Optimal Tourism Development

The early days of tourism development had a naïve vision of tourism’s impacts on society in terms of economic, social, and environmental benefits. Time has passed, and we have learnt lessons regarding the success and failure of tourism development. Mass tourism development has pros and cons and is not necessarily the optimal development model. Alternative development strategies should be contemplated. This Special Issue deals with different topics concerning optimal tourism development. Destination management requires further understanding of different issues, such as carrying capacity, income-based optimal supply size, identification and development of optimal market niches, and adaptation or environmental protection strategies. Tourism planning is concerned with the role of economies of agglomeration, i.e., the advantages of spatial clusters vs scattered development. Additionally, support for and investment in innovation, accessibility, and mobility are relevant nowadays. From the stakeholders’ perspective, it is relevant to discuss ways of cooperating and sources of conflicts among different sectors and actors, governance and incentives for sustainable tourism practices, and equity and economic distribution of benefits. Finally, the development of methodological tools for the assessment of optimal tourism development is necessary for policy making, in particular the development of methods that are capable of integrating economic, environmental, and social criteria

Estadística espacial al servicio del turismo: una aplicación al caso de Extremadura

En los últimos años se observa un incremento de la importancia del espacio y de la interacción espacial entre las ciencias sociales. Pero si existe un sector económico en el que dicha corriente esté cobrando especial importancia es, sin lugar a duda, en el sector turístico. El turismo es un fenómeno geográfico y, por tanto, conocer cómo se distribuyen y relacionan sus variables en el espacio constituye una valiosa información para realizar una correcta gestión de la actividad turística. Es por ello, que el presente trabajo de investigación parte con el objetivo de indagar sobre el patrón existente en la distribución del turismo en una región de interior, el caso de Extremadura. Para ello, en primer lugar, se utilizan las medidas de asociación espacial para analizar el patrón existente entre dos de las variables más representativas de la actividad turística, el número de viajeros y el grado de ocupación. Posteriormente, se contrasta mediante el empleo de técnicas de estadística espacial diferentes a las medidas de asociación espacial, tradicionalmente utilizadas para este fin, la existencia de una distribución no aleatoria de la actividad turística. Para ello, se estima una función de intensidad turística mediante tres métodos alternativos: función K (r) de Ripley, función de densidad de Kernel y conteo por cuadrantes. Para finalizar, se propone el modelo que presente un buen grado de ajuste con el patrón espacial de alojamientos. Para este fin, la intensidad turística es modelada mediante un proceso no estacionario de Poisson que pretende contribuir a que las estructuras identificadas puedan ser caracterizadas, mapeadas y medidas, con el fin de poder convertirse en una valiosa herramienta para la gestión público-privada de la actividad turística en la región.In recent years there has been an increase in the importance of space and spatial interaction among the social sciences. But if there is an economic sector in which this trend is gaining special importance, it is undoubtedly in the tourism sector. Tourism is a geographical phenomenon and, therefore, knowing how its variables are distributed and related in space constitutes valuable information for the correct management of tourism activity. For this reason, the aim of this research work is to investigate the existing pattern in the distribution of tourism in an inland region, the case of Extremadura. To this end, first of all, spatial association measures are used to analyze the existing pattern between two of the most representative variables of tourism activity, the number of travelers and the degree of occupancy. Subsequently, the existence of a non-random distribution of tourism activity is contrasted by using spatial statistical techniques other than spatial association measures, traditionally used for this purpose. To this end, a tourism intensity function is estimated using three alternative methods: Ripley's K (r) function, Kernel density function and quadrat counting. Finally, the model that presents a good degree of fit with the spatial pattern of accommodations is proposed. For this purpose, the tourist intensity is modeled by means of a non-stationary Poisson process that aims to contribute to the characterization, mapping and measurement of the identified structures, in order to become a valuable tool for the public-private management of tourism activity in the region

Assessing Health Vulnerability to Air Pollution in Seoul Using an Agent-Based Simulation

