Category: Earth Observation & Climate Data

Using Earth Observation data in climate risk assessment for financial institutions

Using Earth Observation data in climate risk assessment for financial institutions

By Robin Hamaker-Taylor and Jennifer Steeves

Working with financial institutions to understand analyse and disclose physical climate risks and opportunities to loans, investments and across portfolios demands the application of the most up-to-date climate data and information. By deploying data from historic climate observations, modelled projections of future climate and various social, environmental and economic datasets it is possible to begin to build a picture of risk exposure to financial institutions. In recent years, Acclimatise has also been working with new data sources such as Earth Observation (EO) data, which offer the potential to develop our understanding of real-time risk exposure, especially in areas where other data is sparse.

Acclimatise worked with leading programmes, such as the European Space Agency’s Earth Observation for Sustainable Development Climate Resilience (EO4SD CR) cluster, to demonstrate the potential of EO data to build climate resilience. The potential of EO data is enormous, and the developments in the temporal and spatial resolution of satellite data is a powerful tool of analysis. In recognition of this, Acclimatise this month became an Associate Member of Group on Earth Observations (GEO). The GEO is an intergovernmental partnership that improves the availability, access and use of EOs for a sustainable planet.

What is EO and EO data?

EO is the collection, analysis and presentation of information about the Earth’s physical, chemical and biological systems and has the capability to do so across remote and inaccessible terrain. It involves monitoring and assessing the status of and changes in the natural and man-made environment. There are now thousands of data buoys operating in the world’s oceans, hundreds of thousands of land-based environmental monitoring stations, tens of thousands of observations from aircraft platforms and numerous environmental satellites orbiting the globe, according to GEOSS and other academic research.

EO satellites can collect real-time data on a wide range of indicators such as water distribution, land use, water cycles, atmospheric profiles, heat mapping, sea surface evaluations, and global-regional energy exchanges. EO data provide large quantities of timely and accurate environmental information, which, when combined with other datasets, can give unique insights into managing climate risks.

Of the 50 Global Climate Observing System (GCOS) essential climate variables, roughly half can only be observed from space, making EO an irreplaceable component of climate monitoring. EO datasets are critical in regions where insufficient information is available from weather stations (which is often the case), and its consistency facilitates coordination of information sharing. It is also very useful where on-the-ground assessments of infrastructure are not possible, for example, due to safety concerns.

Why is EO data useful for financial institutions?

Financial institutions (FIs) are accustomed to integrating data from various sources into their risk screening processes. As FIs become increasingly aware of the need to consider physical climate risks in their assessments, EO data offers enormous potential. FIs often lend or invest in diverse geographies with varying levels of available climate hazard data.

EO datasets can complement data held by FIs on their borrowers or investments including data on physical assets, on-site operations, supply chains, markets and logistics. High-quality data on climate parameters combined with other critical investment-relevant information helps investors and asset managers understand current and future risks to their investments across sectors. EO data is often used for post-disaster damage assessment. EO data can also be integrated into existing tools platforms and analyses used by FIs.

Evidence from current uses of EO data by financial institutions

To date, EO data has been used in the context of climate risk primarily by development finance institutions (DFIs), which indicates how commercial FIs could eventually use this type of data. The EO4SD Climate Resilience Cluster provides EO-based products and services to DFIs that have investments in developing countries to support climate resilience. DFIs and other agencies supported through the project include the World Bank, Asian Development Bank (ADB), Inter-American Development Bank (IDB), African Risk Capacity (ARC), Multilateral Investment Guarantee Agency (MIGA) and the International Finance Corporation (IFC).

For example, the EO4SD project is collaborating with a World Bank urban development initiative in Greater Monrovia, Liberia to provide EO-based products and services. An example of this is a coastal erosion service involving 41km of shoreline evolution monitored through a 34-year satellite series, which has been acquired through analysis of satellite images from Landsat, Sentinel 2 and Worldview 3. The analysis estimates that the land loss area from 1984 to 2019 in the 50 km coastline of Greater Monrovia is 0.8 km2. This can be overlaid with data on population and critical infrastructure to aid investment planning.

Flood mapping is also benefiting from EO-based services as EO data provides consistent historical information on floods. The 34-year high-resolution sea-level rise data was also used to identify coastal and inland flood risk areas in parts of Monrovia. The model integrates sea level rise projections to 2030, mapped against a digital terrain model to identify high flood risk areas. These flood maps help the World Bank and local authorities identify the most effective flood management actions and enable better planning decisions to avoid unnecessary development in risky areas.

The direction of travel: What next for EO?

EO data can help banks and lenders around the world understand and prepare for climate change impacts, accounting for future climate risks and opportunities in investment and lending decisions. As EO data gets easier to extract and apply, its use in climate risk assessments will continue to unfold.

