Among the most invasive species, the Coypu (Myocastor coypus) best exemplifies the widespread effect of alien species on ecosystems. Among the impacts, the induced erosion in riverbanks has an increasing economic and social importance. Despite its significance, this type of erosion is rarely quantified, and the available information is limited to local knowledge, grey literature, and maintenance reports. This research shows the potential of freely and instantly available Structure-from-Motion (SfM) photogrammetry to obtain crowdsourced information based on smartphone images. The results highlight how it is possible to provide a rough estimate of the damages with relatively low or null cost of application, and limited expert knowledge and expenditure of time, depending on the scale of analysis. The proposed technique provides a fresh approach to a known long-standing issue, offering a new source of information for farmers, researchers, wildlife managers, as well as for land managers and planners. The potential applications of such a technique and its unprecedented ease of use and very low cost offer effective tools for management plans and scientific research, providing a basis to relate eroded volumes to the functioning of the drainage system and the connected agroecosystem. The method would also enable the opportunity of participatory and opportunistic crowdsourced sensing. Further scientific research on the crowd-based data on erosion should encourage standardisation of data gathering and accessibility, together with a public involvement in information exchange, to generate a better understanding and awareness of erosion problems also for other fields of research.

Prospects for crowdsourced information on the geomorphic ‘engineering’ by the invasive Coypu (Myocastor coypus)

SOFIA, GIULIA;MASIN, ROBERTA;TAROLLI, PAOLO
2017

Abstract

Among the most invasive species, the Coypu (Myocastor coypus) best exemplifies the widespread effect of alien species on ecosystems. Among the impacts, the induced erosion in riverbanks has an increasing economic and social importance. Despite its significance, this type of erosion is rarely quantified, and the available information is limited to local knowledge, grey literature, and maintenance reports. This research shows the potential of freely and instantly available Structure-from-Motion (SfM) photogrammetry to obtain crowdsourced information based on smartphone images. The results highlight how it is possible to provide a rough estimate of the damages with relatively low or null cost of application, and limited expert knowledge and expenditure of time, depending on the scale of analysis. The proposed technique provides a fresh approach to a known long-standing issue, offering a new source of information for farmers, researchers, wildlife managers, as well as for land managers and planners. The potential applications of such a technique and its unprecedented ease of use and very low cost offer effective tools for management plans and scientific research, providing a basis to relate eroded volumes to the functioning of the drainage system and the connected agroecosystem. The method would also enable the opportunity of participatory and opportunistic crowdsourced sensing. Further scientific research on the crowd-based data on erosion should encourage standardisation of data gathering and accessibility, together with a public involvement in information exchange, to generate a better understanding and awareness of erosion problems also for other fields of research.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3235487
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