This study aims to investigate the exposure to air pollution in Seoul and the consequent health effects in Seoul South Korea, and suggest possible solutions using agent-based modelling (ABM). ABM is a useful technique that can simulate pollution generation and exposure, mobility patterns of unique individuals, and explore future scenarios. The first study compared Universal Kriging and Generalised Additive Models to spatially interpolate pollution station data over Seoul. A new method was discovered to enhance the accuracy of NO2 on roads. Next, ABM was used to evaluate potential health loss for a set of demographic groups after being cumulatively exposed to particulates (PM10), with a nominal heath impact threshold of 100µg/m3. Finally, a traffic simulation examined the coupled problem of non-exhaust emissions and behaviour and estimate exposure to PM10 for groups of drivers and pedestrians in central Seoul. Having tested the sensitivity to calibrated parameters, scenarios of traffic restriction and modification of pedestrian behaviour to avoid polluted areas was investigated. With less difference between interpolation methods, the result showed a remarkable contrast between roadside and background NO2 as well as a daily cycle, while PM10 had a small variance between hours but had greater seasonal oscillation. The first ABM study showed that disparities in health may arise as a result of differences in socioeconomic status, especially when the group was exposed over a long period, and road proximity caused additional health loss. In the traffic simulation study, extreme PM10 was found along roadways, but although drivers were exposed to extreme values, longer exposure for pedestrians led to higher health risks. Despite the absence of reliable data linking exposure to actual health effects, it is possible to make progress with ABM. In addition, pollution exposure can vary by commuting patterns and the urban development of one’s location. Scenarios can be advantageous for healthcare policy – to aid the most vulnerable groups and districts

Modelling of commercial property market segmentation to improve price prediction accuracy in Malaysia

The commercial property market is strategic to the global economy. Significant attention is therefore given to its pricing by various stakeholders. The most common price modelling technique is the traditional hedonic price model. The commercial property market is too complex to be modelled by the traditional single equilibrium model. Property market segmentation models are used to improve the accuracy of price modelling, mostly reported in the housing market. This research, therefore, aims to propose a commercial property market segmentation model to improve price prediction accuracy in Malaysia. 14,043 commercial property transaction records obtained from Malaysia’s National Property Information Centre (NAPIC) was used. The submarkets were delineated using conventional hedonic, data-driven and spatial econometrics approaches. The evidence of submarket existence was determined using the Chow test and weighted RMSE, MAE and MAPE. The research found a significantly high level of spatial dependence in Malaysia’s commercial property market. Submarkets were efficiently delineated using all the methods except using submarket dummies. The research proposed the spatial error model using adaptive kernel maximum KNN spatial weight matrix as the optimal model for commercial property market segmentation in Malaysia. The proposed model improved the model fit by 19.76 per cent, reduced the RMSE, MAE and MAPE by 20.82 per cent, 24.63 per cent, and 25.92 per cent, respectively. The research shows that accounting for spatial dependence in the commercial property market reduces error, improves model fit and increases the accuracy of price modelling. The research has contributed to the existing body of knowledge by extending the commercial property market segmentation from a priori methods to the empirical data-driven and spatial econometrics approach in Malaysia. The implication to policymakers, financial institutions, the economy, property valuers, and property investors is that the findings will guide them in making informed decisions regarding the differentiated commercial property market

Air Pollution Control and Sustainable Development

This book brings together the latest research findings on the state of air pollution control and its impact on economic growth in different countries. The book has substantial content and rich discussion. It is suitable for students and researchers at different levels to learn the status of air pollution, governance policies and their effects, and the relationship between pollution control and economic growth in countries around the world

Uso y cobertura del suelo en las islas macaronésicas de Portugal y España: nuevos métodos para cuantificar y visualizar información de patrones espaciales

