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Design of an Intelligently Irrigated Agriculture Decision Support Service System

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posted on 2019-07-23, 19:56 authored by Eugene Yu, Liping Di, Li Lin, Haoteng Zhao, Md. Shahinoor Rahman, Chen Zhang, Junmei Tang
Decisions on efficient irrigation in agriculture call for information service requirements of supporting diverse data products, reactive, responsive, and progressive. A full stack design of Web geographical information service system is developed to efficiently serve farmers in irrigated agriculture up to fields. This poster was presented in July 2019 at the Earth Science Information Partners (ESIP) Summer Meeting held in Tacoma Washington.


The study was funded by NSF INFEWS/T2 Award #1739705. The project Principle Investigator is Professor Liping Di.