. The MODIS instruments produce approximately 40 geophysical products devoted to observing land, ocean, and atmospheric processes and trends. To meet the scientific objectives associated with the NASA Earth sciences efforts the MODIS instruments must be and have been carefully calibrated and the performance characterized to meet specifications and goals such as five percent radiance and two percent relative to the sun accuracy in the twenty bands providing reflected solar radiation observations and one percent radiance accuracy in the sixteen bands observing in the thermal infrared. Over the time spanning instrument development and the pre-launch calibration and characterization of the instrument through the years of operation in space, the performance of the MODIS instruments have changed in multiple ways and appropriate adjustments made in relevant algorithms and look-up tables necessary to produce observations that meet the scientific objectives and requirements. The changes have been quantified and accounted for through careful use of on-board calibration devices such as the Spectro-Radiometric Calibration Assembly (SRCA), the Solar Diffuser (SD) and its companion Solar Diffuser Stability Monitor (SDSM), deep-space and lunar observations, and calibration targets on the Earth's surface. The strictest and most difficult challenges have come in trying to meet the requirements for observing Ocean color and related ocean biology processes over time and space. Overall the MODIS observations have been very successful in providing valuable scientific and applications results. The essential capabilities of MODIS are to be provided in the future by the Visible and Infrared Imaging Radiometer Suite (VIIRS) on the National Polar Orbiting Environmental Satellite Series (NPOESS).

Salomonson, Vincent V.↗

A Robust, Low-Cost Virtual Archive for Science Data

Despite their expense tape silos are still often the only affordable option for petabytescale science data archives, particularly when other factors such as data reliability, floor space, power and cooling load are accounted for. However, the complexity, management software, hardware reliability and access latency of tape silos make online data storage ever more attractive. Drastic reductions in low-cost mass-market PC disk drivers help to make this more affordable (approx. 1$/GB), but are challenging to scale to the petabyte range and of questionable reliability for archival use, On the other hand, if much of the science archive could be "virtualized", i.e., produced on demand when requested by users, we would need store only a fraction of the data online, perhaps bringing an online-only system into in affordable range. Radiance data from the satellite-borne Moderate Resolution Imaging Spectroradiometer (MODIS) instrument provides a good opportunity for such a virtual archive: the raw data amount to 140 GB/day, but these are small relative to the 550 GB/day making up the radiance products. These data are routinely processed as inputs for geophysical parameter products and then archived on tape at the Goddard Earth Sciences Distributed Active Archive (GES DAAC) for distributing to users. Virtualizing them would be an immediate and signifcant reduction in the amount of data being stored in the tape archives and provide more customizable products. A prototype of such a virtual archive is being developed to prove the concept and develop ways of incorporating the robustness that a science data archive requires.

Lynnes, Christopher↗

Crop Surveillance Demonstration Using a Near-Daily MODIS Derived Vegetation Index Time Series

Effective response to crop disease outbreaks requires rapid identification and diagnosis of an event. A near-daily vegetation index product, such as a Normalized Difference Vegetation Index (NDVI), at moderate spatial resolution may serve as a good method for monitoring quick-acting diseases. NASA s Moderate Resolution Imaging Spectroradiometer (MODIS) instrument flown on the Terra and Aqua satellites has the temporal, spatial, and spectral properties to make it an excellent coarse-resolution data source for rapid, comprehensive surveillance of agricultural areas. A proof-of-concept wide area crop surveillance system using daily MODIS imagery was developed and tested on a set of San Joaquin cotton fields over a growing season. This area was chosen in part because excellent ground truth data were readily available. Preliminary results indicate that, at least in the southwestern part of the United States, near-daily NDVI products can be generated that show the natural variations in the crops as well as specific crop practices. Various filtering methods were evaluated and compared with standard MOD13 NDVI MODIS products. We observed that specific chemical applications that produce defoliation, which would have been missed using the standard 16-day product, were easily detectable with the filtered daily NDVI products.

