Eric F. Vermote

AERONET-a federated instrument network and data archive for aerosol Characterization

Abstract The concept and description of a remote sensing aerosol monitoring network initiated by NASA, developed to support NASA, CNES, and NASDA’s Earth satellite systems under the name AERONET and expanded by national and international collaboration, is described. Recent development of weather-resistant automatic sun and sky scanning spectral radiometers enable frequent measurements of atmospheric aerosol optical properties and precipitable water at remote sites. Transmission of automatic measurements via the geostationary satellites GOES and METEOSATS’ Data Collection Systems allows reception and processing in near real-time from approximately 75% of the Earth’s surface and with the expected addition of GMS, the coverage will increase to 90% in 1998. NASA developed a UNIX-based near real-time processing, display and analysis system providing internet access to the emerging global database. Information on the system is available on the project homepage, http://spamer.gsfc.nasa.gov . The philosophy of an open access database, centralized processing and a user-friendly graphical interface has contributed to the growth of international cooperation for ground-based aerosol monitoring and imposes a standardization for these measurements. The system’s automatic data acquisition, transmission, and processing facilitates aerosol characterization on local, regional, and global scales with applications to transport and radiation budget studies, radiative transfer-modeling and validation of satellite aerosol retrievals. This article discusses the operation and philosophy of the monitoring system, the precision and accuracy of the measuring radiometers, a brief description of the processing system, and access to the database.

The MODIS Aerosol Algorithm, Products, and Validation

The Moderate Resolution Imaging Spectroradiometer (MODIS) aboard both NASA’s Terra and Aqua satellites is making near-global daily observations of the earth in a wide spectral range (0.41–15 m). These measurements are used to derive spectral aerosol optical thickness and aerosol size parameters over both land and ocean. The aerosol products available over land include aerosol optical thickness at three visible wavelengths, a measure of the fraction of aerosol optical thickness attributed to the fine mode, and several derived parameters including reflected spectral solar flux at the top of the atmosphere. Over the ocean, the aerosol optical thickness is provided in seven wavelengths from 0.47 to 2.13 m. In addition, quantitative aerosol size information includes effective radius of the aerosol and quantitative fraction of optical thickness attributed to the fine mode. Spectral irradiance contributed by the aerosol, mass concentration, and number of cloud condensation nuclei round out the list of available aerosol products over the ocean. The spectral optical thickness and effective radius of the aerosol over the ocean are validated by comparison with two years of Aerosol Robotic Network (AERONET) data gleaned from 132 AERONET stations. Eight thousand MODIS aerosol retrievals collocated with AERONET measurements confirm that one standard deviation of MODIS optical thickness retrievals fall within the predicted uncertainty of 0.03 0.05 over ocean and 0.05 0.15 over land. Two hundred and seventy-one MODIS aerosol retrievals collocated with AERONET inversions at island and coastal sites suggest that one standard deviation of MODIS effective radius retrievals falls within reff 0.11 m. The accuracy of the MODIS retrievals suggests that the product can be used to help narrow the uncertainties associated with aerosol radiative forcing of global climate.

An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data

Daily daytime Advanced Very High Resolution Radiometer (AVHRR) 4‐km global area coverage data have been processed to produce a Normalized Difference Vegetation Index (NDVI) 8‐km equal‐area dataset from July 1981 through December 2004 for all continents except Antarctica. New features of this dataset include bimonthly composites, NOAA‐9 descending node data from August 1994 to January 1995, volcanic stratospheric aerosol correction for 1982–1984 and 1991–1993, NDVI normalization using empirical mode decomposition/reconstruction to minimize varying solar zenith angle effects introduced by orbital drift, inclusion of data from NOAA‐16 for 2000–2003 and NOAA‐17 for 2003–2004, and a similar dynamic range with the MODIS NDVI. Two NDVI compositing intervals have been produced: a bimonthly global dataset and a 10‐day Africa‐only dataset. Post‐processing review corrected the majority of dropped scan lines, navigation errors, data drop outs, edge‐of‐orbit composite discontinuities, and other artefacts in the composite NDVI data. All data are available from the University of Maryland Global Land Cover Facility (http://glcf.umiacs.umd.edu/data/gimms/).

