Abstract
The topographic survey of rural canal network is a crucial task to allow a sustainable irrigation management and planning in rural areas and, always more frequently, to control the interactions with urban areas (flood protection, in particular). However, to date, datasets of canal and ditch geomorphological characteristics, such as layout, cross-sections, slopes and canal bed characteristics, are almost completely absent, or unreliable. This work tests the use of four different data sources—two from remote sensing and two from ground survey—for detecting the geometrical characteristics of rural canals at increasingly high resolution, providing cross sections and slopes over a pilot study domain of about two hectares located in south Milan (Italy). Specifically, rural canal geometries were obtained from the processing of data from (i) a Lidar and a photogrammetric flight at different altitude (ii) a ground-fixed laser scanner and (iii) a GPS spot acquisition to complete surveys with a further level of detail. 3D models of the rural canals were obtained from the processing of the data of each of the three sources. Results of the comparison of the models are presented, focusing on canal cross sections, slope, and bed characteristics; moreover, the impact of these differences on the flow and storage capacity of the channels will be discussed and, finally, an assessment of the costs of data acquisition and processing is provided.
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The activity presented in the work is part of the research funded by Fondazione Sviluppo Ca’ Granda on the detection of rural canal characteristics.
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Masseroni, D., Passoni, D., Castagna, A., Civelli, L., Pinto, L., Gandolfi, C. (2020). Comparison of Different Methods for Topographic Survey of Rural Canals. In: Coppola, A., Di Renzo, G., Altieri, G., D'Antonio, P. (eds) Innovative Biosystems Engineering for Sustainable Agriculture, Forestry and Food Production. MID-TERM AIIA 2019. Lecture Notes in Civil Engineering, vol 67. Springer, Cham. https://doi.org/10.1007/978-3-030-39299-4_7
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DOI: https://doi.org/10.1007/978-3-030-39299-4_7
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