One exciting potential application of EO data is in the context of trend analysis where past events are correlated to experienced losses to help paint a picture of risk. There is also potential to develop statistical information using EO data for certain climate hazards such as flooding. Processed climate data will soon be available on flood return periods, for example, as will statistics on flood extent and flood duration. Acclimatise are now gearing up for phase 2 of the EO4SD project, which will build the capacity of DFIs and partner agencies in the practical application of EO data.


Stay in touch with how this project unfolds and how we are using EO to build climate resilience here.

Acclimatise becomes an Associate Member of GEO

Acclimatise becomes an Associate Member of GEO

Acclimatise is proud to announce that it has been officially recognised as an Associate Member of the Group on Earth Observations (GEO). Formally accepted at the 48th GEO Executive Committee in Geneva, Switzerland last month, Acclimatise will join the GEO Member governments and participating organisations in informing the development and implementation of the GEO Work Programme.

The GEO is an intergovernmental partnership that improves the availability, access and use of Earth observations for a sustainable planet. Promoting open, coordinated and sustained data sharing and infrastructure for better research, the GEO offers all countries the opportunity to benefit from collective knowledge, expertise and skills to develop national Earth observations programmes.

“With the in-depth understanding of its wide-ranging clients’ analytics needs and long-standing industry experience, Acclimatise is uniquely positioned to take full advantage of the opportunities that the Associate Membership of the GEO would present,” said Head of Analytics Dr Xianfu Lu.  “In particular, through leveraging the wealth of data, information and knowledge and the partnerships made possible by the GEO, Acclimatise aims to develop cutting-edging analytics tools that enable climate resilience solutions and investment opportunities.”

Acclimatise is unique in the Earth Observation community drawing on its fifteen years’ of experience advising corporates, financial institutions and governments to develop climate resilience solutions based on EO-data. In doing so, Acclimatise is able to provide significant added value through its unique focus on cloud-based software to deploy EO-based data in combination with climate projections and other socio-economic data sets. Such solutions will support the efforts of governments, corporates and the financial services sectors in delivering climate- and disaster-resilient development.

For more information, view the full list of GEO Associates here.


Cover photo of Iraq flood posted under CC by-SA 3.0-igo from Wikimedia Commons.
EO4SD climate cluster collaborates with World Bank applying EO support to Lake Victoria Basin projects

EO4SD climate cluster collaborates with World Bank applying EO support to Lake Victoria Basin projects

The Earth Observation for Sustainable Development (EO4SD) Climate Resilience Cluster has been working with International Financial Institutes (IFIs) to develop a satellite-based integrated climate screening and risk management service to build capacity in IFI client states and help them meet long-term climate resilient development planning goals. The Cluster is supporting future environment and natural resources management (ENRM) projects in partnership with the Lake Victoria Basin Commission (LVBC) to develop an environmental management project for the Lake Victoria Basin. The LVBC coordinates the partner states of the East African Community in managing the Basin.

The Basin is Africa’s largest freshwater lake and is spread across 5 countries – Tanzania, Uganda, Kenya, Burundi and Rwanda. The ENRM projects in the Great Lakes region aim to strengthen transboundary natural resource management by improving regional information services on water quality and ecosystem health, encouraging sustainable land and water resource management (SLWM) and building climate resilience in select hotspots in the Basin. These projects will increase the LVBC’s capacity to deliver on its mandate of coordinating the management of water quality in the Basin.

The Basin currently faces multiple environmental, economic and social challenges. Different hotspots in the Basin are under pressure from a combination of factors such as high population density, land use change, and water and land pollution due to inefficient waste management and treatment. These factors are contributing to the degradation of Lake Victoria.

The Lake has turbid waters with high chlorophyll concentrations turning them green. Excessive turbidity and chlorophyll concentrations indicate high mineral density in the water and poor water quality, a problem that is being exacerbated by climate change, which will increase the rate of environmental degradation in the Lake. Rising temperatures will accelerate the growth of floating macrophytes (aquatic plants), which will reduce the oxygen content of the lake. The conditions for disease vectors such as mosquitos are also likely to become more favourable and the increasing frequency and severity of floods and droughts will further drive erosion and increase sediment in runoff.

Water hyacinth in Winam Gulf (Lake Victoria). Floating water hyacinth areas are depicted in red. Obtained from satellite imagery: MODIS (250 m) on 22nd March 2019 (left) and Sentinel-2 (10 m) on 18th March 2019 (right). More explanations in this Youtube video.
The image shows us the trend in lake surface temperature in the Basin from 1991 to 2010. Displayed in the EO4SD CR platform

Hotspots under pressure

In the Nyabugogo catchment in Rwanda, one of the Lake Victoria’s hotspots, urban settlements within the catchment are already living with the consequences of environmental degradation due to the exploitation of natural resources for agricultural and industrial activities, severe pollution and significant changes in land use. The catchment is at high risk of fluvial and pluvial flooding, with surrounding farmland and villages being frequently inundated. The economy in the Basin area is entirely dependent on water and land resources for agriculture and industry. These effects will be exacerbated by changing climate patterns and climate related events, threatening the economic stability of the region.

