Crop classification using crop knowledge of the previous-year: Case study in Southwest Kansas, USA-Reference-Cited by-同舟云学术

Crop classification using crop knowledge of the previous-year: Case study in Southwest Kansas, USA

Published:2016-01 Issue:1 Volume:49 Page:1061-1077
ISSN:2279-7254
Container-title:European Journal of Remote Sensing
language:en
Short-container-title:European Journal of Remote Sensing

Author:

Hao Pengyu¹²,Wang Li¹,Zhan Yulin¹,Wang Changyao¹,Niu Zheng¹,Wu Mingquan¹

Affiliation:

1. The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, CAS Olympic S & T Park, No. 20 Datun Road, P.O. Box 9718, 100101 Beijing, China

2. University of Chinese Academy of Sciences, No. 19A Yuquan Road, 100049 Beijing, China

Publisher

Informa UK Limited

Subject

Applied Mathematics,Atmospheric Science,Computers in Earth Sciences,General Environmental Science

Link

https://www.tandfonline.com/doi/pdf/10.5721/EuJRS20164954

Reference25 articles.

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4. Gallego J., Craig M., Michaelsen J., Bossyns B., Fritz S. (2008)—Best practices for crop area estimation with Remote Sensing. GEOSS Community of Practice Ag 0703a, European Commission, Joint Research Centre, Institute for the Protection and Security of the Citizen.

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