• Stars
    star
    1
  • Language
    R
  • Created about 1 year ago
  • Updated about 1 year ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

Session at the Summer Institute for Computation Social Science - Calabar university

More Repositories

1

wopr

An R package and Shiny application to provide API access to the WorldPop Open Population Repository (WOPR)
HTML
35
star
2

BEARmod

Basic Epidemic, Activity, and Response COVID-19 model
R
32
star
3

wpgpRFPMS

Random Forests population modelling scripts
R
31
star
4

popRF

Random Forest-informed Population Disaggregation R package
R
30
star
5

foot

An R package for processing building footprints
HTML
29
star
6

peanutButter

An R package and shiny application to produce gridded population estimates from building footprints using the "peanut butter" method.
HTML
17
star
7

wpgpDownloadPy

A toolset for finding and downloading WorldPop (Global Project) products.
Python
16
star
8

bottom-up-tutorial

Bottom-up population model tutorial
HTML
11
star
9

wpgpDataQPD

Find and Download WorldPop rasters through QGIS
Python
9
star
10

wpgpCovariates

R
8
star
11

wpgpDownloadR

A toolset for finding and downloading WorldPop (Global Project) products.
R
5
star
12

wpCPR

An R package to submit a custom polygon request to the WorldPop API
R
4
star
13

Bayesian-Top-Down-Modelling

Implement a top-down disagregation using bartMachine R package
R
3
star
14

BFA_population_v1_0_methods

This repo contains the code related to the BFA_population_v1_0_gridded estimates. See https://wopr.worldpop.org/ for more information
R
3
star
15

health_dev

A repository containing the R scripts used for the analyses in the research "Subnational reproductive, maternal, newborn, child and adolescent health and development atlas for India"
R
3
star
16

grid3Covariates

grid3Covariates is an R Package interface for downloading raster datasets from WorldPop FTP
R
2
star
17

lpsmapper

Piloting the collection of geographic information from Longitudinal Population Studies (LPS) for future climate-health research
HTML
2
star
18

python_tools

This repo contains some python-based tools for processing geospatial data
Python
2
star
19

NGA_Pop_V2_Update

This script update NGA population using building footprint v2
R
2
star
20

PNG_Bottom_Up_Modelling

R scripts for Papua New Guniea's population estimation models. There are three main R scripts contained in the folder - covariates selection, model fitting and model cross-validation.
R
2
star
21

WPGP_adj_ppp_calc

Module to adjust WorldPop Population rasters (available at ftp://ftp.worldpop.org.uk/GIS/Population/Global_2000_2020/) according to user-define rates
Python
1
star
22

wpgpDataAPD

wpArcAddon
Python
1
star
23

A-Poisson-NB-Alternative-to-Bottom-Up-Modelling

R scripts demonstrating alternative modelling approaches to bottom-up population modelling that are independent of settlement data (building count) whilst accounting for potential overdispersion within the observed population data.
R
1
star
24

imcover

Spatio-temporal immunisation coverage modelling
C++
1
star
25

Efficient-Population-Modelling-using-INLA-SPDE

R codes for INLA-SPDE bottom-up population modelling (Cameroon Application)
R
1
star
26

top-down-tutorial

Tutorials for Brazil workshop on top-down modelling
HTML
1
star
27

wpUtilities

R
1
star
28

DRC_modelling_simulation_study1

R scripts used for DRC population modelling simulation study at area unit level.
R
1
star
29

vipaper

A repository containing the R scripts used for the analyses in the research "A zero-dose vulnerability index for equity assessment and spatial prioritization in low and middle-income countries"
R
1
star
30

Two-Step-Bottom-Up-population-modelling-

R scripts used for developing a Bayesian Hierarchical Bottom-Up Population Modelling which adjusted for biases in satellite-based settlement data first before the prediction of population counts - a case study of Papua New Guinea
R
1
star
31

Admin_Unit_Urban_Classify

R-Script to Assign an GHSL-SMOD Urban Classification to L2 Admin Units
R
1
star