McKellip, Rodney↗

Apperception of Clouds in AIRS Data

Our capacity to simulate the radiative characteristics of the Earth system has advanced greatly over the past decade. However, new space based measurements show that idealized simulations might not adequately represent the complexity of nature. For example, AIRS simulated multi-layer cloud clearing research provides an excellent groundwork for early Atmospheric Infra-Red Sounder (AIRS) operational cloud clearing and atmospheric profile retrieval. However, it doesn't reflect the complicated reality of clouds over land and coastal areas. Thus far, operational AIRS/AMSU (Advanced Microwave Sounding Unit) cloud clearing is not only of low yield but also of unsatisfying quality. This is not an argument for avoiding this challenging task, rather a powerful argument for exploring other synergistic approaches, and for adapting these strategies toward improving both indirect and direct use of cloudy infrared sounding data. Ample evidence is shown in this paper that the indirect use of cloudy sounding data by way of cloud clearing is sub-optimal for data assimilation. Improvements are needed in quality control, retrieval yield, and overall cloud clearing retrieval performance. For example, cloud clearing over land, especially over the desert surface, has led to much degraded retrieval quality and often a very low yield of quality controlled cloud cleared radiances. If these indirect cloud cleared radiances are instead to be directly assimilated into NWP models, great caution must be used. Our limited and preliminary cloud clearing results from AIRS/AMSU (with the use of MODIS data) and an AIRS/MODIS synergistic approach have, however, shown that higher spatial resolution multispectral imagery data can provide much needed quality control of the AIRS/AMSU cloud clearing retrieval. When AIRS and Moderate Resolution Imaging Spectroradiometer (MODIS) are used synergistically, a higher spatial resolution over difficult terrain (especially desert areas) can be achieved and with a much improved accuracy. Preliminary statistical analyses of cloud cleared radiances derived from (1) operational AIRS/AMSU, (2) operational AIRS/AMSU plus the use of MODIS data as quality control, and (3) AIRS/MODIS synergistic single channel and two field of views cloud clearing are Our capacity to simulate the radiative characteristics of the Earth system has

Huang, Hung-Lung↗

Automated Wildfire Detection Through Artificial Neural Networks

Wildfires have a profound impact upon the biosphere and our society in general. They cause loss of life, destruction of personal property and natural resources and alter the chemistry of the atmosphere. In response to the concern over the consequences of wildland fire and to support the fire management community, the National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data and Information Service (NESDIS) located in Camp Springs, Maryland gradually developed an operational system to routinely monitor wildland fire by satellite observations. The Hazard Mapping System, as it is known today, allows a team of trained fire analysts to examine and integrate, on a daily basis, remote sensing data from Geostationary Operational Environmental Satellite (GOES), Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors and generate a 24 hour fire product for the conterminous United States. Although assisted by automated fire detection algorithms, N O M has not been able to eliminate the human element from their fire detection procedures. As a consequence, the manually intensive effort has prevented NOAA from transitioning to a global fire product as urged particularly by climate modelers. NASA at Goddard Space Flight Center in Greenbelt, Maryland is helping N O M more fully automate the Hazard Mapping System by training neural networks to mimic the decision-making process of the frre analyst team as well as the automated algorithms.

