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

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