Today, a growing number of regulatory agencies (including EPA, the Securities and Exchange Commission, and the Food and Drug Administration) see social media and online collaboration as a means of providing richer, more useful, and more interactive pathways for community participation. For EPA and its stakeholders, the question is whether the agency can take advantage of this growing social interconnectivity to engage the public in environmental protection better while bolstering both its science activities and its capacity for effective regulatory monitoring and enforcement. There are a number of ways in which crowdsourcing or citizen science could augment or enhance EPA’s scientific and regulatory capabilities. They include harnessing new technologies to engage broader communities along the lines of crowdsourced data collection, especially in the context of environmental monitoring, exposure assessment, health surveillance, and social behaviors; crowdsourced data classification and analysis; and crowdsourced environmental problem-solving. Crowdsourcing also provides an opportunity for EPA to gain a better understanding of the general sentiment of the public on issues that are of concern to EPA.
Crowdsourcing initiatives are typically low in cost because the most expensive resource (people’s time) is supplied voluntarily. Whether classifying galaxies or recording observations of bird species or local environmental quality, participants in a crowdsourcing project are intrinsically motivated to participate. For an agency like EPA, crowdsourcing presents an opportunity to gather and analyze large amounts of data or input inexpensively. That being said, crowdsourcing projects are not free to run either. There are costs involved in supplying the infrastructure for participation (typically a Web site or mobile interface where participants can record observations and discuss issues) and managing the overall effort.
Acquisition of Environmental Data through Remote Sensing
In the 40 years since the launch of Landsat 1—the first Earth-observing satellite-borne sensor designed expressly to study the planet’s land surfaces— there have been enormous advances in remote-sensing systems for environmental mapping and monitoring. They include multispectral digital imaging systems and imaging radar (1970s), hyperspectral imaging systems (1980s), and profiling and imaging LiDAR (1990s to present). In that period, remote sensing has benefited from rapid improvements in instrument capabilities and calibration, positional control and global positioning systems, computer performance, processing algorithms and software, fusion of imagery from multiple sensors, and closer integration with geographic information system and ground measurements and monitoring systems. As a result, remote sensing of the environment has evolved from a narrow research community to a large and diverse user community that is applying remote-sensing products on local, regional, and global scales (Schaepman et al. 2009).