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Renewable energy sources are expanding opportunities for industrial development and can boost economic growth and create new jobs. In all European Union (EU) countries, including Latvia, it is possible to use renewable energy resources cost-effectively. The world is now at the beginning of the global energy transformation. Cost-effective renewable energy technologies provided an opportunity for sufficient development to reach ambitious climate targets of the EU Directive 2009/28/EC. Some systems are not only dependent on the interaction of many elements and dynamics over time, but they are also variable in space. In this context, energy production from local and renewable resources is one of the most relevant examples. It is characterized by many spatially variable elements, such as biomass availability, wind speed, solar radiation, location of power plants, transmission network infrastructure, energy demand, etc. It is crucial to explore the spatial distribution of resources to plan territorially-unified development of renewable energy and, consequently, promote efficient use of resources. This paper describes the data acquisition process of the spatial distribution of renewable energy sources. ArcGIS PRO and data collected from the various databases were used to describe the energy sectors according to resources, spheres of consumption and regions.

Urban barriers are often a consequence of the unplanned expansion of transport infrastructures, housing growth nearby existing transport infrastructures, and the vehicular traffic itself. This process, also known as “community severance”, is a problem that affects the travel patterns of the population and causes negative impacts to adjacent communities, but it is not easy to assess. As an alternative to the costly technologies and restricted-access data sometimes used to analyze urban barriers, we propose an analytical approach that assesses community severance levels by classifying the quality of Pedestrian Crossings on Urban Streets (the PeCUS index). Additionally, the approach is used to identify possible inequities nearby the different classification groups regarding demographic data. We used the chi-square (χ2) test of independence and the standardized Pearson residuals to indicate deficits and excesses of residents regarding the demographic characteristics studied surrounding the urban streets. We found the following evidences of associations: residents with low-income or those aged up to 19 tend to live close to the worst crossings, whereas residents with permanent mobility constraints or the elderly tend to live near the crossings with the best classifications. Therefore, the study shows that the assessment of community severance by the analysis of the PeCUS index is feasible. Moreover, it reveals that the distribution of residents surrounding the distinct classes of quality of crossings is equitable for vulnerable social groups, except for low-income or young residents.

The Physical Internet (PI) concept presents a radical change with the aim to revert the unsustainable practices that are used for transporting goods. It identifies dedicated freight flows and transforms them into transparent open logistics networks which can be accessed by other users, such as shippers and carriers. In this paper, we test the universal network openness in which the users can tap into the PI network and place orders that will be assigned to the nearest available transport service and consequently delivered to the order sender. The objective of our paper is to investigate the impact of inserting extra service points into existing dedicated freight flows of a service‐driven company. We simulate different transparency levels and routings to new pickup locations and evaluate the impact in terms of altered lead times, covered distances, and fill rates. The novel aspects presented herein are (1) deliveries based on decentralized location detection of the nearest order sender, (2) dynamically changing speed parameters of agents within specific geographic clusters based on their geo‐locations in order to account for congestion levels, (3) more realistic routing strategies that consider the urban layout, and (4) transparent querying of nearest agents in space and time that meet specific conditions such as current ongoing processes, available capacity, and position. Finally, we identify the impact from a general/holistic perspective that emerges once extra orders are assigned to the service‐driven company's fleet.

At present, most governments, particularly in low and middle-income countries, are not effectively using ecosystem services (ES) indicators for conservation monitoring, which is in part due to the complexity of current indicators. This study seeks to contribute to this implementation gap by illustrating the performance of a remote sensing based indicator, the Ecosystem Services Provision Index (ESPI) (based on the Normalized Difference Vegetation Index), as a feasible indicator for monitoring ES supply. We examined ESPI’s performance by analyzing its spatial congruence (regression and cluster analysis) with four type-specific ES indicators, namely timber provision, forage provision, opportunities for recreation and water regulation, for different types of temperate native forests, non-native tree plantations, shrublands and grasslands, within a southern district in Chile. We additionally compared values of ESPI and ES indicators across land uses and covers by means of ANOVA and Tuckey test (post-hoc). The regression analysis showed medium to low fitting of ES indicators to linear and non-linear variations of ESPI. Unexplained variation can arise from different dispersion sources: a) uncaptured variation in specific ES flow by variation in their corresponding indicators (specific ES indicators and ESPI), b) distances between parametric values of different ES indicators and ESPI, and c) mismatches between ESPI and ES indicator scales and resolutions. Cluster analysis showed ESPI-ES hotspot congruence of 62% for water regulation, followed by the ES bundle (56%), recreation opportunities (38%), timber supply (36%) and forage provision (32%). The values of ESPI, water regulation and recreation opportunities were significantly higher on old growth forests. Our study contributes to establish to what extent remote sensing indicators can be used as a proxy of ES supply, which is relevant for the adoption of these indicators in monitoring conservation outcomes when specific ES indicators are not available or they lack the necessary spatial and temporal coverage.

Medical facilities help to ensure a higher quality of life and improve social welfare. The spatial accessibility determines the allocation fairness and efficiency of medical facilities. It also provides information about medical services that residents can share. Although critical, scholars often overlooked the level of medical facilities, the composition of integrated transportation networks, and the size of service catchment in the literature on accessibility. This study aims to fill this research gap by considering the integrated transportation network, population scale, travel impedance between medical facilities and residential areas, and the impact of medical facilities’ levels on residents’ medical choices. An improved potential model was constructed to analyze the spatial accessibility of medical facilities in Changning District of Shanghai, China. Interpolation analysis was conducted to reveal the spatial accessibility pattern. Cluster and outlier analysis and Getis-Ord Gi* analysis were applied for the cluster analysis. Results show that the spatial accessibility of medical facilities is quite different in different residential areas of Changning District, Shanghai. Among them, the spatial accessibility of medical facilities is relatively high in Hongqiao subdistrict, Xinjing Town, and part of Xinhua Road subdistrict. In addition, residents have overall better access to secondary hospitals than to primary and tertiary hospitals in the study area. This study provides a spatial decision support system for urban planners and policymakers regarding improving the accessibility of healthcare facilities. It extends the literature on spatial planning of public facilities and could facilitate scientific decision making.

Archaeologists are using spatial data in increasingly sophisticated analyses and invoking more explicit considerations of space in their interpretations. Geographic information systems (GIS) have become standard technology for professional archaeologists in the collection and management of spatial data. Many calls have been made to develop and adapt digital geospatial technologies for interpretation and understanding past social dynamics, but this has been limited to some extent by the static nature of map-oriented GIS approaches. Here, we illustrate how coupling GIS with agent-based modeling (ABM) can assist with more dynamic explorations of past uses of space and geospatial phenomena.

