The Role of Citizen Science in Earth Observation

Abstract

Citizen Science (CS) and crowdsourcing are two potentially valuable sources of data for Earth Observation (EO), which have yet to be fully exploited. Research in this area has increased rapidly during the last two decades, and there are now many examples of CS projects that could provide valuable calibration and validation data for EO, yet are not integrated into operational monitoring systems. A special issue on the role of CS in EO has revealed continued trends in applications, covering a diverse set of fields from disaster response to environmental monitoring (land cover, forests, biodiversity and phenology). These papers touch upon many key challenges of CS including data quality and citizen engagement as well as the added value of CS including lower costs, higher temporal frequency and use of the data for calibration and validation of remotely-sensed imagery. Although still in the early stages of development, CS for EO clearly has a promising role to play in the future.

Capacity Building for High-Resolution Land Cover Intercomparison and Validation: What Is Available and What Is Needed

“…The non-stop developments in space technology and the success of crowdsourcing projects currently produce a rich and constant amount of data (space and in-situ observations, respectively) with great potential for LC-related purposes. The combination of these two types of data is also opening new and interesting possibilities (Fritz et al, 2017). However, if on one side there is an increased availability of LC maps, on the other side it is fundamental that their usage is preceded by a proper quality assessment.…”

“…For instance, in the last few years a number of EU projects (so-called Citizen Observatories) have been funded with this exact purpose, including LandSense (https://landsense.eu), SCENT (https://scent-project.eu) and GroundTruth2.0 (http://gt20.eu). Fritz et al (2017) observe that the primary actions performed by citizens in this context consist of image interpretation and in-situ data collection, both of which are useful for calibrating and validating satellite imagery or derived products such as LC maps. Fonte et al (2015) review the use of crowdsourced geographic information as reference data for LC map validation and analyse the potentially most useful projects and types of citizen-sensed datasets.…”

Open educational resources for validation of global high-resolution land cover maps

“…Secondly, as the software available for validation are often complicated to use and not well-documented , a set of user-friendly software to validate LC maps was developed, and detailed educational resources were created to address this issue. Lastly, as there is often a lack of accurate and up-to-date reference data because their collection is labor intensive and expensive (Stehman et al, 2000), an application was developed for collecting LC data in situ to assist in the creation of LC reference dataset that is of great importance for validation (See et al, 2015;Fritz et al, 2017;Stehman et al, 2018;McCallum et al, 2018). All the software developed was presented to the participants of the workshops with step-by-step instructions.…”

Improving Land Cover Mapping: A Mobile Application Based on Esa Sentinel 2 Imagery

“…The diffusion of the Internet has encouraged the geographic information sharing as well as the development and the availability of volunteered geographic information (VGI) tools (Flanaginì et al, 2008) in the Land Cover domain too (Fritz et al, 2009;Gengler et al, 2016;Salk et al, 2016). In the meanwhile, the circulation of locationenabled mobile devices has created a number of opportunities to involve citizens in field data acquisition (Fritz et al, 2017;Clark et al, 2011) and collection: citizens are sensors of location-based information (Goodchild, 2007). Geospatial information is a good challenge for remote sensing science: map services allows users to reach remote sensing products as well as other map layers with a relatively simple usability.…”