Operational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer

Daily distribution of the aerosol optical thickness and columnar mass concentration will be derived over the continents, from the EOS moderate resolution imaging spectroradiometer (MODIS) using dark land targets. Dark land covers are mainly vegetated areas and dark soils observed in the red and blue channels; therefore the method will be limited to the moist parts of the continents (excluding water and ice cover). After the launch of MODIS the distribution of elevated aerosol concentrations, for example, biomass burning in the tropics or urban industrial aerosol in the midlatitudes, will be continuously monitored. The algorithm takes advantage of the MODIS wide spectral range and high spatial resolution and the strong spectral dependence of the aerosol opacity for most aerosol types that result in low optical thickness in the mid-IR (2.1 and 3.8 pm). The main steps of the algorithm are (1) identification of dark pixels in the mid-IR; (2) estimation of their reflectance at 0.47 and 0.66 pm; and (3) derivation of the optical thickness and mass concentration of the accumulation mode from the detected radiance. To differentiate between dust and aerosol dominated by accumulation mode particles, for example, smoke or sulfates, ratios of the aerosol path radiance at 0.47 and 0.66 pm are used. New dynamic aerosol models for biomass burning aerosol, dust and aerosol from industrial/urban origin, are used to determine the aerosol optical properties used in the algorithm. The error in the retrieved aerosol optical thicknesses, r,, is expected to be AT, = 0.05 5 0.27,. Daily values are stored on a resolution of 10 X 10 pixels (1 km nadir resolution). Weighted and gridded 8-day and monthly composites of the optical thickness, the aerosol mass concentration and spectral radiative forcing are generated for selected scattering angles to increase the accuracy. The daily aerosol information over land and oceans (Tunr& et al., this issue), combined with continuous aerosol remote sensing from the ground, will be used to study aerosol climatology, to monitor the sources and sinks of specific aerosol types, and to study the interaction of aerosol with water vapor and clouds and their radiative forcing of climate. The aerosol information will also be used for atmospheric corrections of remotely sensed surface reflectance. In this paper, examples of applications and validations are provided.

The Moderate Resolution Imaging Spectroradiometer (MODIS): land remote sensing for global change research

The first Moderate Resolution Imaging Spectroradiometer (MODIS) instrument is planned for launch by NASA in 1998. This instrument will provide a new and improved capability for terrestrial satellite remote sensing aimed at meeting the needs of global change research. The MODIS standard products will provide new and improved tools for moderate resolution land surface monitoring. These higher order data products have been designed to remove the burden of certain common types of data processing from the user community and meet the more general needs of global-to-regional monitoring, modeling, and assessment. The near-daily coverage of moderate resolution data from MODIS, coupled with the planned increase in high-resolution sampling from Landsat 7, will provide a powerful combination of observations. The full potential of MODIS will be realized once a stable and well-calibrated time-series of multispectral data has been established. In this paper the proposed MODIS standard products for land applications are described along with the current plans for data quality assessment and product validation.

A Landsat surface reflectance dataset for North America, 1990-2000

The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center has processed and released 2100 Landsat Thematic Mapper and Enhanced Thematic Mapper Plus surface reflectance scenes, providing 30-m resolution wall-to-wall reflectance coverage for North America for epochs centered on 1990 and 2000. This dataset can support decadal assessments of environmental and land-cover change, production of reflectance-based biophysical products, and applications that merge reflectance data from multiple sensors [e.g., the Advanced Spaceborne Thermal Emission and Reflection Radiometer, Multiangle Imaging Spectroradiometer, Moderate Resolution Imaging Spectroradiometer (MODIS)]. The raw imagery was obtained from the orthorectified Landsat GeoCover dataset, purchased by NASA from the Earth Satellite Corporation. Through the LEDAPS project, these data were calibrated, converted to top-of-atmosphere reflectance, and then atmospherically corrected using the MODIS/6S methodology. Initial comparisons with ground-based optical thickness measurements and simultaneously acquired MODIS imagery indicate comparable uncertainty in Landsat surface reflectance compared to the standard MODIS reflectance product (the greater of 0.5% absolute reflectance or 5% of the recorded reflectance value). The rapid automated nature of the processing stream also paves the way for routine high-level products from future Landsat sensors.