Knowledge of the sunshine requirements of landscape plants is important information for the adaptive selection and configuration of plants for urban greening, and is also a basic attribute of plant databases. In the existing studies, the light compensation point (LCP) and light saturation point (LSP) have been commonly used to indicate the shade tolerance for a specific plant, however, these values are difficult to adopt in practice because the landscape architect does not always know what range of solar radiation is the best for maintaining plant health, i.e., normal growth and reproduction. In this paper, to bridge the gap, we present a novel digital framework to predict the sunshine requirements of landscape plants. First, the research introduces the proposed framework, which is composed of a black-box model, solar radiation simulation, and a health standard system for plants. Then, the data fitting between solar radiation and plant growth response is used to obtain the value of solar radiation at different health levels. Finally, we adopt the LI-6400XT Portable Photosynthetic System (Li-Cor Inc., Lincoln, NE, USA) to verify the stability and accuracy of the digital framework through 15 landscape plant species of a residential area in the city of Wuhan, China, and also compared and analyzed the results of other researchers on the same plant species. The results show that the digital framework can robustly obtain the values of the healthy, sub-healthy, and unhealthy levels for the 15 landscape plant species. The purpose of this study is to provide an efficient forecasting tool for large-scale surveys of plant sunshine requirements. The proposed framework will be beneficial for the adaptive selection and configuration of urban plants and will facilitate the construction of landscape plant databases in future studies.

0000-0003-4538-4944 0000-0002-3406-3144 WOS:000621467400006 The advantages of logistics centers for companies, cities, and countries have been discussed in the literature and generally mathematical model-based evaluations besides multi-criteria approaches are proposed for site selection processes. However, since mathematical modeling of multiple site selection often turns out to be NP-hard problem structure, it is not always possible to obtain an optimal solution by the solvers. For this reason, various meta-heuristic approaches have emerged to solve these complex models. In this context, the aim of this study is to propose an integrated methodology which seeks an optimum result efficiently regarding a logistics center location selection problem. Thus, the optimal clustering of logistics mobility in a metropolitan area was carried out with GIS and a meta-heuristic approach. GIS produced the spatial information needed by p-median model, then the meta-heuristic approach determined the optimal result that considers the logistics costs. BPSO algorithm has employed as the meta-heuristic and it is observed that the algorithm can reach the optimum results within superior times for the problem sizes tested where binary integer programming verified the optimums and the algorithm continued to reach improved solutions where the exact algorithms failed for larger instances. The integrated solution methodology is applied to a large metropolitan region and it is found that it can be used properly by the urban city planners and supply chain managers to analyze critical nodes of transportation networks of megacities.

Digital images represent the primary tool for diagnostics and documentation of the state of preservation of artifacts. Today the interpretive filters that allow one to characterize information and communicate it are extremely subjective. Our research goal is to study a quantitative analysis methodology to facilitate and semi-automate the recognition and polygonization of areas corresponding to the characteristics searched. To this end, several algorithms have been tested that allow for separating the characteristics and creating binary masks to be statistically analyzed and polygonized. Since our methodology aims to offer a conservator-restorer model to obtain useful graphic documentation in a short time that is usable for design and statistical purposes, this process has been implemented in a single Geographic Information Systems (GIS) application.

Cultivation-based land suitability has become an essential research topic because of increased interest in agricultural sustainability and negative environmental effects due to rapid population growth and a decrease in arable lands due to urbanization. Therefore, this study investigates land suitability for the olive plant, which has a high economic value in the Mediterranean city of Mersin, Turkey. First, areas that cannot be cultivated were excluded from the study using exclusion analysis so that only agricultural areas were included in the analyses. Afterward, the weightage of the meteorological, topographic, soil, and infrastructural and economical criteria were determined using the analytic hierarchy process (AHP), and a land suitability map for olive cultivation was created using Geographic Information Systems (GIS). The resulting map showed that 2.72% (438.12 km2) of the study area is very suitable for olive cultivation and 0.99% (159.28 km2) is very unsuitable. It was determined that the Tarsus region, located in the east of the study area, and the Mut region, located in the northwest, have very suitable land for olive cultivation.

Geospatial potential for harvesting wind energy is not an easy task to perform in conditions of deficiency of accurate data in remote and large areas (macro to medium locations). There are different methodologies available to identify the most suitable location for the installation of wind power generators. One of the most suitable approaches that employ the Multi-Criteria Analysis method for wind energy potential of the Municipality of Knjaževac (East Serbia) is combining the Analytic Hierarchy Process (AHP) and Geographic Information Systems. Collection and creation of geospatial data for the research encompassed meteorological data from all available sources, digital elevation model (DEM) to analyze the orography of the terrain, and Landsat 8 satellite data to analyze six land cover (LC) classes. The identification of three best locations for the wind power generators (wind farms) using Multi-Criteria Decision Making (MCDM) analysis solved the major location problem: how to select the best locations for investment in the renewable energy sector and minimize the impact on the environment. The result indicates that only one part of the municipality, at the hub height of 100 m, has enough wind potential to produce energy.

Głównym problemem badawczym niniejszego artykułu jest sprawdzenie, czy i w jaki sposób wybrane formy i funkcje zagospodarowania przestrzeni miejskiej wpływają na rozmieszczenie kradzieży oraz kradzieży z włamaniem. W analizie wykorzystano dane dotyczące przestępstw zarejestrowanych w latach 2016–2018 w obrębie administracyjnych granic miasta Krakowa. Rezultaty przeprowadzonych badań są zasadniczo zgodne z wynikami podobnych analiz, w zakresie w jakim wskazują one na związek pomiędzy wzmożoną aktywnością przestępczą sprawców a dostępnością potencjalnych ofiar lub obiektów ataku. Większe zagęszczenie zarówno przestępstw ogółem, jak i kradzieży ogółem występowało przede wszystkim w tych obiektach lub bezpośredniej bliskości obiektów, które w różnych celach gromadzą duże zbiorowości (węzły aktywności) lub są miejscem licznych przepływów ludzkich (węzły komunikacji). Co jednak istotne, jedne tego typu funkcje zagospodarowania współwystępują ze zwiększonym zagęszczeniem wszystkich typów kradzieży, inne zaś jedynie niektórych z nich. Wyniki niniejszych badań nie pozostają natomiast w zgodzie z podstawowym założeniem teorii racjonalnego wyboru, wskazując na wysokie zagęszczenie przestępstw w bezpośrednim sąsiedztwie kamer monitoringu publicznego i prywatnego, jak również w odległości do 50 metrów od komisariatów policji. The main research problem of this article is to check whether and how selected land use and facilities influence the spatial distribution of different kinds of urban thefts (and burglary) in Krakow. The analysis uses data on all crimes committed in Krakow in the years 2016–2018. Its results are generally consistent with the results of other similar studies in so far as they indicate a relationship between the increased criminal activity of perpetrators and the availability of potential victims or objects of attack. Both the higher density of crimes in general and theft, in general, occurred above all in facilities or in the immediate vicinity of facilities which accumulate large communities for various purposes (activity nodes) or in places that produce the high intensity of people flows (communication nodes). One land use and facilities coexist with an increased density of all types of thefts, while others coexist only with some of them. The results, however, seem inconsistent with the rational choice theory assumptions as high crime density rates were observed in the immediate vicinity of public and private monitoring cameras, as well as within 50 meters of police stations.

