Artificial neural networks applied for soil class prediction in mountainous landscape of the Serra do Mar¹

Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.

The Moroccan political partisan landscape : a polarized microcosm?

Using an original investigative protocol and a data base of 4,127 national delegates from ten Moroccan political organizations, surveyed between 2008 and 2012, this article examines the characteristics of party members in Morocco. Initial results indicate that the field of Moroccan political parties is a small world dominated by city dwellers, mature men, and the most highly educated, wealthiest individuals. However, far from being isolated from ordinary citizens, there are social dynamics at work. While it cannot be reduced to a segmented clientele, it is, nonetheless, shaped by an ideal-typical opposition between parties of notables and parties of activists.

Damage spreading transition in glasses: A probe for the ruggedness of the configurational landscape

We consider damage spreading transitions in the framework of mode-coupling theory. This theory describes relaxation processes in glasses in the mean-field approximation which are known to be characterized by the presence of an exponentially large number of metastable states. For systems evolving under identical but arbitrarily correlated noises, we demonstrate that there exists a critical temperature T0 which separates two different dynamical regimes depending on whether damage spreads or not in the asymptotic long-time limit. This transition exists for generic noise correlations such that the zero damage solution is stable at high temperatures, being minimal for maximal noise correlations. Although this dynamical transition depends on the type of noise correlations, we show that the asymptotic damage has the good properties of a dynamical order parameter, such as (i) independence of the initial damage; (ii) independence of the class of initial condition; and (iii) stability of the transition in the presence of asymmetric interactions which violate detailed balance. For maximally correlated noises we suggest that damage spreading occurs due to the presence of a divergent number of saddle points (as well as metastable states) in the thermodynamic limit consequence of the ruggedness of the free-energy landscape which characterizes the glassy state. These results are then compared to extensive numerical simulations of a mean-field glass model (the Bernasconi model) with Monte Carlo heat-bath dynamics. The freedom of choosing arbitrary noise correlations for Langevin dynamics makes damage spreading an interesting tool to probe the ruggedness of the configurational landscape.

Audit report on America’s Agricultural Industrial Heritage Landscape, Inc., d/b/a Silos and Smokestacks National Heritage Area, in Waterloo, Iowa for the years ended December 31, 2011 and 2010

Audit report on America’s Agricultural Industrial Heritage Landscape, Inc., d/b/a Silos and Smokestacks National Heritage Area, in Waterloo, Iowa for the years ended December 31, 2011 and 2010

Inferring landscape effects on dispersal from genetic distances: how far can we go?

Functional connectivity affects demography and gene dynamics in fragmented populations. Besides species-specific dispersal ability, the connectivity between local populations is affected by the landscape elements encountered during dispersal. Documenting these effects is thus a central issue for the conservation and management of fragmented populations. In this study, we compare the power and accuracy of three methods (partial correlations, regressions and Approximate Bayesian Computations) that use genetic distances to infer the effect of landscape upon dispersal. We use stochastic individual-based simulations of fragmented populations surrounded by landscape elements that differ in their permeability to dispersal. The power and accuracy of all three methods are good when there is a strong contrast between the permeability of different landscape elements. The power and accuracy can be further improved by restricting analyses to adjacent pairs of populations. Landscape elements that strongly impede dispersal are the easiest to identify. However, power and accuracy decrease drastically when landscape complexity increases and the contrast between the permeability of landscape elements decreases. We provide guidelines for future studies and underline the needs to evaluate or develop approaches that are more powerful.

Audit report on America’s Agricultural Industrial Heritage Landscape, Inc., d/b/a Silos and Smokestacks National Heritage Area and Silos and Smokestacks Natural Heritage Area Foundation in Waterloo, Iowa for the years ended December 31, 2012 and 2011

Audit report on America’s Agricultural Industrial Heritage Landscape, Inc., d/b/a Silos and Smokestacks National Heritage Area and Silos and Smokestacks Natural Heritage Area Foundation in Waterloo, Iowa for the years ended December 31, 2012 and 2011

Soils in a young landscape on the coast of southern Finland

Selostus: Nuoria maita Viikin pelloilla