Paper Abstract and Keywords |
Presentation |
2023-12-08 09:10
Large-Scale Urban Mapping Using Earth Observation Data: A Systematic Review Ahmad Luthfi Hadiyanto, Ahmad Maryanto, Muchammad Soleh, Farikhotul Chusnayah, Deni Kartika, Kurdianto (BRIN) SANE2023-66 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Large-scale urban mapping using remote sensing data may provide detailed information represented as individual objects or parcels. Unfortunately, there is no fixed guidance to build the map effectively. A systematic review is performed, showing that remote sensing data has been well used for land cover mapping and 3D modeling using deep learning. Aerial and satellite images at ≤ 2m spatial resolution, Lidar, and SAR are common data sources. There are still limitations in land use (LU) and urban structural unit (USU) mapping; therefore, future work may explore deep learning with more accurate datasets to better distinguish LU and USU classes. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Large-scale / Urban mapping / Land cover / Land use / Urban structural unit / / / |
Reference Info. |
IEICE Tech. Rep., vol. 123, no. 298, SANE2023-66, pp. 36-41, Dec. 2023. |
Paper # |
SANE2023-66 |
Date of Issue |
2023-11-30 (SANE) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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SANE2023-66 |
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