Analysis of Tourism Directory Using Google Maps API and Multimedia (Case Study : Yogyakarta, Indonesia)

Indonesian citizens, especially the youth has a very strategic role in any case, including the development of tourism. Their involvement is essential to achieve sustainable tourism development. This becomes more relevant when it is associated with a variety of efforts to accelerate tourism activities in order to support the development process in various regions in Indonesia. Targets to be achieved is to help the tourism sector to attract more travelers to the use of one technology, which is a potential tourism business directory. Tourism directory if implemented would simplify and optimize the tourism destinations by providing information that is more complete and richer as well as relevant to potential tourists. Tourism directory will be equipped with the power of geocoding, so every tourist destination location can be easily reviewed on the map. The map will be constructed by using the function of the web-based Google Maps API. The method used to achieve the purpose of the first phase are: observation; interviews; modeling and classifying tourism directory. The second stage is the design specifications, descriptions, and some prototype tourism directory. The third stage is the installation and testing of a prototype directory of tourism; socialization; and application of tourism directory on the web server

The identification of spatial patterns in city limits through Self-Organized maps of the centrality of the road network

The characterization of city limits is of especial interest since it may provide hints to understanding the urban growth taking place in peripheries, and it also makes it possible to identify the keys to the continuous and discontinuous relationships between cities and their surroundings. Within this context, many different approaches could be adopted to undertake this kind of analysis. This paper specifically explores the possibilities offered by the use of self-organized maps created from the results of the application of different centrality measures in the mixed road network, which is comprised of systems of streets, metropolitan roads and rural roads. The implementation of centrality measures to a mixed road network is already an innovative exercise, considering that centrality analyses are normally carried out in more purely intra-urban contexts. The spatial representation of the profiles obtained with the self-organized maps shows different structural characteristics throughout city limits, which can be used to interpret the nature of the boundary itself. The proposed methodology was tested in the city of Granada (Spain), specifically on the limit in contact with the area surrounding the Vega de Granada, a singular agricultural landscape linked to the Genil River.La caracterización morfológica del borde urbano es un ejercicio que reviste un interés especial porque, por una parte, ayuda a entender los crecimientos urbanos que tienen lugar en las zonas periféricas y, por otra, permite descifrar las claves de las relaciones de continuidad o discontinuidad que existen entre la ciudad y su entorno. En este contexto, son muchos los enfoques desde el análisis. En este artículo, se exploran en concreto las posibilidades que ofrece la utilización de mapas auto-organizados, elaborados a partir de los resultados de la aplicación de medidas de centralidad de la red viaria mixta que forman los sistemas de calles, los viarios metropolitanos y los caminos agrarios. La aplicación de diferentes medidas de centralidad en una red viaria mixta, supone en sí un ejercicio innovador, ya que, normalmente, los análisis de centralidad se aplican en el ámbito más puramente intraurbanos. La base espacial de los perfiles obtenidos en las series se puede comparar con la naturaleza del propio borde. La Metodología propuesta se ha testeado en la ciudad de Granada (España), específicamente, sobre el borde de contacto de la ciudad con el entorno de la Vega de Granada, un paisaje agrario singular ligado al Río Genil

Evaluación comparativa del nivel de Desarrollo Orientado al Transporte (dot) en torno a nodos de transporte de grandes ciudades: métodos complementarios de ayuda a la decisión

El Desarrollo Orientado al Transporte (dot) es un enfoque de la planificación que promueve el desarrollo sostenible de un área urbana. Evaluar el nivel dot resulta interesante para determinar la idoneidad de los desarrollos urbanos al respecto, así como su potencial de mejora. El objeto del trabajo consiste en evaluar el nivel dot de importantes áreas urbanas mediante dos métodos diferentes: índice global y análisis multivariable mediante redes neuronales artificiales. Los métodos se contrastan entre sí, clarificando sus límites y grado de complementariedad. Adicionalmente, los resultados se verifican mediante el análisis espacial sig de un caso concreto. Según resultados: la evaluación mediante índice es limitada; el análisis multivariable determina perfiles de áreas semejantes, independientemente de sus índices globales; el análisis espacial pormenoriza los valores medios obtenidos. Estos métodos aportan conocimiento en sus respectivos campos. Si se usan complementariamente entre sí, mejoran su efectividad como herramientas de análisis útiles en planificación.Transit Oriented Development (tod) is a planning approach that promotes sustainable development of an urban area. Assessing the levels of tod may allow determining the appropriateness of urban development in this regard, as well as its potential for improvement. The purpose of this work is to assess the levels of tod using two different methods: Global Index and Multivariate Analysis based on Artificial Neural Networks. The methods contrast each other, clarifying both their limits and complementarity degree. Additionally, the results are verified through gis spatial analysis applied on a case study. According to the results, the Global Index Assessment is limited; the multivariable analysis shows profiles of similar urban areas, regardless of their global indexes; the spatial analysis details the average values obtained. These methods provide knowledge in their respective fields. If used in a complementary way, they improve their effectiveness as useful analysis tool for urban plannin

Self-Organizing Map Methodology and Google Maps Services for Geographical Epidemiology Mapping

The Health Geographical Information System (GIS) has been used in many organizations for the management and visualization of public health data. As epidemiology information has become a part of health data repository in the health data management system, many health researchers have dedicated their research areas to geographical epidemiology information analysis and visualization. The Population Health Epidemiology Unit of the Department of Health and Human Services (DHHS) in Tasmania uses the web-based epidemiology system (‘WebEpi’) to conduct monitoring and surveillance of the health of Tasmanian population. In this paper, the epidemiology data Self-Organizing Map (SOM) analysis methodology and Google Maps services techniques of WebEpi are presented. SOM has been used as a tool to recognize patterns with data sets measuring epidemiology data and related geographical information. Google Maps services offer Web GIS Application Programming Interface (API) and GIS views. The integration of SOM and Google Maps facilitates the epidemiology data pattern recognition and geovisualization which enables health research to be conducted in a novel and effective way