Application Programming Interface for Flood Forecasting from Geospatial Big Data and Crowdsourcing Data
Dublin Core
Title
Application Programming Interface for Flood Forecasting from Geospatial Big Data and Crowdsourcing Data
Subject
Application Programming Interface
Big Data
Flood Forecasting
Description
Nowadays, natural disasters tend to increase and become more severe. They do affect life and belongings of great numbers of people. One kind of such disasters that hap-pen frequently almost every year is floods in all regions across the world. A prepara-tion measure to cope with upcoming floods is flood forecasting in each particular area in order to use acquired data for monitoring and warning to people and involved per-sons, resulting in the reduction of damage. With advanced computer technology and remote sensing technology, large amounts of applicable data from various sources are provided for flood forecasting. Current flood forecasting is done through computer processing by different techniques. The famous one is machine learning, of which the limitation is to acquire a large amount big data. The one currently used still requires manpower to download and record data, causing delays and failures in real-time flood forecasting. This research, therefore, proposed the development of an automatic big data downloading system from various sources through the development of applica-tion programming interface (API) for flood forecasting by machine learning. This research relied on 4 techniques, i.e., maximum likelihood classification (MLC), fuzzy logic, self-organization map (SOM), and artificial neural network with RBF Kernel. According to accuracy assessment of flood forecasting, the most accurate technique was MLC (99.2%), followed by fuzzy logic, SOM, and RBF (97.8%, 96.6%, and 83.3%), respectively.
Creator
Puttinaovarat, Supattra
Horkaew, Paramate
Source
International Journal of Interactive Mobile Technologies (iJIM); Vol. 13 No. 11 (2019); pp. 137-156
1865-7923
Publisher
International Association of Online Engineering (IAOE), Vienna, Austria
Date
2019-11-15
Rights
Copyright (c) 2019 Supattra Puttinaovarat, Paramate Horkaew
Relation
Format
application/pdf
Language
eng
Type
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
Identifier
Citation
Supattra Puttinaovarat and Paramate Horkaew, Application Programming Interface for Flood Forecasting from Geospatial Big Data and Crowdsourcing Data, International Association of Online Engineering (IAOE), Vienna, Austria, 2019, accessed November 22, 2024, https://igi.indrastra.com/items/show/1526