PREFACE: TECHNICAL COMMISSION I

Hinz, S.; Feitosa, R. Q.; Weinmann, M.; Jutzi, B.

doi:https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-7-2020

Novel View Synthesis with Neural Radiance Fields for Industrial Robot Applications

Markus Hillemann, Robert Langendörfer, Max Heiken, Max Mehltretter, Andreas Schenk, Martin Weinmann, Stefan Hinz, Christian Heipke, and Markus Ulrich

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-2024, 137–144, https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-137-2024,https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-137-2024, 2024

HoloGS: Instant Depth-based 3D Gaussian Splatting with Microsoft HoloLens 2

Miriam Jäger, Theodor Kapler, Michael Feßenbecker, Felix Birkelbach, Markus Hillemann, and Boris Jutzi

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-2024, 159–166, https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-159-2024,https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-159-2024, 2024

The Potential of Neural Radiance Fields and 3D Gaussian Splatting for 3D Reconstruction from Aerial Imagery

Dennis Haitz, Max Hermann, Aglaja Solana Roth, Michael Weinmann, and Martin Weinmann

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-2-2024, 97–104, https://doi.org/10.5194/isprs-annals-X-2-2024-97-2024,https://doi.org/10.5194/isprs-annals-X-2-2024-97-2024, 2024

USING TIME SERIES IMAGE DATA TO IMPROVE THE GENERALIZATION CAPABILITIES OF A CNN – THE EXAMPLE OF DEFORESTATION DETECTION WITH SENTINEL-2

M. X. Ortega, D. Wittich, F. Rottensteiner, C. Heipke, and R. Q. Feitosa

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-1-W1-2023, 961–970, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-961-2023,https://doi.org/10.5194/isprs-annals-X-1-W1-2023-961-2023, 2023

FUSING SENTINEL-1 AND SENTINEL-2 IMAGES WITH TRANSFORMER-BASED NETWORK FOR DEFORESTATION DETECTION IN THE BRAZILIAN AMAZON UNDER DIVERSE CLOUD CONDITIONS

F. Ferrari, M. P. Ferreira, and R. Q. Feitosa

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-1-W1-2023, 999–1006, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-999-2023,https://doi.org/10.5194/isprs-annals-X-1-W1-2023-999-2023, 2023

3D DENSITY-GRADIENT BASED EDGE DETECTION ON NEURAL RADIANCE FIELDS (NERFS) FOR GEOMETRIC RECONSTRUCTION

M. Jäger and B. Jutzi

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W3-2023, 71–78, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-71-2023,https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-71-2023, 2023

GEOMETRIC ACCURACY ANALYSIS BETWEEN NEURAL RADIANCE FIELDS (NERFS) AND TERRESTRIAL LASER SCANNING (TLS)

I. Petrovska, M. Jäger, D. Haitz, and B. Jutzi

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W3-2023, 153–159, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-153-2023,https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-153-2023, 2023

COMBINING HOLOLENS WITH INSTANT-NERFS: ADVANCED REAL-TIME 3D MOBILE MAPPING

D. Haitz, B. Jutzi, M. Ulrich, M. Jäger, and P. Hübner

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W1-2023, 167–174, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-167-2023,https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-167-2023, 2023

POTENTIAL OF MOBILE MAPPING TO CREATE DIGITAL TWINS OF FORESTS

D. Iwaszczuk, M. Goebel, Y. Du, J. Schmidt, and M. Weinmann

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W1-2023, 199–206, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-199-2023,https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-199-2023, 2023

A COMPARATIVE NEURAL RADIANCE FIELD (NERF) 3D ANALYSIS OF CAMERA POSES FROM HOLOLENS TRAJECTORIES AND STRUCTURE FROM MOTION

M. Jäger, P. Hübner, D. Haitz, and B. Jutzi

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W1-2023, 207–213, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-207-2023,https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-207-2023, 2023

MATHEMATICAL AND PHYSICAL APPROACHES TO INFER ABSOLUTE ZENITH WET DELAYS FROM DOUBLE DIFFERENTIAL INTERFEROMETRIC OBSERVATIONS USING ERA5 ATMOSPHERIC REANALYSIS

B. Kamm, A. Schenk, P. Yuan, and S. Hinz

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-M-1-2023, 153–159, https://doi.org/10.5194/isprs-archives-XLVIII-M-1-2023-153-2023,https://doi.org/10.5194/isprs-archives-XLVIII-M-1-2023-153-2023, 2023

