{"type":"ScholarlyArticle","title":"AwakeForest: An Interactive Geospatial Platform for Large-Scale Forest Imagery","authors":[{"name":"Suraj Prasai","slug":"suraj-prasai","given":"Suraj","family":"Prasai","affiliation":""},{"name":"Kangning Cui","slug":"kangning-cui","given":"Kangning","family":"Cui","affiliation":""},{"name":"Rongkun Zhu","slug":"rongkun-zhu","given":"Rongkun","family":"Zhu","affiliation":""},{"name":"Sarra Alqahtani","slug":"sarra-alqahtani","given":"Sarra","family":"Alqahtani","affiliation":""},{"name":"Ying Zhang","slug":"ying-zhang","given":"Ying","family":"Zhang","affiliation":""},{"name":"Victor Paúl Pauca","slug":"victor-paul-pauca","given":"Victor Paúl","family":"Pauca","affiliation":""},{"name":"Miles R. Silman","slug":"miles-r-silman","given":"Miles R.","family":"Silman","affiliation":""},{"name":"Fan Yang","slug":"fan-yang","given":"Fan","family":"Yang","affiliation":""}],"abstract":"Forest imagery analysis often involves multiple tightly coupled vision tasks, which must be performed under substantial variation in geographic regions, sensors, and acquisition conditions. However, practitioners often lack a unified tool that is geospatial-native, cloud-optimized, and ML-integrated for end-to-end workflows spanning annotation, prediction, visualization, and downstream analysis at scale. We present AwakeForest, an interactive end-to-end platform designed for large-scale forest imagery that integrates model-assisted inference, automatic annotation, and human-in-the-loop refinement within a single workflow. Our platform supports plug-and-play integration of pretrained models and enables scalable interaction with forest imagery ranging from standard aerial scenes to large orthomosaics that can span several gigabytes to hundreds of gigabytes. AwakeForest produces analysis-ready outputs that can be directly used for downstream analysis and to support iterative model and annotation updates on new scenes. We demonstrate the system on the PALMS dataset and illustrate how AwakeForest supports an end-to-end workflow for practical forest management and analysis.","doi":"10.24963/ijcai.2026/986","url":"https://ijcai.org/proceedings/2026/986","pdf":"https://ijcai.org/proceedings/2026/0986.pdf","markdown":"https://ijcai.org/proceedings/2026/986.md","bibtex":"https://ijcai.org/proceedings/2026/bibtex/986","volume":{"slug":"2026","title":"Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2026","url":"https://ijcai.org/proceedings/2026/","year":2026,"location":"Bremen, Germany","dates":"15-21 August 2026","editors":"Diego Calvanese","isbn":"978-1-956792-09-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2026"},"section":"Demo Track","track":"Demo Track","number":986,"pages":{"first":8487,"last":8491},"keywords":["AI: Multidisciplinary Topics and Applications","AI: Natural Language Processing","AI: Computer Vision","AI: Knowledge Representation and Reasoning"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}