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arXiv 1904.04329cs.CVcs.LG

Automated Monitoring Cropland Using Remote Sensing Data: Challenges and Opportunities for Machine Learning

University of Minnesota, Twin Cities(明尼苏达大学双城分校)

Xiaowei Jia, Ankush Khandelwal, Vipin Kumar

英文摘要:

This paper provides an overview of how recent advances in machine learning and the availability of data from earth observing satellites can dramatically improve our ability to automatically map croplands over long period and over large regions. It discusses three applications in the domain of crop monitoring where ML approaches are beginning to show great promise. For each application, it highlights machine learning challenges, proposed approaches, and recent results. The paper concludes with discussion of major challenges that need to be addressed before ML approaches will reach their full potential for this problem of great societal relevance.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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