As the population is aging rapidly, the irrationality of residential care facility (RCF) configuration has impacted the efficiency and quality of the aged care services so significantly that the optimization of RCF configuration is urgently required. A multi-objective spatial optimization model for the RCF configuration is developed by considering the demands of three stakeholders, including the government, the elderly, and the investor. A modified immune algorithm (MIA) is implemented to find the optimal solutions, and the geographic information system (GIS) is used to extract information on spatial relationships and visually display optimization results. Jing&rsquo, an District, part of Shanghai, China, is analyzed as a case study to demonstrate the advantages of this integrated approach. The configuration rationality of existing residential care facilities (RCFs) is analyzed, and a detailed recommendation for optimization is proposed. The results indicate that the number of existing RCFs is deficient, the locations of some RCFs are unreasonable, and there is a large gap between the service supply of existing RCFs and the demands of the elderly. To fully meet the care demands of the elderly, 6 new facilities containing 1193 beds are needed to be added. In comparison with the optimization results of other algorithms, MIA is superior in terms of the calculation accuracy and convergence rate. Based on the integration of MIA and GIS, the quantity, locations, and scale of RCFs can be optimized simultaneously, effectively, and comprehensively. The optimization scheme has improved the equity and efficiency of RCF configuration, increased the profits of investors, and reduced the travel costs of the elderly. The proposed method and optimization results have reference value for policy-making and planning of RCFs as well as other public service facilities.

Summary Between 2007 and 2010 the Netherlands experienced the largest documented Q fever outbreak to date. This outbreak and several other incidents with infectious disease spill-overs from livestock to humans, initiated research focussing on the impact on human health of living in the vicinity of livestock farms. In this thesis, information about outdoor activities -mobility and activities outdoors near the home- were collected using GPS logging and self-reporting, in a rural population in the Netherlands. This was performed to include a measure for duration and frequency of exposure to exposure assessment methods for livestock related infections. Outdoor activity patterns were combined with data about livestock farms in the research area, which acted as exposure source. Time spent outdoors close to home in the presence of goat farms translated into an increased pneumonia risk. The specific agent or mechanism underlying this increased risk for pneumonia was not identified and is currently under study. Mobility outdoors in the vicinity of goat farms did not markedly change risk estimates, but this might be expected given that the time spent on active mobility was relatively limited. Still, it was observed that outdoor exposure, a combination of time spent outdoors near the home and active mobility, contributed to the risk of becoming C. burnetii serology positive during the 2007-2010 Dutch Q fever outbreak. These associations were stronger if people lived closer to C. burnetii positive farms. Given these findings, time activity patterns, when included to exposure assessment, provided somewhat stronger associations, than for measures earlier used in spatial epidemiological studies such as home distance from the source. Time spent in the vicinity of an emitting infectious source is likely to play a role in exposure assessment to livestock related zoonotic pathogens and information about time activity data should therefore be considered for exposure assessment methods. The method how to include this factor is a topic for further study. It was shown that study participants significantly overestimated their time spent outdoors in active transport when self-reported data were compared to GPS measured data, but several general characteristics correlating to differences in mobility patterns were identified. Using this information, three different approaches were designed to predict active mobility for exposure assessment. These estimation methods however, were equally unable to accurately predict active mobility, when compared to matching GPS data. Measurements therefore, still represent the best possible tool to evaluate outdoor activity and active mobility. Given the identified associations in this thesis, in the event of a future livestock related outbreak of a zoonotic disease, depending on the causal pathogen, active mobility and outdoors activities should be limited in the vicinity of infected farms. Among residents living near future infected farms, health and time-activity data should be collected, this will provide additional data that may strengthen the findings in this thesis.

Urban flooding is the most common type of disaster and the one that hit people most. Unplanned urbanization processes increase the recurrence of these events due to soil impermeabilization. Thus, land-use and land-cover is an important factor for urban flood research. Besides, mapping flood-prone areas has been an alternative for disaster prevention and urban planning. However, the use of future land-use and land-cover scenarios for flood mapping is a factor that still requires investigation. The study that is being developed by the authors of this paper aims to identify flood-prone areas in the upper third of the Ligeiro River basin in the city of Pato Branco, Parana, Brazil. For this purpose, this research makes use of the GIS-AHP integration, considering a current scenario and future land-use and land-cover scenarios. Therefore, the objective of the present study is to construct possible land-use and land-cover scenarios, according to municipal legislation, that could serve as a basis for mapping flood-prone areas. Two scenarios were built using Geographic Information Systems software. This tool proved to be efficient in the elaboration of maps and land representation. Pato Branco already has a history of flooding with the current scenario of land-use and land-cover. With future land-use and land-cover scenarios, it is possible to verify the influence of urban sprawl on urban flooding. Keywords: Land-use and land-cover (LULC), Floods, Geographic Information Systems (GIS), Analytic Hierarchy Process (AHP)

Malaria is one of the most cited vector-borne infectious diseases by climate change expert panels. Malaria vectors often need water sheets or wetlands to complete the disease life cycle. The current context of population mobility and global change requires detailed monitoring and surveillance of malaria in all countries. This study analysed the spatiotemporal distribution of death and illness cases caused by autochthonous and imported malaria in Spain during the 20th and 21st centuries using multidisciplinary sources, Geographic Information System (GIS) and geovisualisation. The results obtained reveal that, in the 20th and 21st centuries, malaria has not had a homogeneous spatial distribution. Between 1916 and 1930, 77% of deaths from autochthonous malaria were concentrated in only 20% of Spanish provinces, in 1932, 88% of patients treated in anti-malarial dispensaries were concentrated in these same provinces. These last data reveal the huge potential that anti-malarial dispensaries could have as a tool to reconstruct historical epidemiology. Spanish autochthonous malaria has presented epidemic upsurge episodes, especially those of 1917&ndash, 1922 and 1939&ndash, 1944, influenced by armed conflict, population movement and damaged health and hygiene conditions. Although meteorological variables have not played a key role in these epidemic episodes, they contributed by providing suitable conditions for their intensification. After the eradication of autochthonous malaria in 1961, imported malaria cases began to be detected in 1973, reaching more than 700 cases per year at the end of the second decade of the 21st century. Therefore, consistent and detailed historical studies are necessary to better understand the drivers that have led to the decline and elimination of malaria in Europe and other temperate countries.

