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  4. Using a self-organizing map to explore local weather features for smart urban agriculture in Northern Taiwan
 
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Using a self-organizing map to explore local weather features for smart urban agriculture in Northern Taiwan

Journal
Water (Switzerland)
Journal Volume
13
Journal Issue
23
Date Issued
2021
Author(s)
Huang A
FI-JOHN CHANG  
DOI
10.3390/w13233457
URI
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120784188&doi=10.3390%2fw13233457&partnerID=40&md5=ba93ee85962772749fd72a47060ae8b0
https://scholars.lib.ntu.edu.tw/handle/123456789/605808
Abstract
Weather plays a critical role in outdoor agricultural production; therefore, climate information can help farmers to arrange planting and production schedules, especially for urban agriculture (UA), providing fresh vegetables to partially fulfill city residents’ dietary needs. General weather information in the form of timely forecasts is insufficient to anticipate potential occurrences of weather types and features during the designated time windows for precise cultivation planning. In this research, we intended to use a self-organizing map (SOM), which is a clustering technique with powerful feature extraction ability to reveal hidden patterns of datasets, to explore the represented spatiotemporal weather features of Taipei city based on the observed data of six key weather factors that were collected at five weather stations in northern Taiwan during 2014 and 2018. The weather types and features of duration and distribution for Taipei on a 10-day basis were specifically ex-amined, indicating that weather types #2, #4, and #7 featured to manifest the dominant seasonal patterns in a year. The results can serve as practical references to anticipate upcoming weather types/features within designated time frames, arrange potential/further measures of cultivation tasks and/or adjustments in response, and use water/energy resources efficiently for the sustainable production of smart urban agriculture. ? 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Subjects
Artificial neural network
Meteorological feature extraction
Resource utilization efficiency
Self-organizing map (SOM)
Urban agriculture
Urban northern Taiwan
Weather types and features
Cultivation
Extraction
Feature extraction
Production control
Self organizing maps
Features extraction
Northern Taiwan
Resources utilizations
Self-organizing map
Urban agricultures
Urban northern taiwan
Utilization efficiency
Weather type and feature
Weather types
Conformal mapping
energy resource
seasonal variation
self organizing map
spatiotemporal analysis
sustainability
urban agriculture
water resource
Taipei
Taiwan
SDGs

[SDGs]SDG2

[SDGs]SDG12

[SDGs]SDG13

Type
journal article

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