Geo-Spatial Information System for Developing Tourism Industry in Kandy District, Sri Lanka

Tourism is a rapidly growing investment point in Sri Lanka, where huge investment is takeing place. Even though the investment is very massive, the planning, development, and marketing are key components of success in tourism zone enhancement. The main objective of this study was to implement a geo-spatial information system for development of tourism in Kandy district. Primary data collection methods i.e. questionnaire survey, interviews, focus group interviews, and observations were employed for data collection. Google maps with Google API standards which are specially designed for developers and computer programmers were used for implementation of the system. System requirements were identified by interviewing tourists and observations made on tourist sites. Proximity analysis, spatial joint, and network analysis with Google direction application program interface （API） and Google place API were used to analyze data. The study highlights the potential tourist attractions and the accessibility and other required details through a web output. Issues and challenges faced by travelers are mainly lack of specific location information, public transport schedules, and reliable tourist attraction information. Online geo-spatial information system created in this study provides a guide for tourists to fred the destination routes, the service areas, and all necessary details on particular destinations.

An event-driven dynamic updating method for 3D geo-databases

With the rapid development of 3D Digital City, the focus of research has shifted from 3D city modeling and geo-database construction to 3D geo-database service and maintenance. The frequent modifications on geometry, texture, attribute, and topology present a great challenge to the 3D geo-database updating.This article proposes an event-driven spatiotemporal database model (ESDM) that combines the historical and present 3D city models with the semantic classification and state expression, triggered by changing events predefined. In addition, a corresponding dynamic updating method based on adaptive matching algorithm is presented to perform the dynamic updating operation for the complex 3D city models automatically, according to the compound matching of semantics, attributes, and spatial locations. finally, the validity and feasibility of the proposed ESDM and its updating method are demonstrated through a 3D geo-database with more than 1.5 million 3D city models.

Monthly soil erosion monitoring based on remotely sensed biophysical parameters: a case study in Strymonas river basin towards a functional pan-European service

Currently,many soil erosion studies at local,regional,national or continental scale use models based on the USLE-family approaches.Applications of these models pay little attention to seasonal changes,despite evidence in the literature which suggests that erosion risk may change rapidly according to intra-annual rainfall figures and vegetation phenology.This paper emphasises the aspect of seasonality in soil erosion mapping by using month-step rainfall erosivity data and biophysical time series data derived from remote-sensing.The latter,together with other existing pan-European geo-databases sets the basis for a functional pan-European service for soil erosion monitoring at a scale of 1:500,000.This potential service has led to the establishment of a new modelling approach(called the G2 model)based on the inheritance of USLE-family models.The G2 model proposes innovative techniques for the estimation of vegetation and protection factors.The model has been applied in a 14,500 km 2 study area in SE Europe covering a major part of the basin of the cross-border river,Strymonas.Model results were verified with erosion and sedimentation figures from previous research.The study confirmed that monthly erosion mapping would identify the critical months and would allow erosion figures to be linked to specific land uses.