Scanned maps need to be georeferenced, to be useful in a GIS environment for data extraction (vectorization), web publishing or spatially-aware archiving. Widely used software solutions with georeferencing functionality are designed to suit a universal scenario for georeferencing many different kinds of data sources. Such general nature also makes them very time-consuming for georeferencing a l...

This paper proposes a predictive approach of semantic land use changes based on data mining techniques, specifically association rules (AR). Its main idea is centered around studying the past to predict the future. In other words, applying association rules technique to discover rules governing the city’s past land use changes, then use them to forecast future changes. Taking La Plaine Zone in ...

In this study, a new tool for quantitative, data-driven susceptibility zoning (SZ) is presented. The SZ plugin has been implemented as QGIS to maximize its operational use within the geoscientific community. in fact commonly used open-source geographic information system. We have scripted Python, and developed it collection of functions that allow one pre-process input data, calculate susceptib...

The use of topographic airborne LiDAR data has become an essential part archaeological prospection. However, as a step towards theoretically aware, impactful, and reproducible research, more rigorous transparent method processing is required. To this end, we set out to create pipeline for archaeology-specific point cloud derivation products that are optimized general-purpose data. proposed impr...

This paper presents a Python QGIS (PyQGIS) plugin, which has been developed for the purpose of producing Land Surface Temperature (LST) maps from Landsat 5 TM, Landsat 7 ETM+ and Landsat 8 TIRS, Thermal Infrared (TIR) imagery. The plugin has been developed purposely to ease the process of LST extraction from Landsat Visible, Near Infrared (VNIR) and TIR imagery. It has the ability to estimate L...

Earth observation sciences, astronomy, and seismology have large data sets which have inherently rich spatial and geospatial information. In combination with large collections of semantically rich objects which have a large number of thematic properties, they form a new source of knowledge for urban planning, smart cities and natural resource management. Modeling and storing these properties in...

Objective of the study is to identify sub-state regions with significantly high and low prevalence of smoking tobacco We also explored whether smoking was spatially correlated with the different background variables like education, occupation etc in order to find its present condition so that control intervention can be done. Methods: We used data from the cross-sectional survey DLHS-4 (2012-20...

In Switzerland, the requirement for a clearly defined data model that can be adapted in flexible ways resulted in a conceptual schema and object oriented language INTERLIS. The cadastral core data model and many other models (i.e. utility services, urban planning, etc.) have been defined with INTERLIS in Switzerland. The concept of the data description language INTERLIS is compatible with inter...