Following a high-level climate risk analysis of the Nyabugogo catchment, the cluster identified several adaptation options along with relevant EO data layers. One of the options identified involves synthesis of multi-parameter remote sensing data to monitor and manage catchment changes, which will help monitor catchment health and identify and remedy incipient catchment hazards. This can be enabled by building the GIS and Remote Sensing (RS) capacity of LVBC to enable them to receive, store and synthesise up-to-date and quality remotely sensed spatial data and information on the Basin. Data may cover a broad spectrum of themes, such as lake levels, lake water quality, water hyacinth, land use/land cover changes and biodiversity trends.

Shoreline changes in the mouth of the Nyando River from 1984 to 2019. Its basin is one of the most degraded of all the river basins in the Kenyan portion of the Lake Victoria Basin. False colour is chosen to emphasize changes in vegetation. Plant-covered land is red. Water bodies are dark blue, while turbid water appears in shades of cyan compared to clear water.

Products developed by the cluster include the historic evolution of hyacinth and lake surface temperature, along with the evolution of lake shoreline erosion, for the Winam Gulf part of the Basin. This information can be used, for example, to identify the location and sources of pollution hotspots in industrial and agricultural areas. Following the development of these prototypes, the climate resilience cluster plans to extend the analysis to other hot spots of the Lake Victoria as part of a regular monitoring service, such as monthly changes in water hyacinth cover or lake shoreline erosion. Access to this level of data can improve the LVBC’s capacity to manage its resources across country boundaries and improve regulations to meet the immediate and long-term needs of the Basin to maintain its ecological integrity.

The datasets used for the Lake Victoria project, land surface temperature (LST) and water hyacinth detection (currently based on vegetation indexes) are global and can be provided for other parts of the world. The products developed for Lake Victoria Basin can also be applied to other areas, improving data availability for informed decision making and for mainstreaming climate resilience in development planning.


This article was originally published on the EO4SD Climate Resilience website.
Cover photo of Lake Victoria from Wikimedia Commons.
Earth observation data supports flood resilience in ADB projects in China and Philippines

Earth observation data supports flood resilience in ADB projects in China and Philippines

There is considerable excitement about the potential for Earth Observation (EO) data to support climate resilience planning, design and implementation. As the temporal and spatial resolution of satellite data increases, and costs continue to fall, the potential of EO data to support climate resilience projects is beginning to be realised. Over the past twelve months, the European Space Agency’s Earth Observation for Sustainable Development Climate Resilience cluster (EO4SD CR) has been working with the Asian Development Bank providing EO data in support of climate resilience projects in the Philippines and China.

Inundation Monitoring Service in the Philippines

Analysing flood basins in the Philippines required a tailored approach. The Philippines ranks third among countries with the highest disaster risk and is among the top 10 countries with the most number of people affected by disasters. Storms, typhoons, and associated floods devastate and account 80% of all deaths, 90% of affected people, and 92% of economic impact, and disproportionately affect vulnerable groups of people (World Risk Report 2016 from Alliance Development Works and United Nations University).

According to the Philippines Dashboard of the Climate Change Knowledge Portal Climate change is likely to increase the intensity and frequency of typhoons and heavy rainfalls, exacerbating flooding in existing flood-prone areas, increasing landslides and mudslides, and extend flooding to new areas (). Flood risk management in the Philippines has been ineffective due to a lack of integrated flood risk management planning, suboptimal flood protection infrastructure, limited investment, and inadequate local flood risk management.

To support improved flood management in the region, the EO4SD CR developed a prototype Inundation Monitoring Service (IMS) for the Jaluar River Basin, Panay Island. The IMS provides satellite-based, highly automated, open water surface identification tools that detect both seasonal fluctuations of water bodies and long-term changes. The service maps provide the extent of flooded areas over time, which can help build a picture of the flood response of an area.

Maximum inundation extents – Jalaur River Basin (1990 – 2015).

Flood risk assessment in Yanji City

Yanji City in the People’s Republic of China is highly exposed to flood risk, having experienced between ten and twenty-seven large flood events during the period between 1985 and 2011. The city is home to half a million people, 90% of whom live in urban areas. At the same time, Yanji suffers from inadequate infrastructure and lacks basic flood protection and water management systems, causing inconvenience and disruptions to daily life. Climate change increases the flood risk and threat to water supply, only making these problems worse.

