This month we explore various data challenges, tutorials, and other resources. There are also numerous machine learning methodologies and applications, including information on applying models in disparate geophysical and geospatial datasets, building better dust detection models and classifying drivers of global forest watch, to name a few. Read September’s ML4EO market news roundup below.
In this month’s ML4EO market news, explore new public data available on Radiant MLHub, Maxar, and Mapbox, ML applications that detect transformers in agricultural fields, tutorials, and, more highlights from the EO community’s continued contributions to the pandemic response, including NASA’s Earth Data’s COVID-19 Dashboard.
This month, Radiant Earth released LandCoverNet, a land cover classification training dataset, and Facebook and Esri partnered to release new OSM ready datasets. Other highlights include data challenge announcements, continued EO expert support towards the COVID-19 pandemic response, upcoming STAC sprint 6, ML4EO tutorials, and more. Explore the details below.
New public datasets from Digital Earth Africa & Development Seed, an Earth Observation COVID-19 Dashboard from ESA, JAXA & NASA, examples of ML applications using EO, and the STAC 1.0-beta.1 release made for an eventful June in the ML4EO market. Learn more about these highlights below:
This month, Agrilinks organized their annual Earth Observations for Food Security and Agriculture theme, NASA Earth Science Data Systems Program, and Radiant Earth released their report on using ML4EO, and the EO community continued to support the COVID-19 pandemic response. Read May’s ML and EO market highlights below:
From the virtual Computer Vision 4 Agriculture workshop to the launch of Azavea’s GroundWork platform, April proved to be eventful for machine learning in the Earth observation field. Explore market highlights and the EO community’s continued contributions the COVID-19 pandemic response in this month’s EO market news.
During this turbulent month, the Earth observation community put their skills and resources towards supporting the emergency response to COVID-19. Experts also continued to push EO advancements, including releasing a new STAC intake driver, soil moisture prediction deep learning model, and image labeler platform.
The public release of open datasets in response to the Australian wildfires and Taal volcanic eruption, the retirement of the Rapideye Planet constellation, and the announcements of STAC v0.9.0 and a new Capella SAR constellation all made for a busy and exciting first month of the year in the EO market. Read more below.