FSLAM: A QGIS plugin for fast regional susceptibility assessment of rainfall-induced landslides

QCircularStats: A QGIS-Plugin for Evaluation Bidimensional Data by Circular Statistics

“…(1): where parameters µ and k are analogous to the mean and variance values in the normal distribution. Indeed µ is the mean direction, indicating the point where the pdf reaches its maximum value, whilst k is the positive concentration parameter that quantifies the data dispersion, i.e., 1/k could be roughly understood as the circular equivalent of the variance parameter 1 , and depends on the uniformity of the distribution.…”

“…GIS are popular tools for the representation and analysis of two-dimensional spatial data. In this context, the literature offers a vast amount of works that take advantage of GIS features to perform remotely sensed data analysis, such as the evaluation of landslides [1]; the mapping, assessment, and quantification of the societal values of ecosystem services [2]; aquatic ecosystem models [3]; environmental indices computing using Landsat data [4]; hydraulic simulation tools [5]; soil and water assessment [6]; modelling of rockfall run-out [7]; evapo-transpiration predictions [8]; positional accuracy analysis of satellite imagery [9], among many others. In particular, the Quantum GIS (QGIS) is one of the most popular and widely used GIS due to its multi-purpose nature, its visualisation characteristics and its flexibility and versatility in managing, editing, and analysing data, as well as in the designing of maps and graphs.…”

Characteristics and mechanisms of large-scale old landslides and landslide dams in the Loess Plateau—A case study from Daning County, Shanxi Province, China

“…Landslides have been one of the most frequent natural hazards worldwide since the prehistoric period [ [1] , [2] , [3] ]. Among landslide-prone areas worldwide, the Loess Plateau is famous for its complex landforms and frequent human engineering activities.…”

Quantifying forest land-use changes using remote-sensing and CA-ANN model of Madhupur Sal Forests, Bangladesh

“…Nowaday's various updated models are used in LULC prediction. For example; ANN model [ 22 ]; Markov model [ 23 ]; CA-Markov model [ 24 ]; CA-ANN model [ 25 , 26 ]; MLP-ANN model [ 27 ]; Multi-model ensemble [ [28] , [29] , [30] ], CA-ANN MOLUSCE model [ 31 ] and to simulate the spatiotemporal changes inside the research region, an integrated CA-artificial neural network (ANN) model using MOLUSCE was adopted for the current investigation. Additionally, we examined spatial driving factors for land surface dynamics in the district using the Geodetector tool.…”