Editorial Note

Heipke, C.

doi:https://doi.org/10.5194/isprs-archives-XL-5-W7-543-2016

DEEP LEARNING FOR THE DETECTION OF EARLY SIGNS FOR FOREST DAMAGE BASED ON SATELLITE IMAGERY

D. Wittich, F. Rottensteiner, M. Voelsen, C. Heipke, and S. Müller

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2022, 307–315, https://doi.org/10.5194/isprs-annals-V-2-2022-307-2022,https://doi.org/10.5194/isprs-annals-V-2-2022-307-2022, 2022

INVESTIGATING 2D AND 3D CONVOLUTIONS FOR MULTITEMPORAL LAND COVER CLASSIFICATION USING REMOTE SENSING IMAGES

M. Voelsen, M. Teimouri, F. Rottensteiner, and C. Heipke

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 271–279, https://doi.org/10.5194/isprs-annals-V-3-2022-271-2022,https://doi.org/10.5194/isprs-annals-V-3-2022-271-2022, 2022

COOPERATIVE LOCALISATION USING IMAGE SENSORS IN A DYNAMIC TRAFFIC SCENARIO

P. Trusheim, Y. Chen, F. Rottensteiner, and C. Heipke

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2021, 117–124, https://doi.org/10.5194/isprs-archives-XLIII-B1-2021-117-2021,https://doi.org/10.5194/isprs-archives-XLIII-B1-2021-117-2021, 2021

CNN-BASED MULTI-SCALE HIERARCHICAL LAND USE CLASSIFICATION FOR THE VERIFICATION OF GEOSPATIAL DATABASES

C. Yang, F. Rottensteiner, and C. Heipke

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 495–502, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-495-2021,https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-495-2021, 2021

THERMAL ANOMALY DETECTION BASED ON SALIENCY ANALYSIS FROM MULTIMODAL IMAGING SOURCES

A. Sledz and C. Heipke

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2021, 55–64, https://doi.org/10.5194/isprs-annals-V-1-2021-55-2021,https://doi.org/10.5194/isprs-annals-V-1-2021-55-2021, 2021

MOUNTING CALIBRATION OF A MULTI-VIEW CAMERA SYSTEM ON A UAV PLATFORM

M. Mohammadi, A. Khami, F. Rottensteiner, I. Neumann, and C. Heipke

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2021, 97–104, https://doi.org/10.5194/isprs-annals-V-1-2021-97-2021,https://doi.org/10.5194/isprs-annals-V-1-2021-97-2021, 2021

SEMI-SUPERVISED SEGMENTATION OF CONCRETE AGGREGATE USING CONSENSUS REGULARISATION AND PRIOR GUIDANCE

M. Coenen, T. Schack, D. Beyer, C. Heipke, and M. Haist

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2021, 83–91, https://doi.org/10.5194/isprs-annals-V-2-2021-83-2021,https://doi.org/10.5194/isprs-annals-V-2-2021-83-2021, 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

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

AUTOMATICALLY GENERATED TRAINING DATA FOR LAND COVER CLASSIFICATION WITH CNNS USING SENTINEL-2 IMAGES

M. Voelsen, J. Bostelmann, A. Maas, F. Rottensteiner, and C. Heipke

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 767–774, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-767-2020,https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-767-2020, 2020

IMPROVING DISPARITY ESTIMATION BASED ON RESIDUAL COST VOLUME AND RECONSTRUCTION ERROR VOLUME

J. Kang, L. Chen, F. Deng, and C. Heipke

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 135–142, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-135-2020,https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-135-2020, 2020

IMPROVING THE CLASSIFICATION OF LAND USE OBJECTS USING DENSE CONNECTIVITY OF CONVOLUTIONAL NEURAL NETWORKS

A. Gujrathi, C. Yang, F. Rottensteiner, K. M. Buddhiraju, and C. Heipke

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 667–673, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-667-2020,https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-667-2020, 2020

PRECISION OF VISUAL LOCALIZATION USING DYNAMIC GROUND CONTROL POINTS

P. Trusheim and C. Heipke

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2020, 363–370, https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-363-2020,https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-363-2020, 2020

