Driving innovation through Earth observation

Leveraging AI and remote sensing science to develop a scalable seagrass mapping methodology, fine-tuning remote sensing AI models for 4 pilot geographies, and creating maps of seagrass extent, change, threats, and carbon stocks.

With Climate TRACE, identified nearly 400K large-scale livestock facilities that have significant environmental impacts, including contributing to ~10% of global greenhouse gas emissions.

Environmental journalists Mongabay and Earth Genome detected 67 clandestine airstrips used for transporting drugs in the Peruvian Amazon, threatening Indigenous communities and the rainforest.

With Stanford University researchers, we developed high-resolution, up-to-date land-use maps capable of capturing the fine-scale habitat variation most relevant to disease transmission.

Amazon Mining Watch uses machine learning to map the scars of mining activities in the Amazonian countries.

Earth Index, a search tool for the environment, harnesses satellite imagery and machine learning to extract an area's "genetic signature." Obtain insights in a day, instead of months.

Using AI and Machine Learning to identify plastic waste before they enter our oceans.

Our platform uses collaborative mapping and satellite imagery to support real-world investigations for students.