A spatiotemporal collaborative approach for precise crop planting structure mapping based on multi-source remote-sensing data-Reference-Cited by-同舟云学术

A spatiotemporal collaborative approach for precise crop planting structure mapping based on multi-source remote-sensing data

Published:2023-06-19 Issue: Volume: Page:1-17
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Sun Yingwei¹,Yao Na²,Luo Jiancheng³,Leng Pei¹,Liu Xiangyang¹

Affiliation:

1. Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China

2. Institute of Rural Development and Construction, Academy of Agricultural Planning and Engineering, Beijing, China

3. State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

Funder

National Natural Science Foundation of China

China Postdoctoral Fund

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2023.2217985

Reference39 articles.

1. Sentinel SAR-optical fusion for crop type mapping using deep learning and Google Earth Engine

2. A new phenology-based method for mapping wheat and barley using time-series of Sentinel-2 images

3. Optical time series for the separation of land cover types with similar spectral signatures: cocoa agroforest and forest

4. Mapping of crop types and crop sequences with combined time series of Sentinel-1, Sentinel-2 and Landsat 8 data for Germany

5. Combination of Time Series of L-, C-, and X-Band SAR Images for Land Cover and Crop Classification

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