ISPRS Journal of Photogrammetry and Remote Sensing Vol.149 March 2019

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1. Automated detection and measurement of individual sorghum panicles using density-based clustering of terrestrial lidar data p. 1-13
2. 3D gray level co-occurrence matrix and its application to identifying collapsed buildings p. 14-28
3. Geometric comparison and quality evaluation of 3D models of indoor environments p. 29-39
4. A new waveform decomposition method for multispectral LiDAR p. 40-49
5. Height estimation from single aerial images using a deep convolutional encoder-decoder network p. 50-66
6. Investigating the gravitational stability of a radio telescope’s reference point using a terrestrial laser scanner: Case study at the Onsala Space Observatory 20-m radio telescope p. 67-76
7. A new algorithm for the estimation of leaf unfolding date using MODIS data over China’s terrestrial ecosystems p. 77-90
8. DuPLO: A DUal view Point deep Learning architecture for time series classificatiOn p. 91-104
9. Modelling the effects of fundamental UAV flight parameters on LiDAR point clouds to facilitate objectives-based planning p. 105-118
10. Tree species classification in tropical forests using visible to shortwave infrared WorldView-3 images and texture analysis p. 119-131
11. Radiometric calibration assessments for UAS-borne multispectral cameras: Laboratory and field protocols p. 132-145
12. Integrating UAV optical imagery and LiDAR data for assessing the spatial relationship between mangrove and inundation across a subtropical estuarine wetland p. 146-156
13. A line-based progressive refinement of 3D rooftop models using airborne LiDAR data with single view imagery p. 157-175
14. Simulation of satellite reflectance data using high-frequency ground based hyperspectral canopy measurements for in-season estimation of grain yield and grain nitrogen status in winter wheat p. 176-187
15. Recurrently exploring class-wise attention in a hybrid convolutional and bidirectional LSTM network for multi-label aerial image classification p. 188-199
16. 3D hyperspectral point cloud generation: Fusing airborne laser scanning and hyperspectral imaging sensors for improved object-based information extraction p. 200-214
17. Thin cloud removal from optical remote sensing images using the noise-adjusted principal components transform p. 215-225
18. Application of remote sensing technologies to identify impacts of nutritional deficiencies on forests p. 226-241
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Elsevier : Amsterdam.,

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241 hlm.; ilus 28cm




0924 - 2716



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Vol.149 March 2019

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