REVIEW PAPER
Geoprocessing of archival aerial photos and their scientific applications: A review
Adam Kostrzewa 1, A,D-F
 
 
 
More details
Hide details
1
Department of Photogrammetry, Remote Sensing and Spatial Information Systems, Faculty of Geodesy and Cartography, Warsaw University of Technology, Pl. Politechniki 1, 00-661, Warsaw, Poland
 
 
A - Research concept and design; B - Collection and/or assembly of data; C - Data analysis and interpretation; D - Writing the article; E - Critical revision of the article; F - Final approval of article
 
 
Submission date: 2024-03-11
 
 
Final revision date: 2024-05-13
 
 
Acceptance date: 2024-06-03
 
 
Publication date: 2024-07-15
 
 
Corresponding author
Adam Kostrzewa   

Department of Photogrammetry, Remote Sensing and Spatial Information Systems, Faculty of Geodesy and Cartography, Warsaw University of Technology, Pl. Politechniki 1, 00-661, Warsaw, Poland
 
 
Reports on Geodesy and Geoinformatics 2024;118:1-16
 
KEYWORDS
TOPICS
ABSTRACT
Poland as well as other countries keep extensive collections of 20th and 21st-century aerial photos, which are underexploited compared to such other archival materials as satellite imagery. Meanwhile, they offer significant research potential in various areas, including urban development, land use changes, and long-term environmental monitoring. Archival photographs are detailed, often obtained every five to ten years, and feature high resolution, from 20 cm to 1 m. Their overlap can facilitate creating precise digital models that illustrate topography and land cover, which are essential variables in many scientific contexts. However, rapidly transforming these photographs into geographically accurate measurements of the Earth’s surface poses challenges. This article explores the obstacles in automating the processing of historical photographs and presents the main scientific research directions associated with these images. Recent advancements in enhancing workflows, including the development of modern digital photogrammetry tools, algorithms, and machine learning techniques are also discussed. These developments are crucial for unlocking the full potential of aerial photographs, making them easier accessible and valuable for a broader range of scientific fields. These underutilized photographs are increasingly recognized as vital in various research domains due to technological advancements. Integrating new methods with these historical images offers unprecedented opportunities for scientific discovery and historical understanding, bridging the past with the future through innovative research techniques.
 
REFERENCES (140)
1.
Adami, A. et al. (2015). 4D City transformations by time series of aerial images. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 40(5W4):339–344.
 
2.
Aguiar, F. C., Martins, M. J., Silva, P. C., and Fernandes, M. R. (2016). Riverscapes downstream of hydropower dams: Effects of altered flows and historical land-use change. Landscape and Urban Planning, 153:83–98, doi:10.1016/j.landurbplan.2016.04.009.
 
3.
Aguilar, M. A., Aguilar, F. J., Fernández, I., and Mills, J. P. (2012). Accuracy assessment of commercial self-calibrating bundle adjustment routines applied to archival aerial photography. The Photogrammetric Record, 28(141):96–114, doi:10.1111/j.1477-9730.2012.00704.x.
 
4.
Aleithe, W. (2022). AFS150 – The new, fast photogrammetric scanner for analog airborne imagery. In 2nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, Rome, Italy, 5–6 December 2022.
 
5.
Antic, J. (2024). Jantic/DeOldify [Python]. https://github.com/jantic/DeOl..., (Original work published 2018.
 
6.
Appeaning Addo, K., Walkden, M., and Mills, J. (2008). Detection, measurement and prediction of shoreline recession in Accra, Ghana. ISPRS Journal of Photogrammetry and Remote Sensing, 63(5):543–558, doi:10.1016/j.isprsjprs.2008.04.001.
 
7.
Bakker, M. and Lane, S. N. (2017). Archival photogrammetric analysis of river-floodplain systems using Structure from Motion (SfM) methods. Earth Surface Processes and Landforms, 42(8):1274–1286, doi:10.1002/esp.4085.
 
8.
Baltsavias, E. P. (1999). On the performance of photogrammetric scanners. Technical report.
 
9.
Baltsavias, E. P. and Käser, C. (1999). Quality evaluation of the DSW200, DSW300, SCAI and OrthoVision photogrammetric scanners. doi:10.3929/ETHZ-A-004334177.
 
10.
Bozzini, C. (2022). Monoplotting and historical aerial images for 3D GIS. In 2nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, Rome, Italy, 5–6 December 2022.
 
11.
Brenner, S., Zambanini, S., and Sablatnig, R. (2018). Detection of bomb craters in WWII aerial images. In Proceedings of the OAGM Workshop, volume 2018, pages 94–97. Verlag der Technischen Universität Graz Graz, Austria, doi:10.3217/978-3-85125-603-1-20.
 
12.
Buller, H. (2019). Preservation and digitizing of historical aerial images in Norway. In 1nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, IGN, Paris, France, 3–4 June 2019.
 