A DEBIASING VARIATIONAL AUTOENCODER FOR DEFORESTATION MAPPING

M. X. Ortega Adarme, P. J. Soto Vega, G. A. O. P. Costa, R. Q. Feitosa, and C. Heipke

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-M-1-2023, 217–223, https://doi.org/10.5194/isprs-archives-XLVIII-M-1-2023-217-2023,https://doi.org/10.5194/isprs-archives-XLVIII-M-1-2023-217-2023, 2023

Tropospheric water vapor: a comprehensive high-resolution data collection for the transnational Upper Rhine Graben region

Benjamin Fersch, Andreas Wagner, Bettina Kamm, Endrit Shehaj, Andreas Schenk, Peng Yuan, Alain Geiger, Gregor Moeller, Bernhard Heck, Stefan Hinz, Hansjörg Kutterer, and Harald Kunstmann

Earth Syst. Sci. Data, 14, 5287–5307, https://doi.org/10.5194/essd-14-5287-2022,https://doi.org/10.5194/essd-14-5287-2022, 2022

Short summary

PREFACE: TECHNICAL COMMISSION I

S. Hinz, R. Q. Feitosa, M. Weinmann, and B. Jutzi

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2022, 7–7, https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-7-2022,https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-7-2022, 2022

CORROSION DETECTION FOR INDUSTRIAL OBJECTS: FROM MULTI-SENSOR SYSTEM TO 5D FEATURE SPACE

D. Haitz, B. Jutzi, P. Hübner, and M. Ulrich

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2022, 143–150, https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-143-2022,https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-143-2022, 2022

COMPARISON AND EVALUATION OF DIFFERENT APPROACHES FOR EFFICIENT PROCESSING OF LONG GROUND-BASED SAR TIMES SERIES

M. Rebmeister, A. Schenk, and S. Hinz

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 341–348, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-341-2022,https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-341-2022, 2022

A COMPARISON OF CLOUD REMOVAL METHODS FOR DEFORESTATION MONITORING IN AMAZON RAINFOREST

J. A. C. Martinez, M. X. O. Adarme, J. N. Turnes, G. A. O. P. Costa, C. A. De Almeida, and R. Q. Feitosa

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 665–671, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-665-2022,https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-665-2022, 2022

DEFORESTATION DETECTION WITH WEAK SUPERVISED CONVOLUTIONAL NEURAL NETWORKS IN TROPICAL BIOMES

P. J. Soto, G. A. O. P. Costa, M. X. Ortega, J. D. Bermudez, and R. Q. Feitosa

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 713–719, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-713-2022,https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-713-2022, 2022

NORMAL CLASSIFICATION OF 3D OCCUPANCY GRIDS FOR VOXEL-BASED INDOOR RECONSTRUCTION FROM POINT CLOUDS

P. Hübner, S. Wursthorn, and M. Weinmann

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-4-2022, 121–128, https://doi.org/10.5194/isprs-annals-V-4-2022-121-2022,https://doi.org/10.5194/isprs-annals-V-4-2022-121-2022, 2022

PREFACE: TECHNICAL COMMISSION I

S. Hinz, R. Q. Feitosa, M. Weinmann, and B. Jutzi

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2022, 7–7, https://doi.org/10.5194/isprs-annals-V-1-2022-7-2022,https://doi.org/10.5194/isprs-annals-V-1-2022-7-2022, 2022

ARM-NMS: SHAPE BASED NON-MAXIMUM SUPPRESSION FOR INSTANCE SEGMENTATION IN LARGE SCALE IMAGERY

A. Michel, W. Gross, S. Hinz, and W. Middelmann

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2022, 291–298, https://doi.org/10.5194/isprs-annals-V-2-2022-291-2022,https://doi.org/10.5194/isprs-annals-V-2-2022-291-2022, 2022

HOW FAR SHOULD I LOOK? A NEURAL ARCHITECTURE SEARCH STRATEGY FOR SEMANTIC SEGMENTATION OF REMOTE SENSING IMAGES

M. C. M. de Paulo, J. N. Turnes, P. N. Happ, M. P. Ferreira, H. A. Marques, and R. Q. Feitosa

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 17–23, https://doi.org/10.5194/isprs-annals-V-3-2022-17-2022,https://doi.org/10.5194/isprs-annals-V-3-2022-17-2022, 2022

PSDEFOPAT – TOWARDS AUTOMATIC MODEL BASED PSI POST-PROCESSING

M. Evers, A. Thiele, H. Hammer, and S. Hinz

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 107–114, https://doi.org/10.5194/isprs-annals-V-3-2022-107-2022,https://doi.org/10.5194/isprs-annals-V-3-2022-107-2022, 2022

MULTI-ATTENTION GHOSTNET FOR DEFORESTATION DETECTION IN THE AMAZON RAINFOREST

M. X. Ortega Adarme, G. A. O. P. Costa, and R. Q. Feitosa

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 657–664, https://doi.org/10.5194/isprs-annals-V-3-2022-657-2022,https://doi.org/10.5194/isprs-annals-V-3-2022-657-2022, 2022

