DOE OSTI · 3029730
Morphology-Based Building Use-Type Modeling: Learnability-First Schema Discovery
Abstract
This technical memorandum documents an update to the building use-type classification workflow, used in LandScan Mosaic, that replaces a fixed, semantically defined class schema with a learnability-first schema discovery procedure. Historically, the target label schema was specified a priori (e.g., predicting a chosen set of use-type codes), and model training and evaluation were performed within that fixed label space. In the updated workflow, the pipeline first evaluates which non-residential distinctions are learnable under spatial generalization and then collapses ambiguous classes into data-driven groupings before finalizing the schema used for production training.
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Adams, Daniel [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000196950577), Stewart, Robert [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000281867559). 2026-01-01. Morphology-Based Building Use-Type Modeling: Learnability-First Schema Discovery. https://doi.org/10.2172/3029730
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