Evaluation of Three Deep Learning Models for Early Crop Classification Using Sentinel-1A Imagery Time Series—A Case Study in Zhanjiang, China

Evaluation of Three Deep Learning Models for Early Crop Classification Using Sentinel-1A Imagery Time Series—A Case Study in Zhanjiang, China

Timely and accurate estimation of the area and distribution of crops is vital for food security. Optical remote sensing has been a key technique for acquiring crop area and conditions on regional to global scales, but great challenges arise due to frequent cloudy days in southern China. This makes o...

Full description

Bibliographic Details
Main Authors: Hongwei Zhao, Zhongxin Chen, Hao Jiang, Wenlong Jing, Liang Sun, Min Feng
Format: Article
Language:English
Published: MDPI AG 2019-11-01
Series:Remote Sensing
Subjects:
early crop classification
one-dimensional cnns
long short-term memory
gated recurrent unit
incremental classification
rnns
synthetic aperture radar
sentinel-1a
Online Access:https://www.mdpi.com/2072-4292/11/22/2673

Internet

https://www.mdpi.com/2072-4292/11/22/2673

Similar Items