Macrobenthos habitat potential mapping using GIS-based artificial neural network models
作者： Saro Lee , Inhye Park , Bon Joo Koo , Joo-Hyung Ryu , Jong-Kuk Choi
DOI: 10.1016/J.MARPOLBUL.2012.10.023
关键词: Environmental science 、 Environmental monitoring 、 Invertebrate 、 Macrobenthos 、 Hydrology 、 Artificial neural network 、 Spatial database 、 Habitat 、 Benthos 、 Geographic information system
摘要: This paper proposes and tests a method of producing macrobenthos habitat potential maps in Hwangdo tidal flat, Korea based on an artificial neural network. Samples were collected during field work, eight control factors compiled as spatial database from remotely sensed data GIS analysis. The produced using network model. Macrobenthos made for Macrophthalmus dilatatus, Cerithideopsilla cingulata, Armandia lanceolata. validated by compared with the surveyed locations. A strong correlation between species locations was revealed. validation result showed average accuracies 74.9%, 78.32%, 73.27% M. C. A. lanceolata, respectively. GIS-based model combined remote sensing techniques is effective tool mapping areas flats.
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