Mapping Cropland in Ethiopia Using Crowdsourcing

The spatial distribution of cropland is an important input to many applications including food security monitoring and economic land use modeling. Global land cover maps derived from remote sensing are one source of cropland but they are currently not accurate enough in the cropland domain to meet the needs of the user community. Moreover, when compared with one another, these land cover products show large areas of spatial disagreement, which makes the choice very difficult regarding which land cover product to use. This paper takes an entirely different approach to mapping cropland, using crowdsourcing of Google Earth imagery via tools in Geo-Wiki. Using sample data generated by a crowdsourcing campaign for the collection of the degree of cultivation and settlement in Ethiopia, a cropland map was created using simple inverse distance weighted interpolation. The map was validated using data from the GOFC-GOLD validation portal and an independent crowdsourced dataset from Geo-Wiki. The results show that the crowdsourced cropland map for Ethiopia has a higher overall accuracy than the individual global land cover products for this country. Such an approach has great potential for mapping cropland in other countries where such data do not currently exist. Not only is the approach inexpensive but the data can be collected over a very short period of time using an existing network of volunteers.

Collecting volunteered geographic information from the Global Navigation Satellite System(GNSS):experiences from the CAMALIOT project

Raw observations(carrier-phase and code observations)from the Global Navigation Satellite System(GNSS)can now be accessed from Android mobile phones(Version 7.0 onwards).This paves the way for GNSS data to be utilized for low-cost precise positioning or in ionospheric or tropospheric applications.This paper presents results from data collection campaigns using the CAMALIOT mobile app.In the frst campaign,116.3 billion measurements from 11,828 mobile devices were collected from all continents.Although participation decreased during the second campaign,data are still being collected globally.In this contribution,we demonstrate the potential of volunteered geographic information(VGl)from mobile phones to fill data gaps in geodetic station networks that collect GNSS data,e.g.in Brazil,but also how the data can provide a denser set of observations than current networks in countries across Europe.We also show that mobile phones capable of dual-frequency reception,which is an emerging technology that can provide a richer source of GNSS data,are contributing in a substantial way.Finally,we present the results from a survey of participants to indicate that participation is diverse in terms of backgrounds and geography,where the dominant motivation for participation is to contribute to scientific research.

Technologies to Support Community Flood Disaster Risk Reduction

Floods affect more people globally than any other type of natural hazard. Great potential exists for new technologies to support flood disaster risk reduction. In addition to existing expert-based data collection and analysis, direct input from communities and citizens across the globe may also be used to monitor, validate, and reduce flood risk. New technologies have already been proven to effectively aid in humanitarian response and recovery. However, while ex-ante technologies are increasingly utilized to collect information on exposure, efforts directed towards assessing and monitoring hazards and vulnerability remain limited. Hazard model validation and social vulnerability assessment deserve particular attention. New technologies offer great potential for engaging people and facilitating the coproduction of knowledge.

GEOEssential–mainstreaming workflows from data sources to environment policy indicators with essential variables

When defining indicators on the environment,the use of existing initiatives should be a priority rather than redefining indicators each time.From an Information,Communication and Technology perspective,data interoperability and standardization are critical to improve data access and exchange as promoted by the Group on Earth Observations.GEOEssential is following an end-user driven approach by defining Essential Variables(EVs),as an intermediate value between environmental policy indicators and their appropriate data sources.From international to local scales,environmental policies and indicators are increasingly percolating down from the global to the local agendas.The scientific business processes for the generation of EVs and related indicators can be formalized in workflows specifying the necessary logical steps.To this aim,GEOEssential is developing a Virtual Laboratory the main objective of which is to instantiate conceptual workflows,which are stored in a dedicated knowledge base,generating executable workflows.To interpret and present the relevant outputs/results carried out by the different thematic workflows considered in GEOEssential(i.e.biodiversity,ecosystems,extractives,night light,and food-water-energy nexus),a Dashboard is built as a visual front-end.This is a valuable instrument to track progresses towards environmental policies.

Developing food,water and energy nexus workflows

There is a growing recognition of the interdependencies among the supply systems that rely upon food,water and energy.Billions of people lack safe and sufficient access to these systems,coupled with a rapidly growing global demand and increasing resource constraints.Modeling frameworks are considered one of the few means available to understand the complex interrelationships among the sectors,however development of nexus related frameworks has been limited.We describe three opensource models well known in their respective domains(i.e.TerrSysMP,WOFOST and SWAT)where components of each if combined could help decision-makers address the nexus issue.We propose as a first step the development of simple workflows utilizing essential variables and addressing components of the above-mentioned models which can act as building-blocks to be used ultimately in a comprehensive nexus model framework.The outputs of the workflows and the model framework are designed to address the SDGs.