Improving the Accuracy of Land Use and Land Cover Classification of Landsat Data in an Agricultural Watershed

Improving the Accuracy of Land Use and Land Cover Classification of Landsat Data in an Agricultural Watershed

Classification of remotely sensed imagery for reliable land use and land cover (LULC) remains a challenge in areas where spectrally similar LULC features occur. For example, bare soils of harvested crop fields in agricultural watersheds exhibit spectral characteristics similar to high-intensity deve...

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Bibliographic Details
Main Authors: Padmanava Dash, Scott L. Sanders, Prem Parajuli, Ying Ouyang
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:Remote Sensing
Subjects:
land use and land cover
classification
agricultural watershed
maximum likelihood
support vector machine
random forest
Online Access:https://www.mdpi.com/2072-4292/15/16/4020

Internet

https://www.mdpi.com/2072-4292/15/16/4020

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