Laboratory for development of open source geospatial technologies: Role in education and research

International Cartographic CBOs (International Cartographic Association-ICA) in partnership with the Open Source Geospatial Foundation-OSGeo has started the initiative ICA-OSGeo Labs to promote and use open source technologies in education and research. For many years, the use and development of the open source software and technologies have been present in the field of research and education at the Faculty of Civil Engineering at the Department of Geodesy and Geoinformatics, University of Belgrade. Additionally, at the University of Belgrade, Faculty of Civil Engineering a laboratory called 'Laboratory for development of the open source geospatial technologies - OSGL' has recently been established. This paper presents the current experience of the lab members in using the open source software in geoinformatics, research and education as well as the perspectives and future activities of the newly formed laboratory

An integrative dynamic model of Colombian population distribution, based on the maximum entropy principle and matter, energy, and information flow

Human society has increased its capacity to exploit natural resources thanks to new technologies, which are one of the results of information exchange in the knowledge society. Many approaches to understanding the interactions between human society and natural systems have been developed in the last decades, and some have included considerations about information. However, none of them has considered information as an active variable or flowing entity in the human–natural/social-ecological system, or, moreover, even as a driving force of their interactions. This paper explores these interactions in socio-ecological systems by briefly introducing a conceptual frame focused on the exchange of information, matter, and energy. The human population is presented as a convergence variable of these three physical entities, and a population distribution model for Colombia is developed based on the maximum entropy principle to integrate the balances of related variables as macro-state restrictions. The selected variables were electrical consumption, water demand, and higher education rates (energy, matter, and information). The final model includes statistical moments for previous population distributions. It is shown how population distribution can be predicted yearly by combining these variables, allowing future dynamics exploration. The implications of this model can contribute to bridging information sciences and sustainability studies

Spatial aspects of demographic processes in Serbia

Changes in the trends, distribution and structures of the population identified through censuses (such as the changes in total population, gender, educational, age and other structures) are crucial for understanding spatial phenomena and processes like urbanization. Numerous urban geography studies researching the development of systems of settlements in former Yugoslavia, which carried on in Serbia, were the foundation for a singular theoretical and methodological framework for researching spatial phenomena and processes focused precisely on the understanding of dynamic changes in the structures of the population and their territorial manifestation. Other than in scientific research, this approach found direct application in spatial and urban planning, when defining the measures directing demographic development, arrangement of urban functions, formation of a system of settlements, planning infrastructure development, etc. More recently, this theoretical and methodological framework was enhanced using GIS technologies, which allow for the integration of spatial and statistical data and provide for a powerful analytical tool. Data integration has spurred new research on the correlation between demographic and spatial phenomena and the mutual relationships and influences between spatial and demographic development. This paper presents an overview of existing research on the mutual influence between population development trends and spatial changes manifest through the fluctuations in the intensity of built-up areas, population density, infrastructure development, etc. A model of population distribution was created by using selected census statistical data and correlating them with phenomena in actual geospace. Emphasis is placed on the significance of using this and similar models in further research on the population’s impact on the environment, directing economic development, protection in emergency situations, and numerous other areas

Modelling Day and Night-Time Population using a 3D Urban Model

Dasymetric methods are commonly used to redistribute or disaggregate (census) population data, using either simple binary or multi-layer models. Most models show limitations in high density built-up areas as they commonly ignore the 3D dimension (meaning buildings height) of multi-story urban environments. For example, simple dasymetric models only allocate the population counts to built-up areas, without considering differences between areas of multi-story and single-story buildings. Furthermore, such models only allow the disaggregation of ‘night-time’ population data, while for many urban applications such as transport, health or hazard, the location of ‘day-time’ population is of interest. This research presents an initial approach to model day and night-time population using as case study an Indian city (Kalyan-Dombivli). For most Indian cities, census population data is only available for wards, while day-time population data is either not available or of very poor quality. Besides census data and ancillary spatial data, this research uses a 3D urban model, extracted from Cartosat stereo-images. First, the extracted height from the stereo-image is used in combination with building footprints to disaggregate census population data at wards to ‘night-time’ population per building. Second, a classification of economically active areas is constructed based on the 3D urban model in combination with other spatial layers (e.g. transport layers) to model the day-time population. The result shows different concentration of population during day and night-time across ward boundaries as well as it confirms the potential of 3D data to disaggregate population data