DEFORESTATION DETECTION IN THE AMAZON RAINFOREST WITH SPATIAL AND CHANNEL ATTENTION MECHANISMS

P. Tovar, M. O. Adarme, and R. Q. Feitosa

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 851–858, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-851-2021,https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-851-2021, 2021

PREFACE: TECHNICAL COMMISSION I

S. Hinz, R. Q. Feitosa, M. Weinmann, and B. Jutzi

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2021, 7–7, https://doi.org/10.5194/isprs-archives-XLIII-B1-2021-7-2021,https://doi.org/10.5194/isprs-archives-XLIII-B1-2021-7-2021, 2021

REAL-TIME DENSE 3D RECONSTRUCTION FROM MONOCULAR VIDEO DATA CAPTURED BY LOW-COST UAVS

M. Hermann, B. Ruf, and M. Weinmann

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 361–368, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-361-2021,https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-361-2021, 2021

LARGE SCALE SEMANTIC SEGMENTATION OF VIRTUAL ENVIRONMENTS TO FACILITATE CORROSION MANAGEMENT

R. L. Garcia, P. N. Happ, and R. Q. Feitosa

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 465–470, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-465-2021,https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-465-2021, 2021

TOWARDS LIFELONG CROP RECOGNITION USING FULLY CONVOLUTIONAL RECURRENT NETWORKS AND SAR IMAGE SEQUENCES

J. A. Chamorro, R. Q. Feitosa, P. N. Happ, and J. D. Bermudez

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 923–929, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-923-2021,https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-923-2021, 2021

CONCEPT TO ANALYZE THE DISPLACEMENT TIME SERIES OF INDIVIDUAL PERSISTENT SCATTERERS

M. Evers, A. Thiele, H. Hammer, E. Cadario, K. Schulz, and S. Hinz

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 147–154, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-147-2021,https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-147-2021, 2021

PREFACE: TECHNICAL COMMISSION I

S. Hinz, R. Q. Feitosa, M. Weinmann, and B. Jutzi

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2021, 7–7, https://doi.org/10.5194/isprs-annals-V-1-2021-7-2021,https://doi.org/10.5194/isprs-annals-V-1-2021-7-2021, 2021

ADVERSARIAL DISCRIMINATIVE DOMAIN ADAPTATION FOR DEFORESTATION DETECTION

J. Noa, P. J. Soto, G. A. O. P. Costa, D. Wittich, R. Q. Feitosa, and F. Rottensteiner

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2021, 151–158, https://doi.org/10.5194/isprs-annals-V-3-2021-151-2021,https://doi.org/10.5194/isprs-annals-V-3-2021-151-2021, 2021

INVESTIGATIONS ON FEATURE SIMILARITY AND THE IMPACT OF TRAINING DATA FOR LAND COVER CLASSIFICATION

M. Voelsen, D. Lobo Torres, R. Q. Feitosa, F. Rottensteiner, and C. Heipke

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2021, 181–189, https://doi.org/10.5194/isprs-annals-V-3-2021-181-2021,https://doi.org/10.5194/isprs-annals-V-3-2021-181-2021, 2021

KNOWLEDGE AND SKILLS RELATED TO ACTIVE OPTICAL SENSORS IN THE BODY OF KNOWLEDGE FOR EARTH OBSERVATION AND GEOINFORMATION (EO4GEO BOK)

C. Dubois, B. Jutzi, M. Olijslagers, C. Pathe, C. Schmullius, M. A. Stelmaszczuk-Górska, D. Vandenbroucke, and M. Weinmann

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-5-2021, 9–16, https://doi.org/10.5194/isprs-annals-V-5-2021-9-2021,https://doi.org/10.5194/isprs-annals-V-5-2021-9-2021, 2021

SEMANTIC SEGMENTATION OF ENDANGERED TREE SPECIES IN BRAZILIAN SAVANNA USING DEEPLABV3+ VARIANTS

D. L. Torres, R. Q. Feitosa, L. E. C. La Rosa, P. N. Happ, J. Marcato Junior, W. N. Gonçalves, J. Martins, and V. Liesenberg

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W12-2020, 355–360, https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-355-2020,https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-355-2020, 2020

FCRN-BASED MULTI-TASK LEARNING FOR AUTOMATIC CITRUS TREE DETECTION FROM UAV IMAGES

L. E. C. La Rosa, M. Zortea, B. H. Gemignani, D. A. B. Oliveira, and R. Q. Feitosa

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3-W2-2020, 65–70, https://doi.org/10.5194/isprs-annals-IV-3-W2-2020-65-2020,https://doi.org/10.5194/isprs-annals-IV-3-W2-2020-65-2020, 2020