In order to improve the city’s infrastructure and increase climate resilience of vulnerable people, the ADB and Chinese government embarked on the Jilin Yanji Low-Carbon Climate-Resilient Urban Development project Yanji City wanted to learn how to fine-tune the design of their activities, based on the EO data. Specifically, the project aimed to:

  • Develop an intelligent, sustainable, low carbon, urban transport system
  • Create a climate resilience plan for a ‘sponge city’
  • Improve water support and wastewater management systems
  • Increase institutional capacity for carbon and climate resilient urban infrastructure planning.

In order to accomplish this, a climate risk assessment was conducted that went beyond using downscaled GCM data, and was practically applicable and stakeholder oriented in order to highlight particular vulnerabilities and solutions.

To support the assessment the EO4SD CR used past EO images and precipitation and soil moisture data to map in great detail (up to 10m resolution) the extent and location of past flooding events. This identified areas repeatedly affected by flooding, and those only affected in large or unusual flooding events. Understanding how an area floods, and when, means that effective investments can be made in adopting the most appropriate flood management systems and infrastructure.

Maps showing Sentiel-2B imagery to assess flooding in Yanji, China. The image on the left shows the city before the heavy rains between July 20-23 2017. The image on the right from 22 July 2017 shows the city after the flood event. The blue lines indicate areas of flooding. Images are provided at a 10m resolution. Results have been crosschecked with SAR imagery from Sentinel-1B.

The satellite imagery was able to provide detailed information about a recent, historic flood event in Yanji City (see figure above). This information helped to identify areas, infrastructure and populations at risk from similar flood events.

EO data was also able to identify changes in land use and vegetation cover over time. This helps measure the impact of wetland rehabilitation on urban hydrology and river base flow. Satellite imagery can also be used to monitor levels of terrestrial water storage, providing baseline records of water level fluctuation and monthly updates. Future climate models projected an increase in rainfall for every month of the year, and some change in wind speed which could indicate changes in cyclone behaviour. The water supply is forecast to experience greater stress driven mainly by increases in demand, but climate change is also projected to diminish the availability of water. This feedback was delivered to the project at the end of May 2019, and is now being integrated in the delivery of their four project activities.

As demonstrated, EO data clearly has a wide range of applications, and as technology and access to data improves, the ability for EO data to play a key role in improving climate resilience and identifying effective capacity building development only increases. The ADB projects in both Yanji and the Philippines are ongoing, and the EO data provided by the EO4SD CR feeds into the planning and risk assessments phases of the projects. This will provide more robust information on which the ADB can base its future feasibility studies and investment design and implementation phases.

The engagement with the EO4SD CR will continue in both locations. Alongside the EO service provision the EO4SD CR have identified capacity building support to stakeholders to help build their awareness of EO services and how they might usefully be applied. With several capacity building options having been scoped, the stakeholders are better equipped in their decision making by having access to and a greater understanding of the impacts from EO Data. In the Philippines for example, capacity building responses included nature-based flood protection solutions with EO data identifying suitable locations, and the use of real-time EO data to monitor rivers, helping to strengthen early flood warning systems.


This article was originally published on the EO4SD Climate Resilience website.
Cover photo by Theodor Lundqvist on Unsplash.
Earth observation data enhances top climate tools through collaboration with International Finance Institutions

Earth observation data enhances top climate tools through collaboration with International Finance Institutions

Some of the most well-known and established climate change data platforms and tools are being further enhanced by integrating Earth Observation (EO) data. Through an ongoing collaboration between several International Finance Institutions (IFIs) and the European Space Agency’s Earth Observation for Sustainable Development Climate Resilience (EO4SD CR) cluster, Earth Observation products are in process to be integrated into platforms including the World Bank’s Climate Change Knowledge Portal, the International Finance Corporation’s (IFC) Risk Tools, Africa Risk Capacity’s (ARC) Africa RiskView, and the Inter-American Development Bank’s (IDB) Hydro-BID system.

The EO4SD CR cluster has been working with IFIs over the past year, to demonstrate how EO services can be applied to help build climate resilience. The cluster’s work has focussed on applying EO services to existing IFI investment projects, including Asian Development Bank projectsin the Philippines and China, and World Bank projects in Liberia and Lake Victoria basin. Alongside these projects, the EO4SD CR cluster has also sought to add value to existing services and tools that IFIs use to help facilitate improved climate resilience decision making.

The World Bank’s Climate Change Knowledge Portal

One such initiative is the EO4SD CR cluster’s collaboration with the World Bank’s Climate Change Knowledge Portal (CCKP); one of the world’s most high-profile, publicly available climate change data platforms. The WB’s CCKP provides global data on historical and future climate vulnerabilities and impacts. It is explorable through a web-based platform organised by ‘country’, ‘region’ and ‘watersheds’. The platform also includes socio-economic data to support climate resilient decision making.

