Ourania Kounadi

• Dr.rer.nat
• Professor (Assistant) at University of Vienna

The present study compares the performance of three different supervised machine learning methods, namely an Ensemble Neural Network algorithm (ENN), a Random Forest algorithm (RF), and a K-Nearest Neighbor algorithm (KNN), in predicting residential burglary hot spots across different cities in Europe, i.e., Brussels, Vienna and London. Crime and c...

This study delineates transaction price submarkets of dwellings in Vienna by performing spatiotemporal clustering and analysing the change in purchasing prices in these clusters between 2018 and 2022. The submarkets are created using a novel spatiotemporal clustering method referred to as Multidimensional Spatiotemporal Change–DBSCAN (MDSTC-DBSCAN)...

This study addresses the challenge of incorporating spatial heterogeneity in predictive modeling by introducing regionalization methods in the preprocessing step of the modeling workflow. Spatial heterogeneity, where the mean of attribute values varies across spatial units, poses difficulties for traditional models. To tackle this, we propose a nov...

Concerns about data privacy are omnipresent, given the increasing usage of digital applications and their underlying business model that includes selling user data. Location data is particularly sensitive since they allow us to infer activity patterns and interests of users, e.g., by categorizing visited locations based on nearby points of interest...

This study tests the law of crime concentration at place in Brussels Capital Region (approx. 1.2 million inhabitants) and examines the spatial stability of crime concentrations by applying Andresen’s Spatial Point Pattern Test. Besides testing the law of crime concentration city-wide, this study also tests the law of crime concentration in the cont...

Applications of machine-learning-based approaches in the geosciences have witnessed a substantial increase over the past few years. Here we present an approach that accounts for spatial autocorrelation by introducing spatial features to the models. In particular, we explore two types of spatial features, namely spatial lag and eigenvector spatial f...

The European Union (EU) Commission’s whitepaper on Artificial Intelligence (AI) proposes shaping the emerging AI market so that it better reflects common European values. It is a master plan that builds upon the EU AI High-Level Expert Group guidelines. This article reviews the masterplan, from a culture cycle perspective, to reflect on its potenti...

Geomasks assure the protection of individuals in a discrete spatial point data set by aggregating, transferring or altering original points. This study develops an alternative approach, referred to as Adaptive Voronoi Masking (AVM), which is based on the concepts of Adaptive Aerial Elimination (AAE) and Voronoi Masking (VM). It considers the underl...

Geographies of crime are based on the spatial concept that combines social, natural, and environmental sciences. Geographic information systems crime analysts are highly sought after by law enforcement agencies from the local to the international level around the globe. Positive spatial autocorrelation (SA) is an arrangement where crime locations w...

Evidence exists that people’s perception of crime is not often consistent with the actual incidents statistics, and there is a tendency of underestimating or overestimating safety. We examine a phenomenon called the crime perception gap via participatory geographical information derived from sketch maps. The study area is Budapest, Hungary for whic...

Background: Predictive policing and crime analytics with a spatiotemporal focus get increasing attention among a variety of scientific communities and are already being implemented as effective policing tools. The goal of this paper is to provide an overview and evaluation of the state of the art in spatial crime forecasting focusing on study desi...

Digital Earth scholars have recently argued for a code of ethics to protect individuals’ location privacy and human dignity. In this chapter, we contribute to the debate in two ways. First, we focus on (geo)privacy because information about an individual’s location is substantially different from other personal information. The compound word (geo)p...

The General Data Protection Regulation (GDPR) protects the personal data of natural persons and at the same time allows the free movement of such data within the European Union (EU). Hailed as majestic by admirers and dismissed as protectionist by critics, the Regulation is expected to have a profound impact around the world, including in the Afric...

Inference attacks and protection measures are two sides of the same coin. Although the former aims to reveal information while the latter aims to hide it, they both increase awareness regarding the risks and threats from social media apps. On the one hand, inference attack studies explore the types of personal information that can be revealed and t...

In this paper we forecast hotspots of street crime in Portland, Oregon. Our approach uses geosocial media posts, which define the predictors in geographically weighted regression (GWR) models. We use two predictors that are both derived from Twitter data. The first one is the population at risk of being victim of street crime. The second one is the...

Participatory sensing applications collect personal data of monitored subjects along with their spatial or spatiotemporal stamps. The attributes of a monitored subject can be private, sensitive, or confidential information. Also, the spatial or spatiotemporal attributes are prone to inferential disclosure of private information. Although there is e...

The most prominent law in geography is Tobler’s first law (TFL) of geography, which states that “everything is related to everything else, but near things are more related than distant things.” No other law in geography has received more attention than TFL. It is important because many spatial statistical methods have been developed since its publi...

This paper proposes an approach towards practical privacy guidelines for the different stages of a research effort that collects and/or uses "sensitive" spatial data. Specifically, we focus on: a) initial tasks as prior to starting a survey, b) storing, anonymization, and assessment of da-tasets, and c) actions to eliminate disclosure from publishe...

Population at risk of crime varies due to the characteristics of a population as well as the crime generator and attractor places where crime is located. This establishes different crime opportunities for different crimes. However, there are very few efforts of modeling structures that derive spatiotemporal population models to allow accurate asses...

Geographical masking is the conventional solution to protect the privacy of individuals involved in confidential spatial point datasets. The masking process displaces confidential locations to protect individual privacy while maintaining a fine level of spatial resolution. The adaptive form of this process aims to further minimize the displacement...

Geographical masks are a group of location protection methods for the dissemination and publication of confidential and sensitive information, such as health- and crime-related geo-referenced data. The use of such masks ensures that privacy is protected for the individuals involved in the datasets. Nevertheless, the protection process introduces sp...

Crime is an ubiquitous part of society. The way people express their concerns about crimes has been of particular interest to the scientific community. Over time, the numbers and kinds of available communication channels have increased. Today, social media services, such Twitter, present a convenient way to express opinions and concerns about crime...

Advances in Geographic Information Science (GISc) and the increasing availability of location data have facilitated the dissemination of crime data and the abundance of crime mapping websites. However, data holders acknowledge that when releasing sensitive crime data there is a risk of compromising the victims' privacy. Hence, protection methodolog...

We examined published maps containing sensitive data, and the protection methods, if any, that were used. We investigated whether the many published warnings about disclosure risk have been effective in reducing privacy risk. During an 8-year period (2005-2012), 19 journals related to GIScience, geography, spatial crime analysis, and health geograp...

Public media such as TV or newspapers, paired with crime statistics from the authority, raise awareness of crimes within society. However, in today's digital society, other sources rapidly gain importance as well. The Internet and social networks act heavily as information distribution platforms. Therefore, this paper aims at exploring the influenc...

The Web 2.0 technology introduced dynamic web mapping, which in turn has dramatically changed the distribution and use of geographical information in our society. Some of the many advantages of online mapping include the fast information dissemination to the public, the interactivity between the users and the map interface, as well as the frequent...

http://www.tandfonline.com/loi/tcag20

Reverse geocoding is defined as the extraction of textual information, such as a name or an address, from geographic coordinates. This technique is common in many geo-application scenarios, e.g., in freely available online-based mapping services. However, if personal data are mapped, confidentiality issues may arise, such as if the data are derived...

Performance efficiency versus privacy protection in reverse geocoding services