OPTIMIZING CLASSIFICATION ACCURACY OF ESTUARINE MACROPHYTES: BY COMBINING SPATIAL AND PHYSICS-BASED IMAGE ANALYSIS

被引：2

作者：

Anstee, J. M. ^{[1
]}

Botha, E. J. ^{[1
]}

Williams, R. J. ^{[2
]}

Dekker, A. G. ^{[1
]}

Brando, V. E. ^{[1
]}

机构：

[1] CSIRO Land & Water, Canberra, ACT, Australia

[2] Ind & Invest NSW, Cronulla, NSW, Australia

来源：

2010 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2010年

关键词：

D O I：

10.1109/IGARSS.2010.5649995

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

Accurate baseline data of macrophyte extent is vital in estuarine monitoring. Previous techniques have often been laborious and subjective, while a purely empirical methodology often precludes transferring the method to other systems. The development of objective physics-based inversions models allows for the retrieval of; water depth, substratum composition and concentration of the water constituents from hyperspectral imagery. This paper describes approaches required to apply this method to QuickBird multispectral data from 2003 and 2008 over an estuarine lake. The addition of the inversion models quality control, improved the classification accuracy.

引用

页码：1367 / 1370

页数：4

共 17 条

[1]

[Anonymous], FISHERIES B DEP AGR

[2]

[Anonymous], NSW COMPREHENSIVE CO

[3] Mapping the distribution of coral reefs and associated sublittoral habitats in Pacific Panama: a comparison of optical satellite sensors and classification methodologies [J].