DocumentCode
1947100
Title
Use of high resolution space imagery to monitor the abundance, distribution, and migration patterns of marine mammal populations
Author
Abileah, Ron
Author_Institution
SRI Int., Menlo Park, CA, USA
Volume
3
fYear
2001
fDate
2001
Firstpage
1381
Abstract
Aerial surveys are routinely used to study marine mammal populations. The resolution of imagery from commercial satellites has improved to the point where individual marine mammals can be detected. It may therefore be possible to perform remote sensing of marine mammal populations from space. This paper presents an initial assessment of detectability. A simple signal and noise model is developed to predict the signal-to-noise ratio (SNR) for a whale-like target. SNR is calculated for three cases: detection limited by sensor quantization noise ("best case"); detection in real noise, using one spectral band image; and detection in real noise, using a two-band noise reduction technique. An Ikonos satellite image was used for a realistic noise spectrum. The calculations show that a canonical target of length =14 in and average spectral reflectivity can be detected up to a depth of 24 m. Thus a case can be made for using satellites to monitor marine mammal abundance and geographical distributions, and to observe migratory patterns in remote areas
Keywords
noise; oceanographic techniques; remote sensing; zoology; Ikonos satellite image; abundance; geographical distributions; high resolution space imagery; marine mammal populations; migration patterns; migratory patterns; real noise; remote sensing; sensor quantization noise; signal-to-noise ratio; two-band noise reduction technique; whale-like target; Image resolution; Image sensors; Noise reduction; Predictive models; Quantization; Remote monitoring; Satellites; Signal detection; Signal resolution; Signal to noise ratio;
fLanguage
English
Publisher
ieee
Conference_Titel
OCEANS, 2001. MTS/IEEE Conference and Exhibition
Conference_Location
Honolulu, HI
Print_ISBN
0-933957-28-9
Type
conf
DOI
10.1109/OCEANS.2001.968035
Filename
968035
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