Screenshot showing the map view of the CCKP organised by watershed. Source: World Bank’s Climate Change Knowledge Portal

Screenshot showing the map view of the CCKP organised by watershed. Source: World Bank’s Climate Change Knowledge PortalThe EO4SD CR cluster developed functions that would allow EO products to be served to the platform seamlessly when demanded by users. From a user perspective there is no difference in the operation of the CCKP, which simply draws down the data and serves it to the user. This has enabled the WB’s CCKP to include climate data that was not previously available to its users including sea level anomaly data (1993-2015), 2-meter surface temperatures (1979-2018), and sea surface temperatures (1991-2018).

These EO-based Essential Climate Variables (ECV) are provided in both raster and time-series formats allowing for images and time-series data to be used and overlaid. As shown in the image below, the sea level anomaly data can be displayed as a map, and several data points can be selected and compared using time series data, showing clearly the levels of variation across different geographies.

Sea level anomaly time series data (1993-2015) for Madagascar, Monrovia (Liberia) and Venice (Italy).

With the 2m temperature data the EO service provides the full time series and can show temperature variability and averages, making it possible to compare different time periods against each other.

2m surface temperature for Mozambique with data from the years 2016 and 2018 compared against the 2010-2015 average.

Provision to other tools and services

As well as collaborating with the World Bank’s CCKP, the cluster is also providing EO data to climate resilience tools from other organisations, including:

  • 1-day maximum precipitation data for a 20-year return level to the IFC’s Risk Tool.
  • Soil moisture monitoring (1978-present), daily precipitation (2006-present) for Sub-Saharan Africa to ARC’s Africa Risk View tool.
  • Algal pigment concentration for Ypacarai Lake (Paraguay), Titicaca Lake (Bolivia/Peru), and Panama Bay (Panama) 1997-2018 and wetland and water inventory for Pantanal (Brazil) to be integrated into IDB’s Hydro-Bid tool.

Over the next year, the cluster will continue to explore how EO services can be further integrated into existing climate risk portals and platforms. The work done so far indicates that there is a lot of potential for deploying EO services for climate resilience and using existing products provides a good opportunity for putting EO data to work in the near term.


This article was originally published on the EO4SD Climate Resilience website.
Cover photo by Mohit Kumar on Unsplash.
EO4SD Climate Resilience Cluster’s story so far

EO4SD Climate Resilience Cluster’s story so far

Earth Observation (EO) has emerged as a powerful method of providing timely and accurate information about the Earth’s atmosphere, landmasses, and oceans to inform and facilitate climate resilience development globally. This information combined with socioeconomic data, helps portray a very powerful idea surrounding a location’s adaptive capacity, its climate risks, and resilience building opportunities.

Since 2008, the European Space Agency (ESA) has collaborated with International Financing Institutions (IFIs) and their client countries to exploit the benefits of EO. Earth Observation for Sustainable Development (EO4SD) is an ESA initiative which aims to facilitate a merge of EO-based information with development operations at regional and national scales. The ESA EO4SD’s Climate Resilience Cluster is working to bring EO and climate-resilient decision making together through the development of an EO-based integrated climate screening and risk management service. The solution will provide an easily-accessible and accurate assessment of a location’s climate anomalies and climate risk indicators.

You can learn more about the EO4SD Climate Resilience Cluster’s work here.

This infographic gives an overview of the EO4SD’s Climate Resilience Cluster’s work so far:


This article was originally published on the EO4SD Climate Resilience website.
Cover photo by Nasa on Unsplash.
EO4SD climate cluster’s support further improves Africa’s leading drought and food security modelling tool

EO4SD climate cluster’s support further improves Africa’s leading drought and food security modelling tool

The African Risk Capacity’s Africa RiskView (ARV) tool combines Earth Observation (EO) data with population vulnerability data to provide an early-warning model that measures food insecurity and estimates response costs, enabling decision-makers to plan and respond quickly and efficiently to drought stresses. Through an ongoing collaboration with the European Space Agency’s (ESA) Earth Observation for Sustainable Development Climate Resilience (EO4SD CR) cluster, new data is being integrated into ARV allowing it to incorporate previously unavailable essential climate variables.

Rainfall is the main determinant of food security in Africa, as staple crop production is predominantly rainfed. As such, ARV uses a drought index based on a water balance model developed by the Food and Agriculture Organisation (FAO). This index compiles data on rainfall estimates, potential evapotranspiration, water holding capacity in the soil, crop type and their water demands, sowing dates, and length of growing period. These are used to estimate the extent to which the water requirements of the crop have been met, and therefore the food security risk. Predefined benchmarks are used to work out if the drought conditions at the end of a season are an anomaly or not.

