Resources

Publications

Tools for mapping multi-scale settlement patterns of building footprints: An introduction to the R package foot

Spatial datasets of building footprint polygons are becoming more widely available and accessible for many areas in the world. These datasets are important inputs for a range of different analyses, such as understanding the development of cities, identifying areas at risk of disasters, and mapping the distribution of populations. The growth of high spatial resolution imagery and computing power is enabling automated procedures to extract and map building footprints for whole countries.

Semi-automatic mapping of pre-census enumeration areas and population sampling frames

Enumeration Areas (EAs) are the operational geographic units for the collection and dissemination of census data and are often used as a national sampling frame for various types of surveys. In many poor or conflict-affected countries, EA demarcations are incomplete, outdated, or missing. Even for countries that are stable and prosperous, creating and updating EAs is one of the most challenging yet essential tasks in the preparation for a national census. Commonly, EAs are created by manually digitising small geographic units on high-resolution satellite imagery or physically walking the boundaries of units, both of which are highly time, cost, and labour intensive.

Using GIS and Machine Learning to Classify Residential Status of Urban Buildings in Low and Middle Income Settings

Utilising satellite images for planning and development is becoming a common practice as computational power and machine learning capabilities expand. In this paper, we explore the use of satellite image derived building footprint data to classify the residential status of urban buildings in low and middle income countries.

National population mapping from sparse survey data: A hierarchical Bayesian modeling framework to account for uncertainty

Population estimates are critical for government services, development projects, and public health campaigns. Such data are typically obtained through a national population and housing census. However, population estimates can quickly become inaccurate in localized areas, particularly where migration or displacement has occurred.

Classifying settlement types from multi-scale spatial patterns of building footprints

Urban settlements and urbanised populations continue to grow rapidly and much of this transition is occurring in less developed countries. Remote sensing techniques are now often applied to monitor urbanisation and changes in settlement patterns. In particular, increasing availability of very high resolution imagery (<1 m spatial resolution) and computing power is enabling complete sets of settlement data in the form of building footprints to be extracted from imagery.

A grid-based sample design framework for household surveys

Traditional sample designs for household surveys are contingent upon the availability of a representative primary sampling frame. This is defined using enumeration units and population counts retrieved from decennial national censuses that can become rapidly inaccurate in highly dynamic demographic settings. To tackle the need for representative sampling frames, we propose an original grid-based sample design framework introducing essential concepts of spatial sampling in household surveys.

Geospatial variation in measles vaccine coverage through routine and campaign strategies in Nigeria: analysis of recent household surveys

Measles vaccination campaigns are conducted regularly in many low- and middle-income countries to boost measles control efforts and accelerate progress towards elimination. National and sometimes first-level administrative division campaign coverage may be estimated through post-campaign coverage surveys (PCCS). However, these […]

National and sub-national variation in patterns of febrile case management in sub-Saharan Africa

Given national healthcare coverage gaps, understanding treatment-seeking behaviour for fever is crucial for the management of childhood illness and to reduce deaths. Here, we conduct a modelling study triangulating household survey data for fever in children under the age of […]

Geospatial mapping of access to timely essential surgery in sub-Saharan Africa

Despite an estimated one-third of the global burden of disease being surgical, only limited estimates of accessibility to surgical treatment in sub-Saharan Africa exist and these remain spatially undefined. Geographical metrics of access to major hospitals were estimated based on […]

Spatially disaggregated population estimates in the absence of national population and housing census data

Population numbers at local levels are fundamental data for many applications, including the delivery and planning of services, election preparation, and response to disasters. In resource-poor settings, recent and reliable demographic data at subnational scales can often be lacking.

Mapping Health Facilities

Discusses GRID3’s work with local stakeholders and data collectors to build capacity for the production and management of geospatial data on health facilities. This paper focuses on case studies in Nigeria, the Democratic Republic of Congo, Zambia, and Sierra Leone.

Radio Transmitter Coverage in Sierra Leone

This project is part of a continued collaboration between Sierra Leone’s Ministry of Basic and Senior Secondary Education (MBSSE, referred henceforth as “the ministry”) and GRID3. Identifying gaps in Frequency Modulated coverage is the concern of the ministry and this report, along with recommendations for how these gaps might best be filled in line with the ministry’s Policy on Radical Inclusion in Schools.

COVID-19: Supporting the Government of Namibia with mobility data

Anonymised and aggregated data from Mobile Network Operators is a key data source for understanding the mobility patterns of populations, and improving decision-making and scenario planning during the COVID-19 epidemic. This data can be analysed in near real-time and provide an overview of mobility patterns across all of Namibia

GRID3 Mapping for Health – Brochure

Supported by Gavi through its INFUSE initiative, GRID3 Mapping for Health in the Democratic Republic of the Congo (DRC) is a Ministry of Health initiative, delivered in partnership with Flowminder and the Center for International Earth Science Information Network at […]

COVID-19: Supporting the Government of Sierra Leone with mobility data

Anonymised and aggregated data from Mobile Network Operators is a key data source for understanding the mobility patterns of populations, and improving decision-making and scenario planning during the COVID-19 epidemic. This data can be analysed in near real-time and provide an overview of mobility patterns across all of Sierra Leone.

Education Coverage in Sierra Leone

The Ministry of Basic and Senior Secondary Education (MBSSE, referred henceforth as “the ministry”)
is interested in identifying suitable school catchment areas across Sierra Leone (SLE) and publishing
a companion strategy for school development. This report outlines the findings from a preliminary school mapping and coverage analysis whose aim is to provide insights into existing school coverage using the population estimates created jointly by Statistics Sierra Leone and GRID3 (WorldPop and Statistics Sierra Leone, 2020) and the existing school locations from the 2019 Annual School Census (MBSSE, 2019).

Harmonising Subnational Boundaries

Discusses GRID3’s work to support the harmonisation, production, and use of digitised legal/administrative units, operational units, and statistical areas. The paper focuses on case studies in Nigeria, the Democratic Republic of Congo, and Zambia.

Mapping and Classifying Settlement Locations

Discusses GRID3’s work on collecting and analysing settlements data. GRID3’s settlements work has two areas of focus: creating a comprehensive settlement layer that enables a real-world picture of communities, and using building footprints, geospatial data layers, and machine learning algorithms to classify structures and local areas within settlements. The paper also discusses the applications of GRID3’s methods in Nigeria, the Democratic Republic of the Congo, and Zambia.