One of the main objectives of human society in the present century is to achieve clean and sustainable energy through utilization of renewable energy sources (RESs). In this paper, the main purpose is to identify the locations that are suitable for solar energy in the Kurdistan province of Iran. Initially, solar-related data are collected, and suitable criterion and assessment methods are chosen according to the available data. Then, the theoretical potential of solar energy is assessed and the solar radiation map is prepared. Moreover, the technical potential of various solar technologies is evaluated in that study area. These technologies include concentrating solar power (CSP) and photovoltaic (PV) in power plant applications, and rooftop PV panels and solar water heaters in general applications. The results show that the Kurdistan province has the potential capacity for 691 MW of solar photovoltaic power plants and 645 MW of CSP plants. In the case of using solar water heaters, 283 million cubic meters of natural gas and 1.2 million liters of gasoline could be saved in fuel consumption. The savings in the application of domestic PV will be 10.2 MW in power generation.

Due to the abundance of surface water in the province of Quebec, Canada, it is suspected that many groundwater wells are pumping a mixture of groundwater and surface water via induced bank filtration (IBF). The regulatory framework in Quebec provides comprehensive guidelines for the development and monitoring of surface water and groundwater drinking water production systems. However, the regulations do not specifically address hybrid groundwater-surface water production systems such as IBF sites. More knowledge on the use of IBF in the province is needed to adjust the regulations with respect to the particularities of these systems. In order to provide a first evaluation of municipal wells potentially using IBF and the corresponding population served by these wells, a Geographic Information Science framework (GISc) was used to implement an IBF spatial database and calculate the distance from each well to the nearest surface water body. GISc is based on open source GIS programs and openly available data, to facilitate the reproducibility of the work. From this provincial scale approach, we show that nearly one million people are supplied by groundwater from municipal wells located &lt, 500 m from a surface water body, and half a million have a significant probability to be supplied by IBF wells. A more focused look at the watershed scale distribution of wells allows us to improve our interpretations by considering the aquifer type and other regional factors. This approach reveals strong spatial variability in the distribution of wells in proximity to surface water. Of the three selected regions, one has a high potential for IBF (Laurentides), one requires additional information do draw precise conclusions (Nicolet), and the third region (Vaudreuil-Soulanges) is unlikely to have widespread use of IBF. With this study, we demonstrate that extensive use of IBF is likely and that there is a need for improved understanding and management of these sites in order to properly protect the drinking water supply.

The aim of the study was to indicate the possibility of using the tools of spatial information systems (GIS) in education at the higher education level based on graduate theses realized at the Poznań University of Life Sciences. Research was carried out on selected bechelor and master's theses which had been written at the faculties of Environmental Engineering and Spatial Management and Agriculture and Bioengineering, on Spatial Management and Environmental Protection courses. The years 2008–2017 were analyzed. Celem artykułu było wskazanie możliwości zastosowania narzędzi Systemów Informacji Geograficznej (GIS) w edukacji na poziomie kształcenia wyższego, na przykładzie prac dyplomowych realizowanych na Uniwersytecie Przyrodniczym w Poznaniu. Przeprowadzono badania wybranych prac inżynierskich i magisterskich, które zostały napisane na dwóch Wydziałach: Inżynierii Środowiska i Gospodarki Przestrzennej oraz Rolnictwa i Bioinżynierii, na kierunkach Gospodarka przestrzenna oraz Ochrona środowiska. Analizy dokonano w latach 2011–2017.

Lake disappearance as a natural stage of evolution of lakes is an extremely important issue in the landscape and ecosystem research context. Studies of the changes that occur in the lake landscape, characteristic in the northern part of Poland, are aimed at defining the cause and forecasting the results. The possibilities of the Geographic Information Systems (GIS) were used in this paper to analyse and visualise the process of lake disappearance in the Iława Lakeland Landscape Park. GIS technologies which primarily are used for gathering, storing, processing and presenting spatial data have been used to interpret changes in lakes coverage over a period of 100 years. The analysis were based on data bases and cartographic former maps such as hydrographic maps, attribute data and bathymetric plans. The data was gathered by transfer from different geoportals, next vectorised, and then preprocessed. Former maps were rectified. The lake disappearance process was presented in several forms: lake cards, animations and interactive map. Basing on the GIS analysis about lake disappearance in Iława Lakeland Landscape Park it was possible to state that lakes are disappearing in rate of 3.99 ha a−1.

Whenever disaster situations occur the civil protection authorities need to have fast access to data that may help to plan emergency response. To contribute to the collection and integration of all available data a platform that aims to harvest Volunteered Geographical Information (VGI) from social networks and collaborative projects was created. This enables the integration of VGI with data coming from other sources, such as data collected by physical sensors in real time and made available through Applications Programming Interface (APIs), as well as, for example, official maps. The architecture of the created platform is described and its first prototype presented. Some example queries are performed and the results are analyzed.

Consumers and institutional kitchens, as well as traders, have shown increasing interest towards local food. This is particularly due to the transparency and traceability characteristic of a short supply chain and social aspects related to food origins. The trend has been increasingly common during the past decade in Europe and North America, and it is strongly evident in the case area of this study in Northern Ostrobothnia, Finland. In general, ease of access to food is highly important for consumers and crucial for institutional kitchens, in addition to quality aspects and price. However, regardless of proximity, poor accessibility is one of the key issues preventing the further growth of local food markets. Due to scale economics in food value chain, food transport is presently organised mainly by centralised, large-scale logistics companies directed via hubs serving millions of consumers. Accordingly, production volumes required to enter large-scale markets are often unattainable for disjointed small-scale local food producers. In this study, geographic information system (GIS)-based accessibility analyses are applied for analysing potential for integral networking of local food production and transport companies. Berry production was selected as a case study because it has a relatively strong role in Northern Ostrobothnia, while its logistics are notably underdeveloped. Spatial data of primary production volumes consists of register records of farm-specific cultivation areas and average yields in Northern Ostrobothnia and Finland. Accessibility computations are based on the digital model of the Finnish road network, Digiroad. Two surveys were also implemented to farmers and food processing companies to seek views on food processing, sales, logistics and procurements regarding local food. Data from the surveys was used in accessibility analysis, which enables exploration of opportunities for establishing ‘local food’ clusters integrating small producers into a more effective and competitive network. Information about favourable conditions for cooperative networks in the local food sector may help in establishing companies and their growth. Again, successful networking may increase scale economies in local production in transport, processing and marketing.

