Remote sensing vs. field-based monitoring of agricultural terrace degradation

Pijl, Anton; Quarella, Edoardo; Vogel, Teun A.; D’Agostino, Vincenzo; Tarolli, Paolo

doi:10.1016/j.iswcr.2020.09.001

Cited by 26 publications

(18 citation statements)

References 57 publications

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“…In the present study, the UAV flight plan was set to an altitude and a flight speed equal respectively to 20 m and 3 m s −1 , this way it was possible to obtain an average overlap between two consecutive multispectral photos of 75% both vertically (along the flight direction) and horizontally (orthogonal to the flight direction) as well as minimize the influence of wind turbulence generated by UAV rotors on the examined Arundo donax stands. All the multispectral images acquired here were then processed via a structurefrom-motion algorithm to rectify, stitch, and assemble the orthomosaic of the vegetated drainage channel [31,32].…”

Section: Uav-acquired Multispectral Imagesmentioning

confidence: 99%

Bulk Drag Predictions of Riparian Arundo donax Stands through UAV-Acquired Multispectral Images

Lama

Crimaldi

Pasquino

et al. 2021

Water

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Estimating the main hydrodynamic features of real vegetated water bodies is crucial to assure a balance between their hydraulic conveyance and environmental quality. Riparian vegetation stands have a high impact on vegetated channels. The present work has the aim to integrate riparian vegetation’s reflectance indices and hydrodynamics of real vegetated water flows to assess the impact of riparian vegetation morphometry on bulk drag coefficients distribution along an abandoned vegetated drainage channel fully covered by 9–10 m high Arundo donax (commonly known as giant reed) stands, starting from flow average velocities measurements at 30 cross-sections identified along the channel. A map of riparian vegetation cover was obtained through digital processing of Unnamed Aerial Vehicle (UAV)-acquired multispectral images, which represent a fast way to observe riparian plants’ traits in hardly accessible areas such as vegetated water bodies in natural conditions. In this study, the portion of riparian plants effectively interacting with flow was expressed in terms of ground-based Leaf Area Index measurements (LAI), which easily related to UAV-based Normalized Difference Vegetation Index (NDVI). The comparative analysis between Arundo donax stands NDVI and LAI map enabled the analysis of the impact of UAV-acquired multispectral imagery on bulk drag predictions along the vegetated drainage channel.

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Section: Uav-acquired Multispectral Imagesmentioning

confidence: 99%

Bulk Drag Predictions of Riparian Arundo donax Stands through UAV-Acquired Multispectral Images

Lama

Crimaldi

Pasquino

et al. 2021

Water

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“…The optimal scene size is limited to a few square kilometres (particularly with lightweight RPASs), which makes it a powerful tool for the mapping of damages in agriculture (Colomina & Molina, 2014). Numerous scientific studies of recent years have explored this potential, for example, for the monitoring of landslides (Casagli et al, 2017; Giordan et al, 2018; Scaioni et al, 2014); terrace wall failure (Pijl, Tosoni, et al, 2019; Pijl, Quarella, et al, in press) and other terrace dynamics (Wei et al, 2017); and countless examples of agricultural sheet erosion (e.g., Eltner et al 2016b; Pineux et al, 2017; Prosdocimi et al, 2017). The success of RPASs is largely promoted by the modern SfM photogrammetry technique, allowing the reconstruction of three‐dimensional geometry from simple two‐dimensional photography (see Figure 3).…”

Section: Opportunities From Remote Sensingmentioning

confidence: 99%

“…Numerous examples have followed where agricultural terrace failures could be attributed to surface flow paths, thanks to accurate and precise LiDAR (Preti et al, 2018; Tarolli et al, 2014) or RPAS‐SfM data sets (Pijl, Tosoni, et al, 2019; Pijl, Quarella, et al, in press). In the context of terraced landscapes, Giordan et al (2017) provided a large‐scale topographic analysis of >1,600 shallow landslides and statistically attributed their susceptibility to three anthropogenic factors: the presence of terraces, their state of maintenance, and the presence of roads.…”

Section: Opportunities From Remote Sensingmentioning

confidence: 99%

Slope instabilities in steep cultivation systems: Process classification and opportunities from remote sensing

et al. 2020

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The cultivation of steep slopes is a widespread practice in hilly and mountainous areas around the world. Such environments often result in particular agricultural systems linked with unique local values of historical and cultural heritage, economy, and food security. However, steep‐slope agriculture is inherently exposed to slope instability processes, which are now widely aggravated due to natural (e.g., growing rainfall aggressiveness) and anthropogenic factors (e.g., unsuitable maintenance or agronomic practices). In the literature, among the many articles published on soil erosion, a specific focus on the analysis of slope instabilities in steep cultivation systems is lacking. The purpose of this article is, therefore, to create a specific overview of this problem, with some useful insights into the role of remote sensing. We introduce the problem first, highlighting the main issues related to slope instabilities in steep cultivated areas. Then we provided a classification of key published papers, based on the different types of mass movements studied and their location in the world. The spatial comparison of past research and estimated global hazard of the mass movement in agricultural areas highlighted a relevant bias: a strong scientific focus on southern European countries, yet large rural areas are at risk on all continents, many of these unexplored by science. The third section is related to the contribution of remote sensing technologies (e.g., LiDAR and RPAS photogrammetry) in mapping the investigated processes. This study could help to guide future research for better management of such socio‐economically relevant agricultural landscapes.

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“…Recent developments in scientific and technological research techniques have offered the possibility of increasing knowledge of the terracing-hydrogeological hazard nexus, including, for instance, advanced and detailed geomorphological analysis [8,9], and hydraulic, geotechnical, and hydrological modeling [4,[10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Terraced Landscapes and Hydrological-Geological Hazards: Innovative Approaches and Future Perspectives

Preti

Errico

Castelli

2021

Water

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Remote sensing vs. field-based monitoring of agricultural terrace degradation

Cited by 26 publications

References 57 publications

Bulk Drag Predictions of Riparian Arundo donax Stands through UAV-Acquired Multispectral Images

Bulk Drag Predictions of Riparian Arundo donax Stands through UAV-Acquired Multispectral Images

Slope instabilities in steep cultivation systems: Process classification and opportunities from remote sensing

Terraced Landscapes and Hydrological-Geological Hazards: Innovative Approaches and Future Perspectives

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