13.
Buller, H. (2022). Historical aerial images – What’s going on in Norway. In 2nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, Rome, Italy, 5–6 December 2022.
 
14.
Bygren, A. and Hedqvist, E. (2019). Making it digital – Processing the aerial image archive of Sweden. In 1nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, IGN, Paris, France, 3–4 June 2019.
 
15.
Caridade, C., Marçal, A. R., and Mendonça, T. (2008). The use of texture for image classification of black & white air photographs. International Journal of Remote Sensing, 29(2):593–607, doi:10.1080/01431160701281015.
 
16.
Carvalho, R. C., Kennedy, D. M., Niyazi, Y., Leach, C., Konlechner, T. M., and Ierodiaconou, D. (2020). Structure-from-motion photogrammetry analysis of historical aerial photography: Determining beach volumetric change over decadal scales. Earth Surface Processes and Landforms, 45(11):2540–2555, doi:10.1002/esp.4911.
 
17.
Chilczuk, M. and Ciołkosz, A. (1966). Zastosowanie zdjęć lotniczych w geografii (The use of aerial photographs in geography). Państwowe Wydawnictwo Naukowe.
 
18.
Cléri, I., Pierrot-Deseilligny, M., and Vallet, B. (2014). Automatic georeferencing of a heritage of old analog aerial photographs. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, II–3:33–40, doi:10.5194/isprsannals-ii-3-33-2014.
 
19.
Cowley, D. C., Ferguson, L. M., and Williams, A. (2013). The aerial reconnaissance archives: A global aerial photographic collection. In Hanson, W. and Oltean, I., editors, Archaeology from historical aerial and satellite archives, pages 13–30. Springer, doi:10.1007/978-1-4614-4505-0_2.
 
20.
Craciun, D. and Le Bris, A. (2022). Automatic algorithm for georeferencing historical-to-nowadays aerial images acquired in natural environments. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B2-2022:21–28, doi:10.5194/isprs-archives-xliii-b2-2022-21-2022.
 
21.
Cramer, M. (2022). On the use of historical imagery for cadastral photogrammetry: Case study from the Heilbronn district. In 2nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, Rome, Italy, 5–6 December 2022.
 
22.
Cusicanqui, D., Rabatel, A., Bodin, X., Vincent, C., Thibert, E., Allain Duvillard, P., and Revil, A. (2021). Using historical aerial imagery to assess multidecadal kinematics and elevation changes. Application to mountain permafrost in the French Alps. In EGU General Assembly Conference Abstracts, pages EGU21–16371. doi:10.5194/egusphere-egu21-16371.
 
23.
Davidson, L. and Peppa, M. V. (2019). Experiences with processing and co-registration of archival image datasets. In 1nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, IGN, Paris, France, 3–4 June 2019.
 
24.
Dias, M., Monteiro, J., Estima, J., Silva, J., and Martins, B. (2019). Semantic segmentation of high-resolution aerial imagery with W-Net models. In Progress in Artificial Intelligence: 19th EPIA Conference on Artificial Intelligence, EPIA 2019, Vila Real, Portugal, September 3–6, 2019, Proceedings, Part II 19, pages 486–498. Springer, doi:10.1007/978-3-030-30244-3_40.
 
25.
Dias, M., Monteiro, J., Estima, J., Silva, J., and Martins, B. (2020). Semantic segmentation and colorization of grayscale aerial imagery with W-Net models. Expert systems, 37(6):e12622, doi:10.1111/exsy.12622.
 
26.
Dušánek, P., Potůčková, M., and Hodač, J. (2019). Historical aerial images of Czechia – Archiving and applications in landscape studies. In 1nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, IGN, Paris, France, 3–4 June 2019.
 
27.
Falkowski, P., Kuczyński, Z., and Uchański, J. (2007). Ortofoto zniszczonej Warszawy (Orthophoto of destroyed Warsaw). Geodeta: magazyn geoinformacyjny, pages 14–18.
 
28.
Farella, E. M., Malek, S., and Remondino, F. (2022a). Colorizing the past: Deep learning for the automatic colorization of historical aerial images. Journal of Imaging, 8(10):269, doi:10.3390/jimaging8100269.
 
29.
Farella, E. M., Morelli, L., Remondino, F., Mills, J. P., Haala, N., and Crompvoets, J. (2022b). The EuroSDR time benchmark for historical aerial images. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B2-2022:1175–1182, doi:10.5194/isprs-archives-xliii-b2-2022-1175-2022.
 
30.
Faure, E., Ratajczak, R., Crispim-Junior, C., Perol, O., Tougne, L., and Fervers, B. (2018). Development of a software based on automatic multi-temporal aerial images classification to assess retrospective environmental exposures to pesticides in epidemiological studies. Revue d’Épidémiologie et de Santé Publique, 66:S429, doi:10.1016/j.respe.2018.05.529.
 
