GeoFairy2: A Cross-Institution Mobile Gateway to Location-Linked Data for In-Situ Decision Making

Author:

Sun ZihengORCID,Di Liping,Cvetojevic Sreten,Yu ZhiqiORCID

Abstract

To effectively disseminate location-linked information despite the existence of digital walls across institutions, this study developed a cross-institution mobile App, named GeoFairy2, to overcome the virtual gaps among multi-source datasets and aid the general users to make thorough accurate in-situ decisions. The app provides a one-stop service with relevant information to assist with instant decision making. It was tested and proven to be capable of on-demand coupling and delivering location-based information from multiple sources. The app can help general users to crack down the digital walls among information pools and serve as a one-stop retrieval place for all information. GeoFairy2 was experimented with to gather real-time and historical information about crops, soil, water, and climate. Instead of a one-way data portal, GeoFairy2 allows general users to submit photos and observations to support citizen science projects and derive new insights, and further refine the future service. The two-directional mechanism makes GeoFairy2 a useful mobile gateway to access and contribute to the rapidly growing, heterogeneous, multisource, and location-linked datasets, and pave a way to drive us into a new mobile web with more links and less digital walls across data providers and institutions.

Funder

National Aeronautics and Space Administration

National Science Foundation

Publisher

MDPI AG

Subject

Earth and Planetary Sciences (miscellaneous),Computers in Earth Sciences,Geography, Planning and Development

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Geospatial Web Services for Geospatial Cloud Computing Paradigm: Architectures and Selective Applications Case Studies;2024 1st International Conference on Cognitive, Green and Ubiquitous Computing (IC-CGU);2024-03-01

2. Modeling, Prediction, and Decision Making Based on Remote Sensing Big Data;Springer Remote Sensing/Photogrammetry;2023

3. WaterSmart-GIS: A Web Application of a Data Assimilation Model to Support Irrigation Research and Decision Making;ISPRS International Journal of Geo-Information;2022-04-19

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