Land Cover Mapping from Colorized CORONA Archived Greyscale Satellite Data and Feature Extraction Classification
Problem
Land cover mapping typically relies on multispectral data; extracting land cover information from archived greyscale CORONA satellite imagery is difficult.
Why it matters
Archive greyscale satellite data is an underused source of historical land cover information.
What the AI did
Applied the DeOldify deep learning method (MyHeritage platform) to colorise a CORONA image over Larnaca, Cyprus, then performed geometric correction, segmentation, and SVM classification into five land cover classes.
Results
not stated in source
Impact
Shows archived greyscale satellite imagery can be colorised and classified for land cover mapping.
Record
| Venue | Land |
|---|---|
| Published | 2021 |
| Work type | article |
| Authors | Άθως Αγαπίου |
| Citations | 14 (OpenAlex, at import time) |
| References | 44 |
| Model or method | DeOldify; SVM classifier |
| Organization | not stated in source |
| Primary source | https://doi.org/10.3390/land10080771 |
| Open access | gold |
| Keywords | CORONA, colorization, DeOldify, SVM, land cover, remote sensing |
Importance rating
incremental / niche
Niche methodological advance showing archived greyscale imagery can be colorised and classified for land cover mapping; no population or industry-scale impact stated.
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