Spatio-Temporal Analysis of Urbanization Using GIS and Remote Sensing

Dear Colleagues,

Digitized old maps from different periods of the last centuries, aerial photogrammetric products for the past three-quarters of a century, periodically captured satellite imagery from different sensors starting globally 50 years ago, constantly updated spatial datasets and maps, outcomes of predictions, our accumulated knowledge, etc., all have the potential to be used or re-used for analysis with different spatio-temporal analyses for a wide range of urbanization purposes. An alternative scenario is a near real-time spatio-temporal analysis of data concerning currently running events.

The concept of GIS, which is based mainly on vector and raster data layers, and attributes is well recognized, where the associated tools and services support the implementation of the spatial analysis with visualizations and animations. This well-established system is also commonly used by the temporal component which appears as an additional, special unidirectional akin dimension related to the 2D or 3D physical space. In this case, the sequence of themes sampled to the time slices can be captured in the individual layers, e.g., as a multi-annual dataset of the built-up areas. Another common option is to assign different attributes to the single layer, e.g., number of inhabitants in settlements (as point features), recorded in a multi-column table for each year. There are numerous other options, for example, to map a difference from the previous state, outline features moving over the geographic space on a single layer, e.g., to present vehicle positions in the city over time, or even employ a space-time cube structure with its extensive analytical capabilities, etc.

This Special Issue aims to focus on two components that influence the result of the typical urbanization research, firstly different kinds of data sources (e.g., generated with remote sensing) and secondly their interaction with the relevant spatial analysis in GIS. In addition to the two, there is a third, temporal dimension, which integratively implements the conceptual complexity. The questions that can arise are, how to efficiently harmonize data from different sources which may comprise historical maps, aerial photographs, satellite imagery from various passive and active sensors with different resolutions, surveying data, etc., into a spatio-temporal form? Related to the above, how to optimally archive data for future spatio-temporal analysis?  In addition, what alternative analyses of changes through space-time should be developed, which may involve various disciplines, such as spatial statistics, geography, geomorphometry, environmental, economic social and human sciences, health, etc., to examine urbanization patterns, transport modalities, city growth, the impact of climate change on urban areas, and similar?

The Special Issue aims to examine a complex temporal component of the geospatial approaches to the data that come from various sensors and data sources, where the continuous nature of the time needs to be quantized into discrete forms, which can be further analyzed with the remote sensing and GIS tools.

We suggest themes that focus on optimal solutions between types of spatial data sources and Spatio-temporal analysis in RS and especially in GIS to get an optimal result. We propose to focus the authors’ solutions primarily on the improved data sets, new methods, and overall innovative solutions, where the applications are primarily presented in the form of the use cases.

We prefer original research articles, as well as encourage the following article types: perspective and technical note.

Dr. Tomaž Podobnikar
Guest Editor

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• time series
• spatio-temporal data
• spatio-spatial analysis
• spatio-temporal statistics
• spatio-temporal concept in GIS
• spatio-temporal visual data exploration
• spatio-temporal urbanization patterns
• movement analysis
• GIS
• remote sensing
• geospatial