The Statistical Institute of Belize Launches Second Phase of GIS Project in Collaboration with AMEXID and INEGI

FOR IMMEDIATE RELEASE

The Statistical Institute of Belize Launches Second Phase of GIS Project in Collaboration with AMEXID and INEGI

 

Belmopan City, Cayo, May 29, 2024 – The Statistical Institute of Belize (SIB), in collaboration with the Mexican Agency for International Development Cooperation (AMEXID) and the National Institute of Statistics and Geography (INEGI), launched the second phase of its training program, “Strengthening of the Capacities of the Geographic Information System Unit for the Management of Spatial Databases, Statistical Spatial Analysis, and Remote Sensing Applications”. The sessions are being held at the SIB’s training room from May 27th – May 31st, 2024.

 

The second phase of the project aims to equip the SIB’s GIS unit with the skills and knowledge necessary to utilize remote sensing technologies and machine learning techniques for the detection, recognition, and classification of urban areas. Esteemed experts, Dr. Abel Alejandro Coronado Iruegas and Dr. Ranyart Rodrigo Suarez Ponce de Leon will facilitate the training, and will focus on the following specific objectives:

1. Foundational Understanding of Remote Sensing Technologies: Participants will gain insights into the core concepts of remote sensing, with a particular focus on Landsat and Sentinel-2 satellite imagery.

 

2. Introduction to Python and Data Science for Remote Sensing: The training will cover the basics of Python programming and its application in data science for remote sensing projects.

 

3. Google Earth Engine Familiarization: Attendees will learn to generate and utilize Sentinel Geomedian and grid data for Belize using Google Earth Engine.

 

4. Object Extraction using QGIS: Practical sessions will cover techniques for extracting objects from satellite imagery using QGIS.

 

5. Machine Learning Essentials: The training will introduce supervised learning, various machine learning models, and the fundamentals of training and validating models using sci-kit-learn and TPOT.

 

6. Detection and Classification of Built-up Areas: A specific focus will be placed on using TPOT to detect and classify built-up areas in Belize.

 

 

This project underscores SIB’s unwavering commitment to integrating innovative technologies in the production of accurate and reliable statistics.

 

For more information, please contact:

Javier Romero

Communications and Marketing Officer

Statistical Institute of Belize

jromero@mail.sib.org.bz

+501 822 2207 ext. 209

 

 

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