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ISPRS Journal of Photogrammetry and Remote Sensing Volume 167 September 2020

1. A low-cost UAV framework towards ornamental plant detection and counting in the wild p.1-11
2. X-ModalNet: A semi-supervised deep cross-modal network for classification of remote sensing data p. 12-33
3. Mapping quality prediction for RTK/PPK-equipped micro-drones operating in complex natural environment p. 24-38
4. Vehicle detection of multi-source remote sensing data using active fine-tuning network p. 39-53
5. Multi-level monitoring of three-dimensional building changes for megacities: Trajectory, morphology, and landscape p. 54-70
6. Radar-based multipoint displacement measurements of a 1200-m-long suspension bridge p. 71-84
7. The potential of in-situ hyperspectral remote sensing for differentiating 12 banana genotypes grown in Uganda p. 85-103
8. Mapping croplands of Europe, Middle East, Russia, and Central Asia using Landsat, Random Forest, and Google Earth Engine p. 104-122
9. HyperLi-Net: A hyper-light deep learning network for high-accurate and high-speed ship detection from synthetic aperture radar imagery p. 123-153
10. Cross-regional oil palm tree counting and detection via a multi-level attention domain adaptation network p. 154-77
11. Geographically and temporally weighted neural networks for satellite-based mapping of ground-level PM2.5 p. 178-188
12. A novel deep learning instance segmentation model for automated marine oil spill detection p. 190-200
13. Multi-scale deep feature learning network with bilateral filtering for SAR image classification p. 201-213
14. Generating spatiotemporally consistent fractional vegetation cover at different scales using spatiotemporal fusion and multiresolution tree methods p. 214-229
15. Efficient structure from motion for large-scale UAV images: A review and a comparison of SfM tools p. 230-251
16. Water level prediction from social media images with a multi-task ranking approach p. 252-262
17. Weakly-supervised domain adaptation for built-up region segmentation in aerial and satellite imagery p. 263-275
18. Improved land cover map of Iran using Sentinel imagery within Google Earth Engine and a novel automatic workflow for land cover classification using migrated training samples p. 276-288
19. Gaussian processes retrieval of LAI from Sentinel-2 top-of-atmosphere radiance data p. 289-304
20. Remote sensed-based rainfall estimations over the East and West Africa regions for disaster risk management p. 305-320
21. Estimation of 1-km all-weather remotely sensed land surface temperature based on reconstructed spatial-seamless satellite passive microwave brightness temperature and thermal infrared data p. 321-344
22. Detection of radioactive waste sites in the Chornobyl exclusion zone using UAV-based lidar data and multispectral imagery p. 345-362
23. GESAC: Robust graph enhanced sample consensus for point cloud registration p. 363-374
24. Use of multi-temporal satellite data for monitoring pool surface areas occurring in non-perennial rivers in semi-arid environments of the Western Cape, South Africa p. 375-384
25. Fully convolutional networks for land cover classification from historical panchromatic aerial photographs p. 385-395
26. Semi-automated framework for generating cycling lane centerlines on roads with roadside barriers from noisy MLS data p. 396-417
27. From LiDAR point cloud towards digital twin city: Clustering city objects based on Gestalt principles p. 418-431
28. Structure-aware Building Mesh Polygonization p. 432-442
29. Deeply supervised convolutional neural network for shadow detection based on a novel aerial shadow imagery dataset p. 443-457

Ketersediaan
M-4414-14-XII-2020526.982Perpustakaan BIGTersedia
Informasi Detail
Judul Seri
-
No. Panggil
526.982
Penerbit
Amsterdam : Elsevier.,
Deskripsi Fisik
457 hlm. : illus. ; 28 cm.
Bahasa
Inggris
ISBN/ISSN
0924-2716
Klasifikasi
526.982
Tipe Isi
text
Tipe Media
other
Tipe Pembawa
unspecified
Edisi
Volume 167 September 2020
Subjek
Penginderaan Jauh
Fotogrametri
Info Detail Spesifik
-
Pernyataan Tanggungjawab
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Tidak tersedia versi lain

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