The Remote Sensing and Data Science (DATOS) Help Desk aims to produce and communicate relevant disaster information to agencies and key end-users to complement the current efforts of existing government agencies and initiatives. DATOS builds on and integrates past and ongoing DOST-supported projects; and different Geographic Information System (GIS), Remote Sensing (RS) and other Data Science techniques.

The DATOS logo represents the project's main fields of study. The interconnected dots represent data points, as DATOS makes use of data science and its underlying technologies. One of the DOST-ASTI projects that DATOS heavily relies on is the CoARE project, which provides support for its data science needs, such as data archiving and machine learning. The satellite dish in the project name represents remote sensing, which is incidentally one of the data acquisition methods used by the project. Another DOST-ASTI project, PEDRO, is one of the primary sources of satellite images that are processed by the DATOS Project.

Flood Map of areas in Biliran affected by Typhoon Vinta (2017)

The DATOS Project uses GIS, RS, AI, and other data science methods in producing relevant disaster-related information. The outputs produced, such as this flood map, are examples of visualization tools that will allow LGUs, policy makers, and other stakeholders to have an idea of the hazards and actual impacts of severe weather events. These tools can aid them in making science-based decisions and as springboard for further research opportunities.

This map shows potentially flooded areas in the province of Biliran due to rains brought by Typhoon Vinta in December 2017—cyan-colored areas are areas that were flooded. These areas were identified using object-based image analysis and classification using Orfeo Toolbox, an open-source project for state-of-the-art remote sensing. The map is still subject to validation and interpretation of remote sensing experts.

DISCLAIMER:

This output is part of an ongoing research project under the DOST-Advanced Science & Technology Institute. The information produced by the project is intended to complement and supplement the current government DRRM efforts.

For official alerts and recommended courses of action, kindly refer to your local government units or the mandated government agencies concerned.

Flood Map of Areas in Pangasinan Affected by Typhoon Henry (2018)

Part of our research employs the use of Convolutional Neural Networks in processing satellite images to detect potentially flooded areas during hazard events. This map of Dagupan City, for example, shows the application of remote sensing and artificial neural networks to "automate" the identification of flooded areas in a satellite image.

Areas shown in red were identified via AI as areas in Dagupan City that may have been flooded during the onslaught of Typhoon Henry (July 2018). These areas were identified using composite of C band radar images.

DISCLAIMER:

This output is part of an ongoing research project under the DOST-Advanced Science & Technology Institute. The information produced by the project is intended to complement and supplement the current government DRRM efforts.

For official alerts and recommended courses of action, kindly refer to your local government units or the mandated government agencies concerned.