Web Processing Services for Forestry and Environmental Applications

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.Nowadays spatial processing on the web is becoming a requirement for more and more web applications. The use of processes helps to find solutions to a wide range of spatial problems and extends the common functionality of Web GIS. There are many open source technologies that can be implemented in each component of a Web GIS application. Forestry and environmental problems, with their strong territorial implications, are especially suitable to be analyzed applying these technologies. In order to create an application with spatial processes, we propose a framework with a layered service-based architecture. It is layered because its structure is divided in a set of functional layers: the user layer (geoportal or client), the service layer (inside the server) and the data layer (spatial database). The access and processing of spatial data is accomplished through adequate service standards of OGC (Open Geospatial Consortium): Web Map Services (WMS), Web Feature Services (WFS), Web Coverage Services (WCS) and Web Processing Services (WPS). We implement a complete forestry – related application from scratch that offers access, visualization, querying and processing of spatial data and an active user interaction. The key of the application is WPS. Additionally, other processing solutions (like making queries with the spatial database) are discussed. In brief, this work presents an overview of the current technology and possible solutions for integrating spatial processes on the web and proposes some guidelines to implement them in a fully working system

CPR Algorithm—A new interpolation methodology and QGIS plugin for Colour Pattern Regression between aerial images and raster maps

The Colour Pattern Regression (CPR) algorithm complement for QGIS is presented for determining and quantifying the relationship between aerial images and raster maps. Aerial images can be readily decomposed into their standard RGB spaces that assign numerical values to their colours. According to them, a linear regression can be established to correlate raster values with the colour patterns, and if the model performance is considered satisfactory, the result will provide a raster interpolation with finest resolution according to colour nuances within the aerial image. The CPR Algorithm allow both, the calculation of the regression coefficient and the evaluation of the goodness of fit of the model. The use of the present QGIS complement could enable the study of the relationships of aerial images and earth surface products – e.g. soil moisture content, landcover, vegetation and forests, soils, urban heat islands – or marine products – e.g. chlorophyll, total suspended solids. The tool is open source and will be readily adapted with additional features and improved general performance ratings thresholds for the physical problems to be solved