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ISPRS Journal of Photogrammetry and Remote Sensing Vol.157 November 2019

Derek Lichti - Nama Orang;

1.Large-scale MODIS AOD products recovery: Spatial-temporal hybrid fusion considering aerosol variation mitigation p.1-12
2.Optimizing multiscale segmentation with local spectral heterogeneity measure for high resolution remote sensing images p.13-25
3.Modelling of instrument repositioning errors in discontinuous Multi-Campaign Ground-Based SAR (MC-GBSAR) deformation monitoring p.26-40
4.Ship detection from PolSAR imagery using the ambiguity removal polarimetric notch filter p.41-58
5.Efficiently utilizing complex-valued PolSAR image data via a multi-task deep learning framework p.59-72
6.Photogrammetric assessment of shoreline retreat in North Africa: Anthropogenic and natural drivers p.73-92
7.Blind cloud and cloud shadow removal of multitemporal images based on total variation regularized low-rank sparsity decomposition p.93-107
8.Accurate modelling of canopy traits from seasonal Sentinel-2 imagery based on the vertical distribution of leaf traits p.108-123
9.Deep learning for multi-modal classification of cloud, shadow and land cover scenes in PlanetScope and Sentinel-2 imagery p.124-136
10.Coral reef geomorphology of the Spratly Islands: A simple method based on time-series of Landsat-8 multi-band inundation maps p.137-154
11.Comparison between convolutional neural networks and random forest for local climate zone classification in mega urban areas using Landsat images p.155-170
12.Multi-season RapidEye imagery improves the classification of wetland and dryland communities in a subtropical coastal region p. 171-187
13.A closed-form solution for multi-view color correction with gradient preservation p.188-200
14.Context pyramidal network for stereo matching regularized by disparity gradients p.201-215


Ketersediaan
M.4142-XII-2019526.982Perpustakaan BIG (500)Tersedia
Informasi Detail
Judul Seri
-
No. Panggil
526.982
Penerbit
Amsterdam : Elsevier., 2019
Deskripsi Fisik
215 hlm.: illus 25cm
Bahasa
Inggris
ISBN/ISSN
0924-2716
Klasifikasi
526.982
Tipe Isi
text
Tipe Media
other
Tipe Pembawa
unspecified
Edisi
Vol.157
Subjek
Penginderaan Jauh
Info Detail Spesifik
-
Pernyataan Tanggungjawab
Editor-in-Chief Derek Lichti
Versi lain/terkait

Tidak tersedia versi lain

Lampiran Berkas
  • Large-scale MODIS AOD products recovery: Spatial-temporal hybrid fusion considering aerosol variation mitigation
  • Optimizing multiscale segmentation with local spectral heterogeneity measure for high resolution remote sensing images
  • Modelling of instrument repositioning errors in discontinuous Multi-Campaign Ground-Based SAR (MC-GBSAR) deformation monitoring
  • Ship detection from PolSAR imagery using the ambiguity removal polarimetric notch filter
  • Efficiently utilizing complex-valued PolSAR image data via a multi-task deep learning framework
  • Photogrammetric assessment of shoreline retreat in North Africa: Anthropogenic and natural drivers
  • Blind cloud and cloud shadow removal of multitemporal images based on total variation regularized low-rank sparsity decomposition
  • Accurate modelling of canopy traits from seasonal Sentinel-2 imagery based on the vertical distribution of leaf traits
  • Deep learning for multi-modal classification of cloud, shadow and land cover scenes in PlanetScope and Sentinel-2 imagery
  • Coral reef geomorphology of the Spratly Islands: A simple method based on time-series of Landsat-8 multi-band inundation maps
  • Comparison between convolutional neural networks and random forest for local climate zone classification in mega urban areas using Landsat images
  • Multi-season RapidEye imagery improves the classification of wetland and dryland communities in a subtropical coastal region
  • A closed-form solution for multi-view color correction with gradient preservation
  • Context pyramidal network for stereo matching regularized by disparity gradients
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Perpustakaan Badan Informasi Geospasial (BIG) adalah sebuah perpustakaan yang berada di bawah Badan Informasi Geospasial Indonesia. Perpustakaan ini memiliki koleksi yang berkaitan dengan informasi geospasial, termasuk peta, data geospasial, dan literatur terkait. Selengkapnya

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