Tesis de la Universidad Complutense de Madrid, Facultad de Geografía e Historia, Departamento de Geografía Humana, leída el 23/11/2016The aim of this research is to propose novel methods for quantifying and visualizing geographical information, in order to aid the spatial planning decision-making process when addressing land use and land cover patterns. In doing so, several modeling and geographic visualization methods are developed and demonstrated by using the Macaronesian islands of Portugal and Spain as study areas. Macaronesia is a biogeographical region consisting of several archipelagos in the Atlantic Ocean belonging to three countries: Portugal, Spain, and Cape Verde. This research encompasses three archipelagos: the Azores, Madeira, and the Canary Islands. From these three archipelagos, the four most densely populated islands were further selected for the land use and land cover assessments: São Miguel, Madeira, Tenerife, and Gran Canaria. A common feature of the Macaronesian islands is that, ever since European colonization in the fifteenth century, up until the mid-twentieth century, anthropogenic land change was predominately attributable to agricultural activities consuming forests and natural areas. In the mid-twentieth century, owing to profound social and economic changes, the tertiary sector started its rise in becoming the main economic sector. Because the secondary sector in this region has always been minor, this substantial shift to the tertiary sector would dictate a progressive abandonment of the primary sector. Hence, agricultural areas started to recede. As a result, the last decades of the twentieth century were marked by a significant shift in land use dynamics. Agricultural activities ceased to be the main driving force of land change and were replaced by a rampant increase of the artificial surfaces, mainly on the southern coastal areas, where tourism-related and real estate pressure constitute a major impact on the landscape. A direct consequence of this pressure was the drastic transformation across the islands’ leeward coastal landscapes...El objetivo principal de esta investigación es proponer nuevos métodos para cuantificar y visualizar información geográfica, con el fin de facilitar el proceso de toma de decisiones en relación a los patrones de uso y ocupación del suelo. De este modo, se desarrollan y aplican varios métodos de modelación y visualización geográfica, utilizando las islas macaronésicas de Portugal y España como áreas de estudio. La Macaronesia es una región biogeográfica que integra varios archipiélagos en el Océano Atlántico pertenecientes a tres países: Portugal, España y Cabo Verde. Esta investigación abarca tres archipiélagos: Azores, Madeira y Canarias. Para una evaluación detallada de uso y cobertura del suelo se seleccionaron las cuatro islas más densamente pobladas: San Miguel, Madeira, Tenerife y Gran Canaria. Una característica común a las islas macaronésicas es que, desde de la colonización en el siglo XV hasta mediados del siglo XX, el cambio antropogénico del suelo se debió principalmente a las actividades agrícolas, que ocuparon bosques y áreas naturales. A mediados del siglo XX, debido a profundos cambios sociales y económicos, el sector terciario empezó su ascenso para convertirse en el principal sector económico. Debido a que el sector secundario en esta región siempre ha tenido una importancia menor, este proceso de terciarización de la economía supuso un progresivo abandono del sector primario. Por lo tanto, las áreas agrícolas comenzaron a experimentar un claro retroceso. Como resultado de este proceso, las últimas décadas del siglo XX se caracterizaron por un cambio significativo en las dinámicas de uso y cobertura del suelo. Las actividades agrícolas dejaron de ser la principal fuerza impulsora en el cambio de lo suelo y fueron reemplazadas por el aumento desenfrenado de las superficies artificiales, principalmente en las zonas costeras del sur, donde el turismo y la especulación inmobiliaria ejercen una gran presión sobre el paisaje. Consecuencia directa de esta presión fueron las drásticas transformaciones de los paisajes costeros de las islas...Esta investigação tem como principal objectivo propor novos métodos para quantificar e visualizar informação geográfica, de modo a auxiliar o processo de tomada de decisão quando seja necessário analisar padrões de uso e ocupação do solo. Ao longo da investigação são apresentados vários métodos de modelação e visualização geográfica, usando como área de estudo as ilhas da Macaronésia pertencentes a Portugal e Espanha. A Macaronésia é uma região biogeográfica no Oceano Atlântico constituída por vários arquipélagos pertencentes a três países: Portugal, Espanha e Cabo Verde. Este trabalho de investigação abrange três arquipélagos: os Açores, a Madeira e as Ilhas Canárias. Para uma avaliação mais detalhada quanto ao uso e ocupação do solo, foram seleccionadas as quatro ilhas mais densamente povoadas: São Miguel, Madeira, Gran Canaria e Tenerife. Uma característica comum às ilhas da Macaronésia reside na particularidade de, desde a sua colonização no século XV, até meados do século XX, as alterações antropogénicas do solo terem estado predominantemente associadas às actividades agrícolas que consumiram extensas áreas de floresta e espaços naturais. Em meados do século XX, devido a profundas alterações sociais e económicas, o sector terciário iniciou a sua ascensão para se tornar o principal sector económico. Uma vez que, nesta região, o sector secundário foi sempre pouco significativo, a terciarização da actividade económica ditou um progressivo abandono do sector primário. Deste modo, as áreas agrícolas começaram a recuar. Como resultado deste processo, as últimas décadas do século XX foram marcadas por uma mudança significativa na dinâmica de uso e ocupação do solo nas ilhas desta região. As actividades agrícolas deixaram de ser a principal força motriz para as alterações no uso do solo, sendo substituídas pelo aumento galopante das superfícies artificiais, principalmente nas áreas costeiras do sul, onde as actividades relacionadas com o turismo e a especulação imobiliária causaram um grande impacto na paisagem, e contribuiram para a transformação drástica do litoral sotavento das ilhas...Depto. de GeografíaFac. de Geografía e HistoriaTRUEunpu

Changes in capture fisheries and harvesting of wild marine invertebrates.

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