Practices for reducing the impacts of floods are becoming more and more advanced, centered on communities and reaching out to vulnerable populations. Vulnerable individuals are characterized by social and economic attributes and by societal dynamics rooted in each community. These indicators can magnify the negative impacts of disasters together with the capacity of each individual to cope with these events. The Social Vulnerability Index (SoVI) provides an empirical basis to compare social differences in various spatial scenarios and for specific environmental hazards. This research shows the application of the SoVI to the floodplain of northern Italy, based on the use of 15 census variables. The chosen study area is of particular interest for the high occurrence of flood events coupled with a high level of human activity, landscape transformations, and an elevated concentration of assets and people. The analysis identified a positive spatial autocorrelation across the floodplain that translates into the spatial detection of vulnerable groups, those that are likely to suffer the most from floods. In a second stage, the output of the index was superimposed on the flood hazard map of the study area to analyze the resulting risk. The Piemonte and Veneto regions contain the main areas prone to flood “social” risk, highlighting the need for a cohesive management approach at all levels to recognize local capacities and increase communication, awareness, and preparedness to mitigate the undesirable effects of such events.

Since the introduction of geographic information systems (GIS) in the 1960s, it has evolved tremendously to an extent that it permeates our daily lives. Initially, GIS usage started in the developed countries and now increasingly filtered to developing countries. The town planning profession was one of the early adopters of GIS. Geospatial information is a useful source of data that is needed in urban planning. In these days of the New Urban Agenda 2030, smart cities are even more required from planners in using geospatial information to face urban challenges such as sustainable urban development and climate change. Although GIS has promised a lot for urban planning, it has not reached its full potential. Moreover, many studies have focused on developed countries with limited studies on geospatial information application in municipalities and GIS education from a perspective of developing countries. In this study, a survey on the usage of geospatial information science (GSIS) in two cities, namely Bulawayo in Zimbabwe and Ekurhuleni in South Africa, was conducted, and an overview of the state of GIS curricula in planning schools is discussed. The results indicate that considerable progress has been made in the application of geospatial information in municipal planning; however, there are impediments limiting the full utilization of geospatial information in local municipalities. These impediments include: inadequate GIS curricula in planning schools, lack of resources, and lack of political will. These challenges manifest differently in well-resourced municipalities and those with limited resources. The study proposes planning-relevant GIS curricula to improve the level of GIS use in planning practice.

Background This paper reports on a case study of the use of visualization of geospatial data that is distributed across data sets and requires integration over time and space to aid decision makers. Like many State Highway Agencies (SHAs) in the United States, the Texas Department of Transportation (TxDOT) is organized along the traditional functional lines of planning, design, construction, maintenance, and operations. It has historically relied on experience and longevity of its staff to efficiently and effectively plan its construction and maintenance projects. Although functional boundaries of maintenance and construction are fairly clearly defined, there tends to be some overlap in projects that can be executed by either of the functional groups. The department currently does not have a robust integrated information system for identifying potential planning conflicts between its construction and maintenance projects. This has led to suboptimal use of resources, including overlapping plans for maintenance and mobility enhancement projects. Case description With over 650 highway projects assigned across two functional groups within the district’s (TxDOT Fort Worth district) boundary, it is a challenging task to assemble a coherent plan for managing these projects over a multi-year planning period that is subject to external stakeholder input as well as shifting funding constraints. Temporal and spatial data needed for integrated planning resides in specialized information systems developed for the needs of individual functional groups. To address this challenge, this district decided to integrate and visualize data from individual information systems in a Geographic Information System (GIS). A GIS-based tool was developed to integrate, visualize, and analyze projects data from multiple information systems. Discussion and evaluation This paper documents the benefits associated with visualization and integration of projects data in a GIS to address planning challenges facing a typical highway agency. Among the lessons learned are the potential uses of GIS, which include detecting spatially and temporally overlapping projects, supporting integrated planning, and improving communication among functional groups within a state highway agency. Conclusion The study demonstrates that such spatial-temporal representations of project data can lead to early identification of potential overlaps during the planning phase. In a broader context, such geospatial visualization efforts can also form the basis for eliciting practitioners’ perspectives and knowledge input in the development of spatial decision support systems.

This article introduces and implements an interdisciplinary approach to the examination of historical text corpora. It presents a case study that combines corpus analysis, automated geoparsing and geographic information systems (GIS) to investigate the geographies associated with some of the key aesthetic terms historically used in writing about the English Lake District: a culturally prestigious region of lakes and mountains in northwest England. The basis of this investigation is a corpus of travel writing and topographical literature about the Lake District containing more than 1.5 million words. The corpus mainly consists of works from the eighteenth and nineteenth centuries. In investigating this corpus we identify and analyse a correspondence between eighteenth-century aesthetic theory and the use of the terms beautiful, picturesque, sublime and majestic in contemporaneous and later accounts of the Lakes region. Our analyses afford new insights into the historical use of these four aesthetic terms. Our findings, moreover, reveal how ephemeral publications, such as tourist guidebooks, helped to consolidate the application of the aesthetic principles and vocabulary formulated by canonical thinkers, including William Gilpin and Edmund Burke. In presenting this research, we demonstrate how a hybrid geographical and corpus-based methodology, which we call geographical text analysis, can advance the study of the connections between literature, aesthetics and physical geography.

The constantly growing process of the Earth Observation (EO) data and their heterogeneity require new systems and tools for effectively querying and understanding the available data archives. In this paper, we present a tool for heterogeneous geospatial data analytics. The system implements different web technologies in a multilayer server–client architecture, allowing the user to visually analyze satellite images, maps, and in-situ information. Specifically, the information managed is composed of EO multispectral and synthetic aperture radar products along with the multitemporal in-situ LUCAS surveys. The integration of these data provides a very useful information during the EO scene interpretation process. The system also offers interactive tools for the detection of optimal datasets for EO multitemporal image change detection, providing at the same time ground-truth points for both human and machine analyses. Furthermore, we show by means of visual analytic representations a way to analyze and understand the content and distribution of the EO databases.

Extreme weather events are increasingly affecting the climate of our planet and they cause natural disasters that are often dangerous to human life. Furthermore, the management of extreme events is very important and can be mitigated by artificial reservoirs, such as those existing in the region. From this point of view, the management of extreme events would become an opportunity for development linked to the production of energy through artificial reservoirs. The aim of this study is to assess the changes of these phenomena, in a small area of central Italy (Marche region), calculating 11 extreme precipitation indices from 1961 to 2017. The analysis shows an extremisation of rain events, with an increase in indices CDD, CWD and R99. However the innovativeness of this research lies in the spatialization of these extreme indices, through areal interpolations performed by GIS software. The territorial assessment of extreme precipitation events has revealed significant local countertrends, useful for hydrogeological protection, water resource management and energy production. Keywords: Extreme indices, Geographic information systems (GIS), Precipitation

Buildings in cities represent potential point sources of human excreta-derived nutrients, while agricultural land in (peri)urban areas demand nutrients as fertilizers. Here we present a new geographic information system (GIS)-based modelling tool, Resource Dynamo, that optimizes the allocation of excreta-derived nutrients from buildings in cities to nearby agricultural fields. The model minimizes the number of supply sites needed to match the demand by prioritizing sites with the highest nutrient supply, i.e. the hotspots. Furthermore the model delineates exact transport routes between the discrete supply and demand sites. The transport distances are minimized as transport costs are a key factor for economic viability of nutrient management. The high resolution of the model allows it to function as a decision-support tool for bringing cyclic nutrient management into practice. To disclose the potential of the model, we used it to match phosphorus supply in human-derived urine with phosphorus demands from agricultural fields within the municipality of Amsterdam on a temporal scale of 1 year.

