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Date limite
11 nov 2022
Les inscriptions sont terminées

Introductory Training on Landslide Susceptibility Mapping

Type
Course
Emplacement
Suva, Fiji
Date
Durée
1 Days
Zone du programme
Climate Change, Satellite Imagery and Analysis
Prix
0.00 $US
Personne de référence de l'évenement
wittawat.bunnasarn@unitar.org
Partenariat
NORWEGIAN MINISTRY OF FOREIGN AFFAIRS
University of South Pacific
Ministry of Economy, Republic of Fiji
Inscription
Private – by invitation
Mode de livraison
Face-to-Face
Langue (s)
English
Pilier
United Nations Satellite Centre UNOSAT
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The project “Strengthening Capacities in the Use of Geospatial Information for Improved Resilience in Asia-Pacific and Africa.” (2021-2024) intends to develop sustainable capacities and implement ad-hoc and tailored geospatial solutions in the eight target countries: Fiji, Bangladesh, Bhutan, Lao PDR, Nigeria, Solomon Islands, Uganda, and Vanuatu. In Fiji, this 3-year long project builds on the legacy of the CommonSensing Project (2019-2022) and aims to further enhance capacities by leveraging technological advances and innovation and providing integrated geospatial solutions for improved decision making in the fields of Climate Resilience, Disaster Risk Management, and Climate Finance. The project’s focal point is the Climate Change and International Cooperation Division (CCICD) of the Ministry of Economy. The project will have other beneficiaries such as the Ministry of Lands and Mineral Resources (MLMR), Ministry of Agriculture, Ministry of Rural and Maritime Development and Disaster Management (MRMDDM), the Ministry of Waterways, and the Fiji Meteorological Services.

With the closure of the CommonSensing project on 31 March 2022, UNOSAT has conducted a rescoping study in close collaboration with CCICD and identified the need to deliver face-to-face micro-learning training on advanced topics offered for technical staff across line ministries. Fiji frequently experiences landslides following torrential rain. UNOSAT produced an earthquake-triggered landslide susceptibility map for the NDMO in 2019, where validation of the model was requested from the Mineral Resources Department. The MRD then sought advice on testing a rainfall-triggered landslide susceptibility model, the more frequent landslide hazard. Based on these consultations, UNOSAT will offer Rainfall-triggered Landslide Susceptibility Training for technical staff in the Mineral Resource Department.

Landslides can cause devastating human and economic losses with an increasing trend due to urban expansion and climate change. A lot of research has been carried out on predicting landslides, trying to find out “where”, “when”, “why”, “how big” etc. about landslide occurrence. Local authorities also started taking landslides into account for urban planning and other engineering works. Therefore, many qualitative and quantitative landslide susceptibility and hazard assessment methods have been developed. This course will illustrate a weighted overlay method to assess landslide susceptibility.

At the end of the course participants should be able to:

  1. Recall the basic concepts of landslide susceptibility mapping;
  2. Apply basic methods and functionalities of GIS software (ArcGIS) to prepare the spatial dataset for landslide susceptibility assessment;
  3. Prepare factor maps and produce the landslide susceptibility map;
  4. Interpret landslide susceptibility results for risk reduction planning

Landslides can cause devastating human and economic losses with an increasing trend due to urban expansion and climate change. A lot of research has been carried out on predicting landslides, trying to find out “where”, “when”, “why”, “how big” etc. about landslide occurrence. Local authorities also started taking landslides into account for urban planning and other engineering works. Therefore, many qualitative and quantitative landslide susceptibility and hazard assessment methods have been developed. This course will illustrate a weighted overlay method to assess landslide susceptibility.

Modality: This is a 1-day full-time face-to-face technical training. This face-to-face course will consist of lecture and GIS lab exercises using GIS datasets and real case scenarios, whereas 70% of the training content will focus on lab exercises while 30% will be lectures and discussions.

Expected Workload: 8 hours

The course is designed to accommodate selected participants with a variety of backgrounds and professional experiences, from Mineral Resource Department, Ministry of Lands & Mineral Resources, National Disaster Management Office, and Fiji Meteorological Office. The criteria of selection include:

  • 50% of female participants.
  • GIS or Remote Sensing knowledge or experience are needed.
  • Commitment to use the knowledge and skills acquired to support disaster risk management operations.