Miller, Jerry↗

An Overview of MODIS Calibration and Characterization

The MODerate Resolution Imaging Spectroradiometer (MODIS) is one of the key instruments for the NASA s Earth Observing System (EOS). It is currently operating on both EOS Terra and Aqua satellites. The MODIS is a major advance over its heritage sensors in terms of its spectral, spatial, and temporal resolutions with frequent global observations and a broad range of science applications. There are 20 reflective solar bands (RSB) with center wavelengths ranging from 0.41 to 2.l microns and 16 thermal emissive bands (TEB) from 3.7 to 14.4 microns. The absolute radiometric accuracy requirements (lsigma) at the typical spectral radiance levels are plus or minus 2% for the RSB reflectance factors and plus or minus 5% for the RSB radiance products. With few exceptions, the TEB requirements are plus or minus 1%. To verify that the instruments met their specified design requirements both Terra and Aqua MODIS underwent extensive pre-launch calibration and characterization at various levels, including system-level thermal vacuum testing. On-orbit calibration and characterization are performed by the on-board calibrators: a solar diffuser (SD) and a solar diffuser stability monitor (SDSM), a V-groove flat panel blackbody (BB), and a spectro-radiometric calibration assembly (SRCA). In this paper, we present an overview of MODIS calibration and characterization activities, methodologies, and lessons learned from pre-launch testing and on-orbit operations. Key issues to be discussed include our on-orbit efforts of monitoring detectors noise characterization, tracking solar diffuser and optics degradation, and updating sensor s response versus scan-angle. The MODIS experience has provided invaluable lessons that are being used in designing and testing the Visible Infrared Imaging Radiometer Suite (VIIRS), a direct follow-on to the MODIS that will be flown on the National Polar-Orbit Operational Environmental Satellite System (NPOESS) missions.

Xiong, X.↗

NASA's Next Generation Sunphotometer for Ground-based Remote Sensing Applications

Atmospheric aerosol concentrations and their optical properties, in terms of which cause differential warming/cooling effects in the atmosphere and on the surface, constitute one of the largest sources of uncertainty in current assessments and predictions of global climatic change. This is especially true over the regions of bright-reflecting surface, such as desert and urban areas. Under the name of AERONET since the 90's, Cimel's sunphotometers have been deployed worldwide as the standard instrument for aerosol monitoring network, developed to support NASA, CNES, and NASDA's Earth satellite systems. PREDE's skyradiometers, as deployed in SKYNET, serve the similar role. One of the key ingredients for achieving accurate aerosol retrievals from satellite observations is comprehensive understanding of surface spectral BRF's (Bidirectional Reflectance Factors), defined as a ratio of radiance measurements reflected from a targeted surface and from a spectral-angular featureless referencing plate. Although the weather-resistant, automatic, sun/sky-scanning spectroradiometers enable Frequent measurements of atmospheric aerosol optical properties and precipitable water at remote sites, they are too slow for surface BRF measurements (20-25 seconds per 360 degree scan, in addition to filter wheel rotation time). We have designed a next generation sun photometer whose sensor head has no moving parts. A dedicated detector for each channel enables 12 simultaneous measurements ranging from the UV (380 nm) to shortwave-IR (2.13 micron) regions. The scan platform will be capable of traveling 360 degrees in about 6 seconds. This is sufficient to finish a BRDF scan every 30 degrees in azimuth and 15 degrees in elevation in less than 4 minutes. More details about this instrument will be presented, together with its applications to the aerosol and trace gas studies. The current plan for this instrument is to deploy during the EAST-AIRE (East Asian Study of Tropospheric Aerosols: an International Regional Experiment) and BASE-ASIA (Biomass-burning Aerosols in South East-Asia: Smoke Impact Assessment).

Shu, Peter K.↗

Snow and Ice Mask for the MODIS Aerosol Products

The atmospheric products have been derived operationally from multichannel imaging data collected with the Moderate Resolution Imaging SpectroRadiometers (MODIS) on board the NASA Terra and Aqua spacecrafts. Preliminary validations of the products were previously reported. Through analysis of more extensive time-series of MODIS aerosol products (Collection 4), we have found that the aerosol products over land areas are slightly contaminated by snow and ice during the springtime snow-melting season. We have developed an empirical technique using MODIS near-IR channels centered near 0.86 and 1.24 pm and a thermal emission channel near 11 pm to mask out these snow-contaminated pixels over land. Improved aerosol retrievals over land have been obtained. Sample results from application of the technique to MODIS data acquired over North America, northern Europe, and northeastern Asia are presented. The technique has been implemented into the MODIS Collection 5 operational algorithm for retrieving aerosols over land from MODIS data.

