The number and severity of natural disasters in coastal regions in Latin America and the Caribbean (LAC) have steadily increased over the past two decades, causing significant impact on the economic and social development of many countries in our region and affecting disproportionately the poorest communities.
Coastal zones are some of the most vulnerable areas to the impacts of natural hazards. The population concentrated along low-elevation shorelines and the added threat of climate change are putting our coasts at an increased risk of flooding, erosion, and extreme weather events. These coastal hazards imperil hundreds of millions of vulnerable people, crucial infrastructure, tourism activities, and trade, causing significant human suffering and losses to national economies.
Managing coastal risk and response to disasters is a national priority for many LAC countries. As a result, the Inter-American Development Bank (IDB) has prioritized risk management strategies to cope with existing risk, prepare for future impacts of climate change, and build coastal resilience (rather than spending humanitarian and other aid only after disasters strike). One of such strategies is the broader use of nature-based solutions for coastal risk reduction.
Using coral reefs, seagrasses and mangroves can deflect or dampen wave energy, absorb flood waters, and consequently reduce flood damages. In other words, nature can provide sustainable, cost-effective, multi-purpose and flexible alternatives to built infrastructure for coastal protection. The challenge now is to foster rapid mainstreaming of these approaches in disaster risk management policies.
This is more easily said than done. One major technical challenge for mainstreaming ecosystem services in disaster risk management is that there is an exorbitant cost (both in monetary terms and time commitment) associated with collecting primary data on coastal ecosystems.
Through a technical cooperation on innovation in integrated coastal zone management (ICZM) (RG-T3081), the IDB has identified innovative data sources that are essential for estimating economic benefits of coastal ecosystem services, including the application of new technologies that are facilitating use of more comprehensive data in ecosystem service and risk modeling at lower costs.
Some of the important data technologies that we have piloted include imagery (multispectral satellite data, aerial photographs) and minimally processed data sources (LiDAR, social media data), as well as products derived through substantial processing (WorldPop population estimates or crowdsourcing). These data have enormous potential to improve ecosystem service-based decision making, which frequently requires up-to-date information that is globally comparable but locally relevant. Our research shows that four sources provide data that are comprehensive over large areas, available at regular time intervals, and usually are relatively low-cost or even free.
First, elevation data, (either of the land surface, or features on the surface, such as buildings) can be created using laser altimetry (e.g. LiDAR), stereo imagery or Structure from Motion (SFM) which uses overlapping images to create a three-dimensional view and therefore, elevation values. Because of the increased availability of remote sensing data sets, computing power, and cloud platforms (e.g. Google Earth Engine; (Pangeo), novel spatial analyses involving fusion of data sources, time-series, and machine learning algorithms are now possible and cost-effective.
Second, social media data from a growing number of sources (e.g., Flickr, Twitter, Instagram) also are useful for certain applications in data-poor situations or to supplement other data sources. For example, social media’s geo-tagged spatial information has been used and tested in estimating tourism visitation rates in a wide range of locations, including in coastal and marine systems.
Third, crowdsourced data, which refers to topic-specific data derived from a network of individual contributors, can be used to characterize biodiversity and human infrastructure such as roads and buildings. In our pilots, we have used two of the most well-known worldwide crowdsourced data sets: OpenStreetMap and iNaturalist, infrastructure and science focused data platforms and communities.
Fourth, free and open-source data sources are another valuable resource for developing repeatable, open, transferable, and cost-efficient databases. For example, a variety of global free and/or open-source Digital Elevation Models (DEMs) are available, including MERIT DEM, ALOS Global Digital Surface Model, and TanDEM-X. Population information can be accessed through the global WorldPop while proxies for economic activity ca be generated using Nighttime light datasets.
The IDB continues to embrace technological innovations in earth observations, in order to increase the accuracy and relevance of nature-based solutions information in disaster risk reduction approaches. We have established innovative partnerships with academia to test and implement nature-based options, with the goal of rapidly transforming ICZM. These data technologies offer hope that more resilient, nature-based approaches can increasingly be part of solutions for managing risk.
Image credits: IDB
Leave a Reply