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Publications (3)0 Total impact

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    ABSTRACT: Accurate and reliable information about land cover and land use is essential to carbon cycle and climate change modeling. While historical regional-to-global scale land cover and land use data products had been produced by AVHRR and MSS/TM, this task has been advanced by sensors such as MODIS and ETM since the latter 1990s. While the accuracies and reliabilities of these data products have been improved, there have been reports from the modeling community that additional work is needed to reduce errors so that the uncertainties associated with the global carbon cycle and climate change modeling can be addressed. Remotely sensed data collected in different wavelength regions, at different viewing geometries, usually provide complementary information. Their combination has the potential to enhance remote sensing capabilities in discriminating important land cover components. In this paper, we studied multi-angle data fusion, and optical-SAR data fusion for land cover classification at regional spatial scale in the temperate forests of the eastern United States. Data from EOS-MISR, Landsat-ETM+ and RadarSat-SAR were used. The results showed significantly improved land cover classification accuracy when using the data fusion approach. These results may benefit future land cover products for global change research.
    Advances in Techniques for Analysis of Remotely Sensed Data, 2003 IEEE Workshop on; 11/2003
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    ABSTRACT: Dust storms present environmental risks and affect the climate. They have worsened in the Mediterranean and East Asia regions over the last decade due to massive deforestation and increased droughts. Storms can travel over large parts of the Earth, in Asia, Africa, even affecting North America and Europe. Moreover dust storms are related to precipitation, soil moisture, land use/land cover practices, and other human activities. This work is a continuation of previous research in which we analyzed several remote sensing instruments capabilities in monitoring dust storms. We introduce the usage of the Multi-angle Imaging SpectroRadiometer (MISR) and TRMM Microwave Imager (TMI) as an optical and microwave combination in enhancing dust storm detection.
    Geoscience and Remote Sensing Symposium, 2003. IGARSS '03. Proceedings. 2003 IEEE International; 08/2003
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    ABSTRACT: Virginia Access (VAccess) is a regional, remote sensing and Geographical Information Sciences project among several educational institutions. It is a prototype for regional projects in other states and other countries, and is funded by NASA's applications program. The user communities VAccess serves are the Commonwealth of Virginia and State of Maryland, local and regional users represented in a Technical Advisory Committee. Remote sensing data include global NASA and NOAA data tailored for regional applications as well as high-resolution multispectral (Landsat, MODIS, etc.), hyperspectral, LIDAR and SAR data sets. Broad beam LIDAR technology can provide canopy structure as well as other information for environmental concerns such as the state of wetlands. The data information system is based on a distributed architecture to serve remote sensing and GIS data to a variety of users via the WWW. Several remote sensing and GIS-based environmental and Earth systems science applications projects are discussed here, including flood and fire hazard mitigation, forestry, land use/land cover and epidemiology projects; as well as innovative data fusion, data access and analysis and various tools serving the users and their applications.
    Proc SPIE 01/2003;