Towards improved land use mapping of irrigated croplands: performance assessment of different image classification algorithms and approaches

Towards improved land use mapping of irrigated croplands: performance assessment of different image classification algorithms and approaches

Accurate agricultural land use (LU) map is essential for many agro-environmental applications. With advances in technology, object-based image classification and non-parametric machine learning algorithms evolved. Still, no particular method has universal applicability. This paper compares robust no...

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Bibliographic Details
Main Authors: Amit Kumar Basukala, Carsten Oldenburg, Jürgen Schellberg, Murodjon Sultanov, Olena Dubovyk
Format: Article
Language:English
Published: Taylor & Francis Group 2017-01-01
Series:European Journal of Remote Sensing
Subjects:
Land use (LU) mapping
random forest
support vector machine
maximum likelihood
field-based
Uzbekistan
Online Access:http://dx.doi.org/10.1080/22797254.2017.1308235

Internet

http://dx.doi.org/10.1080/22797254.2017.1308235

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