Abstract

Urban geomorphology focuses on the changes to the natural landscape caused by human activities in cities. Cities have different geological-geomorphological substrates, and several human activities have been operating within them in different times. Humans as “geomorphic agents” have been generating anthropogenic erosion and accumulation, moving a “tremendous amounts of soil and rock” since the Paleolithic [1]. Study of urban geomorphology helps understanding the natural, historical and anthropogenic landscape evolution, the changes imposed by settlements in relation with natural morphologies, and the effects of the development of cities on natural geomorphological processes. Quantitative geomorphodiversity [2,3] describes the variety of landforms and morphological processes characterizing the landscape, representing a valuable tool for landscape classification in urban areas [4,5]. Geomorphodiversity maps can be prepared using heterogeneous spatial data, at different geographical scales. The land surface diversity index (GmI) of Italy [6] is a quantitative geomorphodiversity index, considering multiple input quantities to describe geological constraints and geomorphological processes. It uses moving windows for focal statistics operations, to calculate local diversity of slope, lithology, drainage density and terrain forms, and eventually combines these ingredients in an individual, classified raster map. The GmI approximates field-based geomorphological maps, containing accurate representations of landforms in the real world. One relevant example of the latter, in Italy, is the geomorphological survey recently carried out in Rome, with a method that integrated field surveys, historical maps, aerial photographs, archaeological and geomorphological literature [5]. In this work, we compare the land surface diversity index, obtained with a simple and objective approach [6], with real-world geomorphological maps of 3 locations describing the rural-urban gradient of Rome urban area to understand the representativeness of the GmI, in general, and its advantages and limitations, in urban areas. The methodological approach is a simple overlay of the GmI and geomorphological dataset, in a first approximation. For the comparison, we implemented different spatial analysis techniques to build suitable density functions from both datasets, to pin down to a common ground the five diversity classes, in the GmI, and the number of landforms mapped in the field, in the geomorphological map. Most notably, the latter distinguishes natural and anthropogenic landforms along the rural-urban gradient in Rome, allowing an assessment of GmI from these substantially different points of view. The results of this work are relevant to understand the applicability of geomorphodiversity indices for landscape classification in a data-rich area. It has the potential of paving the way for larger scale analyses of the natural and human-made landforms in rural and urban areas in Italy [7], to gain insight on how to plan and maintain a resilient urban environment.   [1]Bathrellos G.D., Bulletin Geol Soc Greece (2007). https://www.pmf.unizg.hr/_download/repository/clanak_1%5B1%5D.pdf [2] Benito-Calvo et al, Earth Surf Proc Land (2009). https://doi.org/10.1002/esp.1840 [3] Melelli et al., Sci Tot Env (2017). https://doi.org/10.1016/j.scitotenv.2017.01.101 [4] Vergari et al., Rendiconti Online Soc Geol Ital (2022). https://doi.org/10.3301/ROL.2022.09 [5] Del Monte et al., Journal of Maps (2016). https://doi.org/10.1080/17445647.2016.1187977 [6] Burnelli et al., Earth Surf Proc Land (2023). https://doi.org/10.1002/esp.5679 [7] Alvioli, Landscape and Urban Planning (2020). https://doi.org/10.1016/j.landurbplan.2020.1039

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