Many of these datasets are reliant upon EO data. For instance, NOAA provides estimates of evapotranspiration and rainfall estimates are obtained from different satellite-based sources. To complement this the EO4SD CR have worked with the Africa Risk Capacity to identify other climate variables that could usefully be incorporated into ARV.

After extensive consultation and engagement, the EO4SD CR cluster is now in the process of providing long time series and monitoring on soil moisture, which informs soil water holding capacity estimates, as well as new datasets of precipitation measurements for drought monitoring. The EO4SD and ARC teams are currently working hand-in-hand to allow Africa RiskView ingesting new Copernicus and ESA products.

ARV data can be aggregated to make a particular shape that corresponds to an administrative region, agro-ecological zones, or crop growing regions, making it easier to observe specific areas over time. The frequency and scale of these observations make it possible for the ARV to provide early warnings of drought, as it monitors the growing season from crop sowing time to maturity, indicating which areas in a region, country or province have received minimal rainfall, water deficits, or excess water at the various stages of crop growth, all of which can effect crop yield.

Africa RiskView default My View showing Kenya EAR1 Arid (long rains) season

Africa RiskView combines these observations with data on the population to estimate how many people may be directly affected by the observed drought, and how much the response costs may be. The vulnerability profile is based on household survey data from national governments and the World Food Programme’s Comprehensive Food Security and Vulnerability Analysis surveys. This data can be adjusted and input by different users, and matched with the different clusters of observational data to provide a truly tailored description of drought effects to specific populations. By identifying and quantifying risk in this objective way, this early warning tool can also help countries to plan appropriate drought response actions and food security investments.

The information produced by Africa Risk View also has broader applications. The EO time-series data sets can build understanding about the scale of effects associated with different drought impacts, helping to develop early food security assessments in specific geographic areas or contingency planning and emergency preparedness for future shocks in a country. It can also improve understanding of the drivers and causes of food insecurity in areas and identify which investments or risk management strategies are best. The tool could also be helpful in guiding planning and investment decisions aimed at enhancing agricultural productivity or market development and be used to support micro insurance programmes. Currently, the tool focuses on drought, but there is ongoing work to include other risks, including river flooding and tropical cyclones.


This articles was originally published on the EO4SD Climate Resilience Cluster website.
Cover photo from Wikimedia Commons.
Meet ADAM

Meet ADAM

ADAM is an online, cross-domain application and software platform that facilitates the access to a large volume and variety of global, Earth Observation (EO)-based, environmental data. Rather than serving as a generic data access platform, dedicated interfaces can be developed for specific needs in the fields of education, agriculture, cultural heritage and public health, amongst others.

Given ADAM’s flexibility and enormous capabilities, the Earth Observation for Sustainable development (EO4SD) Climate Resilience cluster project, an initiative of the European Space Agency (ESA), has adapted ADAM to provide International Financing Institutions (IFI)’s regional and global programmes with enhanced climate risk management capabilities. With the help of the ADAM platform, the ESA EO4SD Climate Resilience project aims to provide insights about the real potential of EO in support of climate resilient decision-making.

ADAM’s primary benefit is its ability to make all essential datasets readily available in a single dynamic, adaptable and progressive platform. Data can be portrayed in a number of ways; visualised via a 3D globe, including near real time observations from satellites and climate change projection information up to 2100; extracted and processed from via Jupyter notebooks, inbuilt processing services and via dedicated application programming interfaces (APIs); and finally downloaded, both original data and / or processing results.

To increase the impact of ADAM in the EO4SD project, training and capacity building programmes offered by the EO4SD consortium aim to provide project stakeholders with the opportunity to utilise ADAM for their own purposes. The ultimate objective is to foster a new economic sector, with local start-ups providing innovative EO-based climate services.

The EO4SD climate resilience platform has already been used in real-life cases to support IFIs in assessing climate impacts, as well as managing the risks and capitalising on the opportunities related to climate change. This solution provides an easy assessment of climate anomalies and the ability to undertake rapid calculation of climate risk indicators, including their evolution over time. But this is only the start…

The next steps for the platform are to extend the data offered, implement data aggregation and processing functions, and perform capacity building activities that allow local users to exploit the platform to the maximum extent.

