Comparison of machine learning algorithms for mapping mango plantations based on Gaofen-1 imagery-Reference-Cited by-同舟云学术

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Comparison of machine learning algorithms for mapping mango plantations based on Gaofen-1 imagery

Published:2020-11 Issue:11 Volume:19 Page:2815-2828
ISSN:2095-3119
Container-title:Journal of Integrative Agriculture
language:en
Short-container-title:Journal of Integrative Agriculture

Author:

LUO Hong-xia,DAI Sheng-pei,LI Mao-fen,LIU En-ping,ZHENG Qian,HU Ying-ying,YI Xiao-ping

Publisher

Elsevier BV

Subject

Plant Science,Agronomy and Crop Science,Animal Science and Zoology,Food Animals,Ecology,Biochemistry,Food Science

Reference49 articles.

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2. A refined crop drought monitoring method based on the Chinese GF-1 wide field view data;Chang;Sensors,2018

3. Mapping tropical forests and deciduous rubber plantations in Hainan Island, China by integrating PALSAR 25-m and multi-temporal Landsat images;Chen;International Journal of Applied Earth Observation and Geoinformation,2016

4. A comparative analysis of machine learning with WorldView-2 pan-sharpened imagery for tea crop mapping;Chung;Sensors,2016

5. A comparison of pixel-based and object-based image analysis with selected machine learing algorithms for the classification of agricultural landscapes using SPOT-5 HRG imagery;Duro;Remote Sensing of Environment,2012

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