scholarly journals LiDAR derived high resolution topography: the next challenge for the analysis of terraces stability and vineyard soil erosion

2013 ◽  
Vol 44 (2s) ◽  
Author(s):  
Federico Preti ◽  
Paolo Tarolli ◽  
Andrea Dani ◽  
Simone Calligaro ◽  
Massimo Prosdocimi

The soil erosion in the vineyards is a critical issue that could affect their productivity, but also, when the cultivation is organized in terraces, increase the risk due to derived slope failure processes. If terraces are not correctly designed or maintained, a progressively increasing of gully erosion affects the structure of the walls. The results of this process is the increasing of connectivity and runoff. In order to overcome such issues it is really important to recognize in detail all the surface drainage paths, thus providing a basis upon which develop a suitable drainage system or provide structural measures for the soil erosion risk mitigation. In the last few years, the airborne LiDAR technology led to a dramatic increase in terrain information. Airborne LiDAR and Terrestrial Laser Scanner derived high-resolution Digital Terrain Models (DTMs) have opened avenues for hydrologic and geomorphologic studies (Tarolli et al., 2009). In general, all the main surface process signatures are correctly recognized using a DTM with cell sizes of 1 m. However sub-meter grid sizes may be more suitable in those situations where the analysis of micro topography related to micro changes is critical for slope failures risk assessment or for the design of detailed drainage flow paths. The Terrestrial Laser Scanner (TLS) has been proven to be an useful tool for such detailed field survey. In this work, we test the effectiveness of high resolution topography derived by airborne LiDAR and TLS for the recognition of areas subject to soil erosion risk in a typical terraced vineyard landscape of “Chianti Classico” (Tuscany, Italy). The algorithm proposed by Tarolli et al. (2013), for the automatic recognition of anthropic feature induced flow direction changes, has been tested. The results underline the effectiveness of LiDAR and TLS data in the analysis of soil erosion signatures in vineyards, and indicate the high resolution topography as a useful tool to improve the land use management of such areas. The stability conditions have been analyzed under the influence of the measured geometry alterations of the wall structure.

2013 ◽  
Vol 32 ◽  
pp. 281-291 ◽  
Author(s):  
Volker Prasuhn ◽  
Hanspeter Liniger ◽  
Simon Gisler ◽  
Karl Herweg ◽  
Anton Candinas ◽  
...  

2011 ◽  
Vol 65 (1) ◽  
pp. 221-229 ◽  
Author(s):  
Xi Wang Zhang ◽  
Bing Fang Wu ◽  
Xiao Song Li ◽  
Shan Long Lu

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Jarbou A. Bahrawi ◽  
Mohamed Elhag ◽  
Amal Y. Aldhebiani ◽  
Hanaa K. Galal ◽  
Ahmad K. Hegazy ◽  
...  

Soil erosion is one of the major environmental problems in terms of soil degradation in Saudi Arabia. Soil erosion leads to significant on- and off-site impacts such as significant decrease in the productive capacity of the land and sedimentation. The key aspects influencing the quantity of soil erosion mainly rely on the vegetation cover, topography, soil type, and climate. This research studies the quantification of soil erosion under different levels of data availability in Wadi Yalamlam. Remote Sensing (RS) and Geographic Information Systems (GIS) techniques have been implemented for the assessment of the data, applying the Revised Universal Soil Loss Equation (RUSLE) for the calculation of the risk of erosion. Thirty-four soil samples were randomly selected for the calculation of the erodibility factor, based on calculating theK-factor values derived from soil property surfaces after interpolating soil sampling points. Soil erosion risk map was reclassified into five erosion risk classes and 19.3% of the Wadi Yalamlam is under very severe risk (37,740 ha). GIS and RS proved to be powerful instruments for mapping soil erosion risk, providing sufficient tools for the analytical part of this research. The mapping results certified the role of RUSLE as a decision support tool.


2014 ◽  
Vol 11 (2) ◽  
pp. 323-341 ◽  
Author(s):  
M. Fantappiè ◽  
S. Priori ◽  
E.A.C. Costantini

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