FIRST RESULTS OF THE LEM BENCHMARK DATABASE FOR AGRICULTURAL APPLICATIONS

I. D. Sanches, R. Q. Feitosa, B. Montibeller, P. M. Achanccaray Diaz, A. J. B. Luiz, M. D. Soares, V. H. R. Prudente, D. C. Vieira, L. E. P. Maurano, P. N. Happ, J. Chamorro, and L. V. Oldoni

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B5-2020, 251–256, https://doi.org/10.5194/isprs-archives-XLIII-B5-2020-251-2020,https://doi.org/10.5194/isprs-archives-XLIII-B5-2020-251-2020, 2020

EVALUATION OF SEMANTIC SEGMENTATION METHODS FOR DEFORESTATION DETECTION IN THE AMAZON

R. B. Andrade, G. A. O. P. Costa, G. L. A. Mota, M. X. Ortega, R. Q. Feitosa, P. J. Soto, and C. Heipke

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1497–1505, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1497-2020,https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1497-2020, 2020

DOMAIN ADAPTATION WITH CYCLEGAN FOR CHANGE DETECTION IN THE AMAZON FOREST

P. J. Soto, G. A. O. P. Costa, R. Q. Feitosa, P. N. Happ, M. X. Ortega, J. Noa, C. A. Almeida, and C. Heipke

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1635–1643, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1635-2020,https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1635-2020, 2020

INCORPORATING INTERFEROMETRIC COHERENCE INTO LULC CLASSIFICATION OF AIRBORNE POLSAR-IMAGES USING FULLY CONVOLUTIONAL NETWORKS

S. Schmitz, M. Weinmann, and A. Thiele

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2020, 115–122, https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-115-2020,https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-115-2020, 2020

Preface: Technical Commission I

S. Hinz, R. Q. Feitosa, M. Weinmann, and B. Jutzi

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2020, 7–7, https://doi.org/10.5194/isprs-annals-V-1-2020-7-2020,https://doi.org/10.5194/isprs-annals-V-1-2020-7-2020, 2020

URBAN MATERIAL CLASSIFICATION USING SPECTRAL AND TEXTURAL FEATURES RETRIEVED FROM AUTOENCODERS

R. Ilehag, J. Leitloff, M. Weinmann, and A. Schenk

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2020, 25–32, https://doi.org/10.5194/isprs-annals-V-1-2020-25-2020,https://doi.org/10.5194/isprs-annals-V-1-2020-25-2020, 2020

3D INDOOR MAPPING WITH THE MICROSOFT HOLOLENS: QUALITATIVE AND QUANTITATIVE EVALUATION BY MEANS OF GEOMETRIC FEATURES

M. Weinmann, M. A. Jäger, S. Wursthorn, B. Jutzi, M. Weinmann, and P. Hübner

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2020, 165–172, https://doi.org/10.5194/isprs-annals-V-1-2020-165-2020,https://doi.org/10.5194/isprs-annals-V-1-2020-165-2020, 2020

SELF-SUPERVISED LEARNING FOR MONOCULAR DEPTH ESTIMATION FROM AERIAL IMAGERY

M. Hermann, B. Ruf, M. Weinmann, and S. Hinz

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 357–364, https://doi.org/10.5194/isprs-annals-V-2-2020-357-2020,https://doi.org/10.5194/isprs-annals-V-2-2020-357-2020, 2020

EVALUATING A CONVOLUTIONAL NEURAL NETWORK FOR FEATURE EXTRACTION AND TREE SPECIES CLASSIFICATION USING UAV-HYPERSPECTRAL IMAGES

C. Sothe, L. E. C. la Rosa, C. M. de Almeida, A. Gonsamo, M. B. Schimalski, J. D. B. Castro, R. Q. Feitosa, M. Dalponte, C. L. Lima, V. Liesenberg, G. T. Miyoshi, and A. M. G. Tommaselli

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 193–199, https://doi.org/10.5194/isprs-annals-V-3-2020-193-2020,https://doi.org/10.5194/isprs-annals-V-3-2020-193-2020, 2020

VOXEL-BASED INDOOR RECONSTRUCTION FROM HOLOLENS TRIANGLE MESHES

P. Hübner, M. Weinmann, and S. Wursthorn

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-4-2020, 79–86, https://doi.org/10.5194/isprs-annals-V-4-2020-79-2020,https://doi.org/10.5194/isprs-annals-V-4-2020-79-2020, 2020

Observing geometry effects on a Global Navigation Satellite System (GNSS)-based water vapor tomography solved by least squares and by compressive sensing