To learn more, visit the ADAM website here


This article was originally published on the EO4SD Climate Resilience Website.
Cover photo by NASA on Unsplash.
ESA’s EO4SD climate resilience cluster collaborates with World Bank in Liberia

ESA’s EO4SD climate resilience cluster collaborates with World Bank in Liberia

The European Space Agency’s (ESA) Earth Observation for Sustainable Development (EO4SD) climate resilience cluster, is working with the World Bank to provide Earth observation data in support of its Monrovia Integrated Development Project (MIDP). Although focussed on the Liberian capital, the MIDP aims to identify pragmatic, spatially integrated, and location specific interventions that contribute to service delivery, improved welfare, and the creation of jobs throughout the country. To support the World Bank and its stakeholders, The EO4SD climate cluster has provided several products including modelling sea level rise and its impacts on coastal population (coastal and inland flooding) and coastal shoreline erosion based on historical evidence. Earth observation (EO) data and climate projection derived information can be used to model the impacts of disaster and climate change on the developed land, and offer alternative scenarios of how Monrovia could develop.

A turbulent history

For the past several decades, Liberia has experienced dramatic levels of urbanisation. This trend is primarily a product of its history of instability and conflict. Years of civil war during the late 20th century killed several hundred thousand people and displaced more than a million others, half of Liberia’s population at the time. As of 2018, Liberia remained one of the poorest countries in the world, with its potential for economic growth and job creation remaining largely unexploited. Low capital investments in economic and social infrastructure have exacerbated the development challenges in the country.

With Liberia continuing to urbanise at pace, climate change is projected to aggravate existing developmental challenges, slowing down economic growth through reduced productivity from climate-sensitive sectors and damage to critical infrastructure. Climate change also poses critical threats to Liberia’s public health, the agriculture sector, and its coastal zone where much of the population and assets are concentrated.

Liberia’s capital city, Monrovia, has all the characteristics of a fragile city. A majority of the population in Greater Monrovia lives in slums, with some being subject to frequent flooding, a problem that will be exacerbated by climate change. Electricity and piped water are scarce and are typically found in houses belonging to the upper class. Additionally, Greater Monrovia’s road capacity and education systems lag far behind those of other cities.

The World Bank’s MIDP aims to identify adaptation policies that can help Monrovia be better prepared to absorb urban growth in a context of extreme poverty, fragility and increasing risks from climate change. Several adaptation solutions were offered up by the EO4SD climate cluster, but two activities were ultimately chosen to compliment the World Bank’s Great Monrovia Urban Review project.

1) Soil erosion service

Since 2013, sea level rise and coastal erosion has displaced more than 6,500 and destroyed 800 houses in the West Point township of Monrovia. Sea level rise leads to erosion and causes the shoreline to retreat landwards, increasing the risk of displacement. Dwellings built in 2010, favoured by land gains due to the shoreline and river dynamics, are at a high risk of flooding.

To support this issue, the cluster undertook shoreline monitoring and change detection in Greater Monrovia, evidencing 41km shoreline changes from a 34-year satellite (1984-2019) series. The service uses a thoroughly tested methodology for consistent and reliable water body detection based on High Resolution optical imagery. Optimal regular detection of surface water was obtained through appropriate spectral indices and biophysical variables derived from the EO images. The analysis estimates that the land loss area from 1984 to 2019 in the Greater Monrovia’s coastline is not likely to be less than 0.8 square kilometres.

The soil erosion service based on EO data helps the World Bank determine where to best make investments and identify hotspot areas that need immediate attention.

Shoreline retreat from 1984 to 2019 in New Kru Town (Greater Monrovia)

2) Flood Risk Service

The second EO based service involves hot spot analysis of flood modelling in Monrovia, evidencing the potential coastal and inland flooding for the city in the year 2030. Using high-resolution sea-level rise data obtained from shoreline change in Monrovia’s metropolitan area from 1985 to 2019, the sea level rise estimation is used to identify coastal and inland flood risk areas. The potential of these flood events is then combined with population exposure obtained from the population density (2007 census) in Clara Town, Monrovia to estimate the flood risk to the general population.

The flood risk analysis could also be enhanced, in future, with the inclusion of critical infrastructure analyses, hydrologic information, and projections of coastal erosion and land subsidence. These flood maps can help authorities to identify the most effective actions to manage flood risk, develop adaptation plans, consider where natural flood management could be most effective, and enable better planning decisions to avoid unnecessary development in flood risk areas. This illustrates how EO can support the implementation of climate adaptation solutions for regions affected by sea level rise and flooding.

Hotspot analysis of flood risk intersected with population density for Clara Town (Greater Monrovia). Risk severity depicted by red gradient colours

Next steps and potential for additional application?

The two prototype services described above were delivered within the first phase of the EO4SD climate resilience cluster project, ending July 2019. In the second phase of the project, which runs until June 2021, further EO-based services will be provided, including integration of climate projections and socioeconomic data in the flood risk analysis, to better identify climate risks, and an estimation of projected coastal erosion up to 2030. New products and services can also be provided for different hazards or locations. With the World Bank’s MIDP project currently in its planning stages, these EO-based services help lay the groundwork for the World Bank team and city stakeholders in identifying key climate-resilient interventions for the city of Monrovia, to be implemented over the coming years.