Li, Rong-Rong↗

Observed Land Impacts on Clouds, Water Vapor, and Rainfall at Continental Scales

How do the continents affect large-scale hydrological cycles? How important can one continent be to the climate system? To address these questions, 4-years of National Aeronautics and Space Administration (NASA) Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations, Tropical Rainfall Measuring Mission (TRMM) observations, and the Global Precipitation Climatology Project (GPCP) global precipitation analysis, were used to assess the land impacts on clouds, rainfall, and water vapor at continental scales. At these scales, the observations illustrate that continents are integrated regions that enhance the seasonality of atmospheric and surface hydrological parameters. Specifically, the continents of Eurasia and North America enhance the seasonality of cloud optical thickness, cirrus fraction, rainfall, and water vapor. Over land, both liquid water and ice cloud effective radii are smaller than over oceans primarily because land has more aerosol particles. In addition, different continents have similar impacts on hydrological variables in terms of seasonality, but differ in magnitude. For example, in winter, North America and Eurasia increase cloud optical thickness to 17.5 and 16, respectively, while in summer, Eurasia has much smaller cloud optical thicknesses than North America. Such different land impacts are determined by each continent s geographical condition, land cover, and land use. These new understandings help further address the land-ocean contrasts on global climate, help validate global climate model simulated land-atmosphere interactions, and help interpret climate change over land.

Jin, Menglin↗

Airborne Sunphotometer and Solar Spectral Flux Radiometer Measurements During INTEX/ITCT 2004

During the period 12 July - 8 August 2004, the NASA Ames 14-channel Airborne Tracking Sunphotometer (MTS-14) and Solar Spectral Flux Radiometer (SSFR) were operated aboard a Jetstream 31 (J31) aircraft and acquired measurements during nineteen science flights (approx. 53 flight hours) over the Gulf of Maine in support of the INTEX-NA (INtercontinental chemical Transport Experiment-North America) and ITCT (Intercontinental Transport and Chemical Transformation of anthropogenic pollution) field studies. In this paper, we will present results from analyses of those data sets. AATS-14 measures the direct solar beam transmission at fourteen discrete wavelengths (354-2138 nm), and provides instantaneous measurements of aerosol optical depth (AOD) spectra and water vapor column content, in addition to vertical profiles of aerosol extinction and water vapor density during suitable aircraft ascents and descents. SSFR consists of separate nadir and zenith viewing hemispheric FOV sensors that yield measurements of up- and downwelling solar irradiance at a spectral resolution of approx. 8-12 nm over the wavelength range 300-1700 nm. The objectives of the J31-based measurements during INTEX/ITCT were to provide AOD data for the evaluation of MODIS (MODerate-resolution Imaging Spectroradiometer) and MISR (Multi-angle Imaging Spectro-Radiometer) AOD retrievals, quantify sea surface spectral albedo (which can contribute the largest uncertainty to satellite aerosol retrievals for low aerosol loading), test closure (consistency) among suborbital results, test chemical-transport models using AOD profiles, and assess regional radiative forcing by combining satellite and suborbital results. Specific J31 flight patterns were designed to achieve these objectives, and they included a mixture of vertical profiles (spiral and ramped ascents and descents) and constant altitude horizontal transects at a variety of altitudes. Additional information is included in the original extended abstract.

Russell, P. B.↗

MODIS On-orbit Spectral Calibration for the Reflective Solar Bands

The Moderate Resolution Imaging Spectroradiometer (MODIS) makes observations in 36 spectral bands with wavelengths from 0.41 to 14.5 microns. The bands with center wavelengths below 2.2 microns are referred as the reflective solar bands (RSB) with their radiometric calibration performed by a solar diffuser (SD) and a solar diffuser stability monitor (SDSM). This paper focuses on the MODIS spectral calibration performed by its unique on-board calibrator (OBC): the Spectro-Radiometric Calibration Assembly (SRCA). When operated in the spectral mode, the SRCA acts as a monochromator with internal spherical integration source (SIS) that measures the spectral responses for all the reflective solar bands. A wavelength calibrator, a didymium filter with known spectral profile, is utilized to calibrate the wavelength scale for the grating positions during each SRCA spectral calibration activity. The capability of self-wavelength calibration allows the SRCA to track the center wavelength shifts and to monitor the spectral response changes throughout the instruments lifetime. The MODIS spectral calibration, same for both Terra and Aqua missions, is performed every three months on-orbit. An overview of MODIS spectral characterization approach and a summary of the on-orbit results will be presented in this paper.

