{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/evolving-spatially-aggregated-features-from","title":"Evolving Spatially Aggregated Features from Satellite Imagery for Regional Modeling","arxiv_id":"1706.07888","date":"2017-06-24","proceeding":null,"authors":["Sam Kriegman","Marcin Szubert","Josh C. Bongard","Christian Skalka"],"abstract":"Satellite imagery and remote sensing provide explanatory variables at\nrelatively high resolutions for modeling geospatial phenomena, yet regional\nsummaries are often desirable for analysis and actionable insight. In this\npaper, we propose a novel method of inducing spatial aggregations as a\ncomponent of the machine learning process, yielding regional model features\nwhose construction is driven by model prediction performance rather than prior\nassumptions. Our results demonstrate that Genetic Programming is particularly\nwell suited to this type of feature construction because it can automatically\nsynthesize appropriate aggregations, as well as better incorporate them into\npredictive models compared to other regression methods we tested. In our\nexperiments we consider a specific problem instance and real-world dataset\nrelevant to predicting snow properties in high-mountain Asia.","url_abs":"http://arxiv.org/abs/1706.07888v2","url_pdf":"http://arxiv.org/pdf/1706.07888v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"evolving-spatially-aggregated-features-from","repo_url":"https://github.com/skriegman/ppsn_2016","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"regression-1","task_name":"regression"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}