DocumentCode :
576220
Title :
Submerged macrophytes height estimation by echosounder data sample
Author :
da Silva Rotta, L.H. ; Imai, Nilton Nobuhiro
Author_Institution :
Postgrad. Course in Cartographic Sci., Sao Paulo State Univ., Presidente Prudente, Brazil
fYear :
2012
fDate :
22-27 July 2012
Firstpage :
808
Lastpage :
811
Abstract :
Traditional methods of submerged aquatic vegetation (SAV) survey last long and then, they are high cost. Optical remote sensing is an alternative, but it has some limitations in the aquatic environment. The use of echosounder techniques is efficient to detect submerged targets. Therefore, the aim of this study is to evaluate different kinds of interpolation approach applied on SAV sample data collected by echosounder. This study case was performed in a region of Uberaba River - Brazil. The interpolation methods evaluated in this work follow: Nearest Neighbor, Weighted Average, Triangular Irregular Network (TIN) and ordinary kriging. Better results were carried out with kriging interpolation. Thus, it is recommend the use of geostatistics for spatial inference of SAV from sample data surveyed with echosounder techniques.
Keywords :
geographic information systems; hydrological techniques; remote sensing; rivers; vegetation; Brazil; SAV sample data; Uberaba river; aquatic environment; echosounder data sample; echosounder techniques; geographic information systems; interpolation methods; kriging interpolation; optical remote sensing; ordinary kriging; submerged aquatic vegetation survey; submerged macrophytes height estimation; triangular irregular network; Artificial neural networks; Estimation; Interpolation; Remote sensing; Software; Tin; Vegetation mapping; Geographic Information Systems; Interpolation; Rivers; Submerged aquatic vegetation; Underwater acoustics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
ISSN :
2153-6996
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2012.6351439
Filename :
6351439
Link To Document :
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