Depopulated and Abandoned Areas in Serbia in the 21st Century – From a Local to a National Problem

Depopulated or abandoned spaces are a consequence of the emptying of settlements and the complete disappearance of the human factor in the use of space. The aim of this paper is to determine the size and structure of this space—clusters that can be considered abandoned at the regional level. In the focus of this paper is the space at the district level in Serbia, within which significant changes in land use occurred in the period 1990–2018. Time series of formal databases and data obtained by GIS tools were analysed in order to observe the changes in the structure of surfaces and to define the trend of merging or increasing the empty space during the last two decades. This paper analyses planning documents and strategies in order to determine with which problems the state identifies abandoned areas and what planning solutions are possible. A new method for calculating the homogenization of abandoned space is presented. The results indicate the homogenization of the abandoned space in the border regions in the south of Serbia, as well as major changes in land use, such as reforestation and reclamation of agricultural land

Report on SHAFE policies, strategies and funding

The objective of Working Group (WG) 4 of the COST Action NET4Age-Friendly is to examine existing policies, advocacy, and funding opportunities and to build up relations with policy makers and funding organisations. Also, to synthesize and improve existing knowledge and models to develop from effective business and evaluation models, as well as to guarantee quality and education, proper dissemination and ensure the future of the Action. The Working Group further aims to enable capacity building to improve interdisciplinary participation, to promote knowledge exchange and to foster a cross-European interdisciplinary research capacity, to improve cooperation and co-creation with cross-sectors stakeholders and to introduce and educate students SHAFE implementation and sustainability (CB01, CB03, CB04, CB05). To enable the achievement of the objectives of Working Group 4, the Leader of the Working Group, the Chair and Vice-Chair, in close cooperation with the Science Communication Coordinator, developed a template (see annex 1) to map the current state of SHAFE policies, funding opportunities and networking in the COST member countries of the Action. On invitation, the Working Group lead received contributions from 37 countries, in a total of 85 Action members. The contributions provide an overview of the diversity of SHAFE policies and opportunities in Europe and beyond. These were not edited or revised and are a result of the main areas of expertise and knowledge of the contributors; thus, gaps in areas or content are possible and these shall be further explored in the following works and reports of this WG. But this preliminary mapping is of huge importance to proceed with the WG activities. In the following chapters, an introduction on the need of SHAFE policies is presented, followed by a summary of the main approaches to be pursued for the next period of work. The deliverable finishes with the opportunities of capacity building, networking and funding that will be relevant to undertake within the frame of Working Group 4 and the total COST Action. The total of country contributions is presented in the annex of this deliverable

Automated mapping of climatic variables using spatio-temporal geostatistical methods