31.
Fernandez, L. M. (2022). A mission over time: Preserving and disseminating historical aerial images guarded by the National Geographic Institute (IGN) of Spain. In 2nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, Rome, Italy, 5–6 December 2022.
 
32.
Feurer, D. and Vinatier, F. (2018). Joining multi-epoch archival aerial images in a single SfM block allows 3-D change detection with almost exclusively image information. ISPRS Journal of Photogrammetry and Remote Sensing, 146:495–506, doi:10.1016/j.isprsjprs.2018.10.016.
 
33.
Fieber, K. D., Mills, J. P., Miller, P. E., Clarke, L., Ireland, L., and Fox, A. J. (2018). Rigorous 3D change determination in Antarctic Peninsula glaciers from stereo WorldView-2 and archival aerial imagery. Remote Sensing of Environment, 205:18–31, doi:10.1016/j.rse.2017.10.042.
 
34.
Fleischer, F., Haas, F., Altmann, M., Rom, J., Ressl, C., and Becht, M. (2023). Glaciogenic periglacial landform in the making—geomorphological evolution of a rockfall on a small glacier in the Horlachtal, Stubai Alps, Austria. Remote Sensing, 15(6):1472, doi:10.3390/rs15061472.
 
35.
Ginzler, C. and Hobi, M. (2015). Countrywide stereo-image matching for updating digital surface models in the framework of the Swiss National Forest Inventory. Remote Sensing, 7(4):4343–4370, doi:10.3390/rs70404343.
 
36.
Giordano, S. and Bris, A. L. (2019). Towards fully automatic orthophoto and DSM generation. In 1nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, IGN, Paris, France, 3–4 June 2019.
 
37.
Giordano, S., Le Bris, A., and Mallet, C. (2018). Toward automatic georeferencing of archival aerial photogrammetric surveys. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, IV–2:105–112, doi:10.5194/isprs-annals-iv-2-105-2018.
 
38.
Giordano, S. and Mallet, C. (2019a). Archiving and geoprocessing of historical aerial images. In 1nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, IGN, Paris, France, 3–4 June 2019.
 
39.
Giordano, S. and Mallet, C. (2019b). Archiving and geoprocessing of historical aerial images: Current status in Europe. Technical Report 70, EuroSDR Oficial Publication.
 
40.
Gomez, C., Hayakawa, Y., and Obanawa, H. (2015). A study of Japanese landscapes using structure from motion derived DSMs and DEMs based on historical aerial photographs: New opportunities for vegetation monitoring and diachronic geomorphology. Geomorphology, 242:11–20, doi:10.1016/j.geomorph.2015.02.021.
 
41.
Gonçalves, J. A. (2016). Automatic orientation and mosaicking of archived aerial photography using Structure from Motion. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-3/W4:123–126, doi:10.5194/isprs-archives-xl-3-w4-123-2016.
 
42.
Grottoli, E., Biausque, M., Rogers, D., Jackson, D. W., and Cooper, J. A. G. (2020). Structure-from-motion-derived digital surface models from historical aerial photographs: A new 3D application for coastal dune monitoring. Remote Sensing, 13(1):95, doi:10.3390/rs13010095.
 
43.
Haala, N., Hastedt, H., Wolf, K., Ressl, C., and Baltrusch, S. (2010). Digital photogrammetric camera evaluation generation of digital elevation models. Photogrammetrie-Fernerkundung-Geoinformation, pages 99–115, doi:10.1127/1432-8364/2010/0043.
 
44.
Heisig, H. and Simmen, J.-L. (2021). Re-engineering the past: Countrywide geo-referencing of archival aerial imagery. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 89(6):487–503, doi:10.1007/s41064-021-00162-z.
 
45.
Heller, R. C., Doverspike, G., and Aldrich, R. (1964). Identification of Tree Species on Large-scale Panchromatic and Color Aerial Photographs. US Department of Agriculture, Forest Service, Agriculture Handbook No. 261.
 
46.
Höhle, J. and Höhle, M. (2009). Accuracy assessment of digital elevation models by means of robust statistical methods. ISPRS Journal of Photogrammetry and Remote Sensing, 64(4):398–406, doi:10.1016/j.isprsjprs.2009.02.003.
 
47.
Hirschmüller, H. (2011). Semi-global matching-motivation, developments and applications. In Photogrammetric Week 11, pages 173–184. Wichmann.
 
48.
Hodač, J. and Zemánková, A. (2018). Historical orthophotos created on base of single photos specifics of processing. Stavební obzor-Civil Engineering Journal, 27(3), doi:10.14311/CEJ.2018.03.0034.
 
49.
Hong, X. and Roosevelt, C. H. (2023). Orthorecti¬cation of large datasets of multi-scale archival aerial imagery: A case study from Türkiye. Journal of Geovisualization and Spatial Analysis, 7(2):23, doi:10.1007/s41651-023-00153-1.
 
