- Article
(1292 KB) - Metadata XML
- November 21, 2024
- |
- Home
- |
- Sitemap
- |
- The ISPRS Foundation
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLVIII-1/W2-2023
https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-225-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-225-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
13 Dec 2023
| 13 Dec 2023
TOWARDS LARGE-SCALE BUILDING ATTRIBUTE MAPPING USING CROWDSOURCED IMAGES: SCENE TEXT RECOGNITION ON FLICKR AND PROBLEMS TO BE SOLVED
Data Science in Earth Observation, Technical University of Munich, Germany
A. Kruspe
Faculty of Computer Science, Technische Hochschule Nürnberg, Germany
L. Meng
Cartography and Visual Analytics, Technical University of Munich, Germany
Y. Tian
Data Science in Earth Observation, Technical University of Munich, Germany
E. J. Hoffmann
Data Science in Earth Observation, Technical University of Munich, Germany
S. Auer
Remote Sensing Technology Institute, German Aerospace Center (DLR), Germany
X. X. Zhu
Data Science in Earth Observation, Technical University of Munich, Germany
Related authors
Yifan Tian, Yao Sun, and Xiao Xiang Zhu
Abstr. Int. Cartogr. Assoc., 7, 171, https://doi.org/10.5194/ica-abs-7-171-2024, https://doi.org/10.5194/ica-abs-7-171-2024, 2024
Yao Sun, Stefan Auer, Liqiu Meng, and Xiao Xiang Zhu
Abstr. Int. Cartogr. Assoc., 6, 250, https://doi.org/10.5194/ica-abs-6-250-2023, https://doi.org/10.5194/ica-abs-6-250-2023, 2023
Mengyi Wei, Chenjing Jiao, Chenyu Zuo, Lorenz Hurni, and Liqiu Meng
Abstr. Int. Cartogr. Assoc., 8, 26, https://doi.org/10.5194/ica-abs-8-26-2024, https://doi.org/10.5194/ica-abs-8-26-2024, 2024
Yifan Tian, Yao Sun, and Xiao Xiang Zhu
Abstr. Int. Cartogr. Assoc., 7, 171, https://doi.org/10.5194/ica-abs-7-171-2024, https://doi.org/10.5194/ica-abs-7-171-2024, 2024
Yi Zhen Chew, Ekaterina Chuprikova, Abraham Mejia-Aguilar, Nikolaus Obojes, Holger Kumke, and Liqiu Meng
Abstr. Int. Cartogr. Assoc., 7, 24, https://doi.org/10.5194/ica-abs-7-24-2024, https://doi.org/10.5194/ica-abs-7-24-2024, 2024
Nianhua Liu, Yu Feng, Shengkai Wang, and Liqiu Meng
Abstr. Int. Cartogr. Assoc., 7, 92, https://doi.org/10.5194/ica-abs-7-92-2024, https://doi.org/10.5194/ica-abs-7-92-2024, 2024
Gisela Romero Candanedo, Ekaterina Chuprikova, Abraham Mejia-Aguilar, Holger Kumke, and Liqiu Meng
Abstr. Int. Cartogr. Assoc., 7, 140, https://doi.org/10.5194/ica-abs-7-140-2024, https://doi.org/10.5194/ica-abs-7-140-2024, 2024
Erik Loebel, Mirko Scheinert, Martin Horwath, Angelika Humbert, Julia Sohn, Konrad Heidler, Charlotte Liebezeit, and Xiao Xiang Zhu
The Cryosphere, 18, 3315–3332, https://doi.org/10.5194/tc-18-3315-2024, https://doi.org/10.5194/tc-18-3315-2024, 2024
Short summary
Short summary
Comprehensive datasets of calving-front changes are essential for studying and modeling outlet glaciers. Current records are limited in temporal resolution due to manual delineation. We use deep learning to automatically delineate calving fronts for 23 glaciers in Greenland. Resulting time series resolve long-term, seasonal, and subseasonal patterns. We discuss the implications of our results and provide the cryosphere community with a data product and an implementation of our processing system.