Xiong, X.↗

Detection and Retrieval of Multi-Layered Cloud Properties Using Satellite Data

Four techniques for detecting multilayered clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. A new technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other methods examined here use atmospheric sounding data (CO2-slicing, CO2), BTD, or microwave data. The CO2 and BTD methods are limited to optically thin cirrus over low clouds, while the MWR methods are limited to ocean areas only. This paper explores the use of the BTD and CO2 methods as applied to Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer EOS (AMSR-E) data taken from the Aqua satellite over ocean surfaces. Cloud properties derived from MODIS data for the Clouds and the Earth's Radiant Energy System (CERES) Project are used to classify cloud phase and optical properties. The preliminary results focus on a MODIS image taken off the Uruguayan coast. The combined MW visible infrared (MVI) method is assumed to be the reference for detecting multilayered ice-over-water clouds. The BTD and CO2 techniques accurately match the MVI classifications in only 51 and 41% of the cases, respectively. Much additional study is need to determine the uncertainties in the MVI method and to analyze many more overlapped cloud scenes.

Minnis, Patrick↗

Verification and Validation of NASA-Supported Enhancements to Decision Support Tools of PECAD

This section of the evaluation report summarizes the verification and validation (V&V) of recently implemented, NASA-supported enhancements to the decision support tools of the Production Estimates and Crop Assessment Division (PECAD). The implemented enhancements include operationally tailored Moderate Resolution Imaging Spectroradiometer (MODIS) products and products of the Global Reservoir and Lake Monitor (GRLM). The MODIS products are currently made available through two separate decision support tools: the MODIS Image Gallery and the U.S. Department of Agriculture (USDA) Foreign Agricultural Service (FAS) MODIS Normalized Difference Vegetation Index (NDVI) Database. Both the Global Reservoir and Lake Monitor and MODIS Image Gallery provide near-real-time products through PECAD's CropExplorer. This discussion addresses two areas: 1. Assessments of the standard NASA products on which these enhancements are based. 2. Characterizations of the performance of the new operational products.

Ross, Kenton W.↗

Decision Support Tool Evaluation Report for Coral Reef Early Warning System (CREWS) Version 7.0

The Coral Reef Early Warning System (CREWS) is operated by NOAA's Office of Oceanic and Atmospheric Research as part of its Coral Reef Watch program in response to the deteriorating global state of coral reef and related benthic ecosystems. In addition to sea surface temperatures (SSTs), the two most important parameters used by the CREWS network in generating coral reef bleaching alerts are 1) wind speed and direction and 2) photosynthetically available radiation (PAR). NASA remote sensing products that can enhance CREWS in these areas include SST and PAR products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and wind data from the Quick Scatterometer (QuikSCAT). CREWS researchers are also interested in chlorophyll, chromophoric dissolved organic matter (CDOM), and salinity. Chlorophyll and CDOM are directly available as NASA products, while rainfall (an available NASA product) can be used as a proxy for salinity. Other potential NASA inputs include surface reflectance products from MODIS, the Advanced Spaceborne Thermal Emission and Reflection Radiometer, and Landsat. This report also identifies NASA-supported ocean circulation models and products from future satellite missions that might enchance the CREWS DST.

