Mapa de las Series de Vegetación de la Cuenca Alta del Río Bernesga (León)

In this paper, the vegetal landscape from higher part of Bernesga river (León province) by means of several climatophilous and edaphophilous vegetation series. A mapa of vegetasion series from higher part of Bernesga rrver is presenled.

La ruptura de una economía moral y las deslegitimación de las deudas hipotecarias

In Spain, during the recent housing bubble, purchasing a home seemed the most advantageous strategy to access housing, and there was a wide social consensus about the unavoidability of mortgage indebtedness. However, such consensus has been challenged by the financial and real-estate crisis. The victims of home repossessions have been affected by the transgression of several principles, such as the fair compensation for effort and sacrifice, the prioritisation of basic needs over financial commitments, the possibility of a second chance for over-indebted people, or the State's responsibility to guarantee its citizens' livelihood. Such principles may be understood as part of a moral economy, and their transgression has resulted in the emergence of a social movement, the Plataforma de Afectados por la Hipoteca (PAH), that is questioning the legitimacy of mortgage debts. The article reflects on the extent to which the perception of over-indebtedness and evictions as unfair situations can have an effect on the reproduction of the political-economic system, insofar the latter is perceived as able or unable to repair injustice.

Error sensitive historical GIS: Identifying areal interpolation errors in time series data

Historical GIS has the potential to re-invigorate our use of statistics from historical censuses and related sources. In particular, areal interpolation can be used to create long-run time-series of spatially detailed data that will enable us to enhance significantly our understanding of geographical change over periods of a century or more. The difficulty with areal interpolation, however, is that the data that it generates are estimates which will inevitably contain some error. This paper describes a technique that allows the automated identification of possible errors at the level of the individual data values.