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2024 | OriginalPaper | Buchkapitel

The Role of Semi-Automatic Classification Techniques for Mapping Landscape Components. The Case Study of Tratturo Magno in Molise Region

verfasst von : Andrea Rolando, Domenico D’Uva, Alessandro Scandiffio

Erschienen in: Beyond Digital Representation

Verlag: Springer Nature Switzerland

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Abstract

The aim of the research is to test different mapping techniques that use semi-automatic recognition methods of multispectral satellite imagery, to understand how they may support the work of analysis and interpretation of the landscape crossed by the Tratturo Magno between the inner areas of Molise and the Adriatic coast. Three different approaches have been tested with GIS and Google Earth Engine; the first one concerns the computing of Vegetation Indices; the second one is about the unsupervised classification method and the third one is about the supervised classification method. The methodology has been applied, on the one hand to one single satellite image through the Semi-automatic classification Plugin in GIS and on the other hand to a series of satellite imagery spanned over a period of time through Google Earth Engine. However, no one of the presented methods is fully matching the correct procedure to uniquely map the landscape features crossed by the tratturo.

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Vorheriges Kapitel Classification and Recognition Approaches for the BIM Modeling of Architectural Elements

Nächstes Kapitel The Importance of GAN Networks in Graphic and Creative Learning Processes Associated with Architecture

Tuteri, R.: Strade e storie amiternine: persistenza e discontinuità. In: Pani, L. E., (ed.), Abruzzo sul Tratturo Magno. Edizioni Exorma, Roma (2015)

UNESCO. Transumance, the seasonal droving of livestock along migratory routes in the Mediterranean and in the Alps, https://ich.unesco.org/en/RL/transhumance-the-seasonal-droving-of-livestock-along-migratory-routes-in-the-mediterranean-and-in-the-alps-01470. Last accessed 10 Feb 2023

Sereno, P.: L’archeologia del paesaggio agrario: una nuova frontiera di ricerca. In Gambi, L. (a cura di) Campagna e industria. I segni del lavoro. pp.24–47. Touring Club Italiano, Milano (1981)

Imperiale, P.: Prima Guida al Tratturo Magno. Cerbone Editrice, Napoli (2008)

D’Uva, D., Rolando, A.: A method to select and optimize slow tourism routes using a quality index procedure based on image segmentation and DTM modelling based on NURBS: the case study of multimodal access to inner places from the nodes of the adriatic coastline’s infrastructure bundle. Sustainability 15, 373 (2023). https://doi.org/10.3390/su15010373CrossRef

European Commission Copernicus. Europe’s Eyes on Earth. https://www.copernicus.eu/sites/default/files/documents/Brochure/Copernicus_Brochure_EN_WEB.pdf. Last accessed 10 Feb 2023

Sentinel-2-Missions, https://sentinels.copernicus.eu/web/sentinel/missions/sentinel-2. Last accessed 10 Feb 2023

Meini, M., Adducchio, D., Ciliberti, D., Di Felice, G.: Landscape conservation and valorization by satellite imagery and historic maps. Case Italian Transhumance Routes Euro. J. Remote Sens. 47(1), 375–387 (2014). https://doi.org/10.5721/EuJRS20144722CrossRef

Minotti, M., Giancola, C., Di Marzio, P., Di Martino, P.: Land use dynamics of drove roads: the case of Tratturo Castel di Sangro-Lucera (Molise, Italy). Land 7(1), 3 (2018). https://doi.org/10.3390/land7010003CrossRef

10.

Mastronardi, L., Giannelli, A., Romagnoli, L.: Detecting the land use of ancient transhumance routes (Tratturi) and their potential for Italian inner areas’ growth. Land Use Policy 109, 105695 (2021). https://doi.org/10.1016/j.landusepol.2021.105695CrossRef

11.

Tucker, C.J.: Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens. Environ. 8, 127–150 (1979). https://doi.org/10.1016/0034-4257(79)90013-0CrossRef

12.

Glenn, E.P., Huete, A.R., Nagler, P.L., Nelson, S.G.: Relationship between remotely-sensed vegetation indices, canopy attributes and plant physiological processes: what vegetation indices can and cannot tell us about the landscape. Sensors 8, 2136–2160 (2008)CrossRef

13.

Richards, J.A.: Remote Sensing Digital Image Analysis, 5th edn. Springer, Berlin (2013)CrossRef

14.

Congedo, L.: Semi-automatic classification plugin: a python tool for the download and processing of remote sensing images in QGIS. J. Open Source Softw., 6(64), 3172. (2021). https://doi.org/10.21105/joss.03172

15.

Shafizadeh, H., Khazaei, M., Kazem, S., Alavipanah, S.K., Weng, Q.: Google Earth engine for large-scale land use and land cover mapping: an object-based classification approach using spectral, textural and topographical factors. GIScience Remote Sensing 58(6), 914–928 (2021). https://doi.org/10.1080/15481603.2021.1947623CrossRef

16.

Congedo, L.: Semi-Automatic Classification Plugin Documentation Release 7.9.7.1. (2022). https://readthedocs.org/projects/semiautomaticclassificationmanual-it/downloads/pdf/latest. Last accessed 10 Feb 2023

17.

Zhang, Y.J.: A survey on evaluation methods for image segmentation. Pattern Recogn. 29(8), 1335–1346 (1996). https://doi.org/10.1016/0031-3203(95)00169-7CrossRef

18.

Yang, L., Driscol, J., Sarigai, S., Wu, Q., Chen, H., Lippitt, C.D.: Google Earth engine and artificial intelligence (AI): a comprehensive review. Remote Sensing 14(14), 3253 (2022). https://doi.org/10.3390/rs14143253CrossRef

19.

Study At Home, Supervised classification using Google Earth Engine, 16 May 2021, YouTube video, https://youtu.be/VMab-HAXOpw. Last accessed 10 Feb 2023

Titel: The Role of Semi-Automatic Classification Techniques for Mapping Landscape Components. The Case Study of Tratturo Magno in Molise Region
verfasst von: Andrea Rolando
Domenico D’Uva
Alessandro Scandiffio
Verlag: Springer Nature Switzerland
Buch: Beyond Digital Representation
Print ISBN: 978-3-031-36154-8

Electronic ISBN: 978-3-031-36155-5

Copyright-Jahr: 2024
DOI: https://doi.org/10.1007/978-3-031-36155-5_35

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