@conference {15544,
	title = {Efficient Kriging via Fast Matrix-Vector Products},
	booktitle = {Aerospace Conference, 2008 IEEE},
	year = {2008},
	month = {2008/03//},
	pages = {1 - 7},
	abstract = {Interpolating scattered data points is a problem of wide ranging interest. Ordinary kriging is an optimal scattered data estimator, widely used in geosciences and remote sensing. A generalized version of this technique, called cokriging, can be used for image fusion of remotely sensed data. However, it is computationally very expensive for large data sets. We demonstrate the time efficiency and accuracy of approximating ordinary kriging through the use of fast matrix-vector products combined with iterative methods. We used methods based on the fast Multipole methods and nearest neighbor searching techniques for implementations of the fast matrix-vector products.},
	keywords = {cokriging technique, fast matrix-vector products, fast multipole methods, geophysical techniques, image fusion, Interpolation, iterative methods, nearest neighbor searching, optimal scattered data estimator, Remote sensing, remotely sensed data, scattered data points, sensor fusion, time efficiency},
	doi = {10.1109/AERO.2008.4526433},
	author = {Memarsadeghi,N. and Raykar,V.C. and Duraiswami, Ramani and Mount, Dave}
}
@conference {15592,
	title = {Robust matching of wavelet features for sub-pixel registration of Landsat data},
	booktitle = {Geoscience and Remote Sensing Symposium, 2001. IGARSS {\textquoteright}01. IEEE 2001 International},
	volume = {2},
	year = {2001},
	month = {2001///},
	pages = {706 -708 vol.2 - 706 -708 vol.2},
	abstract = {For many Earth and space science applications, automatic geo-registration at sub-pixel accuracy has become a necessity. In this work, we are focusing on building an operational system, which will provide a sub-pixel accuracy registration of Landsat-5 and Landsat-7 data. The input to our registration method consists of scenes that have been geometrically and radiometrically corrected. Such preprocessed scenes are then geo-registered relative to a database of Landsat chips. The method assumes a transformation composed of a rotation and a translation, and utilizes rotation- and translation-invariant wavelets to extract image features that are matched using statistically robust feature matching and a partial Hausdorff distance metric. The registration process is described and results on four Landsat input scenes of the Washington, D.C., area are presented},
	keywords = {Feature extraction, geo-registration, geophysical measurement technique, geophysical signal processing, geophysical techniques, Hausdorff distance metric, image registration, infrared, IR, land surface, Landsat, Landsat-5, Landsat-7, multispectral remote sensing, robust feature matching, robust matching, sub pixel registration, subpixel accuracy, terrain mapping, visible, wavelet feature, wavelet method, Wavelet transforms},
	doi = {10.1109/IGARSS.2001.976609},
	author = {Le Moigne,J. and Netanyahu,N. S and Masek,J. G and Mount, Dave and Goward, S.N.}
}
@conference {17080,
	title = {Developing the next generation of Earth science data systems: the Global Land Cover Facility},
	booktitle = {Geoscience and Remote Sensing Symposium, 1999. IGARSS {\textquoteright}99 Proceedings. IEEE 1999 International},
	volume = {1},
	year = {1999},
	month = {1999///},
	pages = {616-618 vol.1 - 616-618 vol.1},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {A recent initiative by NASA has resulted in the formation of a federation of Earth science data partners. These Earth Science Information Partners (ESIPs) have been tasked with creating novel Earth science data products and services as well as distributing new and existing data sets to the Earth science community and the general public. The University of Maryland established its ESIP activities with the creation of the Global Land Cover Facility (GLCF). This joint effort of the Institute for Advanced Computer Studies (UMIACS) and the Department of Geography has developed an operational data archiving and distribution system aimed at advancing current land cover research efforts. The success of the GLCF is tied closely to assessing user needs as well. As the timely delivery of data products to the research community. This paper discusses the development and implementation of a web-based interface that allows users to query the authors{\textquoteright} data holdings and perform user requested processing tasks on demand. The GLCF takes advantage of a scaleable, high performance computing architecture for the manipulation of very large remote sensing data sets and the rapid spatial indexing of multiple format data types. The user interface has been developed with the cooperation of the Human-Computer Interaction Laboratory (HCIL) and demonstrates advances in spatial and temporal querying tools as well as the ability to overlay multiple raster and vector data sets. Their work provides one perspective concerning how critical earth science data may be handled in the near future by a coalition of distributed data centers},
	keywords = {Computer architecture, data archiving, data distribution system, Data systems, Distributed computing, Earth science data products, Earth science data system, ESIP, geographic information system, geographic information systems, Geography, geophysical measurement technique, geophysical signal processing, geophysical techniques, Geoscience, GIS, GLCF, Global Land Cover Facility, High performance computing, Indexing, information service, Information services, Institute for Advanced Computer Studies, land cover, NASA, next generation, PACS, Remote sensing, terrain mapping, UMIACS, University of Maryland, User interfaces, web-based interface},
	isbn = {0-7803-5207-6},
	doi = {10.1109/IGARSS.1999.773583},
	author = {Lindsay,F.E. and Townshend,J.R.G. and JaJa, Joseph F. and Humphries,J. and Plaisant, Catherine and Shneiderman, Ben}
}
