Deep Learning in the Mapping of Agricultural Land Use Using Sentinel-2 Satellite Data

Deep Learning in the Mapping of Agricultural Land Use Using Sentinel-2 Satellite Data

Continuous observation and management of agriculture are essential to estimate crop yield and crop failure. Remote sensing is cost-effective, as well as being an efficient solution to monitor agriculture on a larger scale. With high-resolution satellite datasets, the monitoring and mapping of agricu...

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Bibliographic Details
Main Authors:	Gurwinder Singh, Sartajvir Singh, Ganesh Sethi, Vishakha Sood
Format:	Article
Language:	English
Published:	MDPI AG 2022-11-01
Series:	Geographies
Subjects:	ENVINet5-based deep learning agriculture land random forest Sentinel-2 satellite data
Online Access:	https://www.mdpi.com/2673-7086/2/4/42

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