Citizen Science

According to SEPA, 2015, Natural Flood Management (NFM) involves techniques that aim to work with natural hydrological and morphological processes, features and characteristics to manage the sources and pathways of flood waters. These techniques include restoration, enhancement and alteration of natural features and characteristics, but exclude traditional flood defence engineering that works against or disrupts these natural processes. Surface runoff is one key component impacting floods in a catchment area. Changes in the environment caused by human activities, changes to rainfall patterns caused by climate change as well as overall changes in the land surface can greatly contribute to runoff increase. Traditional runoff models use a number of different variables e.g. soil type, ground cover type and rainfall to estimate the runoff for a given area. Earth observation (EO) data has been widely used to monitor environmental variables including surface runoff (Gajbhiye, 2015). EO data applications are well-known to be a very reliable and cost-effective alternative to the conventional methods of monitoring and modelling environmental changes. The present study aims to demonstrate the effectiveness use of Sentinel-1 and Sentinel-2 data in addition to other datasets (DEM and VHR image) to map and monitor areas where runoff hazard is present. A Vulnerability Index is proposed based on value-added information originated from EO data. The proof of concept was carried out in the Hendred Farm (West Thames catchment area, United Kingdom, UK) during the 2016 growing season (March to September). The methodology involved the generation of two Land Cover thematic layers using a combination of co-polarised and cross-polarised images, and extracting the interferometric coherence and intensity over Single Look Complex product pairs from Sentinel-1 images. Sentinel-2 images from two distinct dates during the growing season (6 June and 15 August) were used to generate Vegetation Indexes (NDVI, NDWI, LAI, FAPAR and FCOVER). A slope thematic layer was created using a DEM (SRTM 1-sec resolution). Furthermore, a spatial framework was proposed and tillage distribution and direction thematic layer was created using a very high resolution image (WV3 – 04 May 2016). Classification maps were produced by integrating the different thematic layers and presenting runoff hazard spatial distribution as high, medium and low. Even though the study area was limited, it is believed that the proposed methodology is able to demonstrate that runoff hazard areas can be identified and monitored using radar and optical images over time. The real value of being able to assess and monitor runoff hazard is when large catchment areas are considered and traditional methods of monitoring are not cost-effective. Thus, the future steps of this study is to extend the methodology described here to provide a high level assessment of wider areas prior taking more detailed NFM actions.

SnapPlanet is on a mission to democratise the access and use of Earth Observation data in an easy, affordable and enjoyable way. At its core, SnapPlanet provides a “photographic centric” mobile application to create beautiful images of the Earth from space within seconds, thanks to the freely available ten meters Sentinel-2 imagery. These data ensure a free high-resolution snapping service for all users. These “snaps” can be annotated, commented and shared, making SnapPlanet a great tool to raise awareness of our living planet. Thus, by combining the ever-increasing availability of Earth observation images with the advantages of a social network for everyone, SnapPlanet wants to drive new uses of EO data to empower citizens, journalists, scientists to tell stories that can have a positive impact on society and environment on a global scale.

This study is part of the EU H2020 research Project FLOWERED (de-FLuoridation technologies for imprOving quality of WatEr and agRo-animal products along the East African Rift Valley in the context of aDaptation to climate change). FLOWERED project aims to develop technologies and methodologies at cross-boundary catchment scales to manage the risks associated with high Fluoride water supply in Africa, focusing on three representative test areas along the African Rift Valley (i.e. Ethiopia, Kenya and Tanzania), characterized by high fluoride contents in waters and soils, water scarcity, overexploitation of groundwater and high vulnerability to risks arising from climate change, as drought and desertification. It also is empowering local communities to take responsibility for the integrated-sustainability of the natural resources, growing national and international environmental priorities, enhancing transboundary cooperation and promoting local ownership based on a scientific and technological approach. Within the FLOWERED project, the transition from the land cover to the land use and water use maps is provided through the development of a mobile application (FLOWERED-GeoDBapp ). It is dedicated to the collection of local geo-information on land use, water uses, irrigation systems, household features, use of drinking water and the other information needful for the specific knowledge of water supply involving local communities through participative approach. This system is structured to be populated, through an action of crowd-generating data by local communities (students and people involved mainly by NGOs). The SHAREGEODBapp is proposed as an innovative tool for water management and agriculture institutions at regional and local level.

