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
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