Marion Heublein, Patrick Erik Bradley, and Stefan Hinz

Ann. Geophys., 38, 179–189, https://doi.org/10.5194/angeo-38-179-2020,https://doi.org/10.5194/angeo-38-179-2020, 2020

MAPPING GLACIER CHANGES USING CLUSTERING TECHNIQUES ON CLOUD COMPUTING INFRASTRUCTURE

V. Ayma, C. Beltrán, P. N. Happ, G. A. O. P. Costa, and R. Q. Feitosa

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W16, 29–34, https://doi.org/10.5194/isprs-archives-XLII-2-W16-29-2019,https://doi.org/10.5194/isprs-archives-XLII-2-W16-29-2019, 2019

IMPACT OF DIFFERENT TRAJECTORIES ON EXTRINSIC SELF-CALIBRATION FOR VEHICLE-BASED MOBILE LASER SCANNING SYSTEMS

M. Hillemann, J. Meidow, and B. Jutzi

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W16, 119–125, https://doi.org/10.5194/isprs-archives-XLII-2-W16-119-2019,https://doi.org/10.5194/isprs-archives-XLII-2-W16-119-2019, 2019

A COMPARISON BETWEEN THE HADOOP AND SPARK DISTRIBUTED FRAMEWORKS IN THE CONTEXT OF REGION-GROWING SEGMENTATION OF REMOTE SENSING IMAGES

R. B. Andrade, J. M. F. Santos, G. A. O. P. Costa, G. L. A. Mota, P. N. Happ, and R. Q. Feitosa

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W7, 3–8, https://doi.org/10.5194/isprs-annals-IV-2-W7-3-2019,https://doi.org/10.5194/isprs-annals-IV-2-W7-3-2019, 2019

A MANY-TO-MANY FULLY CONVOLUTIONAL RECURRENT NETWORK FOR MULTITEMPORAL CROP RECOGNITION

J. A. Chamorro, J. D. Bermudez, P. N. Happ, and R. Q. Feitosa

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W7, 25–32, https://doi.org/10.5194/isprs-annals-IV-2-W7-25-2019,https://doi.org/10.5194/isprs-annals-IV-2-W7-25-2019, 2019

IMAGE-TO-IMAGE TRANSLATION FOR ENHANCED FEATURE MATCHING, IMAGE RETRIEVAL AND VISUAL LOCALIZATION

M. S. Mueller, T. Sattler, M. Pollefeys, and B. Jutzi

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W7, 111–119, https://doi.org/10.5194/isprs-annals-IV-2-W7-111-2019,https://doi.org/10.5194/isprs-annals-IV-2-W7-111-2019, 2019

EVALUATION OF DEEP LEARNING TECHNIQUES FOR DEFORESTATION DETECTION IN THE AMAZON FOREST

M. X. Ortega, J. D. Bermudez, P. N. Happ, A. Gomes, and R. Q. Feitosa

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W7, 121–128, https://doi.org/10.5194/isprs-annals-IV-2-W7-121-2019,https://doi.org/10.5194/isprs-annals-IV-2-W7-121-2019, 2019

EFFICIENT SURFACE-AWARE SEMI-GLOBAL MATCHING WITH MULTI-VIEW PLANE-SWEEP SAMPLING

B. Ruf, T. Pollok, and M. Weinmann

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W7, 137–144, https://doi.org/10.5194/isprs-annals-IV-2-W7-137-2019,https://doi.org/10.5194/isprs-annals-IV-2-W7-137-2019, 2019

A COMPARATIVE ANALYSIS OF UNSUPERVISED AND SEMI-SUPERVISED REPRESENTATION LEARNING FOR REMOTE SENSING IMAGE CATEGORIZATION

P. J. Soto, J. D. Bermudez, P. N. Happ, and R. Q. Feitosa

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W7, 167–173, https://doi.org/10.5194/isprs-annals-IV-2-W7-167-2019,https://doi.org/10.5194/isprs-annals-IV-2-W7-167-2019, 2019

PREFACE – ISPRS WORKSHOP LASER SCANNING 2019

J. Boehm, M. Rutzinger, B. Yang, M. Weinmann, B. Riveiro, and W. Yao

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 915–917, https://doi.org/10.5194/isprs-archives-XLII-2-W13-915-2019,https://doi.org/10.5194/isprs-archives-XLII-2-W13-915-2019, 2019

PREFACE – ISPRS WORKSHOP HYPERSPECTRAL SENSING MEETS MACHINE LEARNING AND PATTERN ANALYSIS (HYPERMLPA 2019)