Biological invasions by Invasive Alien Species (IAS) are not only one of the greatest threats to biodiversity and ecosystems functioning worldwide but also a potential health hazard for humans, with extensive economical costs with EU estimating up to 12 Billion € per year. Reducing costs and increasing the efficiency of IAS monitoring is vital for a sustainable strategy to counter biological invasions. Free and open access to Earth Observation data coupled with Citizen Science and data gathering platforms can provide a unique opportunity to curb these costs. Furthermore, these programmes contribute to increase citizen awareness and participation in the topic of IAS monitoring which is crucial for prevention and early detection. The web-platform invasoras.pt has been an example of success in increasing citizen awareness and participation in this topic, specifically towards invasive alien plants. Besides being part of a wider countywide set of activities that encourage active action by citizens it also allows the collection and storage of Volunteered Geographic Information (VGI) of invasive plants. This data is validated by experts and made totally available for public use. Coupling this continuous and increasing collection of data with freely available Earth Observation products offers is a great opportunity to increase the ability of monitoring IAP at very low operational costs. The availability of free Earth Observation products for continuous monitoring and their consistent improvement in recent years is a unique opportunity to improve and increase the scope of IAP monitoring. As a case study we’ve chosen three of the worst IAP in Portugal: Acacia longifolia, Acacia melanoxylon and Acacia dealbata and Acacia saligna. All these are characterized by very strong flowering events that occurring during Portuguese winter. The sheer intensity of their flowering facilitates their visibility in the field and hypothetically also through Earth Observation satellites. Furthermore, a biocontrol has been introduced recently in the country which is expected to seriously disrupt the flower production of A. longifolia. As such it is significant for future monitoring of this biocontrol expansion to establish if flowering is or isn’t detectable by satellite Earth Observation. While previous Earth Observation missions as the Landsat already offered the opportunity for monitoring IAP but they were hindered by the lower spatial resolutions and revisit time. Especially during winter, cloud cover is very prevalent. Therefore Sentinel 2A and 2B satellites are a unique opportunity for detection of these IAP because they offer both an increased spatial resolution as well as a smaller revisit time. In this research we showcase the possibility of using VGI to validate detection of these four IAP throughout various seasons using Sentinel 2A and 2B satellites. To do this, we pre-selected areas of known homogeneous and monospecific stands of these species and evaluated their detectability in the various seasons which are validated by the VGI. It is an example of how free-to-use EO data and simple citizen data gathering platforms can easily contribute to improve the monitoring of IAS at very large scales.

This presentation will document the design and development of a practical solution to climate change: the Cli-Mate? app. Cli-Mate? is a social network service for people interested about climate change. The application allows users to record and share environmental data using their iPhones, acting as a bridge between scientists and citizens concerned about climate change. Data collected through the Cli-Mate? app could form a much needed local record of climate change worldwide, which could help scientists to validate observations made by satellites and help them to make predictions about climate change.

Citizen science, crowdsourcing and volunteered geographic information have become important components of participatory scientific research. Within the domain of post-disaster damage assessment, crowdsourcing can provide data to assist humanitarian organizations in their relief and recovery efforts. Several citizen science powered tools already exist for data collection, including those that support visual image interpretation and online interactive mapping. One example of such a tool is Picture Pile, which is a cross-platform application designed to be a generic and flexible way to ingest satellite imagery for rapid classification. As part of the ESA’s Crowd4Sat initiative led by Imperative Space, this study demonstrates how satellite imagery coupled with a crowdsourcing-based application (Picture Pile) can support humanitarian efforts. We demonstrate how satellite image interpretation tasks within Picture Pile can be crowdsourced in a demonstration case that uses imagery before and after Hurricane Matthew, which affected large regions of Haiti in September 2016. Volunteers were asked a simple yes/no question about what they could see with regards to building damage from the hurricane in images before and after this event. Since the task is simple and clearly formulated, a rapid review of large areas was done with the help of 135 volunteers who completed 120,000+ tasks within a few days of the start of the campaign. We present the latest results and discuss the lessons learned from the campaign which ran in May 2017. We found that most volunteers showed a high agreement rate with our experts, supporting the validity of such a crowd-driven approach for rapid post-disaster damage assessments. The proposed approach brings satellite imagery to volunteers and can be used to detect various features in different disaster events such as damaged buildings, flooded areas, areas burned by wildfires, damaged roads, and storms, among others. These features are easily recognizable from very high resolution satellite imagery, even to the lesser trained eyes of new participants. Other than collecting data, this approach also helps to increase citizen awareness of natural disasters and provides everyone with a unique opportunity to contribute directly to relief efforts. Picture Pile is intended to supplement existing approaches for post-disaster damage assessment and can be used by different networks of volunteers (e.g. the Humanitarian OpenStreetMap Team) to assess damage rapidly and to create up-to-date maps for timely response to disaster events.

By the year 2050, global population living in metropolitan areas is estimated to grow significantly and is expected to cause enormous strain on infrastructure and resources. Metropolitan areas are typically very large areas with dense city centers and large expanding suburbs. With limited resources and rising population and pollution concerns, such areas need to grow in an efficient, sustainable and resilient way. A significant concern is how transport and mobility in such areas can scale up with such increasing demands. To this end, the Seta project is currently developing Big Data solutions to create a technology and methodology that will address these challenges and change the way mobility is organised, monitored and planned in such areas. The project collects massive volumes of mobility data via crowdsourcing, physical sensors, video cameras, and environmental sensors. The data is linked, fused and exploited to model mobility with a precision, granularity and dynamicity that is impossible with today's technologies. Essential to the success of the project is the key role played by citizens and communities. The project exploits different crowdsourcing mechanisms such as participatory and opportunistic to provide massive volumes of Volunteered Geographic Information (VGI). In this talk, we will discuss how hundreds of thousands of users, throughout three use case cities in Europe (Birmingham, UK; Santander, Spain; and Turin, Italy) contribute to opportunistically providing VGI on motorised and non-motorised mobility via mobile applications. While crowdsourced motorised mobility data informs various aspects of traffic and infrastructure management such as road occupancy, vehicle speed, pollution estimation and so on, crowdsourced non-motorised mobility provides significant insights into land use and function as well as how citizens and communities organise their daily commutes, activities and lifestyle. At the core of the project is a citizens observatories approach, where citizens can actively provide real-time information about traffic and mobility conditions and issues. This talk will present how such massive volumes of data is collected, processed and analysed to provide exploratory analysis for decision support. We will share our initial results and insights following the first phase of evaluations in the three cities and discuss how we plan the next phase of development in the project.