This article was originally published on the EO4SD Climate Resilience Cluster website.
Cover photo is of Liberia, Africa / from Wikimedia Commons.
Earth Observation data: the new frontier in climate resilience

Earth Observation data: the new frontier in climate resilience

Climate change is among the top societal challenges with global impact. It has wide-ranging impacts across socio-economic systems, with the most severe effects being faced by poor and vulnerable communities. Making climate-resilient decisions requires good quality data and information, often lacking in many developing regions of the world. Earth observation (EO) data has the capability to capture large-scale environmental data over a range of spatial, spectral and temporal resolutions. Some governments have started accessing EO data to incorporate adaptation options into their planning and improve the climate resilience of livelihoods and production systems. For instance, since 2005, India has launched 17 EO satellites into space to gather invaluable information on different climate variables to improve resource management and disseminate timely disaster warnings.

Building resilience in regions where data is scarce

EO is the gathering of information about the Earth’s physical, chemical and biological systems and has the capability to do so across remote and inaccessible terrain. It involves monitoring and assessing the status of and changes in the natural and man-made environment. EO data provide large quantities of timely and accurate environmental information, which, when combined with socioeconomic data can give unique insights into managing climate risks. This is especially important in regions where insufficient information is available from in-situ measurements, or where on-the-ground assessments of infrastructure are not possible due to safety concerns. EO satellites can collect real time data on a wide range of indicators such as water distribution, land use, water cycles, atmospheric profiles, heat mapping, sea surface evaluations, and global-regional energy exchanges.

EO data can help governments around the world not only prepare for climate change impacts and natural disasters, but also inform sustainable and climate resilient development planning to account for future climate risks.

Image: MODIS daily land surface temperature

The Earth Observation for Sustainable Development (EO4SD) Climate Resilience Cluster, an initiative by the European Space Agency (ESA), combines EO-based environmental information with socioeconomic and climate data in developing countries to help them meet long-term climate resilient development planning goals. Over the past year, the Cluster has been collaborating with international financing institutions (IFIs) and other international agencies such as the World Bank, Asian Development Bank (ADB), Inter-American Development Bank (IDB), African Risk Capacity (ARC), Multilateral Investment Guarantee Agency (MIGA) and the International Finance Corporation (IFC) to support with EO-based data their corporate climate screening tools, to assist on climate resilience investment projects, and to build capacity in IFI client states to integrate EO data in their development planning. The Cluster project is being carried out in 2 phases: Phase 1 (2018-19) has involved strategic planning and stakeholder engagement; and Phase 2 (2019-21) will involve service demonstration and preparing IFIs and their client states to use EO services independently.

Working with the World Bank in Monrovia

One example of the Cluster’s work is in Monrovia, Liberia, in collaboration with World Bank’s Greater Monrovia Urban Review project, which aims identify policies that can help Monrovia be better prepared to absorb urban growth in a context of extreme poverty/informality, fragility and increasing risks from climate change.

Monrovia is at extremely high risk of coastal and inland flooding, which has already displaced poor communities living along the coastline and will only worsen with climate change. The Cluster has developed EO product prototypes for coastal and inland risk flooding due to sea level rise and coastal erosion in Monrovia. In Phase 2, new products will be developed and the prototypes further elaborated by integrating other datasets, for example, the flood risk analysis can integrate critical infrastructure data, hydrologic information, projections for coastal erosion and land subsidence. Employing a mix of EO, climate projections and socioeconomic data will help integrate climate resilience into investments under the Greater Monrovia projects.

Apart from project-specific interventions, the Cluster is also enhancing some IFIs’ existing climate risk assessment tools. One example is the World Bank’s Climate Change Knowledge Portal (CCKP), which aims to improve the integration of scientific data into decision making processes. The portal hosts historical data and climate projections and includes sectoral indicators. The EO4SD cluster is providing EO-based climate data automatically to the CCKP via an Application Programming Interface (API). Products currently provided to CCKP include 2m temperature, sea surface temperature and sea level anomaly. Data provision will continue into Phase 2 (Jun 2019 Jun 2021), expanding to more products as requested by the World Bank.

Access to the sea of data collected by EO satellites, combined with socioeconomic information, can support the implementation of climate adaptation solutions for regions affected by a variety of climate hazards. This will go a long way in helping countries improve their preparedness for natural disasters and minimise economic losses from damage to infrastructure, property and livelihoods, as well as loss of human life.


This article was originally published on the EO4SD Climate Resilience website.
Cover photo by NASA on Unsplash.