M. Weinmann, R. Müller, R. Reulke, E. Honkavaara, D. Tuia, and S. Keller

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1825–1826, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1825-2019,https://doi.org/10.5194/isprs-archives-XLII-2-W13-1825-2019, 2019

FUSION OF HYPERSPECTRAL, MULTISPECTRAL, COLOR AND 3D POINT CLOUD INFORMATION FOR THE SEMANTIC INTERPRETATION OF URBAN ENVIRONMENTS

M. Weinmann and M. Weinmann

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1899–1906, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1899-2019,https://doi.org/10.5194/isprs-archives-XLII-2-W13-1899-2019, 2019

AUTOMATIC CO-REGISTRATION OF AERIAL IMAGERY AND UNTEXTURED MODEL DATA UTILIZING AVERAGE SHADING GRADIENTS

S. Schmitz, M. Weinmann, and B. Ruf

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 581–588, https://doi.org/10.5194/isprs-archives-XLII-2-W13-581-2019,https://doi.org/10.5194/isprs-archives-XLII-2-W13-581-2019, 2019

PREFACE – ISPRS WORKSHOP LASER SCANNING 2019

J. Boehm, M. Rutzinger, B. Yang, M. Weinmann, B. Riveiro, and W. Yao

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W5, 313–315, https://doi.org/10.5194/isprs-annals-IV-2-W5-313-2019,https://doi.org/10.5194/isprs-annals-IV-2-W5-313-2019, 2019

PREFACE – HYPERSPECTRAL SENSING MEETS MACHINE LEARNING AND PATTERN ANALYSIS (HYPERMLPA 2019)

M. Weinmann, R. Müller, R. Reulke, E. Honkavaara, D. Tuia, and S. Keller

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W5, 607–608, https://doi.org/10.5194/isprs-annals-IV-2-W5-607-2019,https://doi.org/10.5194/isprs-annals-IV-2-W5-607-2019, 2019

PREFACE

B. Jutzi, M. Weinmann, and S. Hinz

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1, 1–3, https://doi.org/10.5194/isprs-annals-IV-1-1-2018,https://doi.org/10.5194/isprs-annals-IV-1-1-2018, 2018

SAR TO OPTICAL IMAGE SYNTHESIS FOR CLOUD REMOVAL WITH GENERATIVE ADVERSARIAL NETWORKS

J. D. Bermudez, P. N. Happ, D. A. B. Oliveira, and R. Q. Feitosa

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1, 5–11, https://doi.org/10.5194/isprs-annals-IV-1-5-2018,https://doi.org/10.5194/isprs-annals-IV-1-5-2018, 2018

SEMANTIC SEGMENTATION OF AERIAL IMAGERY VIA MULTI-SCALE SHUFFLING CONVOLUTIONAL NEURAL NETWORKS WITH DEEP SUPERVISION

K. Chen, M. Weinmann, X. Sun, M. Yan, S. Hinz, B. Jutzi, and M. Weinmann

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1, 29–36, https://doi.org/10.5194/isprs-annals-IV-1-29-2018,https://doi.org/10.5194/isprs-annals-IV-1-29-2018, 2018

INFRARED MEASUREMENTS AND ESTIMATION OF TEMPERATURE IN THE RESTRICTIVE SCOPE OF AN INDUSTRIAL CEMENT PLANT

R. Gabriel, S. Keller, J. Matthes, P. Waibel, H. B. Keller, and S. Hinz

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1, 53–60, https://doi.org/10.5194/isprs-annals-IV-1-53-2018,https://doi.org/10.5194/isprs-annals-IV-1-53-2018, 2018

DEVELOPING A MACHINE LEARNING FRAMEWORK FOR ESTIMATING SOIL MOISTURE WITH VNIR HYPERSPECTRAL DATA

S. Keller, F. M. Riese, J. Stötzer, P. M. Maier, and S. Hinz

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1, 101–108, https://doi.org/10.5194/isprs-annals-IV-1-101-2018,https://doi.org/10.5194/isprs-annals-IV-1-101-2018, 2018

FEASIBILITY INVESTIGATION ON SINGLE PHOTON LIDAR BASED WATER SURFACE MAPPING

G. Mandlburger and B. Jutzi

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1, 109–116, https://doi.org/10.5194/isprs-annals-IV-1-109-2018,https://doi.org/10.5194/isprs-annals-IV-1-109-2018, 2018

CNN-BASED INITIAL LOCALIZATION IMPROVED BY DATA AUGMENTATION

M. S. Mueller, A. Metzger, and B. Jutzi

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1, 117–124, https://doi.org/10.5194/isprs-annals-IV-1-117-2018,https://doi.org/10.5194/isprs-annals-IV-1-117-2018, 2018

