New Application Paradigm Of Time Series SAR Data For Sugarcane Mapping
Author:
Affiliation:
1. Chinese Academy of Sciences University of Chinese Academy of Sciences,Shenzhen Institute of Advanced Technology
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10640349/10640352/10641461.pdf?arnumber=10641461
Reference10 articles.
1. Mapping sugarcane plantation dynamics in Guangxi, China, by time series Sentinel-1, Sentinel-2 and Landsat images
2. Early Season Mapping of Sugarcane by Applying Machine Learning Algorithms to Sentinel-1A/2 Time Series Data: A Case Study in Zhanjiang City, China
3. Development of a Phenology-Based Method for Identifying Sugarcane Plantation Areas in China Using High-Resolution Satellite Datasets
4. Deriving Phenological Metrics from Landsat-OLI for Sugarcane Crop Type Mapping: A Case Study in North India
5. Sugarcane crop classification using time series analysis of optical and SAR sentinel images: a deep learning approach
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