scholarly journals Effects of change of use of land on an aquifer in a tectonically active region

2013 ◽  
Vol 05 (02) ◽  
pp. 259-267
Author(s):  
Simón E. Carranco-Lozada ◽  
José A. Ramos-Leal ◽  
Cristina Noyola-Medrano ◽  
Janete Moran-Ramírez ◽  
Briseida López-Álvarez ◽  
...  
The Holocene ◽  
2010 ◽  
Vol 20 (3) ◽  
pp. 405-421 ◽  
Author(s):  
Bruce W. Hayward ◽  
Kate Wilson ◽  
Margaret S. Morley ◽  
Ursula Cochran ◽  
Hugh R. Grenfell ◽  
...  

2020 ◽  
Author(s):  
Silvia Pondrelli ◽  
Simone Salimbeni ◽  
Manuele Faccenda

<p>A general review on measurements of upper mantle seismic anisotropy in the Alpine and Apennines region is now encouraged by the large amount of data produced by several projects (i.e AlpArray, Cifalps1). Geodynamic studies need to have a sketch of mantle flows that drives the evolution of a<br>tectonically active region. This is particularly important for the Italian peninsula, where several slabs have been involved in the Alps and Apennines building and where they are still interacts with the Adriatic plate. Draw mantle flows starting from seismic anisotropy requires to locate the source of what SKS phases detect. The answer, often undetermined, it is frequently hypothesized cross-checking different seismological observation. Overlapping SKS data with tomographic models in this region gives little help, because of the large differences in the shape, depth and dimension of fast bodies identified by different tomographic studies. Mapping and comparing SKSs data with other types of anisotropy measurements (Pn anisotropy, azimuthal anisotropy from surface waves tomography, crustal anisotropy) allow to discretise where fast anisotropy direction is much more probably astenospheric or where it pervades also regions at shallower depths.</p>


Author(s):  
M. R. Mohd Salleh ◽  
N. I. Ishak ◽  
K. A. Razak ◽  
M. Z. Abd Rahman ◽  
M. A. Asmadi ◽  
...  

<p><strong>Abstract.</strong> Remote sensing has been widely used for landslide inventory mapping and monitoring. Landslide activity is one of the important parameters for landslide inventory and it can be strongly related to vegetation anomalies. Previous studies have shown that remotely sensed data can be used to obtain detailed vegetation characteristics at various scales and condition. However, only few studies of utilizing vegetation characteristics anomalies as a bio-indicator for landslide activity in tropical area. This study introduces a method that utilizes vegetation anomalies extracted using remote sensing data as a bio-indicator for landslide activity analysis and mapping. A high-density airborne LiDAR, aerial photo and satellite imagery were captured over the landslide prone area along Mesilau River in Kundasang, Sabah. Remote sensing data used in characterizing vegetation into several classes of height, density, types and structure in a tectonically active region along with vegetation indices. About 13 vegetation anomalies were derived from remotely sensed data. There were about 14 scenarios were modeled by focusing in 2 landslide depth, 3 main landslide types with 3 landslide activities by using statistical approach. All scenarios show that more than 65% of the landslides are captured within 70% of the probability model indicating high model efficiency. The predictive model rate curve also shows that more than 45% of the independent landslides can be predicted within 30% of the probability model. This study provides a better understanding of remote sensing data in extracting and characterizing vegetation anomalies induced by hillslope geomorphology processes in a tectonically active region in Malaysia.</p>


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