Machine Learning for Gully Feature Extraction Based on a Pan-Sharpened Multispectral Image: Multiclass vs. Binary Approach

Machine Learning for Gully Feature Extraction Based on a Pan-Sharpened Multispectral Image: Multiclass vs. Binary Approach

Gullies reduce both the quality and quantity of productive land, posing a serious threat to sustainable agriculture, hence, food security. Machine Learning (ML) algorithms are essential tools in the identification of gullies and can assist in strategic decision-making relevant to soil conservation....

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Bibliographic Details
Main Authors: Kwanele Phinzi, Dávid Abriha, László Bertalan, Imre Holb, Szilárd Szabó
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:ISPRS International Journal of Geo-Information
Subjects:
linear discriminant analysis
random forest
support vector machine
image classification
erosion
Online Access:https://www.mdpi.com/2220-9964/9/4/252

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