| Records |
Author  |
Raul Eduardo Simoni Castanhari; Roberto dos Santos Rocha; Sidgley Camargo de Andrade; João Porto de Albuquerque |
| Title |
A Software Architecture to Integrate Sensor Data and Volunteered Geographic Information for Flood Risk Management |
Type |
Conference Article |
| Year |
2016 |
Publication |
ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2016 |
| Volume |
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Issue |
|
Pages |
|
| Keywords |
Service-Oriented Architecture; Integration; Geospatial Data; Volunteered Geographic Information; Flood Management |
| Abstract |
Natural disasters are phenomena that can cause great damage to people in urban and rural areas, and thus require preventive and reactive measures. If they involve multiple sources of information, these measures can be more useful and effective. However, the integration of heterogeneous data still poses challenges due to the differences in their structures and contents. To overcome this difficulty, this paper outlines a service-oriented architecture, as part of the AGORA platform, which aims to support the integration of sensor data and Volunteered Geographic Information (VGI) related to floods. The composition of the architectural components enables sensor data to be integrated with VGI by using several algorithms in a flexible and automated manner. The architecture was implemented by means of a prototype as a proof of concept and the results were used to generate thematic maps. These maps can improve flood risk awareness and support decision-making in flood risk management. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Federal University of Rio de Janeiro |
Place of Publication |
Rio de Janeiro, Brasil |
Editor |
A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto |
| Language |
English |
Summary Language |
English |
Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
|
| ISSN |
2411-3428 |
ISBN |
978-84-608-7984-49 |
Medium |
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| Track |
Geospatial Data and Geographical Information Science |
Expedition |
|
Conference |
13th International Conference on Information Systems for Crisis Response and Management |
| Notes |
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Approved |
no |
| Call Number |
|
Serial |
1368 |
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| Author |
Sidgley Camargo de Andrade; João Porto de Albuquerque; Alexandre Cláudio Botazzo Delbem |
| Title |
Improving the credibility of unreliable information through static images and data mining: an experimental study to identify floods |
Type |
Conference Article |
| Year |
2016 |
Publication |
ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2016 |
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
Affected locations by flash floods are rich in information for flood management. Usually, there are several types and sources of information which can be related to achieve better reliability to decision-making. However, a major challenge is to achieve the reliability this information within datasets so heterogeneous or complex. For instance, reports of Volunteered Geographic Information (VGI) through a crowdsourcing-based platform can be confirmed by means of images available on site. Thus, we carried out an experiment to identify water level of river through clustering from static images using an evolutionary method of hierarchical data clustering, called DAta-MIning COde REpositories (Sanches, Cardoso, and Delbem, 2011). Our experiment aimed answering the following question: Is DAMICORE able to find matching clusters between static images gathered from the sensor in-situ and water levels provided by the non-automatic interpretation mechanisms in the riverbed? These mechanisms (Figure 1 (a) water level ruler, (b) puppet, and (c) multi-color band) refer to the hazard index at hydrology field and help volunteers to report into the crowdsourcing-based platform (Degrossi, Albuquerque, Fava, Mendiondo, 2014). Moreover, our dataset contains 288 images categorized in (gray) 124 undefined, (orange) 109 acceptable, (red) 17 high, (dark red) 6 very high, and (blue) 32 flood which were obtained from in-situ sensor in a 5-minute temporal resolution on November 23rd, 2015, when a flash flood occurred at 4 p.m. (Figure 1 (d) ) at São Carlos, São Paulo, Brazil. Our preliminaries results have shown a possible matching between clusters found (Figure 2) and interpretation mechanisms of the water level in the riverbed. Therefore, there is evidence that the DAMICORE can support VGI reports collected from dedicated platforms, improving the credibility of information. Nevertheless, further experiments should be performed considering a greater number of images per category and matching between other types of VGI and authoritative data, e.g. social media and sensor. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
Federal University of Rio de Janeiro |
Place of Publication |
Rio de Janeiro, Brasil |
Editor |
A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3388 |
ISBN |
978-84-608-7984-9 |
Medium |
|
| Track |
Poster Session |
Expedition |
|
Conference |
13th International Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
1428 |
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