Identification of tea plantations in typical plateau areas with the combination of Sentinel-1/2 optical and radar remote sensing data based on feature selection algorithm-Reference-Cited by-同舟云学术

Identification of tea plantations in typical plateau areas with the combination of Sentinel-1/2 optical and radar remote sensing data based on feature selection algorithm

Published:2023-04-12 Issue: Volume: Page:1-21
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Gao Shanchuan¹,Tang Bo-Hui¹²,Huang Liang¹^ORCID,Chen Guokun¹

Affiliation:

1. Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming, Yunnan, China

2. State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2023.2198655

Reference42 articles.

1. Breiman, L. 2003. Manual on setting up, using, and understanding random forests, V4.0. [Online]. Accessed 1 August 2018. https://www.stat.berkeley.edu/~breiman/Using_random_forests_v4.0. pdf

2. An Analysis of the Optimal Features for Sentinel-1 Oil Spill Datasets Based on an Improved J–M/K-Means Algorithm

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