Zhenghang Yuan, Zhitong Xiong, Lichao Mou, and Xiao Xiang Zhu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-140, https://doi.org/10.5194/essd-2024-140, 2024
Revised manuscript under review for ESSD
Short summary
Short summary
ChatEarthNet is an image-text dataset that provides high-quality, detailed natural language descriptions for global-scale satellite data. It consists of 163,488 image-text pairs with captions generated by ChatGPT-3.5, and an additional 10,000 image-text pairs with captions generated by ChatGPT-4V(ision). This dataset has significant potential for training and evaluating vision-language geo-foundation models in remote sensing.
Viola Steidl, Jonathan L. Bamber, and Xiao Xiang Zhu
EGUsphere, https://doi.org/10.5194/egusphere-2024-1732, https://doi.org/10.5194/egusphere-2024-1732, 2024
Short summary
Short summary
Glacier ice thickness is difficult to measure directly but is essential for glacier evolution modelling. In this work, we employ a novel approach combining physical knowledge and data-driven machine learning to estimate the ice thickness of multiple glaciers in Spitsbergen, Barentsøya, and Edgeøya in Svalbard. We identify challenges for the physics-aware machine learning model and opportunities for improving the accuracy and physical consistency that would also apply to other geophysical tasks.
Weiyan Lin, Jiasong Zhu, Yuansheng Hua, Qingyu Li, Lichao Mou, and Xiao Xiang Zhu
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-2024, 371–378, https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-371-2024, https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-371-2024, 2024
Tian Li, Konrad Heidler, Lichao Mou, Ádám Ignéczi, Xiao Xiang Zhu, and Jonathan L. Bamber
Earth Syst. Sci. Data, 16, 919–939, https://doi.org/10.5194/essd-16-919-2024, https://doi.org/10.5194/essd-16-919-2024, 2024
Short summary
Short summary
Our study uses deep learning to produce a new high-resolution calving front dataset for 149 marine-terminating glaciers in Svalbard from 1985 to 2023, containing 124 919 terminus traces. This dataset offers insights into understanding calving mechanisms and can help improve glacier frontal ablation estimates as a component of the integrated mass balance assessment.
J. Zhao, F. Roth, B. Bauer-Marschallinger, W. Wagner, M. Chini, and X. X. Zhu
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-1-W1-2023, 911–918, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-911-2023, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-911-2023, 2023
Yao Sun, Stefan Auer, Liqiu Meng, and Xiao Xiang Zhu
Abstr. Int. Cartogr. Assoc., 6, 250, https://doi.org/10.5194/ica-abs-6-250-2023, https://doi.org/10.5194/ica-abs-6-250-2023, 2023
Shengkai Wang, Bing Liu, Chenkun Zhang, Nianhua Liu, and Liqiu Meng
Abstr. Int. Cartogr. Assoc., 6, 267, https://doi.org/10.5194/ica-abs-6-267-2023, https://doi.org/10.5194/ica-abs-6-267-2023, 2023
Mengyi Wei, Chuan Chen, Chenyu Zuo, and Liqiu Meng
Abstr. Int. Cartogr. Assoc., 6, 269, https://doi.org/10.5194/ica-abs-6-269-2023, https://doi.org/10.5194/ica-abs-6-269-2023, 2023
Chuan Chen, Mengyi Wei, and Liqiu Meng
Abstr. Int. Cartogr. Assoc., 6, 35, https://doi.org/10.5194/ica-abs-6-35-2023, https://doi.org/10.5194/ica-abs-6-35-2023, 2023
Dongsheng Chen, Yu Feng, and Liqiu Meng
Abstr. Int. Cartogr. Assoc., 6, 36, https://doi.org/10.5194/ica-abs-6-36-2023, https://doi.org/10.5194/ica-abs-6-36-2023, 2023
Juliane Cron and Liqiu Meng
Abstr. Int. Cartogr. Assoc., 6, 44, https://doi.org/10.5194/ica-abs-6-44-2023, https://doi.org/10.5194/ica-abs-6-44-2023, 2023
