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Md Zia Uddin Foisal

| Humanitarian Response 🌍⛺ | Remote Sensing & GIS 🛰️🗺️ | Machine Learning and Deep Learning💡🧠 | Disaster and Climate Risk Analytics 🌊🏞️ | Biodiversity Conservation 🌱🐘 | Shelter Addressing 🤝🏠 |

👋 Hi, I'm Zia, a dedicated GIS, RS, and data professional with a passion for making a positive impact through humanitarian and environmental initiatives. My expertise lies in the intersection of Remote Sensing & GIS, applying machine learning and deep learning tools and techniques, analyzing and visualizing disaster and climate risk model outputs, land-Use land cover analysis, and biodiversity conservation. I excel in applying my skills in collecting, managing, processing, analyzing, and visualizing both tabular and geospatial data. My experience spans across disaster and climate risk analysis, socioeconomic disaggregated data analysis, multisectoral needs assessment, and landscape restoration.

💻 Technologies & Tools

                     

Md Zia Uddin Foisal's Projects

ccdr-tools icon ccdr-tools

Geoanalytics for climate and disaster risk screening

fieldimager icon fieldimager

FIELDimageR: A R package to analyze orthomosaic images from agricultural field trials. This package is a compilation of functions to analyze pos-mosaicking images from research fields, and allows to: crop the image; remove soil effect; build vegetation indices; rotate the image; build the plot shapefile; extract information for each plot; and evaluate stand count, canopy percentage, and plant height.

geographic-data-science-book icon geographic-data-science-book

This book serves as an introduction to a whole new way of thinking systematically about geographic data, using geographical analysis and computation to unlock new insights hidden within data.

predicting_school_drop-out_using_ml icon predicting_school_drop-out_using_ml

This repository is used to store the codes for the research project of predicting school dropout in Southern Bangladesh using machine learning algorithms.

pythonnumericaldemos icon pythonnumericaldemos

Well-documented Python demonstrations for spatial data analytics, geostatistical and machine learning to support my courses.

reproducible_drought_index icon reproducible_drought_index

A repository to practice reproducible research practices while studing the state of the drought around the world

wbgviz icon wbgviz

Several R packages for World Bank-standard visualisations, building on ggplot2

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