While displaying diversified economic values, agro-ecosystems remain a relevant component of rural landscapes in Southern Europe. Coupled with the expansion of ecologically fragile areas because of climate warming, intensification and simplification of rural landscapes—e.g., in lowland—represent frequent trajectories of rural land-use change (RLUC) in the Mediterranean region and demonstrated to harm ecosystem functionality and ecological quality, especially in a context of socioeconomic transformations of landscapes. Additionally, an incipient ‘extensivation’ of geographically remote and economically marginal agricultural systems was also observed, likely following depopulation and land abandonment. The present study elaborated in this direction, providing an integrated RLUC evaluation scheme based on a multivariate analysis of land-use indicators derived from official statistics. This approach was applied to a continuous, long-term RLUC monitoring of a rural landscape in an ecologically complex Mediterranean region (Latium, Central Italy) experiencing multiple trends (e.g., lowland urbanization, crop intensification in gently sloping areas, and land abandonment/depopulation in steep zones) with diversified environmental implications. Based on administrative inventories, such evaluation was carried out over fifty years (1970–2020) in the study area, considering trends over time in selected crop surfaces at the municipal scale as inputs of a multiway factor analysis (MFA). This analysis quantifies stability in the main rural land-use types and possible changes in the dominant farming systems. Simplified indicators of land configuration (namely a crop intensity index and a rural woodland index reflecting ‘intensification’ or ‘extensivation’ of local farming systems) made available at the same spatial and temporal scales completed the informative picture corroborating MFA results. Taken together, our findings delineate multiple changes in rural landscapes, discriminating land-use trajectories in coastal and inland districts. These development trajectories were basically dependent on processes of (i) land abandonment in relict and remote areas, (ii) crop intensification in dynamic rural districts, and (iii) fringe urbanization along the coastal strip.

Geographic data quality is a complex issue requiring continuous operational improvements. Considering this to be one of the most topical research and technical issues in official statistics and environmental monitoring, this study re-connects the operational dimension of ‘geographic data quality’ with the broader issue of monitoring the quality of official statistics. By estimating the accuracy of public (spatially explicit) data, this study illustrates an operational framework with an exploratory exercise in estimating the geographic data quality characteristic of a specific information source within the official statistical system (i.e., building registry) in a given European country, namely, Italy. The results of this exercise provide a paradigmatic example of profound innovation in the activities of statistical services in Europe and specifically the Italian National Statistical Institute (Istat), transitioning from independent (and poorly connected) field surveys to an integrated system of registries. Since several studies are based on spatially explicit survey units, it is essential to estimate the quality of geographical data, especially those derived from information sources where space is topical information, such as (local, regional, or national) building registers. Thanks to the results of an empirical exercise applied to Italian building registers, the present article will discuss the issue of data accuracy, considered the main issue related to monitoring geographic data quality, from an official statistics’ perspective. Statistical indicators will be proposed for the assessment of systematic and random errors of spatially explicit measures, possibly enabling a quali-quantitative improvement in the semantic content of building registers that address the inherent requirements of official statistics. Such indicators have some positive implications for the entire system of official statistics in Italy and, for generalization, within the European Statistical System.

Climate warming, agricultural intensity, and urban growth are main forces triggering land degradation in advanced economies. Being active over different spatial and temporal scales, they usually reflect—at least indirectly—the impact of additional factors, such as wellbeing, demographic dynamics, and social development, on land quality. Using descriptive statistics and a multiple regression analysis, we analyzed the impact of these three processes comparatively over a decadal scale from 1960 to 2020 at the provincial level (Nuts-3 sensu Eurostat) in Italy. We enriched the investigation with a short-term forecast for 2030, based on four simplified assumptions grounded on a purely deterministic approach. Land degradation was estimated adopting the Environmental Sensitive Area Index (ESAI) measured at the spatio-temporal scale mentioned above. Computing on multiple observations at nearly 300,000 locations all over Italy, provinces were regarded as representative spatial units of the territorial pattern of land degradation. Between 1960 and 1990, the three predictors (climate, agriculture, and urbanization) explained a relatively high proportion of variance, suggesting a modest role for any other (unobserved) factor. All of these factors were found to be highly significant predictors of land degradation intensity across provinces, the most impactful being farming intensity. The highest adjusted-R² coefficient was observed in both 1990 and 2000, and suggests that the three predictors still reflect the most powerful drivers of land degradation in Italy at those times, with a marginal role for additional (unobserved) factors. The impact of farming intensity remained high, with the role of urbanization increasing moderately, and the role of climate aridity declining weakly between 2000 and 2010. In more recent times (2010 and 2020), and in future (2030) scenarios, the adjusted R² diminished moderately, suggesting a non-negligible importance of external (unobserved) factors and the rising role of spatial heterogeneity. The climate factor became progressively insignificant over time, while increasing the role of urbanization systematically. The impact of farming intensity remained high and significant. These results underlie a latent shift in the spatial distribution of the level of land vulnerability in Italy toward a spatially polarized model, influenced primarily by human pressure and socioeconomic drivers and less intensively shaped by biophysical factors. Climate aridity was revealed to be more effective in the explanation of land degradation patterns in the 1960s rather than in recent observation times.