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CrossVIT-augmented Geospatial-Intelligence Visualization System for Tracking Economic Development Dynamics

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Publicado no:arXiv.org (Dec 13, 2024), p. n/a
Autor principal: Bai, Yanbing
Outros Autores: Su, Jinhua, Qiao, Bin, Ma, Xiaoran
Publicado em:
Cornell University Library, arXiv.org
Assuntos:
Spatial data
Tracking
Spatial resolution
Economic development
Visualization
Distributed processing
Resource allocation
Remote sensing
Acesso em linha:Citation/Abstract
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Resumo:Timely and accurate economic data is crucial for effective policymaking. Current challenges in data timeliness and spatial resolution can be addressed with advancements in multimodal sensing and distributed computing. We introduce Senseconomic, a scalable system for tracking economic dynamics via multimodal imagery and deep learning. Built on the Transformer framework, it integrates remote sensing and street view images using cross-attention, with nighttime light data as weak supervision. The system achieved an R-squared value of 0.8363 in county-level economic predictions and halved processing time to 23 minutes using distributed computing. Its user-friendly design includes a Vue3-based front end with Baidu maps for visualization and a Python-based back end automating tasks like image downloads and preprocessing. Senseconomic empowers policymakers and researchers with efficient tools for resource allocation and economic planning.
ISSN:2331-8422
Fonte:Engineering Database