An overview of MODIS land data processing and product status

Data from the first Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on the NASA Terra Platform are being used to provide a new generation of land data products in support of the National Aeronautics and Space Administration (NASA)s Earth Science Enterprise, global change research and natural resource management. The MODIS products include global data sets heretofore unavailable, derived from new moderate resolution spectral bands with spatial resolutions of 250 m to 1 km. A partnership between Science Team members and the MODIS Science Data Support Team is producing data sets of unprecedented volume and number for the land research and applications. This overview paper provides a summary of the instrument performance and status, the data production system, the products, their status and availability for land studies.

Atmospheric correction of MODIS data in the visible to middle infrared: first results

The MODIS instrument provides major advances in moderate resolution earth observation. Improved spatial resolution for land observation at 250 and 500 m and improved spectral band placement provide new remote sensing opportunities. NASA has invested in the development of improved algorithms for MODIS, which will provide new data sets for global change research. Surface reflectance is one of the key products from MODIS and is used in developing several higher-order land products. The surface reflectance algorithm builds on the heritage of the Advanced Very High Resolution Radiometer (AVHRR) and SeaWiFS algorithms, taking advantage of the new sensing capabilities of MODIS. Atmospheric correction by the removal of water vapor and aerosol effects provides improvements over previous coarse resolution products and the basis for a new time-series, which will extend through to the NPOESS generation imagers. This paper summarizes the first evaluation of the MODIS surface reflectance product accuracy, in comparison with other data products and in the context of the MODIS instrument performance since launch. The MODIS surface reflectance product will provide an important time-series data set for quantifying global environmental change.

Atmospheric correction of visible to middle‐infrared EOS‐MODIS data over land surfaces: Background, operational algorithm and validation

The NASA moderate resolution imaging spectroradiometer (MODIS) instrument will provide a global and improved source of information for the study of land surfaces with a spatial resolution of up to 250 m. Prior to the derivation of various biophysical parameters based on surface reflectances, the top of the atmosphere signals need to be radiometrically calibrated and corrected for atmospheric effects. The present paper describes in detail the state of the art techniques that will be used for atmospheric correction of MODIS bands 1 through 7, centered at 648, 858, 470, 555, 1240, 1640, and 2130 nm, respectively. Previous operational correction schemes have assumed a standard atmosphere with zero or constant aerosol loading and a uniform, Lambertian surface. The MODIS operational atmospheric correction algorithm, reported here, uses aerosol and water vapor information derived from the MODIS data, corrects for adjacency effects and takes into account the directional properties of the observed surface. This paper also describes the operational implementation of these techniques and its optimization. The techniques are applied to remote sensing data from the Landsat Thematic Mapper (TM), the NOAA advanced very high resolution radiometer (AVHRR), and the MODIS airborne simulator (MAS) and validated against ground-based measurements from the Aerosol Robotic Network (AERONET).

MODIS land data storage, gridding, and compositing methodology: Level 2 grid

The methodology used to store a number of the Moderate Resolution Imaging Spectroradiometer (MODIS) land products is described. The approach has several scientific and data processing advantages over conventional approaches used to store remotely sensed data sets and may be applied to any remote-sensing data set in which the observations are geolocated to subpixel accuracy. The methodology will enable new algorithms to be more accurately developed because important information about the intersection between the sensor observations and the output grid cells are preserved. The methodology will satisfy the very different needs of the MODIS land product generation algorithms, allow sophisticated users to develop their own application-specific MODIS land data sets, and enable efficient processing and reprocessing of MODIS land products. A generic MODIS land gridding and compositing algorithm that takes advantage of the data storage structure and enables the exploitation of multiple observations of the surface more fully than conventional approaches is described. The algorithms are illustrated with simulated MODIS data, and the practical considerations of increased data storage are discussed.