Multi-Band Bathymetry Mapping with Spiking Neuron Anomaly Detection
نویسندگان
چکیده
The developed method extracts bathymetry distributions from multiple satellite image bands. automated remote sensing function is sparsely coded and combines spiking neural net anomaly filtration, spline, multi-band fittings. Survey data were used to identify an activation threshold, decay rate, spline fittings, weighting factors. Errors computed for remotely sensed Landsat images. Multi-band fittings achieved average error of 25.3 cm. This proved sufficiently accurate automatically extract shorelines eliminate land areas in mapping.
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ژورنال
عنوان ژورنال: Water
سال: 2022
ISSN: ['2073-4441']
DOI: https://doi.org/10.3390/w14050810