Linfang Ding, Guohui Xiao, Albulen Pano, Hongchao Fan, Diego Calvanese, and Liqiu Meng
Abstr. Int. Cartogr. Assoc., 6, 53, https://doi.org/10.5194/ica-abs-6-53-2023, https://doi.org/10.5194/ica-abs-6-53-2023, 2023
Haosheng Huang, Yi Cheng, Weihua Dong, Georg Gartner, Jukka M. Krisp, and Liqiu Meng
Abstr. Int. Cartogr. Assoc., 6, 95, https://doi.org/10.5194/ica-abs-6-95-2023, https://doi.org/10.5194/ica-abs-6-95-2023, 2023
Nianhua Liu, Joel Salazar, Chuan Chen, Shengkai Wang, Rostislav Netek, Stanislav Popelka, and Liqiu Meng
Abstr. Int. Cartogr. Assoc., 6, 144, https://doi.org/10.5194/ica-abs-6-144-2023, https://doi.org/10.5194/ica-abs-6-144-2023, 2023
Zihan Liu, Peng Luo, Christian E. Murphy, and Liqiu Meng
Abstr. Int. Cartogr. Assoc., 6, 145, https://doi.org/10.5194/ica-abs-6-145-2023, https://doi.org/10.5194/ica-abs-6-145-2023, 2023
Peng Luo, Yongze Song, and Liqiu Meng
Abstr. Int. Cartogr. Assoc., 6, 148, https://doi.org/10.5194/ica-abs-6-148-2023, https://doi.org/10.5194/ica-abs-6-148-2023, 2023
Sasanka Madawalagama, Liqiu Meng, and Christian Murphy
Abstr. Int. Cartogr. Assoc., 6, 149, https://doi.org/10.5194/ica-abs-6-149-2023, https://doi.org/10.5194/ica-abs-6-149-2023, 2023
Liqiu Meng, Temenoujka Bandrova, Terje Midtbø, and Vít Voženílek
Abstr. Int. Cartogr. Assoc., 6, 164, https://doi.org/10.5194/ica-abs-6-164-2023, https://doi.org/10.5194/ica-abs-6-164-2023, 2023
Terje Midtbø, Temenoujka Bandrova, Georg Gartner, Miljenko Lapaine, Liqiu Meng, Jie Shen, Vít Voženílek, and Tao Wang
Abstr. Int. Cartogr. Assoc., 6, 166, https://doi.org/10.5194/ica-abs-6-166-2023, https://doi.org/10.5194/ica-abs-6-166-2023, 2023
Jingliang Hu, Rong Liu, Danfeng Hong, Andrés Camero, Jing Yao, Mathias Schneider, Franz Kurz, Karl Segl, and Xiao Xiang Zhu
Earth Syst. Sci. Data, 15, 113–131, https://doi.org/10.5194/essd-15-113-2023, https://doi.org/10.5194/essd-15-113-2023, 2023
Short summary
Short summary
Multimodal data fusion is an intuitive strategy to break the limitation of individual data in Earth observation. Here, we present a multimodal data set, named MDAS, consisting of synthetic aperture radar (SAR), multispectral, hyperspectral, digital surface model (DSM), and geographic information system (GIS) data for the city of Augsburg, Germany, along with baseline models for resolution enhancement, spectral unmixing, and land cover classification, three typical remote sensing applications.
Darya Lapo, Ekaterina Chuprikova, Abraham Mejia-Aguilar, Roberto Monsorno, and Liqiu Meng
Abstr. Int. Cartogr. Assoc., 5, 120, https://doi.org/10.5194/ica-abs-5-120-2022, https://doi.org/10.5194/ica-abs-5-120-2022, 2022
Edyta P. Bogucka and Liqiu Meng
Abstr. Int. Cartogr. Assoc., 5, 124, https://doi.org/10.5194/ica-abs-5-124-2022, https://doi.org/10.5194/ica-abs-5-124-2022, 2022
S. Zhao, S. Saha, and X. X. Zhu
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 1407–1413, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1407-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1407-2022, 2022
S. Saha, J. Gawlikowski, and X. X. Zhu
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 423–428, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-423-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-423-2022, 2022
F. Kurz, P. Mendes, V. Gstaiger, R. Bahmanyar, P. d’Angelo, S. M. Azimi, S. Auer, N. Merkle, C. Henry, D. Rosenbaum, J. Hellekes, H. Runge, F. Toran, and P. Reinartz
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2022, 221–226, https://doi.org/10.5194/isprs-annals-V-1-2022-221-2022, https://doi.org/10.5194/isprs-annals-V-1-2022-221-2022, 2022
