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The Digital Twin of the City of Zurich for Urban Planning
The Digital Twin of the City of Zurich for Urban Planning
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The Digital Twin of the City of Zurich for Urban Planning

Schrotter, Gerhard ; Hürzeler, Christian

Journal of photogrammetry, remote sensing and geoinformation science, 2020-02, Vol.88 (1), p.99-112 [Periódico revisado por pares]

Cham: Springer International Publishing

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2
CityGML 3.0: New Functions Open Up New Applications
CityGML 3.0: New Functions Open Up New Applications
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CityGML 3.0: New Functions Open Up New Applications

Kutzner, Tatjana ; Chaturvedi, Kanishk ; Kolbe, Thomas H.

Journal of photogrammetry, remote sensing and geoinformation science, 2020-02, Vol.88 (1), p.43-61 [Periódico revisado por pares]

Cham: Springer International Publishing

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3
Digital geoTwin Vienna: Towards a Digital Twin City as Geodata Hub
Digital geoTwin Vienna: Towards a Digital Twin City as Geodata Hub
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Digital geoTwin Vienna: Towards a Digital Twin City as Geodata Hub

Lehner, Hubert ; Dorffner, Lionel

Journal of photogrammetry, remote sensing and geoinformation science, 2020-02, Vol.88 (1), p.63-75 [Periódico revisado por pares]

Cham: Springer International Publishing

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4
UAV LiDAR Metrics for Monitoring Crop Height, Biomass and Nitrogen Uptake: A Case Study on a Winter Wheat Field Trial
UAV LiDAR Metrics for Monitoring Crop Height, Biomass and Nitrogen Uptake: A Case Study on a Winter Wheat Field Trial
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UAV LiDAR Metrics for Monitoring Crop Height, Biomass and Nitrogen Uptake: A Case Study on a Winter Wheat Field Trial

Hütt, Christoph ; Bolten, Andreas ; Hüging, Hubert ; Bareth, Georg

Journal of photogrammetry, remote sensing and geoinformation science, 2023-04, Vol.91 (2), p.65-76 [Periódico revisado por pares]

Cham: Springer International Publishing

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5
Efficient 3D Mapping and Modelling of Indoor Scenes with the Microsoft HoloLens: A Survey
Efficient 3D Mapping and Modelling of Indoor Scenes with the Microsoft HoloLens: A Survey
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Efficient 3D Mapping and Modelling of Indoor Scenes with the Microsoft HoloLens: A Survey

Weinmann, Martin ; Wursthorn, Sven ; Weinmann, Michael ; Hübner, Patrick

Journal of photogrammetry, remote sensing and geoinformation science, 2021-08, Vol.89 (4), p.319-333 [Periódico revisado por pares]

Cham: Springer International Publishing

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6
Classification of Tree Species and Standing Dead Trees with Lidar Point Clouds Using Two Deep Neural Networks: PointCNN and 3DmFV-Net
Classification of Tree Species and Standing Dead Trees with Lidar Point Clouds Using Two Deep Neural Networks: PointCNN and 3DmFV-Net
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Classification of Tree Species and Standing Dead Trees with Lidar Point Clouds Using Two Deep Neural Networks: PointCNN and 3DmFV-Net

Hell, Maximilian ; Brandmeier, Melanie ; Briechle, Sebastian ; Krzystek, Peter

Journal of photogrammetry, remote sensing and geoinformation science, 2022-04, Vol.90 (2), p.103-121 [Periódico revisado por pares]

Cham: Springer International Publishing

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7
Exploring the Potential of Thermal Remote Sensing for Marine Freshwater Springs Identification in the United Arab Emirates
Exploring the Potential of Thermal Remote Sensing for Marine Freshwater Springs Identification in the United Arab Emirates
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Exploring the Potential of Thermal Remote Sensing for Marine Freshwater Springs Identification in the United Arab Emirates

Harahsheh, Hussein ; Dasmal, Khalid Ben ; Youssef, Ahmed

Journal of photogrammetry, remote sensing and geoinformation science, 2024-08, Vol.92 (4), p.381-393 [Periódico revisado por pares]

Cham: Springer International Publishing

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8
Classification of ALS Point Clouds Using End-to-End Deep Learning
Classification of ALS Point Clouds Using End-to-End Deep Learning
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Classification of ALS Point Clouds Using End-to-End Deep Learning

Winiwarter, Lukas ; Mandlburger, Gottfried ; Schmohl, Stefan ; Pfeifer, Norbert

Journal of photogrammetry, remote sensing and geoinformation science, 2019-09, Vol.87 (3), p.75-90 [Periódico revisado por pares]

Cham: Springer International Publishing

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9
BathyNet: A Deep Neural Network for Water Depth Mapping from Multispectral Aerial Images
BathyNet: A Deep Neural Network for Water Depth Mapping from Multispectral Aerial Images
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BathyNet: A Deep Neural Network for Water Depth Mapping from Multispectral Aerial Images

Mandlburger, Gottfried ; Kölle, Michael ; Nübel, Hannes ; Soergel, Uwe

Journal of photogrammetry, remote sensing and geoinformation science, 2021-04, Vol.89 (2), p.71-89 [Periódico revisado por pares]

Cham: Springer International Publishing

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10
Optical Imaging and Image Restoration Techniques for Deep Ocean Mapping: A Comprehensive Survey
Optical Imaging and Image Restoration Techniques for Deep Ocean Mapping: A Comprehensive Survey
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Optical Imaging and Image Restoration Techniques for Deep Ocean Mapping: A Comprehensive Survey

Song, Yifan ; Nakath, David ; She, Mengkun ; Köser, Kevin

Journal of photogrammetry, remote sensing and geoinformation science, 2022-06, Vol.90 (3), p.243-267 [Periódico revisado por pares]

Cham: Springer International Publishing

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