Early Season Mapping of Sugarcane by Applying Machine Learning Algorithms to Sentinel-1A/2 Time Series Data: A Case Study in Zhanjiang City, China (2019)
Attributed to:
Regional crop monitoring and assessment with quantitative remote sensing and data assimilation
funded by
Newton Fund
Abstract
No abstract provided
Bibliographic Information
Digital Object Identifier: http://dx.doi.org/10.3390/rs11070861
Publication URI: http://dx.doi.org/10.3390/rs11070861
Type: Journal Article/Review
Parent Publication: Remote Sensing
Issue: 7