Melola Discovery

← Melola Discovery

Open access Jurnal SINTA 1

Monitoring of Landslides in Mountainous Regions based on FEM Modelling and Rain Gauge Measurements

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 6 No. 5 (2016)

DOI
10.11591/ijece.v6i5.10482
ISSN
2088-8708, 2088-8708
Published
2016-10-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc-nd/4.0

Abstract

Vietnam is a country heavily influenced by climate change. The effect of climate change leads to a series of dangerous phenomena, such as landslides. Landslides occur not only in the mountainous province, but also in Delta provinces, where hundreds of landslides are reported annually in the North-Western provinces of Vietnam. These events have catastrophic impact to the community as well as the economy. In mountainous areas, the conditions for landslides to occur are met frequently, especially after heavy rains or geological activity, causing harm to the community as well as damaging or destroying much needed infrastructure and key transport routes. However, in Vietnam, investment in mountainous regions has been often lower than in urban areas. The meteorology monitoring and forecasting systems are ill equipped and overloaded, so they cannot deliver earlier and more accurate forecasts for complex weather events, unable to provide timely warnings. It can be seen that in countries that landslide often occur, researchers have been trying to develop low cost and efficient landslide detection system. This paper precisely addressed the problems mentioned, by designing and implementing an efficient and reliable Landslide Monitoring and Early Warning (LMnE) system based on the 3G/2G mobile communication system, and a rain gauge at the field site along with a carefully FEM (finite element method) simulation using the rain density information on the server. The system uses advanced processing algorithms combining obtained data at the central station.

Collaboration network of the authors

23 authors · 72 co-authorship links · 34 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Trường ĐH Nguyễn Tất Thành
  • Hanoi University of Industry
  • Kalasalingam Academy of Research and Education
  • VNU University of Engineering and Technology
  • Vietnam Academy of Science and Technology
  • Phenikaa University
  • Nam Dinh University of Nursing
  • Other organisations
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Dinh-Chinh NguyenAffiliation unknown2
Tran Duc-TanAffiliation unknown2
Kieu Thi NguyenTrường ĐH Nguyễn Tất Thành2
Le Anh NgocElectric Power University2
Thi Thu NguyenHanoi University of Industry2
Phuc Thinh DoanTrường ĐH Nguyễn Tất Thành2
Kolla Bhanu PrakashKoneru Lakshmaiah Education Foundation2
Subrata ChowdhuryAffiliation unknown2
Gian Quoc AnhNam Dinh University of Nursing1
Kumbesan Sandy SandrasegaranUniversity of Technology Sydney1
Phung Cοng Phi KhanhAffiliation unknown1
Trung HoangThai Nguyen University of Information and Communication Technology1
Nguyễn Văn ThăngThuyloi University1
Ninh Trung BuiVietnam National University, Hanoi1
Balakrishnan BaranitharanKalasalingam Academy of Research and Education1
Karthik ChandranAffiliation unknown1
Vaithilingam Subramaniyan MathanKalasalingam Academy of Research and Education1
Subrata ChowdhuraAffiliation unknown1
Thi-Thu NguyenHanoi University of Industry1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Monitoring of Landslides in Mountainous Regions based on FEM Modelling and Rain Gauge Measurements</dc:title><dc:creator>Gian, Quoc-Anh</dc:creator><dc:creator>Nguyen, Dinh-Chinh</dc:creator><dc:creator>Tran, Duc-Nghia</dc:creator><dc:creator>Tran, Duc-Tan</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;p&amp;gt;&amp;lt;span&amp;gt;Vietnam is a country heavily influenced by climate change. The effect of climate change leads to a series of dangerous phenomena, such as landslides. Landslides occur not only in the mountainous province, but also in Delta provinces, where hundreds of landslides are reported annually in the North-Western provinces of Vietnam. These events have catastrophic impact to the community as well as the economy. In mountainous areas, the conditions for landslides to occur are met frequently, especially after heavy rains or geological activity, causing harm to the community as well as damaging or destroying much needed infrastructure and key transport routes. However, in Vietnam, investment in mountainous regions has been often lower than in urban areas. The meteorology monitoring and forecasting systems are ill equipped and overloaded, so they cannot deliver earlier and more accurate forecasts for complex weather events, unable to provide timely warnings. It can be seen that in countries that landslide often occur, researchers have been trying to develop low cost and efficient landslide detection system. This paper precisely addressed the problems mentioned, by designing and implementing an efficient and reliable Landslide Monitoring and Early Warning (LMnE) system based on the 3G/2G mobile communication system, and a rain gauge at the field site along with a carefully FEM (finite element method) simulation using the rain density information on the server. The system uses advanced processing algorithms combining obtained data at the central station.&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2016-10-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v6i5.10482</dc:identifier><dc:identifier>10.11591/ijece.v6i5.10482</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 6 No 5 (2016); 2106</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://www.iaescore.com/journals/index.php/IJECE/article/viewFile/1136/4194</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc-nd/4.0</dc:rights></oai_dc:dc>