Estimation of Gaussian process regression model using probability distance measures

A new class of parameter estimation algorithms is introduced for Gaussian process regression (GPR) models. It is shown that the integration of the GPR model with probability distance measures of (i) the integrated square error and (ii) Kullback–Leibler (K–L) divergence are analytically tractable. An efficient coordinate descent algorithm is proposed to iteratively estimate the kernel width using golden section search which includes a fast gradient descent algorithm as an inner loop to estimate the noise variance. Numerical examples are included to demonstrate the effectiveness of the new identification approaches.

The persistence of distance: a gravity model of European cross-border real estate development flows

Purpose – This paper aims to investigate the scale and drivers of cross-border real estate development in Western Europe and Central and Eastern Europe. Design/methodology/approach – Placing cross-border real estate development within the framework of foreign direct investment (FDI), conceptual complexities in characterizing the notional real estate developer are emphasized. Drawing upon a transaction database, this paper proxies cross-border real estate development flows with asset sales by developers. Findings – Much higher levels of market penetration by international real estate developers are found in the less mature markets of Central and Eastern Europe. Analysis suggests a complex range of determinants with physical distance remaining a consistent barrier to cross-border development flows. Originality/value – This analysis adds significant value in terms of understanding cross-border real estate development flows. In this study, a detailed examination of the issues based on a rigorous empirical analysis through gravity modelling is offered. The gravity framework is one of the most confirmed empirical regularities in international economics and commonly applied to trade, FDI, migration, foreign portfolio investment inter alia. This paper assesses the extent to which it provides useful insights into the pattern of cross-border real estate development flows.

Working memory, reading ability and the effects of distance and typicality on anaphor resolution in children

We investigated the time course of anaphor resolution in children and whether this is modulated by individual differences in working memory and reading skill. The eye movements of 30 children (10-11 years) were monitored as they read short paragraphs in which (i) the semantic typicality of an antecedent and (ii) its distance in relation to an anaphor, were orthogonally manipulated. Children showed effects of distance and typicality on the anaphor itself, and also on the word to the right of the anaphor, suggesting that anaphoric processing begins immediately but continues after the eyes have left the anaphor. Furthermore, children showed no evidence of resolving anaphors in the most difficult condition (distant atypical antecedent), suggesting that anaphoric processing that is demanding may not occur online in children of this age. Finally, working memory capacity and reading comprehension skill affect the magnitude and time course of typicality and distance effects during anaphoric processing.

How remote are R&D labs? Distance factors and international innovative activities

This paper shows that value creation by multinational enterprises (MNEs) is the result of activities where geographic distance effects can be overcome. We submit that geographic distance has a relatively low impact on international research and development (R&D) investments, owing to the spiky nature of innovation, and to the unique ability of MNEs to absorb and transfer knowledge on a global scale. On the one hand, MNEs need to set up their labs as close as possible to specialized technology clusters where valuable knowledge is concentrated, largely regardless of distance from their home base. On the other, MNEs have historically developed technical and organizational competencies that enable them to transfer knowledge within their internal networks and across technology clusters at relatively low cost. Using data on R&D and manufacturing investments of 6320 firms in 59 countries, we find that geographic distance has a lower negative impact on the probability of setting up R&D than manufacturing plants. Furthermore, once measures of institutional proximity are accounted for, MNEs are equally likely to set up R&D labs in nearby or in more remote locations. This result is driven by MNEs based in Triad countries, whereas for non-Triad MNEs the effect of geographic distance on cross-border R&D is negative and significant.

Datasets related to in-land water for limnology and remote sensing applications: distance-to-land, distance-to-water, water-body identifier and lake-centre co-ordinates

Datasets containing information to locate and identify water bodies have been generated from data locating static-water-bodies with resolution of about 300 m (1/360 deg) recently released by the Land Cover Climate Change Initiative (LC CCI) of the European Space Agency. The LC CCI water-bodies dataset has been obtained from multi-temporal metrics based on time series of the backscattered intensity recorded by ASAR on Envisat between 2005 and 2010. The new derived datasets provide coherently: distance to land, distance to water, water-body identifiers and lake-centre locations. The water-body identifier dataset locates the water bodies assigning the identifiers of the Global Lakes and Wetlands Database (GLWD), and lake centres are defined for in-land waters for which GLWD IDs were determined. The new datasets therefore link recent lake/reservoir/wetlands extent to the GLWD, together with a set of coordinates which locates unambiguously the water bodies in the database. Information on distance-to-land for each water cell and the distance-to-water for each land cell has many potential applications in remote sensing, where the applicability of geophysical retrieval algorithms may be affected by the presence of water or land within a satellite field of view (image pixel). During the generation and validation of the datasets some limitations of the GLWD database and of the LC CCI water-bodies mask have been found. Some examples of the inaccuracies/limitations are presented and discussed. Temporal change in water-body extent is common. Future versions of the LC CCI dataset are planned to represent temporal variation, and this will permit these derived datasets to be updated.

Anticipating future risk in social-ecological systems using fuzzy cognitive mapping: the case of wildfire in the Chiquitania, Bolivia

Understanding complex social-ecological systems, and anticipating how they may respond to rapid change, requires an approach that incorporates environmental, social, economic, and policy factors, usually in a context of fragmented data availability. We employed fuzzy cognitive mapping (FCM) to integrate these factors in the assessment of future wildfire risk in the Chiquitania region, Bolivia. In this region, dealing with wildfires is becoming increasingly challenging due to reinforcing feedbacks between multiple drivers. We conducted semi-structured interviews and constructed different FCMs in focus groups to understand the regional dynamics of wildfire from diverse perspectives. We used FCM modelling to evaluate possible adaptation scenarios in the context of future drier climatic conditions. Scenarios also considered possible failure to respond in time to the emergent risk. This approach proved of great potential to support decision-making for risk management. It helped identify key forcing variables and generate insights into potential risks and trade-offs of different strategies. All scenarios showed increased wildfire risk in the event of more droughts. The ‘Hands-off’ scenario resulted in amplified impacts driven by intensifying trends, affecting particularly the agricultural production. The ‘Fire management’ scenario, which adopted a bottom-up approach to improve controlled burning, showed less trade-offs between wildfire risk reduction and production compared to the ‘Fire suppression’ scenario. Findings highlighted the importance of considering strategies that involve all actors who use fire, and the need to nest these strategies for a more systemic approach to manage wildfire risk. The FCM model could be used as a decision-support tool and serve as a ‘boundary object’ to facilitate collaboration and integration of different forms of knowledge and perceptions of fire in the region. This approach has also the potential to support decisions in other dynamic frontier landscapes around the world that are facing increased risk of large wildfires.