In this study, we present a novel methodology that may be used to analyze tsunami risk along coastal regions. The application of the proposed methodology is demonstrated for the Eastern Mediterranean coast. Economic, social and environmental dimensions of risk are calculated and aggregated to obtain the overall risk maps for a number of elements at risk (EaR) that are identified from seven countries located along the Eastern Mediterranean coastline. Historical earthquakes that are recorded in the region during the period 1900–2013 are used as data, and probabilistic tsunami modeling is carried out using Monte Carlo analysis. Based on historical data, randomly generated earthquakes are simulated, and wave propagation analysis is performed using NAMI-DANCE software. Inundation depth–damage analysis and exceedance probabilities of tsunami inundations are used to evaluate social and economic risks while the environmental risk is calculated using a binary approach. The overall risk map is constructed in the geographic information system environment. Cairo Agricultural Area in Egypt and Fethiye City in Turkey are identified as high-risk EaR in the Eastern Mediterranean coastline. The new risk assessment methodology may be utilized in coastal regions of the world, and the results obtained for the Eastern Mediterranean may be effectively used in developing preventive measures and disaster management strategies for tsunamis that may develop the region.

Oceans are changing faster than even observed before. Unprecedented climate variability is interacting with long-term trends, all against a backdrop of rising anthropogenic use of marine space. The growth of maritime activities is taking place without the full understanding of complex interactions between natural and human-induced changes, leading to a progressive decline of biodiversity and degradation of marine ecosystems. Against this complex interplay, marine managers and policy makers are increasingly calling for new approaches and tools allowing a multi-scenario assessment of environmental impacts arising from the complex interaction between natural and anthropogenic drivers, also in consideration of multiple marine plans objectives. Responding to this need, for the Adriatic Sea we developed a GIS-based Bayesian Network to evaluate the probability (and related uncertainty) of cumulative impacts under four ‘what-if’ scenarios representing different marine management options and climate conditions. We addressed issues concerning consequences of potential planning measures, as well as management programmes required to achieve environmental status targets, as required by relevant EU acquis. Results from the scenario analysis highlighted that an integrated approach to maritime spatial planning is required, combining more sustainable management options of marine spaces and resources with climate adaptation strategies. This approach to planning would allow to reduce human pressures on the marine environment and rise resilience of natural ecosystems to climate and human-induced disturbances, which would result in an overall decrease of cumulative impacts.

WOS: 000511528400050, This study is based on an area in Hatay, Turkey, and involves examining all weather and climate-related data that can be used to determine its suitability for the bioclimatic comfort. It attempts to explain bioclimatic comfort and describes in detail all the variables that make this contemporary concept and why it is important from a landscape architecture planning point of view. According to Koppen climate classification, the general climate character of the study area is classified as medium-altitude, warm summer, and climate type with mild or winters with Csa-Csb letters. As the area is very large in terms of total area, the findings were different across the whole area; which means that some parts were bioclimatic-comfort-friendly and other parts were not to varying degrees. June is the month in which suitable areas cover the province's largest area. Because temperatures have reached a suitable level in terms of climatic comfort, humidity and wind speed have increased. In climatic map result, it shows that Hatay is the highest region area with high altitudes of regions in the center. The examination for thermal comfort took place for months. Hatay's results show that it serves as a helper in future planning of landscape: planning that brings the comfort of bioclimatic to the level of highest and that helps determine new region settlement in Hatay. The study finally proposes that it paves the way for future researches and studies to ultimately standardize bioclimatic comfort in landscape architecture and urban planning that allows achieving the optimal planning objectives in all aspects.

Modern science is going through a period of important reflection on the role of different agents and multiple disciplines in the management and safeguarding of architectural heritage. This new focus generates a greater amount and diversity of information, so the implementation of a unifying tool in the framework of digital information models would mean a better knowledge of cultural heritage as well as aiding its safeguarding and protection. In addition, it must be taken into account that, for the correct management of information in its broadest dimension, this tool must make it possible to relate alphanumeric data about an item of heritage to its spatial location. In this sense, this article proposes a Heritage Information System (HIS)&mdash, understood as a digital knowledge tool&mdash, that consists of a relational database and a map manager with Geographic Information System (GIS) technology (a geodatabase). The methodology suggested here sets out the steps that make up the HIS, so that the system can be applied to other geographical elements or realities. For this reason, a study was made of &ldquo, La Cultura del Agua&rdquo, in Valverde de Burguillos (Spain), a heritage ensemble that consists of rural architecture and dispersed preindustrial elements, which are currently at risk. The HIS seeks to develop a more complete identification of these elements (individually and as a system) and a justified argument for their being given value and great visibility. This new approach encourages sustainable development in terms of efficiency and effectiveness for the analysis, diagnosis, and reactivation of cultural heritage, always placing importance on the balance of social participation with the territory in which the system is applied, and with global society.

The paper explores the use of a “digital twin model” applied to the case study of a residential district, and organized as a three-dimensional data system able to participate to the intelligent optimization and automation of the energy management and efficiency of the building system. The case study focuses on the area called Rinascimento III in Rome, consisting of 16 eight-floor building hosting 216 apartment units with an overall percentage of self-renewable energy produced by the building complex equal to 70%. This already quite high percentage means that the building complex can be defined as a Near Zero Energy Building (NZEB), i.e. a building that has a very high energy performance, and the nearly-zero or very low amount of energy required should be covered to a very significant extent by energy from renewable sources, including energy from renewable source produced on-site or nearby.

Across the United States, there has been a growing interest in local food production, which provides an alternative way to increase self-sufficiency and support greater well-being and food security at the community level. This study focused on the Northern Panhandle region of Idaho, where opportunities derived from the local food movement have emerged in several resort and college towns. This research integrated spatial analysis and modeling in a geographic information system (GIS) environment and a linear-programming (LP) optimization approach to identify, quantify, and map these potential opportunities. The obtained results show that existing local food producers are located in the urban fringe and on productive cropland. The foodshed model further suggests that Northern Idaho has enough farmland to feed its whole population within an average distance of 49 km or 31 miles. An alternative land use scenario was explored that involves removing marginal cropland with high soil erodibility from commodity cropping to improve the ecological benefits of local food production. The results of the study, including nuanced evidence of growing demand for local-food products, the existence of enough cropland capacity to meet demand, and potential environmental benefits, are quite encouraging to local food advocates in Northern Idaho and other areas and demonstrate the utility of land-based foodshed analysis.