DEEP CROSS-DOMAIN BUILDING EXTRACTION FOR SELECTIVE DEPTH ESTIMATION FROM OBLIQUE AERIAL IMAGERY

B. Ruf, L. Thiel, and M. Weinmann

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1, 125–132, https://doi.org/10.5194/isprs-annals-IV-1-125-2018,https://doi.org/10.5194/isprs-annals-IV-1-125-2018, 2018

INVESTIGATIONS ON THE POTENTIAL OF HYPERSPECTRAL AND SENTINEL-2 DATA FOR LAND-COVER / LAND-USE CLASSIFICATION

M. Weinmann, P. M. Maier, J. Florath, and U. Weidner

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1, 155–162, https://doi.org/10.5194/isprs-annals-IV-1-155-2018,https://doi.org/10.5194/isprs-annals-IV-1-155-2018, 2018

PREFACE

B. Jutzi, M. Weinmann, and S. Hinz

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1, 1–3, https://doi.org/10.5194/isprs-archives-XLII-1-1-2018,https://doi.org/10.5194/isprs-archives-XLII-1-1-2018, 2018

ON THE CATEGORIZATION OF HIGH ACTIVITY OBJECTS USING DIFFERENTIAL ATTRIBUTE PROFILES

M. Boldt, A. Thiele, K. Schulz, and S. Hinz

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1, 59–64, https://doi.org/10.5194/isprs-archives-XLII-1-59-2018,https://doi.org/10.5194/isprs-archives-XLII-1-59-2018, 2018

MARKER-BASED LOCALIZATION OF THE MICROSOFT HOLOLENS IN BUILDING MODELS

P. Hübner, M. Weinmann, and S. Wursthorn

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1, 195–202, https://doi.org/10.5194/isprs-archives-XLII-1-195-2018,https://doi.org/10.5194/isprs-archives-XLII-1-195-2018, 2018

LEM BENCHMARK DATABASE FOR TROPICAL AGRICULTURAL REMOTE SENSING APPLICATION

I. D. Sanches, R. Q. Feitosa, P. Achanccaray, B. Montibeller, A. J. B. Luiz, M. D. Soares, V. H. R. Prudente, D. C. Vieira, and L. E. P. Maurano

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1, 387–392, https://doi.org/10.5194/isprs-archives-XLII-1-387-2018,https://doi.org/10.5194/isprs-archives-XLII-1-387-2018, 2018

COMBINING INDEPENDENT VISUALIZATION AND TRACKING SYSTEMS FOR AUGMENTED REALITY

P. Hübner, M. Weinmann, M. Hillemann, B. Jutzi, and S. Wursthorn

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 455–462, https://doi.org/10.5194/isprs-archives-XLII-2-455-2018,https://doi.org/10.5194/isprs-archives-XLII-2-455-2018, 2018

RESIDUAL SHUFFLING CONVOLUTIONAL NEURAL NETWORKS FOR DEEP SEMANTIC IMAGE SEGMENTATION USING MULTI-MODAL DATA

K. Chen, M. Weinmann, X. Gao, M. Yan, S. Hinz, B. Jutzi, and M. Weinmann

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2, 65–72, https://doi.org/10.5194/isprs-annals-IV-2-65-2018,https://doi.org/10.5194/isprs-annals-IV-2-65-2018, 2018

REVISITING EXISTING CLASSIFICATION APPROACHES FOR BUILDING MATERIALS BASED ON HYPERSPECTRAL DATA

R. Ilehag, M. Weinmann, A. Schenk, S. Keller, B. Jutzi, and S. Hinz

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W3, 65–71, https://doi.org/10.5194/isprs-archives-XLII-3-W3-65-2017,https://doi.org/10.5194/isprs-archives-XLII-3-W3-65-2017, 2017

COLLABORATIVE MULTI-SCALE 3D CITY AND INFRASTRUCTURE MODELING AND SIMULATION

M. Breunig, A. Borrmann, E. Rank, S. Hinz, T. Kolbe, M. Schilcher, R.-P. Mundani, J. R. Jubierre, M. Flurl, A. Thomsen, A. Donaubauer, Y. Ji, S. Urban, S. Laun, S. Vilgertshofer, B. Willenborg, M. Menninghaus, H. Steuer, S. Wursthorn, J. Leitloff, M. Al-Doori, and N Mazroobsemnani

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4-W4, 341–352, https://doi.org/10.5194/isprs-archives-XLII-4-W4-341-2017,https://doi.org/10.5194/isprs-archives-XLII-4-W4-341-2017, 2017

