Land Journal

This paper presents the spatial distribution of multiple deprivation in Athens, and links these spatial patterns to the city’s urban development trajectory and the way housing is accessed. Multiple deprivation was measured as the combined concentration of disadvantageous employment situation, access to education and housing conditions. A principal components analysis was utilized for 20 variables from the three said domains. Two components were identified as statistically significant.

As house mortgage appraisal values have played a leading role in the 2007–2012 financial crisis, it is important to develop robust mass appraisal models that correctly estimate these values. The present paper intends to propose a methodology to examine the spatial distribution of house mortgage appraisal values. To do so, we analyzed the effect that these values, cadastral urban land values, characteristics of houses, and socioeconomic conditions and services in neighborhoods, have on house mortgage appraisal values in the 70 boroughs of Valencia (Spain).

Czech agriculture is dealing with the consequences of climate change. Agroforestry cultures are being discursively reintroduced for better adaptability and resilience, with the first practical explorations seen in the field. Scholars have been working with farmers and regional stakeholders to establish a baseline for making agroforestry policy viable and sustainable.

Recurrent Neural Networks (RNNs), including Long Short-Term Memory (LSTM) architectures, have obtained successful outcomes in timeseries analysis tasks. While RNNs demonstrated favourable performance for Land Cover (LC) change analyses, few studies have explored or quantified the geospatial data characteristics required to utilize this method. Likewise, many studies utilize overall measures of accuracy rather than metrics accounting for the slow or sparse changes of LC that are typically observed.