Digital Earth Africa Sustainable Development Goals

Earth observation for sustainable development

DE Africa Services and Tools for the SDGs

Explore Digital Earth Africa datasets, services, and Jupyter notebooks that can support monitoring and reporting for selected Sustainable Development Goal indicators.

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Browse SDGs

Goal 2

Goal 6

Goal 9

Goal 11

Goal 13

Goal 14

Goal 15

Select a goal to jump directly to its indicators and related notebooks.

Overview

How Earth Observation Supports the SDGs

Digital Earth Africa provides consistent satellite observations and analytical tools that can complement national data and strengthen evidence-based monitoring.

Background

A global framework for measurable progress

The Sustainable Development Goals represent a data-driven, evidence-based approach to sustainable development (The CEOS Earth Observation Handbook Special 2018 Edition). The aim of the Sustainable Development Goals (SDG) framework is to end poverty, improve health and education, reduce inequality, design sustainable cities, support economic growth, tackle climate change and leave no one behind (Andries et al. 2022). The purpose of the Global Indicator Framework is to provide means by which to measure, monitor and report progress made in the implementation of the SDGs and their respective targets, for the follow up and review of the 2030 Agenda for Sustainable Development. The Global Indicator Framework is designed around 232 SDG Indicators.

Why Earth Observation matters

Earth Observation data is an essential tool in the development of the information required by many of the SDG Indicators given its cost-effectiveness pertaining to data acquisition on all scales and information richness. (The CEOS Earth Observation Handbook Special 2018 Edition), (Ferreira, B., Iten, M. & Silva, R.G. 2020).

Digital Earth Africa’s contribution

Digital Earth Africa (DE Africa) hosts data, services and Jupyter Notebooks that can be used to address real world problems and contribute to the Global Indicator Framework.

Notebook directory

SDG Indicators Supported by DE Africa Notebooks

The links below show how DE Africa datasets, services, and analytical workflows can contribute to selected Sustainable Development Goal indicators.

SDG Goal 2

Sustainable Development Goal 2

Zero Hunger

End hunger, achieve food security and improved nutrition, and promote sustainable agriculture.

2 indicators

Indicator 2.4.1

Proportion of agricultural area under productive and sustainable agriculture

13 resources

Related notebooks

Global Root-zone moisture Analysis & Forecasting System (GRAFS) →

NDVI Climatology →

Rainfall estimates (CHIRPS) →

Cropland extent maps for Africa →

Land Cover Classification datasets →

Monitoring change through time using satellite imagery filmstrip plots →

Measuring crop health →

Forecasting cropland vegetation condition →

Identifying active irrigated cropping →

Vegetation Phenology (Optical) →

Vegetation Phenology (Radar) →

Monthly vegetation condition anomalies →

Scalable Supervised Machine Learning on the Open Data Cube ReadME →

Indicator 2.c.1

Indicator of food price anomalies

9 resources

Related notebooks

Global Root-zone moisture Analysis & Forecasting System (GRAFS) →

NDVI Climatology →

Rainfall estimates (CHIRPS) →

Measuring crop health →

Forecasting cropland vegetation condition →

Vegetation Phenology (Optical) →

Vegetation Phenology (Radar) →

Monthly vegetation condition anomalies →

Rainfall anomalies from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) →

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SDG Goal 6

Sustainable Development Goal 6

Clean Water and Sanitation

Ensure availability and sustainable management of water and sanitation for all.

4 indicators

Indicator 6.3.2

Proportion of bodies of water with good ambient water quality

2 resources

Related notebooks

Monitoring Water Quality →

Monitoring chlorophyll-a in African waterbodies →

Indicator 6.4.1

Change in water use efficiency over time

2 resources

Related notebooks

WaPOR data →

Inspecting WaPOR data through time →

Indicator 6.4.2

Level of water stress: freshwater withdrawal as a proportion of available freshwater resources

6 resources

Related notebooks

ERA5 climate data →

Cropland extent maps for Africa →

Identifying active irrigated cropping →

Rainfall anomalies from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) →

Determining seasonal extent of waterbodies with Sentinel-2 →

Mapping longer-term changes in water extent with WOfS →

Indicator 6.6.1

Change in the extent of water-related ecosystems over time

20 resources

Related notebooks

Land Cover Classification Datasets →

ERA5 climate data →

Rainfall estimates (CHIRPS) →

Water Observations from Space →

Extracting contour lines →

Monitoring change through time using satellite imagery filmstrip plots →

Water detection with Sentinel-1 →

Rainfall anomalies from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) →

Wetlands Insight Tool →

Determining seasonal extent of waterbodies with Sentinel-2 →

Mapping longer-term changes in water extent with WOfS →

Okavango use case

Monitoring wetlands in the Okavango →

Mapping long-term changes in the annual water extent of the Okavango Delta →

Mapping the seasonal changes to the open water extent of the Okavango delta →

Extracting historical climate (rainfall) data over selected basins →

Visualising the correlation between rainfall, surface water extent, and discharge →

Modelling discharge at Mohembo using uppercatchment rainfall →

Forecasting surface water extent in the Okavango delta →

Monitoring water extent use case

Mapping water extent and rainfall using Sentinel-1 and CHIRPS →

Mapping water extent and rainfall using WOfS and CHIRPS →

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SDG Goal 9

Sustainable Development Goal 9

Industry, Innovation and Infrastructure

Build resilient infrastructure, promote inclusive and sustainable industrialisation, and foster innovation.

