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Showing papers by "Eric Vermote published in 2008"


Journal ArticleDOI
23 May 2008-Science
TL;DR: Free imagery will enable reconstruction of the history of Earth's surface back to 1972, chronicling both anthropogenic and natural changes during a time when the authors' population doubled and the impacts of climate change became noticeable.
Abstract: ![Figure][1] Free image. This Landsat 5 image of the southeastern corner of the Black Sea is part of the general U.S. archive that will be accessible for free under the new USGS policy. CREDIT: BOSTON UNIVERSITY CENTER FOR REMOTE SENSING We are entering a new era in the Landsat Program, the oldest and most venerable of our Earth-observing satellite programs. With little fanfare, the U.S. Geological Survey (USGS) has begun providing imagery for free over the Internet. Throughout the history of the Landsat Program, the cost and access to imagery has always limited our ability to study our planet and the way it is changing. Beginning with a pilot program to provide “Web-enabled” access to Landsat 7 images of the United States that were collected between 2003 and this year, the USGS now plans to provide top-quality image products for free upon request for the entire U.S. archive, including over 2 million images back to Landsat 1 (1972) [for details and schedules, see ([1][2])]. The release by NASA and the USGS in January 2008 of a new Landsat Data Distribution Policy ([2][3]) was a key step to this goal. Free imagery will enable reconstruction of the history of Earth's surface back to 1972, chronicling both anthropogenic and natural changes during a time when our population doubled and the impacts of climate change became noticeable. The Landsat Science Team: 1. 1.[↵][4]USGS Technical Announcement ([http://landsat.usgs.gov/images/squares/USGS\_Landsat\_Imagery_Release.pdf][5]). 2. 2.[↵][6]Landsat Missions ([http://ldcm.usgs.gov/pdf/Landsat\_Data\_Policy.pdf][7]). [1]: pending:yes [2]: #ref-1 [3]: #ref-2 [4]: #xref-ref-1-1 "View reference 1. in text" [5]: http://landsat.usgs.gov/images/squares/USGS_Landsat_Imagery_Release.pdf [6]: #xref-ref-2-1 "View reference 2. in text" [7]: http://ldcm.usgs.gov/pdf/Landsat_Data_Policy.pdf

785 citations


Journal ArticleDOI
TL;DR: In this paper, the authors describe the land surface reflectance product (MOD09), the current Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric correction (AC) algorithm and its recent updates, and provide the evaluation of the algorithm performance and product quality.
Abstract: [1] This paper briefly describes the land surface reflectance product (MOD09), the current Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric correction (AC) algorithm and its recent updates, and provides the evaluation of the algorithm performance and product quality. The accuracy of the AC algorithm has been significantly improved owing to the use of the accurate Second Simulation of a Satellite Signal in the Solar Spectrum, Vector (6SV) radiative transfer code and a better retrieval of aerosol properties by a refined internal aerosol inversion algorithm. The Collection 5 MOD09 surface reflectance product computed by the improved AC algorithm was analyzed for the year of 2003 through the comparison with a reference data set created with the help of Aerosol Robotic Network (AERONET) measurements and the 6SV code simulations. In general, the MOD09 product demonstrated satisfactory quality in all used MODIS bands except for band 3 (470 nm), which is used for aerosol inversion. The impact of uncertainties in MOD09 upon the downstream product, such as vegetation indices and albedo, was also evaluated.

302 citations


Journal ArticleDOI
TL;DR: Four atmospheric radiative transfer codes incorporated into different satellite data processing algorithms are compared, namely, 6SV1.1 (second simulation of a satellite signal in the solar spectrum, vector, version 1.1), RT3 (radiative transfer), MODTRAN (moderate resolution atmospheric transmittance and radiance code), and SHARM (spherical harmonics).
Abstract: Results are summarized for a scientific project devoted to the comparison of four atmospheric radiative transfer codes incorporated into different satellite data processing algorithms, namely, 6SV1.1 (second simulation of a satellite signal in the solar spectrum, vector, version 1.1), RT3 (radiative transfer), MODTRAN (moderate resolution atmospheric transmittance and radiance code), and SHARM (spherical harmonics). The performance of the codes is tested against well-known benchmarks, such as Coulson's tabulated values and a Monte Carlo code. The influence of revealed differences on aerosol optical thickness and surface reflectance retrieval is estimated theoretically by using a simple mathematical approach. All information about the project can be found at http://rtcodes.ltdri.org.

137 citations


Journal ArticleDOI
TL;DR: In this paper, the authors report on satellite observations of the vegetation greening that occurred at the subcontinent scale almost 10 days earlier than the average over the past three decades and show that there is a strong negative temporal correlation between the February-April mean temperature and the start of growth date.
Abstract: [1] Europe has experienced a wide scale warming over the past decades and climate simulations predict further warming and changes in precipitation patterns during the 21st century. The winter of 2006–2007 has been exceptionally mild with averaged temperatures that may become the norm during the second half of the 21st century. Here we report on satellite observations of the vegetation greening that occurred at the subcontinent scale almost 10 days earlier than the average over the past three decades. Even at the relatively coarse resolution of the satellite data, which mixes several vegetation types, there is a strong negative temporal correlation between the February–April mean temperature and the start of growth date. The western Europe mean vegetation onset sensitivity is −3.9 days per degree of temperature, and is mainly driven by crops and grasslands, with a biome-specific sensitivity of −4.7 days/°C. For forested biomes, onset anomalies are better correlated to the March–May mean temperature, with a sensitivity of −3.6 days/°C. Based upon the satellite data, there is no consistent indication that a lack of cold days in the winter 2006–2007 had any effect in delaying the vegetation onset.

35 citations