Application of artificial neural computation in topex waveform data: A case study in water ratio regression

Author

Zhang, B. ; Schwartz, F.W. ; Tong, D.

Author_Institution

Nat. Drought Mitigation Center, Lincoln, NE

fYear

2008

fDate

14-16 Aug. 2008

Firstpage

232

Lastpage

238

Abstract

Using the TOPEX radar altimeter for land cover studies has been of great interest due to the TOPEX near global coverage and its consistent availability of waveform data for about one and a half decades from 1992 to 2005. However, the complexity of the TOPEX Sensor Data Records (SDRs) makes the recognition of the radar echoes particularly difficult. In this paper, artificial neural computation as one of the most powerful algorithms in pattern recognition is investigated for water ratio assessment over Lake of the Woods area using TOPEX reflected radar signals. Results demonstrate that neural networks have the capability in identifying water proportion from the TOPEX radar information, controlling the predicted errors in a reasonable range.

Keywords

echo; geophysical signal processing; hydrological techniques; lakes; neural nets; radar altimetry; radar detection; radar signal processing; regression analysis; remote sensing by radar; Lake of the Woods area; TOPEX radar altimeter; TOPEX radar information; TOPEX reflected radar signals; TOPEX sensor data records; TOPEX waveform data; artificial neural computation; neural networks; radar echoes recognition; water ratio assessment; water ratio regression; Hydrology; Lakes; Land surface; Machine learning algorithms; Microwave sensors; Oceans; Pattern recognition; Satellites; Sea surface; Spaceborne radar;

fLanguage

English

Publisher

ieee

Conference_Titel

Cognitive Informatics, 2008. ICCI 2008. 7th IEEE International Conference on

Conference_Location

Stanford, CA

Print_ISBN

978-1-4244-2538-9

Type

conf

DOI

10.1109/COGINF.2008.4639173

Filename

4639173