50.
Honkavaara, E., Litkey, P., and Nurminen, K. (2013). Automatic storm damage detection in forests using high-altitude photogrammetric imagery. Remote Sensing, 5(3):1405–1424, doi:10.3390/rs5031405.
 
51.
Iizuka, S., Simo-Serra, E., and Ishikawa, H. (2016). Let there be color! Joint end-to-end learning of global and local image priors for automatic image colorization with simultaneous classification. ACM Transactions on Graphics (ToG), 35(4):1–11, doi:10.1145/2897824.292597.
 
52.
Ishiguro, S., Yamano, H., and Oguma, H. (2016). Evaluation of DSMs generated from multi-temporal aerial phoographs using emerging structure from motion-multi-view stereo technology. Geomorphology, 268:64–71, doi:10.1016/j.geomorph.2016.05.029.
 
53.
Ishii, R., Carbonneau, P., and Miyamoto, H. (2021). Colorisation of archival aerial imagery using deep learning. In EGU General Assembly Conference Abstracts, pages EGU21–11925. doi:10.5194/egusphere-egu21-11925.
 
54.
Jabrane, N. and Heisig, H. (2022). Bringing the Swiss Landscape Memory to Life. In 2nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, Rome, Italy, 5–6 December 2022.
 
55.
Jauhiainen, S., Holopainen, M., and Rasinmäki, A. (2007). Monitoring peatland vegetation by means of digitized aerial photographs. Scandinavian Journal of Forest Research, 22(2):168–177, doi:10.1080/02827580701217620.
 
56.
Karel, W. (2022). Implicit/deep georeferencing of WWII aerial reconnaissance images. In 2nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, Rome, Italy, 5–6 December 2022.
 
57.
Karwel, A. K. and Markiewicz, J. (2022). The methodology of the archival aerial image orientation based on the SfM method. Sensors and Machine Learning Applications, 1(2), doi:10.55627/smla.001.02.0015.
 
58.
Kervyn, F. (2022). RMCA’s historical aerial photographs of central Africa: The collection, its management and its potential for environmental studies. In 2nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, Rome, Italy, 5–6 December 2022.
 
59.
Kim, J. S., Miller, C. C., and Bethel, J. (2010). Automated georeferencing of historic aerial photography. Journal of Terrestrial Observation, 2(1):6.
 
60.
Knuth, F. (2022). Historical Structure from Motion (HSfM): Automated processing of historical aerial photographs for long-term geodetic change analysis.
 
61.
Knuth, F., Shean, D., Bhushan, S., Schwat, E., Alexandrov, O., McNeil, C., Dehecq, A., Florentine, C., and O’Neel, S. (2023). Historical Structure from Motion (HSfM): Automated processing of historical aerial photographs for long-term topographic change analysis. Remote Sensing of Environment, 285:113379, doi:10.1016/j.rse.2022.113379.
 
62.
Korpela, I. (2006). Geometrically accurate time series of archived aerial images and airborne lidar data in a forest environment. Silva Fennica, 40(1):109.
 
63.
Kostrzewa, A., Farella, E. M., Morelli, L., Ostrowski, W., Remondino, F., and Bakuła, K. (2024). Digitizing historical aerial images: Evaluation of the effects of scanning quality on aerial triangulation and dense image matching. Applied Sciences, 14(9):3635, doi:10.3390/app14093635.
 
64.
Kruse, C. (2019). Marked point processes for the automatic detection of bomb craters in aerial wartime images. In 1nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, IGN, Paris, France, 3–4 June 2019.
 
65.
Kruse, C., Rottensteiner, F., and Heipke, C. (2019). Marked point processes for the automatic detection of bomb craters in aerial wartime images. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences; 42-2/W13, 42(2/W13):51–60, doi:10.5194/isprs-archives-XLII-2-W13-51-2019.
 
66.
Kuna, J. (2022). The orthophotomap of Lublin 1944: from photographs to map application – idea, methods, contemporary challenges of processing and publishing archival aerial photographs. Polish Cartographical Review, 54(1):123–142, doi:10.2478/pcr-2022-0009.
 
67.
Kupidura, P., Osińska-Skotak, K., Lesisz, K., and Podkowa, A. (2019). The efficacy analysis of determining the wooded and shrubbed area based on archival aerial imagery using texture analysis. ISPRS International Journal of Geo-Information, 8(10):450, doi:10.3390/ijgi8100450.
 
68.
Kurczyński, Z. (1997). Zdjęcia lotnicze dla obszaru Polski realizowane w ramach programu modernizacji krajowego systemu informacji o terenie (aerial photos for the area of Poland carried out as part of the modernization program of the national terrain information system). Archiwum Fotogrametrii, Kartogra¬i i Teledetekcji, 6:31–44.
 