This paper presents a GIS methodological approach for mapping forest landscape multifunctionality. The aims of the present study were: (1) to integrate and prioritize production and protection functions by multicriteria spatial analysis using the Analytic Hierarchy Process (AHP); and (2) to produce a multifunctionality map (e.g., production, protection, conservation and recreation) for a forest management unit. For this, a study area in inner Portugal occupied by forest and with an important protection area was selected. Based on maps for functions identified in the study area, it was possible to improve the scenic value and the biodiversity of the landscape to mitigate fire hazard and to diversify goods and services. The developed methodology is a key tool for producing maps for decision making support in integrated landscape planning and forest management.

In 2000, the United Nations established eight Millennium Development Goals (MDG) to combat worldwide poverty, disease, and lack of primary education. Goal number five aimed to reduce the maternal mortality ratio by three quarters and provide universal access to reproductive healthcare services by 2015. While there has been some progress, MDG 5 fell far short of target goals, highlighting the necessity of further improvement in global maternal health. Using Geographic Information Systems (GIS), this study aims to understand how distance to facility and quality of care, which are components of access, affect maternal service utilization in two of the world’s poorest countries, Haiti and Kenya. Furthermore, this study examines how this relationship may change or hold between urban and rural regions. Data from the United States Agency for International Development Demographic and Health Survey and Service Provision Assessment were linked spatially in a GIS model, drawing comparisons among distance to facility, quality of care, and maternal health service utilization. Results show that in both rural and urban regions, access to maternal health service and maternal health service utilization share a similar spatial pattern. In urban regions, pockets of maternal health disparities exist despite close distance to facility and standard quality of care. In rural regions, there are areas with long distances to facilities and low quality of care, resulting in poor maternal service usage. This study highlights the usefulness of GIS as a tool to evaluate disparities in maternal healthcare provision and usage.

Modern technological advances and trends require new pedagogy and delivery of mapping materials to prepare the future workforce in the disciplines of Science, Technology, Engineering, and Mathematics (STEM) for an increasingly technology-dominated society. The purpose of this study was to develop an Environmental Systems Research Institute (ESRI) Story Map &ldquo, Soil Forming Factors: Climate&rdquo, for multiple STEM disciplines based on the design guidelines from the Cognitive Theory of Multimedia Learning (CTML). The study incorporated a two-group post-test only design that utilized multiple methods of analysis, including a quality assessment of the ESRI Story Map using the five principles of effective storytelling, direct quantitative measures of learning (quiz), and surveys of participants&rsquo, perceptions (PowerPoint presentation versus ESRI Story Map) using QualtricsTM. Survey results were summarized by gender, academic classification (year), and academic major program. The newly developed ESRI Story Map was an effective teaching tool as demonstrated by quiz scores and students&rsquo, positive responses. Post-testing scores indicated that ESRI Story Maps were an effective way to learn and were viewed as effective as traditional teaching methods (e.g., PowerPoint). Additionally, students reported feeling comfortable using ESRI Story Maps. These positive responses were consistent by gender, major, and academic classification (year). This research indicates that adding audio may improve the use of this ESRI Story Map for educational concept delivery. Empirical studies such as this that include multifaceted quantitative and qualitative assessments are critical to understanding the benefits of new types of multimedia learning in an educational setting.

This paper presents an update on some of the activities that have taken place since a World Bank report; “Guidelines for Education and Training in Environmental Information Systems in Sub-Saharan Africa: Some Key Issues” was published and provides details on the current situation. It shows how organizations such as the African Association on Remote Sensing of Environment, International Society of Photogrammetry and Remote Sensing, European Association of Remote Sensing Companies, Group on Earth Observation, and several others have helped to increase manpower resources in the region and strengthened institutional capacity in the field of geoinformatics, through capacity building, technology transfer, international cooperation and the provision of internal African resources. After reviewing what has happened in the field of geoinformatics education and training, we focused on current initiatives taken and challenges in five Sub-Saharan countries: Ethiopia, Nigeria, South Africa, Tanzania, and Zimbabwe. We reviewed GIS education and training in the private sector, government, information communications technology in higher education institutions, GIS application areas and challenges facing GIS education and training. Findings show that; change should involve education stakeholders in all levels of education and curriculum quality, regional and international cooperation through exchange programs, should be a priority for Sub-Saharan Africa countries.

Core samples obtained from scientific drilling could provide large volumes of direct microstructural and compositional data, but generating results via the traditional treatment of such data is often time-consuming and inefficient. Unifying microstructural data within a spatially referenced Geographic Information System (GIS) environment provides an opportunity to readily locate, visualize, correlate, and apply remote sensing techniques to the data. Using 26 core billet samples from the San Andreas Fault Observatory at Depth (SAFOD), this study developed GIS-based procedures for: 1. Spatially referenced visualization and storage of various microstructural data from core billets, 2. 3D modeling of billets and thin section positions within each billet, which serve as a digital record after irreversible fragmentation of the physical billets, and 3. Vector feature creation and unsupervised classification of a multi-generation calcite vein network from cathodluminescence (CL) imagery. Building on existing work which is predominantly limited to the 2D space of single thin sections, our results indicate that a GIS can facilitate spatial treatment of data even at centimeter to nanometer scales, but also revealed challenges involving intensive 3D representations and complex matrix transformations required to create geographically translated forms of the within-billet coordinate systems, which are suggested for consideration in future studies.

This study uses geographic information systems (GIS) and geographical detector techniques to explore the national and regional pattern of the spatial distribution of China’s ski resorts, and quantitatively identifies the main factors that influence their location. Results show that although China’s ski areas are geographically clustered, ski resorts are more likely to be located at high latitudes (northeast and northwest China) than at low latitudes (central and south China). Among the most influential factors are the winter sporting mega-events that explain 70% of the location of China’s ski areas, the 2022 Winter Olympics accounted for 14%. The main factors that contribute to the distribution of ski areas depend on the regions and types of ski resorts. Implications for the ski resorts industry, such as the different practice for hot and cold spot areas of China’s ski resorts, and the future development direction of ski industry, are discussed.

Objective of research: The target of the paper is to develop a model of GIS-based risk monitoring of zoonotic cestodiasis in human. Materials and methods: The use of geographic information systems (GIS) as an epizootiological and epidemiological method for the risk-based monitoring of human cestodiasis enables the development of a multi-level platform for solution of a wide range of tasks related to the control of this disease. The modern GIS tools use the methods of geoinformatics applying powerful software and hardware: open access geographic web servers, tools for multidimensional complex analysis, creating most accurate electronic and paper maps. Full-featured GIS contain a full set for processing geospatial data including acquisition of data, its integration and storage, automatic data processing, editing, creation and maintenance of topology, spatial analysis, access to the database management system (DBMS), visualization and creation of hard copies of any cartographic data. Results and discussion: The use of GIS enables to study more closely the regularities of epizootic process, geography of human cestodiasis and to improve the methodology both for short-term and long-term retrospective epizootiological analyses.

