Md Zia Uddin Foisal (zia-foisal)

zia-foisal

Geek Repo

Company:Disaster and Climate Risk Data Fellow

Location:Bangladesh

Home Page:https://www.gfdrr.org/en

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Md Zia Uddin Foisal's repositories

Bangladseh-Power-Plant-Database-WebMap

Insights drawn for Bangladesh from the global power plant database.

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BGD-Disaster-Climate-Risk-Dashboard-World-Bank

The repo maintains the code for Bangladesh CCDR shiny dashboard

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REACH_BGD_Shelter_Addressing_Methodology_Code_2022

This repository contains the methodology and script used to generate the sequential shelter addresses in the Rohingya Refugee Camps of Cox's Bazar District, Bangladesh.

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CCDR-tools

Geoanalytics for climate and disaster risk screening

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deep-learning-for-earth-observation

Application of deep learning for earth observation.

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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.

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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.

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REACH_BGD_CXB_NatHaz_TWG_DASHBOARD_2022

This dashboard summarizes the current work of the Natural Hazard Risk Analysis Technical Working Group (NatHaz TWG).

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reproducible_drought_index

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

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SpatialDataWithR

examples and practices for learning

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wbgviz

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

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zia-foisal

Config files for my GitHub profile.

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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.

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PythonNumericalDemos

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

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Understanding-Deep-Learning

Understanding Deep Learning - Simon J.D. Prince

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