69.
Kurczyński, Z. (2014). Fotogrametria (Photogrammetry). Wydawnictwo Naukowe PWN SA.
 
70.
Kurczyński, Z. and Bakuła, K. (2013). Generowanie referencyjnego numerycznego modelu terenu o zasięgu krajowym w oparciu o lotnicze skanowanie laserowe w projekcie ISOK (Generating a reference digital terrain model with national scope based on airborne laser scanning in the ISOK project). Archiwum Fotogrametrii, Kartogra¬i i Teledetekcji, pages 59–68.
 
71.
Larsson, G., Maire, M., and Shakhnarovich, G. (2016). Learning representations for automatic colorization. In Leibe, B., Matas, J., Sebe, N., and Welling, M., editors, Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11–14, 2016, Proceedings, Part IV 14, pages 577–593. Springer, doi:10.1007/978-3-319-46493-0_35.
 
72.
Le Bris, A. (2022). Geometric and radiometric processing of historical aerial photogrammetric campaigns. In 2nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, Rome, Italy, 5–6 December 2022.
 
73.
Le Bris, A., Giordano, S., and Mallet, C. (2020). CNN semantic segmentation to retrieve past land cover out of historical orthoimages and DSM: First experiments. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V-2–2020:1013–1019, doi:10.5194/isprs-annals-v-2-2020-1013-2020.
 
74.
Lelégard, L., Le Bris, A., and Giordano, S. (2020). Correction of systematic radiometric inhomogeneity in scanned aerial campaigns using principal component analysis. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V-2–2020:871–876, doi:10.5194/isprs-annals-v-2-2020-871-2020.
 
75.
Lisenbarth, A. (1991). Działalność instytucji i komórek fotogrametrycznych w Polsce (1921–1990) (Activities of photogrammetric institutions and cells in Poland (1921–1990)). 60-lecie Polskiego Towarzystwa fotogrametrycznego, 1:63–76.
 
76.
Lisenbarth, A. (2000). Udział polskich fotogrametrów w rozwoju metod i technik fotogrametrycznych (1911–2000) (Participation of Polish photogrammeters in the development of photogrammetric methods and techniques (1911–2000)). Archiwum Fotogrametrii, Kartografii i Teledetekcji, 10:5–12.
 
77.
Luman, D. E., Stohr, C., and Hunt, L. (1997). Digital reproduction of historical aerial photographic prints for preserving a deteriorating archive. Photogrammetric engineering and remote sensing, 63(10):1171–1179.
 
78.
Lydersen, J. M. and Collins, B. M. (2018). Change in vegetation patterns over a large forested landscape based on historical and contemporary aerial photography. Ecosystems, 21(7):1348–1363, doi:10.1007/s10021-018-0225-5.
 
79.
Maiwald, F., Feurer, D., and Eltner, A. (2023). Solving photogrammetric cold cases using AI-based image matching: New potential for monitoring the past with historical aerial images. ISPRS Journal of Photogrammetry and Remote Sensing, 206:184–200, doi:10.1016/j.isprsjprs.2023.11.008.
 
80.
Mallet, C. and Le Bris, A. (2020). Current challenges in operational very high resolution land-cover mapping. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B2-2020:703–710, doi:10.5194/isprs-archives-xliii-b2-2020-703-2020.
 
81.
Marty, M., Waser, L. T., and Ginzler, C. (2022). Country wide digital vegetation height models from historical stereo imagery for Switzerland. In 2nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, Rome, Italy, 5–6 December 2022.
 
82.
Maurya, L., Lohchab, V., Kumar Mahapatra, P., and Abonyi, J. (2022). Contrast and brightness balance in image enhancement using Cuckoo Search – optimized image fusion. Journal of King Saud University - Computer and Information Sciences, 34(9):7247–7258, doi:10.1016/j.jksuci.2021.07.008.
 
83.
Mboga, N., D’Aronco, S., Grippa, T., Pelletier, C., Georganos, S., Vanhuysse, S., Wolff, E., Smets, B., Dewitte, O., Lennert, M., and Wegner, J. D. (2021). Domain adaptation for semantic segmentation of historical panchromatic orthomosaics in Central Africa. ISPRS International Journal of Geo-Information, 10(8):523, doi:10.3390/ijgi10080523.
 
84.
Mboga, N., Grippa, T., Georganos, S., Vanhuysse, S., Smets, B., Dewitte, O., Wolff, E., and Lennert, M. (2020). Fully convolutional networks for land cover classification from historical panchromatic aerial photographs. ISPRS Journal of Photogrammetry and Remote Sensing, 167:385–395, doi:10.1016/j.isprsjprs.2020.07.005.
 
85.
Meixner, P. (2019). Historical orthophoto of Prague 1945. In 1st EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, IGN, Paris, France, 3–4 June 2019.
 
86.
Meixner, P. (2022). Phase one scan station vs. high precision photogrammetric scanners: Practical experience in performing aerial triangulation in everyday production environment. In 2nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, Rome, Italy, 5–6 December 2022.
 