Geographic information systems (GIS) and their tools support the process of real estate trading. Of key importance is the ability to visualise information about real estate in the form of maps of average real estate transaction prices. The following study presents a methodology for mapping average real estate transaction prices using GIS. The map development process comprised three main stages. In the first stage, the input data was processed and statistically analysed. Official data came from the Register of Real Estate Prices and Values, and open data from the National Register of Boundaries. The second stage involved the visualization of the data in the form of maps of average apartment prices using the cartographic methods of choropleth maps and diagrams. The commercial tool ArcMap 10.3 and the free Quantum GIS software were used in the design of the maps of average real estate transaction prices, to check the options for using these types of programs. As a result, eight maps were designed presenting the average transaction prices for residential properties in the Warsaw district of Ursynów in 2015. The final stage was the analysis of the designed maps. The influence of the selection of the reference units on the visualization content, and the impact of combining cartographic presentation methods on the complexity of the presentation of real estate information, were also analysed.

Research on the geography of Complementary and Alternative Medicine (CAM) is emerging; yet, assessing function at CAM locations remains novel. This paper uses nearest neighbor analysis, closest facilities analysis and point density tools, within the Geographic Information Systems (GIS) environment, to compare the geographies of single, multiple and high-density function locations in 14 intermediately sized centers in the Canadian province of Ontario. Based on a sample of 2,326 CAM functions, 72.9% are concentrated in space and are situated: inside the same neighborhood, at the same address and/or ‘within’ the same CAM provider. Deductively, these clustering benefits, or agglomeration economies, accrue to both CAM practitioners and CAM patients. There is deviation by region, as northern residents travel further to CAM function (more than 6.3 kilometers) compared to those in the south (typically less than 4.0 kilometers). Spatial properties by CAM type show distinctiveness with massage therapy functions more likely to be outside, and naturopathic services within, CAM function concentrations and chiropractic, acupuncture and homeopathic functions intermediate by comparison.

Several decision support systems were developed in recent years to encourage climate adaptation planning in coastal areas, especially at a national to global scale. However, few prototypes are easy to use and accessible for decision-makers to evaluate and manage risks locally. DESYCO is a GIS based decision support system specifically designed to better understand the risks that climate change poses at the regional/subnational scale (e.g. the effect of sea level rise and coastal erosion on human assets and ecosystems) and set the context of strategic adaptation planning within Integrated Coastal Zone Management. It implements a Regional Risk Assessment (RRA) methodology allowing the spatial assessment of multiple climate change impacts in coastal areas and the ranking of key elements at risk (beaches, wetlands, protected areas, urban and agricultural areas). The core of the system is a Multi-Criteria Decision Analysis (MCDA) model used to operationalize the steps of the RRA (hazard, exposure, susceptibility, risk and damage assessment) by integrating a blend of information from climate scenarios (global/regional climate projections and hydrodynamic/hydrological simulations) and from non-climate vulnerability factors (physical, environmental and socio-economic features of the analysed system). User-friendly interfaces simplify the interaction with the system, providing guidance for risk mapping, results communication and understanding. DESYCO was applied to low-lying coastal plains and islands (the North Adriatic Sea, the Gulf of Gabes and the Republic of Mauritius), river basins and groundwater systems (Upper Plain of Veneto and Friuli-Venezia Giulia, Marche Region). The paper presents the RRA methodology, the structure of DESYCO and its software architecture, showing the capabilities of the tool to support decision making and climate proofing in a wide range of situations (e.g. shoreline planning, land use and water resource management, flood risk reduction).

New data sources that I characterize as “bigger data” can offer insight into the causes and consequences of socio-environmental conflicts, especially in the mining and extractive sectors, improving the accuracy and generalizability of findings. This article considers several contemporary methods for generating, compiling, and structuring data including geographic information system (GIS) data, and protest event analysis (PEA). Methodologies based on the use of bigger data and quantitative methods can complement, challenge, and even substitute for findings from the qualitative literature. A review of the literature shows that a particularly promising approach is to combine multiple sources of data to analyze complex problems. Moreover, such approaches permit the researcher to conduct methodologically rigorous desk-based research that is suited to areas with difficult field conditions or restricted access, and is especially relevant in a pandemic and post-pandemic context in which the ability to conduct field research is constrained.

The present study aimed to describe the utilization of Information and Communication Technology (ICT) as a digital infrastructure concerning disaster countermeasures in Japan. Specifically, the study introduced development cases of the systems integrating social media and Geographic Information Systems (GIS), and presented the utilization potential as a digital infrastructure. Additionally, taking up Twitter as a familiar digital infrastructure, the study also presented its utilization potential based on the case of the heavy-rain disaster in Western Japan in 2018. As a result, due to the close relationship between the reality and virtual spaces, the issue is how to make the information circulating in the virtual space efficiently and effectively aid in the rescue and support activities in the reality space. The above systems are effective in order to solve such an issue, because these can efficiently consolidate the essential information on the digital map of Web-GIS. Additionally, it is necessary to set rules for the utilization of social media, and sift through information and share only the necessary information to the affected local governments and those involved in the rescue and support activities. Furthermore, various information communication methods including verbal calls in addition to ICT are necessary especially for people who are vulnerable to information.

The need for improvement of societal disaster resilience and response efforts was evident after the destruction caused by the 2017 Atlantic hurricane season. We present a novel conceptual framework for improving disaster resilience through the combination of serious games, geographic information systems (GIS), spatial thinking, and disaster resilience. Our framework is implemented via Project Lily Pad, a serious geogame based on our conceptual framework, serious game case studies, interviews and real-life experiences from 2017 Hurricane Harvey survivors in Dickinson, TX, and an immersive hurricane-induced flooding scenario. The game teaches a four-fold set of skills relevant to spatial thinking and disaster resilience, including reading a map, navigating an environment, coding verbal instructions, and determining best practices in a disaster situation. Results of evaluation of the four skills via Project Lily Pad through a &ldquo, think aloud&rdquo, study conducted by both emergency management novices and professionals revealed that the game encouraged players to think spatially, can help build awareness for disaster response scenarios, and has potential for real-life use by emergency management professionals. It can be concluded from our results that the combination of serious games, geographic information systems (GIS), spatial thinking, and disaster resilience, as implemented via Project Lily Pad and our evaluation results, demonstrated the wide range of possibilities for using serious geogames to improve disaster resilience spatial thinking and potentially save lives when disasters occur.