Ditapis dengan
Pol-InSAR-Island - A benchmark dataset for multi-frequency Pol-InSAR data lan…
This paper presents Pol-InSAR-Island, the first publicly available multi-frequency Polarimetric Interferometric Synthetic Aperture Radar (Pol-InSAR) dataset labeled with detailed land cover classes, which serves as a challenging benchmark dataset for land cover classification. In recent years, machine learning has become a powerful tool for remote sensing image analysis. While there are numerou…
- Edisi
- Vol.10, December 2023
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 13 hlm PDF, 19,559 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Automatic labelling for semantic segmentation of VHR satellite images: Applic…
The application of deep learning methods to remote sensing data has produced good results in recent studies. A promising application area is automatic land cover classification (semantic segmentation) from very high-resolution satellite imagery. However, the deep learning methods require large, labelled training datasets that are suitable for the study area. Map data can be used as training dat…
- Edisi
- Vol.9, August 2023
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 11 hlm PDF, 15.060 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
A decision-level fusion approach to tree species classification from multi-so…
In this study, an object-oriented, decision-level fusion method is proposed for tree species classification based on spectral, textural, and structural features derived from multi-spectral and panchromatic imagery and Light Detection And Ranging (LiDAR) data. Murphy's average method based on the Dempster Shafer theory (DST) was used to calculate the combined mass function for decision making pu…
- Edisi
- Vol.1, October 2021
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 16 hlm PDF, 4.155 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- -
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