AwakeForest: An Interactive Geospatial Platform for Large-Scale Forest Imagery
2026-06-22 • Computer Vision and Pattern Recognition
Computer Vision and Pattern RecognitionSoftware Engineering
AI summaryⓘ
The authors created AwakeForest, a platform to help analyze large forest images more easily and accurately. It combines computer models and human input to label and study forest pictures from different sources and sizes. AwakeForest works smoothly with big image files and lets users update models and annotations as needed. The authors tested it on a forest dataset and showed it can support practical forest management tasks.
forest imagerymachine learningannotationhuman-in-the-looporthomosaicmodel-assisted inferencegeospatial analysisaerial imageryscalable workflowsforest management
Authors
Suraj Prasai, Kangning Cui, Rongkun Zhu, Sarra Alqahtani, Ying Zhang, Victor Paul Pauca, Miles R. Silman, Fan Yang
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.