D'Sa, Eurico↗

Decision Support Tool Evaluation Report for General NOAA Oil Modeling Environment(GNOME) Version 2.0

NASA's Earth Science Applications Directorate evaluated the potential of NASA remote sensing data and modeling products to enhance the General NOAA Oil Modeling Environment (GNOME) decision support tool. NOAA's Office of Response and Restoration (OR&R) Hazardous Materials (HAZMAT) Response Division is interested in enhancing GNOME with near-realtime (NRT) NASA remote sensing products on oceanic winds and ocean circulation. The NASA SeaWinds sea surface wind and Jason-1 sea surface height NRT products have potential, as do sea surface temperature and reflectance products from the Moderate Resolution Imaging Spectroradiometer and sea surface reflectance products from Landsat and the Advanced Spaceborne Thermal Emission and Reflectance Radiometer. HAZMAT is also interested in the Advanced Circulation model and the Ocean General Circulation Model. Certain issues must be considered, including lack of data continuity, marginal data redundancy, and data formatting problems. Spatial resolution is an issue for near-shore GNOME applications. Additional work will be needed to incorporate NASA inputs into GNOME, including verification and validation of data products, algorithms, models, and NRT data.

Spruce, Joseph P.↗

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

Hurricane Katrina hit southeastern Louisiana and the Mississippi Gulf Coast as a Category 3 hurricane with storm surges as high as 9 m. Katrina devastated several coastal towns by destroying or severely damaging hundreds of homes. Several Federal agencies are assessing storm impacts and assisting recovery using high-spatial-resolution remotely sensed data from satellite and airborne platforms. High-quality IKONOS satellite imagery was collected on September 2, 2005, over southwestern Mississippi. Pan-sharpened IKONOS multispectral data and ERDAS IMAGINE software were used to classify post-storm land cover for coastal Hancock and Harrison Counties. This classification included a storm debris category of interest to FEMA for disaster mitigation. The classification resulted from combining traditional unsupervised and supervised classification techniques. Higher spatial resolution aerial and handheld photography were used as reference data. Results suggest that traditional classification techniques and IKONOS data can map wood-dominated storm debris in open areas if relevant training areas are used to develop the unsupervised classification signatures. IKONOS data also enabled other hurricane damage assessment, such as flood-deposited mud on lawns and vegetation foliage loss from the storm. IKONOS data has also aided regional Katrina vegetation damage surveys from multidate Land Remote Sensing Satellite and Moderate Resolution Imaging Spectroradiometer data.

Spruce, Joseph↗

Utilizing Hierarchical Segmentation to Generate Water and Snow Masks to Facilitate Monitoring Change with Remotely Sensed Image Data

The hierarchical segmentation (HSEG) algorithm is a hybrid of hierarchical step-wise optimization and constrained spectral clustering that produces a hierarchical set of image segmentations. This segmentation hierarchy organizes image data in a manner that makes the image's information content more accessible for analysis by enabling region-based analysis. This paper discusses data analysis with HSEG and describes several measures of region characteristics that may be useful analyzing segmentation hierarchies for various applications. Segmentation hierarchy analysis for generating landwater and snow/ice masks from MODIS (Moderate Resolution Imaging Spectroradiometer) data was demonstrated and compared with the corresponding MODIS standard products. The masks based on HSEG segmentation hierarchies compare very favorably to the MODIS standard products. Further, the HSEG based landwater mask was specifically tailored to the MODIS data and the HSEG snow/ice mask did not require the setting of a critical threshold as required in the production of the corresponding MODIS standard product.

Tilton, James C.↗

A Tamarisk Habitat Suitability Map for the Continental US

This paper presents a national-scale map of habitat suitability for a high-priority invasive species, Tamarisk (Tamarisk spp., salt cedar). We successfully integrate satellite data and tens of thousands of field sampling points through logistic regression modeling to create a habitat suitability map that is 90% accurate. This interagency effort uses field data collected and coordinated through the US Geological Survey and nation-wide environmental data layers derived from NASA s MODerate Resolution Imaging Spectroradiometer (MODIS). We demonstrate the utilization of the map by ranking the lower 48 US states (and the District of Columbia) based upon their absolute, as well as proportional, areas of highly likely and moderately likely habitat for Tamarisk. The interagency effort and modeling approach presented here could be applied to map other harmful species in the US and globally.

Morisette, Jeffrey T.↗