1 indicator

Indicator 9.1.1

Proportion of the rural population who live within 2 km of an all-season

5 resources

Related notebooks

Land Cover Classification Datasets →

Machine learning with the Open Data Cube →

Urban area mapping using Sentinel 1 data →

Urbanization Index Comparisons with Global Human Settlement (GHS) →

Detecting change in urban extent →

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SDG Goal 11

Sustainable Development Goal 11

Sustainable Cities and Communities

Make cities and human settlements inclusive, safe, resilient, and sustainable.

3 indicators

Indicator 11.1.1

Proportion of urban population living in slums, informal settlements or inadequate housing

5 resources

Related notebooks

Land Cover Classification Datasets →

Machine learning with the Open Data Cube →

Urban area mapping using Sentinel 1 data →

Urbanization Index Comparisons with Global Human Settlement (GHS) →

Detecting change in urban extent →

Indicator 11.3.1

Ratio of land consumption rate to population growth rate

3 resources

Related notebooks

Monitoring change through time using satellite imagery filmstrip plots →

Machine learning with the Open Data Cube →

Urban area mapping using Sentinel 1 data →

Indicator 11.7.1

Average share of the built-up area of cities that is open space for public use for all, by sex, age and persons with disabilities

5 resources

Related notebooks

Monitoring change through time using satellite imagery filmstrip plots →

Machine learning with the Open Data Cube →

Urbanization Index Comparisons with Global Human Settlement (GHS) →

Detecting change in urban extent →

Urban area mapping using Sentinel 1 data →

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SDG Goal 13

Sustainable Development Goal 13

Climate Action

Take urgent action to combat climate change and its impacts.

1 indicator

Indicator 13.1.1

Number of deaths, missing persons and directly affected persons attributed to disasters per 100,000 population

6 resources

Related notebooks

Land Cover Classification Datasets →

Digital Elevation Models →

Burnt Area Mapping →

Rainfall anomalies from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) →

Identifying ships with Sentinel-1 →

Monitoring coastal erosion along Africa’s coastline →

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SDG Goal 14

Sustainable Development Goal 14

Life Below Water

Conserve and sustainably use oceans, seas, and marine resources for sustainable development.

2 indicators

Indicator 14.1.1

  1. Index of coastal eutrophication; and (b) plastic debris density

1 resource

Related notebooks

Monitoring chlorophyll-a in African waterbodies →

Indicator 14.5.1

Coverage of protected areas in relation to marine areas

3 resources

Related notebooks

Land Cover Classification Datasets →

Monitoring Mangrove Extents →

Identifying ships with Sentinel-1 →

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SDG Goal 15

Sustainable Development Goal 15

Life on Land

Protect and restore terrestrial ecosystems, manage forests sustainably, combat desertification, and reverse land degradation and biodiversity loss.

4 indicators

Indicator 15.1.1

Forest area as a proportion of total land area

4 resources

Related notebooks

Land Cover Classification Datasets →

Global Mangrove Watch →

Fractional Cover →

Monitoring Mangrove Extents →

Indicator 15.1.2

Proportion of important sites for terrestrial and freshwater biodiversity that are covered by protected areas, by ecosystem type

5 resources

Related notebooks

Land Cover Classification Datasets →

Global Mangrove Watch →

Monitoring Mangrove Extents →

Lake Baringo use case

Vegetation phenology in the Ruko Conservancy →

Per-pixel vegetation phenology in the Ruko Conservancy →

Indicator 15.3.1

Proportion of land that is degraded over total land area

9 resources

Related notebooks

Land Cover Classification Datasets →

Fractional Cover →

NDVI Climatology →

Monitoring change through time using satellite imagery filmstrip plots →

Monitoring coastal erosion along Africa’s coastline →

Vegetation Change Detection →

Monthly vegetation condition anomalies →

Surface Mining Screening →

Scalable Supervised Machine Learning on the Open Data Cube ReadME →

Indicator 15.4.2

Mountain Green Cover Index

4 resources

Related notebooks

Mountain Green Cover Index Notebook →

Burnt Area Mapping →

Vegetation Change Detection →

Monthly vegetation condition anomalies →

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