87.
Meixner, P. and Eckstein, M. (2016). Multi-temporal analysis of WWII reconnaissance photos. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 41:973–978, doi:10.5194/isprs-archives-XLI-B8-973-2016.
 
88.
Micheletti, N., Lane, S. N., and Chandler, J. H. (2015). Application of archival aerial photogrammetry to quantify climate forcing of alpine landscapes. The photogrammetric record, 30(150):143–165, doi:10.1111/phor.12099.
 
89.
Miller, P., Mills, J., Edwards, S., Bryan, P., Marsh, S., Mitchell, H., and Hobbs, P. (2008). A robust surface matching technique for coastal geohazard assessment and management. ISPRS Journal of Photogrammetry and Remote Sensing, 63(5):529–542, doi:10.1016/j.isprsjprs.2008.02.003.
 
90.
Mitrovic, M., Cvijetinovic, Z., and Mihajlovic, D. (2004). Procedures and experiences on using desktop scanner for orthophoto production. In ISPRS 2004 commission IV - Geo-Imagery bridging continents. XXth ISPRS congress, Istanbul, Turkey, pages 53–58.
 
91.
Mölg, N. and Bolch, T. (2017). Structure-from-Motion using historical aerial images to analyse changes in glacier surface elevation. Remote Sensing, 9(10):1021, doi:10.3390/rs9101021.
 
92.
Myklebust, I. and Groesz, F. (2019). Using point clouds from historical imagery for estimating site index in forestry. In 1st EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, IGN, Paris, France, 3–4 June 2019.
 
93.
Nebiker, S., Lack, N., and Deuber, M. (2014). Building change detection from historical aerial photographs using dense image matching and object-based image analysis. Remote Sensing, 6(9):8310–8336, doi:10.3390/rs6098310.
 
94.
Nielsen, M. and Dindorp, A. (2022). 75 years of historical aerial images from Denmark and Greenland – The process from dusty shelves to website. In 2nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, Rome, Italy, 5–6 December 2022.
 
95.
Norin, M. and Klitkou, G. (2022). Actualizing history. In 2nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, Rome, Italy, 5–6 December 2022.
 
96.
Olędzki, J. (2009). Początki teledetekcji środowiska w Polsce (The beginnings of remote sensing of the environment in Poland). Teledetekcja środowiska, 41:5–22.
 
97.
Osińska-Skotak, K., Bakuła, K., Jełowicki, Ł., and Podkowa, A. (2019). Using canopy height model obtained with dense image matching of archival photogrammetric datasets in area analysis of secondary succession. Remote Sensing, 11(18):2182, doi:10.3390/rs11182182.
 
98.
Osińska-Skotak, K. and Rączkowski, W. (2023). Zobrazowania satelitarne (Satellite imagery). In Metody teledetekcyjne dla archeologów, pages 68–114. Narodowy Instytut Dziedzictwa.
 
99.
Ozdemir, E. and Remondino, F. (2019). Machine learning methods applied to WWII aerial images. In 1nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, IGN, Paris, France, 3–4 June 2019.
 
100.
Pasik, M., Bakuła, K., Różycki, S., Ostrowski, W., Kowalska, M. E., Fijałkowska, A., Rajner, M., Łapiński, S., Sobota, I., Kejna, M., and Osińska-Skotak, K. (2021). Glacier geometry changes in the western shore of Admiralty Bay, King George Island over the last decades. Sensors, 21(4):1532, doi:10.3390/s21041532.
 
101.
Peppa, M., Mills, J., Fieber, K., Haynes, I., Turner, S., Turner, A., Douglas, M., and Bryan, P. (2018). Archaeological feature detection from archive aerial photography with a SfM-MVS and image enhancement pipeline. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 42:869–875, doi:10.5194/isprs-archives-XLII-2-869-2018.
 
102.
Persia, M., Barca, E., Greco, R., Marzulli, M. I., and Tartarino, P. (2020). Archival aerial images georeferencing: A geostatistically-based approach for improving orthophoto accuracy with minimal number of ground control points. Remote Sensing, 12(14):2232, doi:10.3390/rs12142232.
 
103.
Piermattei, L. (2022). Review on the processing and application of historical aerial images in the geosciences. In 2nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, Rome, Italy, 5–6 December 2022.
 
104.
Pinto, A. T., Gonçalves, J. A., Beja, P., and Pradinho Honrado, J. (2019). From archived historical aerial imagery to informative orthophotos: A framework for retrieving the past in long-term socioecological research. Remote Sensing, 11(11):1388, doi:10.3390/rs11111388.
 
105.
Poli, D., Casarotto, C., Strudl, M., Bollmann, E., Moe, K., and Legat, K. (2020). Use of historical aerial images for 3D modelling of glaciers in the Province of Trento. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B2-2020:1151–1158, doi:10.5194/isprs-archives-xliii-b2-2020-1151-2020.
 