UAV-BASED THERMAL ANOMALY DETECTION FOR DISTRIBUTED HEATING NETWORKS

A. Sledz, J. Unger, and C. Heipke

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2020, 499–505, https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-499-2020,https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-499-2020, 2020

DEEP LEARNING BASED FEATURE MATCHING AND ITS APPLICATION IN IMAGE ORIENTATION

L. Chen, F. Rottensteiner, and C. Heipke

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 25–33, https://doi.org/10.5194/isprs-annals-V-2-2020-25-2020,https://doi.org/10.5194/isprs-annals-V-2-2020-25-2020, 2020

GEOMETRY-BASED REGULARISATION FOR DENSE IMAGE MATCHING VIA UNCERTAINTY-DRIVEN DEPTH PROPAGATION

M. Höllmann, M. Mehltretter, and C. Heipke

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 151–159, https://doi.org/10.5194/isprs-annals-V-2-2020-151-2020,https://doi.org/10.5194/isprs-annals-V-2-2020-151-2020, 2020

EXPLORING SEMANTIC RELATIONSHIPS FOR HIERARCHICAL LAND USE CLASSIFICATION BASED ON CONVOLUTIONAL NEURAL NETWORKS

C. Yang, F. Rottensteiner, and C. Heipke

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 599–607, https://doi.org/10.5194/isprs-annals-V-2-2020-599-2020,https://doi.org/10.5194/isprs-annals-V-2-2020-599-2020, 2020

USING REDUNDANT INFORMATION FROM MULTIPLE AERIAL IMAGES FOR THE DETECTION OF BOMB CRATERS BASED ON MARKED POINT PROCESSES

C. Kruse, F. Rottensteiner, and C. Heipke

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 861–870, https://doi.org/10.5194/isprs-annals-V-2-2020-861-2020,https://doi.org/10.5194/isprs-annals-V-2-2020-861-2020, 2020

INVESTIGATIONS ON SKIP-CONNECTIONS WITH AN ADDITIONAL COSINE SIMILARITY LOSS FOR LAND COVER CLASSIFICATION

C. Yang, F. Rottensteiner, and C. Heipke

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 339–346, https://doi.org/10.5194/isprs-annals-V-3-2020-339-2020,https://doi.org/10.5194/isprs-annals-V-3-2020-339-2020, 2020

SEMANTIC SEGMENTATION OF BRAZILIAN SAVANNA VEGETATION USING HIGH SPATIAL RESOLUTION SATELLITE DATA AND U-NET

A. K. Neves, T. S. Körting, L. M. G. Fonseca, C. D. Girolamo Neto, D. Wittich, G. A. O. P. Costa, and C. Heipke

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 505–511, https://doi.org/10.5194/isprs-annals-V-3-2020-505-2020,https://doi.org/10.5194/isprs-annals-V-3-2020-505-2020, 2020

SUPERVISED DETECTION OF BOMB CRATERS IN HISTORICAL AERIAL IMAGES USING CONVOLUTIONAL NEURAL NETWORKS

D. Clermont, C. Kruse, F. Rottensteiner, and C. Heipke

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W16, 67–74, https://doi.org/10.5194/isprs-archives-XLII-2-W16-67-2019,https://doi.org/10.5194/isprs-archives-XLII-2-W16-67-2019, 2019

MARKED POINT PROCESSES FOR THE AUTOMATIC DETECTION OF BOMB CRATERS IN AERIAL WARTIME IMAGES

C. Kruse, F. Rottensteiner, and C. Heipke

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 51–60, https://doi.org/10.5194/isprs-archives-XLII-2-W13-51-2019,https://doi.org/10.5194/isprs-archives-XLII-2-W13-51-2019, 2019

TOWARDS BETTER CLASSIFICATION OF LAND COVER AND LAND USE BASED ON CONVOLUTIONAL NEURAL NETWORKS

C. Yang, F. Rottensteiner, and C. Heipke

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 139–146, https://doi.org/10.5194/isprs-archives-XLII-2-W13-139-2019,https://doi.org/10.5194/isprs-archives-XLII-2-W13-139-2019, 2019

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