Miner: A suit of classifiers for spatial, temporal, ancillary, and remote sensing data mining

Ranga Raju Vatsavai, Shashi Shekhar, Thomas E. Burk, Budhendra Bhaduri

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Thematic classification of multi-spectral remotely sensed imagery for large geographic regions requires complex algorithms and feature selection techniques. Traditional statistical classifiers rely exclusively on spectral characteristics, but thematic classes are often spectrally overlapping. The spectral response distributions of thematic classes are dependent on many factors including terrain, slope, aspect, soil type, and atmospheric conditions present during the image acquisition. With the availability of geo-spatial databases, it is possible to exploit the knowledge derived from these ancillary geo-spatial databases to improve the classification accuracies. However, it is not easy to incorporate this additional knowledge into traditional statistical classification methods. On the other hand, knowledgebased and neural network classifiers can readily incorporate these spatial databases, but these systems are often complex to train and their accuracy is only slightly better than statistical classifiers. In this paper we present a new suit of classifiers developed through NASA funding, which addresses many of these problems and provide a framework for mining multi-spectral and temporal remote sensing images guided by geo-spatial databases.

Original languageEnglish (US)
Title of host publicationProceedings - International Conference on Information Technology
Subtitle of host publicationNew Generations, ITNG 2008
Pages801-806
Number of pages6
DOIs
StatePublished - May 27 2008
EventInternational Conference on Information Technology: New Generations, ITNG 2008 - Las Vegas, NV, United States
Duration: Apr 7 2008Apr 9 2008

Publication series

NameProceedings - International Conference on Information Technology: New Generations, ITNG 2008

Other

OtherInternational Conference on Information Technology: New Generations, ITNG 2008
CountryUnited States
CityLas Vegas, NV
Period4/7/084/9/08

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    Vatsavai, R. R., Shekhar, S., Burk, T. E., & Bhaduri, B. (2008). Miner: A suit of classifiers for spatial, temporal, ancillary, and remote sensing data mining. In Proceedings - International Conference on Information Technology: New Generations, ITNG 2008 (pp. 801-806). [4492581] (Proceedings - International Conference on Information Technology: New Generations, ITNG 2008). https://doi.org/10.1109/ITNG.2008.243