Geospatial Data Disaggregation through Self-Trained Encoder–Decoder Convolutional Models

Geospatial Data Disaggregation through Self-Trained Encoder–Decoder Convolutional Models

Datasets collecting demographic and socio-economic statistics are widely available. Still, the data are often only released for highly aggregated geospatial areas, which can mask important local hotspots. When conducting spatial analysis, one often needs to disaggregate the source data, transforming...

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Bibliographic Details
Main Authors: João Monteiro, Bruno Martins, Miguel Costa, João M. Pires
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:ISPRS International Journal of Geo-Information
Subjects:
geospatial data disaggregation
dasymetric disaggregation
self-supervised learning
encoder–decoder neural networks
convolutional neural networks
deep learning
Online Access:https://www.mdpi.com/2220-9964/10/9/619

Internet

https://www.mdpi.com/2220-9964/10/9/619

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