Javno dostupni meteorološki podaci, kako sa stanica tako i iz daljinske detekcije, korišćeni su za prostorno vremensku interpolaciju temperature vazduha iznad površine Zemlje. Zastupljenost i pogodnost javno dostupnih podataka je ocenjena, kroz tri aspekta kontrole kvaliteta: (a) zastupljenost u geografskom i prostornom domenu, (b) zastupljenost u karaktestičnom prostoru (feature space; bazirano na MaxEnt metodi), kao i (c) pogodnost korišćenja podataka za prostorno-vremensku predikciju (na osnovu kros-validacije prostorno-vremnskog regresionog kriginga). Rezultati pokazuju da je kombinovani set podataka (GSOD i ECA&D) značajno klasteriran i u geografskom i u karakterističnom prostoru. Uprkos klasteriranju, preliminarni rezultati globalne interpolacije primenom prostorno-vremenskog regresionog kriginga koristeći merenja sa stanica i snimke daljinske detekcije su pokazali da se tako mogu dobiti precizne globalne karte dnevne temperature. Oko 9000 stanica kombinovanog seta podataka (GSOD i ECA&D) je korišćeno za prostorno-vremensko geostatističko modeliranje i predikciju dnevnih temperatura u rezoluciji 1 km, iznad površine Zemlje. Za predikciju srednjih, minimalnih i maksimalnih temperatura korišćen je regresioni kriging uz pomoćne prediktore: MODIS LST 8-dnevni snimci, topografski lejeri (DEM i TWI) i geometrijski temperaturni trend. Model i predikcija se odnose na 2011 godinu, ali ista metodologija bi se mogla primeniti od 2001 godine do danas (od kada su dostupni MODIS snimci). Rezultati pokazuju da je prosečna tačnost predikcije za srednju, minimalnu i maksimalnu temperaturu vazduha oko ±2°C za oblasti gusto pokrivene stanicama i između ±2°C i ±4°C za oblasti koje su slabo pokrivene stanicama. Najniža tačnost predikcije je dobijena u planinskim predelima i na Antartiku, oko 6°C. R softverski paket, meteo, je razvijen kao resenje za automatsko kartiranje. Razvijen je i paket plotGoogleMaps za automatsku vizuelizaciju na Web-u, koristeći Google Maps API.Publicly available global meteorological data sets, from ground stations and remote sensing, are used for spatio-temporal interpolation of air temperature data for global land areas. Publicly available data sets were assessed for representation and usability for global spatio-temporal analysis. Three aspects of data quality were considered: (a) representation in the geographical and temporal domains, (b) representation in the feature space (based on the MaxEnt method), and (c) usability i.e. fitness of use for spatio-temporal interpolation (based on cross-validation of spatio-temporal regression-kriging models). The results show that clustering of meteorological stations in the combined data set (GSOD and ECA&D) is significant in both geographical and feature space. Despite the geographical and feature space clustering, preliminary tested global spatio-temporal model using station observations and remote sensing images, shows this method can be used for accurate mapping of daily temperature. Around 9000 stations from merged GSOD and ECA&D daily meteorological data sets were used to build spatio-temporal geostatistical models and predict daily air temperature at ground resolution of 1 km for the global land mass. Predictions were made for the mean, maximum and minimum temperature using spatio-temporal regression-kriging with a time series of MODIS 8 day images, topographic layers (DEM and TWI) and a geometrical temperature trend as covariates. The model and predictions were built for the year 2011 only, but the same methodology can be extended for the whole range of the MODIS LST images (2001–today). The results show that the average accuracy for predicting mean, maximum and minimum daily temperatures is RMSE = ± 2°C for areas densely covered with stations, and between ± 2°C and ± 4°C for areas with lower station density. The lowest prediction accuracy was observed in highlands (> 1000 m) and in Antarctica with a RMSE around 6°C. Automated mapping framework is developed and implemented as R package meteo. Likewise, package plotGoogleMaps for automated visualisation on the Web, base on Google Maps API is developed

An Integral Approach to the Modeling of Information Support for Local Sustainable DevelopmentExperiences of a Serbian Enabling Leadership Experiment

Collaborative strategic decision making has to be widely informed, communicated and knowledge-based in order to innovate transformations toward local and global sustainability. It is unimaginable that this process could be effective without computer-aided information support, but the research indicates the utilization constraints within human capacities to recognize their usability and usefulness. These constraints seem to be even more challenging within the intensively transitional social contexts, such as Serbia. We argue that understanding the relationships between sustainability, governance, and planning in a specific social context has profound importance to gain usefulness of information support and to ensure its increasing utilization. Identifying the practical path of information support modeling requires an operational framework that encompasses innovative and socially valid initiatives. Therefore, an integral theory framework was chosen to comprehend all social influences on the information support of successful utilization. This article presents the integral framework of the information support's conceptual setting, which was used to build up community-based collaborative action research (CBCAR) as a transformative social learning process that enables information support utilization, and it was tested in six municipalities of Serbia. The implementation of pilot territorial information support (TIS) initiatives resulted in continuous and proactive local community efforts in information support development and usage