AIR Project Wins GEO-GEE Fund for Tackling Global Challenges with Open Earth Data

According to an announcement released yesterday from the Group on Earth Observations (GEO), GEO and Google Earth Engine (GEE) have planned to sponsor 32 projects from 22 countries, providing $3 million USD towards production licenses and $1 million in technical support from EO Data Science to tackle some of the world’s greatest challenges using open Earth data. Among the winning projects is the Land Degradation Neutrality Program hosted by the Institute of Remote Sensing and Digital Earth (the Aerospace Information Research Institute now, or AIR for short).

Prof. LI Xiaosong, head of the project, and CUI Yuran, a research assistant, expressed the vision for the project on a GEO blog titled “GEO and Google Earth Engine announce funding for 32 projects to improve our planet”, saying that “with the help of Google Earth Engine platform, we would refine the key methodologies for Land Degradation Neutrality monitoring at the global and regional scale, such as improve the accuracy and spatial resolution of land cover and soil carbon, calibrate the climate effects in land productivity change and build the link between field observed degradation and multiple remote sensing indicators, thus to provide dataset, methodology and decision support for United Nations agencies and interested countries, and finally contribute to the realization of Sustainable Development Goals 15.3.1.”

Last year, GEO and Google Earth Engine announced a call to action for Earth observations projects monitoring the pulse of the planet to apply for the GEO-GEE Programme. More than 50 projects were submitted from around the globe on a range of social and environmental topics including climate monitoring, water and coastal observations, sustainable development and other key areas related to environmental protection and conservation, according to the blog.

In the light of the GEO-GEE programme, the winning projects are responding to “a wide range of environmental and social challenges using real-time Earth observation data coupled with cloud computing, some of which include: mapping poverty data and vulnerable settlements, deforestation and land degradation, flood warnings, marine coasts, ice shelf monitoring, environment and climate stress, food and agriculture and many more”.