T. Beker, H. Ansari, S. Montazeri, Q. Song, and X. X. Zhu
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 85–92, https://doi.org/10.5194/isprs-annals-V-3-2022-85-2022, https://doi.org/10.5194/isprs-annals-V-3-2022-85-2022, 2022
K. R. Traoré, A. Camero, and X. X. Zhu
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 217–224, https://doi.org/10.5194/isprs-annals-V-3-2022-217-2022, https://doi.org/10.5194/isprs-annals-V-3-2022-217-2022, 2022
Edyta P. Bogucka and Liqiu Meng
Abstr. Int. Cartogr. Assoc., 3, 33, https://doi.org/10.5194/ica-abs-3-33-2021, https://doi.org/10.5194/ica-abs-3-33-2021, 2021
Andreas Divanis and Liqiu Meng
Abstr. Int. Cartogr. Assoc., 3, 69, https://doi.org/10.5194/ica-abs-3-69-2021, https://doi.org/10.5194/ica-abs-3-69-2021, 2021
Ben Alexander McLeod, Ekaterina Chuprikova, Abraham Mejia-Aguilar, Dana Barthel, Katrin Janik, Ulrich Prechsl, Roberto Monsorno, and Liqiu Meng
Abstr. Int. Cartogr. Assoc., 3, 200, https://doi.org/10.5194/ica-abs-3-200-2021, https://doi.org/10.5194/ica-abs-3-200-2021, 2021
Liqiu Meng, Temenoujka Bandrova, Terje Midtbø, and Vít Voženílek
Abstr. Int. Cartogr. Assoc., 3, 205, https://doi.org/10.5194/ica-abs-3-205-2021, https://doi.org/10.5194/ica-abs-3-205-2021, 2021
Chenyu Zuo, Linfang Ding, and Liqiu Meng
Abstr. Int. Cartogr. Assoc., 3, 331, https://doi.org/10.5194/ica-abs-3-331-2021, https://doi.org/10.5194/ica-abs-3-331-2021, 2021
Lorenzo Libertini, Ekaterina Chuprikova, and Liqiu Meng
Proc. Int. Cartogr. Assoc., 4, 66, https://doi.org/10.5194/ica-proc-4-66-2021, https://doi.org/10.5194/ica-proc-4-66-2021, 2021
Y. Xie, K. Schindler, J. Tian, and X. X. Zhu
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 247–254, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-247-2021, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-247-2021, 2021
P. Ebel, S. Saha, and X. X. Zhu
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 243–249, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-243-2021, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-243-2021, 2021
O. Hagolle, J. Colin, S. Coustance, P. Kettig, P. D’Angelo, S. Auer, G. Doxani, and C. Desjardins
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2021, 9–15, https://doi.org/10.5194/isprs-annals-V-1-2021-9-2021, https://doi.org/10.5194/isprs-annals-V-1-2021-9-2021, 2021
S. Saha, L. Kondmann, and X. X. Zhu
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2021, 311–316, https://doi.org/10.5194/isprs-annals-V-3-2021-311-2021, https://doi.org/10.5194/isprs-annals-V-3-2021-311-2021, 2021
Andreas Divanis, Alissa Lüpke, and Liqiu Meng
AGILE GIScience Ser., 2, 24, https://doi.org/10.5194/agile-giss-2-24-2021, https://doi.org/10.5194/agile-giss-2-24-2021, 2021
D. Hong, J. Yao, X. Wu, J. Chanussot, and X. Zhu
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 423–428, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-423-2020, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-423-2020, 2020
J. Hu, L. Mou, and X. X. Zhu
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 1569–1574, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1569-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1569-2020, 2020
Q. Li, Y. Shi, S. Auer, R. Roschlaub, K. Möst, M. Schmitt, and X. X. Zhu
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 517–524, https://doi.org/10.5194/isprs-annals-V-2-2020-517-2020, https://doi.org/10.5194/isprs-annals-V-2-2020-517-2020, 2020
L. Mou, Y. Hua, P. Jin, and X. X. Zhu
