Historical Rates Of Change Research Articles

Use of U.S. Census Bureau Data to Expose Students to Dynamic Population Growth

Global human population size and understanding how it has changed and will change in the future are important concepts for students. Here I describe exercises that use online databases provided by the U.S. Census Bureau to show students how both population size and the rate of change vary over time. In the first exercise, the U.S. population clock is used to calculate daily birth, death, and migrant and death rates, and how the world population clock is used to calculate the rate of change. These rates can be used to predict what the population size would be if the rates remained unchanged for a predetermined time interval. In the second exercise, historical data are used to determine the years with the most change in U.S. and world population size, then calculate how much larger the current population would be if those historical rates of change remained constant. These exercises have improved quantitative literacy while showing students current and historical trends in human population.

LAND-COVER MODELLING USING CORINE LAND COVER DATA AND MULTI-LAYER PERCEPTRON

Abstract Last decades of research have revealed the environmental impacts of Land-Use/Cover Change (LUCC) throughout the globe. Human activities’ impact is becoming more and more pronounced on the natural environment. The key activity in the LUCC projects has been to simulate the syntheses of knowledge of LUCC processes, and in particular to advance understanding of the causes of land-cover change. Still, there is a need of developing case studies regional models to understand LUCC change patterns. The aim of this work is to reveal and describe the main changes in LUCC patterns occurring in Poznań Lakeland Mesoregion according to CORINE Land Cover database. Change analysis was the basis for the identification of the main drivers in land cover changes in the study area. The dominant transitions that can be grouped and modelled separately were identified. Each submodel was combined with all submodels in the final change prediction process. Driver variables were used to model the historical change process. Transitions were modelled using multi-layer perceptron (MLP) method. Using the historical rates of change and the transition potential model scenario for year 2006 was predicted. Corine Land Cover 2006 database was used for model validation.

Dynamic simulation and visualisation of coastal erosion

A key requirement for effective coastal zone management is good knowledge and prediction of land erosion rates due to encroachment of the sea. However, in addition to demarcation of the hazard through modelling and mapping, a policy of risk mitigation necessitates significant attention should also be addressed to communicating the transient behaviour of the predictions and associated uncertainty. With climate change and sea level rise implying that historical rates of change may not be a reliable guide for the future, enhanced visualisation of the evolving coastline has the potential to improve awareness of this changing risk. This visual content is developed by linking scientific modelling with the transformation of digital elevation models, and then using GIS to integrate other spatiotemporal content. The resulting high-resolution visualisations may meet demands from decision-makers for tools to communicate scientific results more effectively, due to their realism and apparent authenticity. Nevertheless they can also produces a tension with the underlying scientific content because of the necessary extrapolation of extra detail, and the lack of established procedures to communicate the resulting uncertainty in the visualisation. Coastal managers also have concerns about releasing the visualisations to the general public. These issues are explored through analysis of future cliff erosion in Norfolk on the eastern coast of Great Britain.

Mobility of agricultural labour and fluctuating regional labour markets: A demographic and economic analysis with application to West-Germany

Summary The paper is an attempt to contribute to the actual question in how far the reduced economic growth and the lack of non-farm jobs affects the process of agricultural adjustment via a decline of the agricultural labour force. A demographic cohort model is specified to decompose the total rate of change of agricultural labour. It is applied to West-Germany at the national and state (‘Land’) level to quantify the historical rates of change resulting from aging, death, disability and early retirement, respectively. The remaining non-autonomous rate of change (occupational mobility) is then explained within an age-specific econometric model. Explanatory variables relate to the labour market situation, to income and to the national growth rate of GNP. The numerical results show clear interregional differences in the impact of regional labour markets, income differentials and age structures on level and structure of the total rate of change. In order to identify areas where rural labour market policies should have priority, a regional projection of autonomous natural rates of decline is presented at the ‘Kreis’ level. The results indicate that the projected autonomous rates vary from 1.2 to 3.6 per cent. The observed interregional differences of farm size structures and labour market situations do not in all cases compensate for these differences and, hence, call for counteracting regional and labour market policies in selected problem areas.