USING MULTI-SCALE FEATURES FOR THE 3D SEMANTIC LABELING OF AIRBORNE LASER SCANNING DATA

R. Blomley and M. Weinmann

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W4, 43–50, https://doi.org/10.5194/isprs-annals-IV-2-W4-43-2017,https://doi.org/10.5194/isprs-annals-IV-2-W4-43-2017, 2017

PROJECTOR-BASED AUGMENTED REALITY FOR QUALITY INSPECTION OF SCANNED OBJECTS

J. Kern, M. Weinmann, and S. Wursthorn

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W4, 83–90, https://doi.org/10.5194/isprs-annals-IV-2-W4-83-2017,https://doi.org/10.5194/isprs-annals-IV-2-W4-83-2017, 2017

DETERMINING PLANE-SWEEP SAMPLING POINTS IN IMAGE SPACE USING THE CROSS-RATIO FOR IMAGE-BASED DEPTH ESTIMATION

B. Ruf, B. Erdnuess, and M. Weinmann

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W6, 325–332, https://doi.org/10.5194/isprs-archives-XLII-2-W6-325-2017,https://doi.org/10.5194/isprs-archives-XLII-2-W6-325-2017, 2017

POINT CLOUD ANALYSIS FOR UAV-BORNE LASER SCANNING WITH HORIZONTALLY AND VERTICALLY ORIENTED LINE SCANNERS – CONCEPT AND FIRST RESULTS

M. Weinmann, M. S. Müller, M. Hillemann, N. Reydel, S. Hinz, and B. Jutzi

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W6, 399–406, https://doi.org/10.5194/isprs-archives-XLII-2-W6-399-2017,https://doi.org/10.5194/isprs-archives-XLII-2-W6-399-2017, 2017

CONCEPT FOR CLASSIFYING FACADE ELEMENTS BASED ON MATERIAL, GEOMETRY AND THERMAL RADIATION USING MULTIMODAL UAV REMOTE SENSING

R. Ilehag, A. Schenk, and S. Hinz

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W6, 145–151, https://doi.org/10.5194/isprs-archives-XLII-2-W6-145-2017,https://doi.org/10.5194/isprs-archives-XLII-2-W6-145-2017, 2017

SQUEEZEPOSENET: IMAGE BASED POSE REGRESSION WITH SMALL CONVOLUTIONAL NEURAL NETWORKS FOR REAL TIME UAS NAVIGATION

M. S. Müller, S. Urban, and B. Jutzi

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W3, 49–57, https://doi.org/10.5194/isprs-annals-IV-2-W3-49-2017,https://doi.org/10.5194/isprs-annals-IV-2-W3-49-2017, 2017

INVESTIGATIONS ON THE POTENTIAL OF CONVOLUTIONAL NEURAL NETWORKS FOR VEHICLE CLASSIFICATION BASED ON RGB AND LIDAR DATA

R. Niessner, H. Schilling, and B. Jutzi

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1-W1, 115–123, https://doi.org/10.5194/isprs-annals-IV-1-W1-115-2017,https://doi.org/10.5194/isprs-annals-IV-1-W1-115-2017, 2017

GEOMETRIC FEATURES AND THEIR RELEVANCE FOR 3D POINT CLOUD CLASSIFICATION

M. Weinmann, B. Jutzi, C. Mallet, and M. Weinmann

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1-W1, 157–164, https://doi.org/10.5194/isprs-annals-IV-1-W1-157-2017,https://doi.org/10.5194/isprs-annals-IV-1-W1-157-2017, 2017

A METHOD TO ESTIMATE TEMPORAL INTERACTION IN A CONDITIONAL RANDOM FIELD BASED APPROACH FOR CROP RECOGNITION

P. M. A. Diaz, R. Q. Feitosa, I. D. Sanches, and G. A. O. P. Costa

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 205–211, https://doi.org/10.5194/isprs-archives-XLI-B7-205-2016,https://doi.org/10.5194/isprs-archives-XLI-B7-205-2016, 2016

NEXT-BEST-VIEW METHOD BASED ON CONSECUTIVE EVALUATION OF TOPOLOGICAL RELATIONS

K. O. Dierenbach, M. Weinmann, and B. Jutzi

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 11–19, https://doi.org/10.5194/isprs-archives-XLI-B3-11-2016,https://doi.org/10.5194/isprs-archives-XLI-B3-11-2016, 2016

Water vapor mapping by fusing InSAR and GNSS remote sensing data and atmospheric simulations

F. Alshawaf, B. Fersch, S. Hinz, H. Kunstmann, M. Mayer, and F. J. Meyer

Hydrol. Earth Syst. Sci., 19, 4747–4764, https://doi.org/10.5194/hess-19-4747-2015,https://doi.org/10.5194/hess-19-4747-2015, 2015

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PREFACE: TECHNICAL COMMISSION I

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