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 533–540, https://doi.org/10.5194/isprs-annals-V-2-2020-533-2020, https://doi.org/10.5194/isprs-annals-V-2-2020-533-2020, 2020
C. Qiu, P. Gamba, M. Schmitt, and X. X. Zhu
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 787–794, https://doi.org/10.5194/isprs-annals-V-3-2020-787-2020, https://doi.org/10.5194/isprs-annals-V-3-2020-787-2020, 2020
M. Schmitt, J. Prexl, P. Ebel, L. Liebel, and X. X. Zhu
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 795–802, https://doi.org/10.5194/isprs-annals-V-3-2020-795-2020, https://doi.org/10.5194/isprs-annals-V-3-2020-795-2020, 2020
M. Schmitt, L. H. Hughes, C. Qiu, and X. X. Zhu
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W7, 145–152, https://doi.org/10.5194/isprs-annals-IV-2-W7-145-2019, https://doi.org/10.5194/isprs-annals-IV-2-W7-145-2019, 2019
M. Schmitt, L. H. Hughes, C. Qiu, and X. X. Zhu
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W7, 153–160, https://doi.org/10.5194/isprs-annals-IV-2-W7-153-2019, https://doi.org/10.5194/isprs-annals-IV-2-W7-153-2019, 2019
Andreas Divanis and Liqiu Meng
Abstr. Int. Cartogr. Assoc., 1, 64, https://doi.org/10.5194/ica-abs-1-64-2019, https://doi.org/10.5194/ica-abs-1-64-2019, 2019
Georg Gartner, Menno-Jan Kraak, Dirk Burghardt, Liqiu Meng, Juliane Cron, Corné van Elzakker, and Britta Ricker
Abstr. Int. Cartogr. Assoc., 1, 89, https://doi.org/10.5194/ica-abs-1-89-2019, https://doi.org/10.5194/ica-abs-1-89-2019, 2019
Edyta P. Bogucka and Liqiu Meng
Proc. Int. Cartogr. Assoc., 2, 9, https://doi.org/10.5194/ica-proc-2-9-2019, https://doi.org/10.5194/ica-proc-2-9-2019, 2019
Juliane Cron, Liqiu Meng, Edyta P. Bogucka, Georg Gartner, Dirk Burghardt, Menno-Jan Kraak, Corné van Elzakker, and Britta Ricker
Proc. Int. Cartogr. Assoc., 2, 21, https://doi.org/10.5194/ica-proc-2-21-2019, https://doi.org/10.5194/ica-proc-2-21-2019, 2019
Bing Liu, Weihua Dong, Lin Zhu, Huiping Liu, and Liqiu Meng
Proc. Int. Cartogr. Assoc., 2, 75, https://doi.org/10.5194/ica-proc-2-75-2019, https://doi.org/10.5194/ica-proc-2-75-2019, 2019
Chenyu Zuo, Linfang Ding, and Liqiu Meng
Proc. Int. Cartogr. Assoc., 2, 158, https://doi.org/10.5194/ica-proc-2-158-2019, https://doi.org/10.5194/ica-proc-2-158-2019, 2019
L. H. Hughes, S. Auer, and M. Schmitt
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2, 129–136, https://doi.org/10.5194/isprs-annals-IV-2-129-2018, https://doi.org/10.5194/isprs-annals-IV-2-129-2018, 2018
Linfang Ding, Liqiu Meng, Jian Yang, and Jukka M. Krisp
Proc. Int. Cartogr. Assoc., 1, 29, https://doi.org/10.5194/ica-proc-1-29-2018, https://doi.org/10.5194/ica-proc-1-29-2018, 2018
H. Lyu, L. Ding, H. Fan, and L. Meng
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1275–1282, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1275-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1275-2017, 2017
R. Ilehag, S. Auer, and P. d’Angelo
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W1, 55–61, https://doi.org/10.5194/isprs-archives-XLII-1-W1-55-2017, https://doi.org/10.5194/isprs-archives-XLII-1-W1-55-2017, 2017
The International Society for Photogrammetry and Remote Sensing is a non-governmental organization devoted to the development of international cooperation for the advancement of photogrammetry and remote sensing and their applications. The Society operates without any discrimination on grounds of race, religion, nationality, or political philosophy.
Useful Links
Useful External Links
Our Contact
c/o
Leibniz University Hannover
Institute of Photogrammetry and GeoInformation
Nienburger Str. 1
D-30167 Hannover
GERMANY
Email: isprs-sg@isprs.org