{"id":20964,"date":"2024-09-23T14:17:53","date_gmt":"2024-09-23T19:17:53","guid":{"rendered":"https:\/\/uwm.edu\/engineering\/?p=20964"},"modified":"2024-09-23T14:17:55","modified_gmt":"2024-09-23T19:17:55","slug":"ghose-discusses-spatial-data-at-nsf-workshop-on-climate-change","status":"publish","type":"post","link":"https:\/\/uwm.edu\/engineering\/ghose-discusses-spatial-data-at-nsf-workshop-on-climate-change\/","title":{"rendered":"Ghose discusses spatial data at NSF workshop on climate change\u00a0"},"content":{"rendered":"\n

Most of the scientists attending the workshop \u201cSustainable Computing for Sustainability,\u201d hosted by the National Science Foundation last spring, were computer scientists developing algorithms for more nuanced sustainability and climate-change models.<\/p>\n\n\n\n

Rina Ghose, professor, industrial engineering, was one of the minority from another discipline serving as an invited panelist at the workshop. She brought a vital piece to the event\u2019s two broad topics: making the computing industry greener and addressing data and analytical needs for predicting climate change impacts.<\/p>\n\n\n\n

With a background in climatology and data analysis, Ghose was able to share her expertise on the use and interpretation of spatial data, a topic that few computer scientists know much about.<\/p>\n\n\n\n

That interdisciplinary perspective was one of the NSF\u2019s aims for the workshop, Ghose said.<\/p>\n\n\n\n

\u201cThat\u2019s important because the multitude of data that is used in climate-change modeling comes from remote sensing,\u201d she said. \u201cSpatial data collection and analysis using Geographical Information Systems and remote sensing is fundamental to modeling climate change.\u201d<\/p>\n\n\n\n

Large forest fires, ocean temperatures and hurricane flooding are examples of the data that can be mapped from space, she said. And most of the data is free through federal agencies.<\/p>\n\n\n\n

Among the wider findings of the workshop were:<\/p>\n\n\n\n