106.
Poli, D., Strudl, M., Moe, K., Baumann, F., Bollmann, E., and Casarotto, C. (2019). 3D glacier monitoring with historical aerial images – From 1953 to today. In 1nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, IGN, Paris, France, 3–4 June 2019.
 
107.
Poterek, Q., Herrault, P.-A., Skupinski, G., and Sheeren, D. (2020). Deep learning for automatic colorization of legacy grayscale aerial photographs. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13:2899–2915, doi:10.1109/JSTARS.2020.2992082.
 
108.
Price, B., Waser, L. T., Wang, Z., Marty, M., Ginzler, C., and Zellweger, F. (2020). Predicting biomass dynamics at the national extent from digital aerial photogrammetry. International Journal of Applied Earth Observation and Geoinformation, 90:102116, doi:10.1016/j.jag.2020.102116.
 
109.
Pulighe, G. and Fava, F. (2013). DEM extraction from archive aerial photos: accuracy assessment in areas of complex topography. European Journal of Remote Sensing, 46(1):363–378, doi:10.5721/EuJRS20134621.
 
110.
Pulkkinen, M., Ginzler, C., Traub, B., and Lanz, A. (2018). Stereo-imagery-based post-stratification by regression-tree modelling in Swiss National Forest Inventory. Remote sensing of environment, 213:182–194, doi:10.1016/j.rse.2018.04.052.
 
111.
Ratajczak, R., Crispim-Junior, C. F., Faure, É., Fervers, B., and Tougne, L. (2019a). Automatic land cover reconstruction from historical aerial images: An evaluation of features extraction and classification algorithms. IEEE Transactions on Image Processing, 28(7):3357–3371, doi:10.1109/TIP.2019.2896492.
 
112.
Ratajczak, R., Crispim-Junior, C. F., Faure, E., Fervers, B., and Tougne, L. (2019b). Toward an unsupervised colorization framework for historical land use classification. In IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, pages 2678–2681. IEEE, doi:10.1109/IGARSS.2019.8898438.
 
113.
Rault, C., Dewez, T., and Aunay, B. (2020). Structure-from-motion processing of aerial archive photographs: Sensitivity analyses pave the way for quantifying geomorphological changes since 1978 in La Reunion Island. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2:773–780, doi:10.5194/isprs-annals-V-2-2020-773-2020.
 
114.
Rault, C., Dewez, T. J., Belon, R., Ayichemi, A., and Aunay, B. (2019). Serial processing of historical aerial photographs: A story telling the geomorphic impact of cyclones on Reunion Island (Indian Ocean). In 1nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, IGN, Paris, France, 3–4 June 2019.
 
115.
Rault, C., Thiery, Y., Chaput, M., Reninger, P.-A., Dewez, T., Michon, L., Samyn, K., and Aunay, B. (2022). Landslide processes involved in volcano dismantling from past to present: The remarkable open-air laboratory of the Cirque de Salazie (Reunion Island). Journal of Geophysical Research: Earth Surface, 127(5):e2021JF006257, doi:10.1029/2021JF006257.
 
116.
Redecker, A. P. (2008). Historical aerial photographs and digital photogrammetry for impact analyses on derelict land sites in human settlement areas. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci, 37:5–10.
 
117.
Redweik, P., Garzón, V., and Pereira, T. s. (2016). Recovery of stereo aerial coverage from 1934 and 1938 into the digital era. The Photogrammetric Record, 31(153):9–28, doi:10.1111/phor.12137.
 
118.
Redweik, P., Roque, D., Marques, A., Matildes, R., and Marques, F. (2009). Recovering Portugal aerial images repository. International Archives of Photogrammetry and Remote Sensing, 38:1–4.
 
119.
Różycki, S., Karwel, A. K., and Kurczyński, Z. (2023). German extermination camps on WWII reconnaissance photographs. orthorectification process for archival aerial images of cultural heritage sites. Remote Sensing, 15(10):2587, doi:10.3390/rs15102587.
 
120.
Salach, A. (2017). SAPC – Application for adapting scanned analogue photographs to use them in Structure from Motion technology. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-1/W1:197–204, doi:10.5194/isprs-archives-xlii-1-w1-197-2017.
 
121.
Santangelo, M., Zhang, L., Rupnik, E., Deseilligny, M. P., and Cardinali, M. (2022). Landslide evolution pattern revealed by multi-temporal DSMS obtained from historical aerial images. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B2-2022:1085–1092, doi:10.5194/isprs-archives-xliii-b2-2022-1085-2022.
 
122.
Schulz, J., Cramer, M., and Herbst, T. (2021). Evaluation of phase one scan station for analogue aerial image digitisation. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 89(5):461–473, doi:10.1007/s41064-021-00174-9.
 
123.
Schulz, J. and Herbst, T. (2022). Digitisation of historic aerial images in Baden-Württemberg investigating geometric resolution and accuracy of current digitsation systems. In 2nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, Rome, Italy, 5–6 December 2022.
 
