خرید و دانلود نسخه کامل کتاب Geography of Happiness A Spatial Analysis of Subjective Well-Being – Original PDF

On Happiness as a Consequence of Sustainable Development In detriment to economic growth, much of our landscape has changed dramatically over the last decades. With the unprecedented effects of urbanization and popu- lation increase, human beings have significantly jeopardized the natural environ- ment, heritage landscapes, and the stability of itself as a keystone species. The increasing competition and economic growth have led to a neglect of the natural environment, and since Brundtland raised the need for strategies for common goals of sustainable development. However, there is no consensus on what this sustainable development entails, particularly given the complexity of the very notion of what could be discarded and what should be kept for future generations (O’Neill & Kahn, 2000). Scholars agree, however, that sustainable development is crucial for the very survival of our species and that humankind must find a solution to readjust itself to its surrounding environment (Garibaldi & Turner, 2004). One of the culprits of envi- ronmental and landscape degradation has been the excessive growth human being has generated (Vaz, 2016). From an economic standpoint, more significant asymme- tries between social strata lead to loss of resources from a Schumpeterian perspective (Puscaciu et al., 2016). In other words, society has taught us that only a small nucleus of people remains and holds wealth, while the large majority of humankind lives in challenging misery. There is a clear pattern of poverty, crime, and wealth at the spatial level, clearly traceable to the root of hubs of economic growth, such as urban areas. Therefore, urbanization processes are a logical consequence of economic prosperity, and while cities grow, infrastructures spoil the already environmentally depleted land use, where natural resources become scarce. This sinks process has led to new tech- niques that enable better monitoring and understanding of the spatial dimension, Happiness Geography: Defining the Field 3 supporting the planning of urban and rural areas, and defining the socioeconomic strata from a geographic perspective, leading to more sustainable and sounder envi- ronments. Wellbeing is closely related to this very concept, as it assumes social and economic stability and integration of awareness and harmony with the natural envi- ronment. The Aristotelian notion of happiness furthermore expands on the idea that happiness is an absolute objective for humankind, only reflected in the existence of a common goal. From a sustainable development perspective, this common goal may become the attempt to transmit to future generations our social, economic, and natural environment, without any negative externalities that create dramatic changes, but offer a stable system of growth to the generations to come. 3 Spatial Information for Complex Decision-Making With the recent technological development witnessed in the last decades, computa- tional systems have increased dramatically their ability to cope with large amounts of data and offering more complex analysis of data sets. This has brought signif- icant advances in geocomputation, where the assembly, editing, and manipulation of data allow at present much more elaborate computational tasks than a decade ago. A large volume of geostatistical and spatial analysis methodologies has arisen from the possibility of understanding complex interactions, leading to advances in nonlinear modelling approaches that follow out of the traditional body of knowl- edge of statistical toolsets mainly available until the nineties. These new methods embed the possibility to observe behaviours and predict motion over space and time. It is only natural that the traditionally applied visions such as von Neuman and the scholarly work found in genetics have become interesting paths for the advances in spatial analysis and observation of empirical outcomes. One of these methods links to cellular automata, which have primarily been used to prospecting spatial phenomena such as land-use change. The very nature of land-use change modelling utilizing stochastic processes enabled in cellular automata shows that combined method- ologies of geographical analysis embed well into the stream of complex systems, converging to the advances in the field of geographic information scienc