A Semi-Automated Object-Based Gully Networks Detection Using Different Machine Learning Models: A Case Study of Bowen Catchment, Queensland, Australia

A Semi-Automated Object-Based Gully Networks Detection Using Different Machine Learning Models: A Case Study of Bowen Catchment, Queensland, Australia

Gully erosion is a dominant source of sediment and particulates to the Great Barrier Reef (GBR) World Heritage area. We selected the Bowen catchment, a tributary of the Burdekin Basin, as our area of study; the region is associated with a high density of gully networks. We aimed to use a semi-automa...

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Bibliographic Details
Main Authors: Hejar Shahabi, Ben Jarihani, Sepideh Tavakkoli Piralilou, David Chittleborough, Mohammadtaghi Avand, Omid Ghorbanzadeh
Format: Article
Language:English
Published: MDPI AG 2019-11-01
Series:Sensors
Subjects:
geographic object-based image analysis (geobia)
gully erosion
optimal scale detection
stacking model
bowen catchment
Online Access:https://www.mdpi.com/1424-8220/19/22/4893

Internet

https://www.mdpi.com/1424-8220/19/22/4893

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