124.
Seccaroni, S., Santangelo, M., Marchesini, I., Mondini, A. C., and Cardinali, M. (2018). High resolution historical topography: Getting more from archival aerial photographs. In Proceedings, volume 2, page 347. MDPI, doi:10.3390/ecrs-2-05160.
 
125.
Seo, D. K., Kim, Y. H., Eo, Y. D., and Park, W. Y. (2018). Learning-based colorization of grayscale aerial images using random forest regression. Applied Sciences, 8(8):1269, doi:10.3390/app8081269.
 
126.
Sevara, C. (2016). Capturing the past for the future: An evaluation of the effect of geometric scan deformities on the performance of aerial archival media in image-based modelling environments. Archaeological Prospection, 23(4):325–334, doi:10.1002/arp.1539.
 
127.
Sevara, C., Verhoeven, G., Doneus, M., and Draganits, E. (2018). Surfaces from the visual past: Recovering high-resolution terrain data from historic aerial imagery for multitemporal landscape analysis. Journal of archaeological method and theory, 25:611–642, doi:10.1007/s10816-017-9348-9.
 
128.
Shepherd, E., Ceraudo, S., Salerno, G., and Remondino, F. (2019). Analog/digital image processing of historical aerial imagery in the Italian National Photographic Aerial Archive (AFN-ICCD). In 1nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, IGN, Paris, France, 3–4 June 2019.
 
129.
Spalluto, L., Fiore, A., Miccoli, M. N., and Parise, M. (2021). Activity maps of multi-source mudslides from the Daunia Apennines (Apulia, southern Italy). Natural Hazards, 106(1):277–301, doi:10.1007/s11069-020-04461-3.
 
130.
Stark, M., Rom, J., Haas, F., Piermattei, L., Fleischer, F., Altmann, M., and Becht, M. (2022). Long-term assessment of terrain changes and calculation of erosion rates in an alpine catchment based on SfM-MVS processing of historical aerial images. How camera information and processing strategy affect quantitative analysis. Journal of Geomorphology, 1(1):43–77, doi:10.1127/jgeomorphology/2022/0755.
 
131.
Su, J.-W., Chu, H.-K., and Huang, J.-B. (2020). Instanceaware image colorization. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 7968–7977.
 
132.
Tanaka, S., Miyamoto, H., Ishii, R., and Carbonneau, P. (2022). Comparison of deep learning methods for colorizing historical aerial imagery. In EGU General Assembly Conference Abstracts, pages EGU22–7686. doi:10.5194/egusphere-egu22-7686.
 
133.
Thomas, R. (2022). Rapid photogrammetric scanning and processing of aerial film archives. In 2nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, Rome, Italy, 5–6 December 2022.
 
134.
Truquin, P. (2019). The digitization of IGN’s photo/cartographic archives and the web service "Remonterle temps". In 1nd EuroSDR Workshop on "Geoprocessing and Archiving of Historical Aerial Images”, IGN, Paris, France, 3–4 June 2019.
 
135.
Waser, L. T., Fischer, C., Wang, Z., and Ginzler, C. (2015). Wall-to-wall forest mapping based on digital surface models from image-based point clouds and a NFI forest definition. Forests, 6(12):4510–4528, doi:10.3390/f6124386.
 
136.
Wężyk, P. and Matyja, W. (2007). Określenie dynamiki zmian w Puszczy Niepołomickiej na podstawie ortofotomapy wygenerowanej z archiwalnych zdjęć lotniczych z 1949 roku (Determining the dynamics of changes in the Niepołomice Forest based on an orthophotomap generated from archival aerial photos from 1949). Archiwum Fotogrametrii, Kartografii i Teledetekcji, 17:801–809.
 
137.
Wójcik, S. (1991). Osiągniecia fotogrametrii wojskowej w okresie 1920–1990 (Achievements of military photogrammetry in the period 1920–1990). Archiwum Fotogrametrii, Kartografii i Teledetekcji, 60-lecie Polskiego Towarzystwa Fotogrametrycznego, 1:51–62.
 
138.
Zhang, L., Rupnik, E., and Pierrot-Deseilligny, M. (2020). Guided feature matching for multi-epoch historical image blocks pose estimation. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V-2–2020:127–134, doi:10.5194/isprs-annals-v-2-2020-127-2020.
 
139.
Zhang, L., Rupnik, E., and Pierrot-Deseilligny, M. (2021). Feature matching for multi-epoch historical aerial images. ISPRS Journal of Photogrammetry and Remote Sensing, 182:176–189, doi:10.1016/j.isprsjprs.2021.10.008.
 
140.
Zhang, R., Isola, P., and Efros, A. A. (2016). Colorful image colorization. In Computer Vision – ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, volume Part III 14, pages 649–666.
 
eISSN:2391-8152
ISSN:2391-8365
Journals System - logo
Scroll to top