Climate change and infectious diseases: Can we meet the needs for better prediction?

The next generation of climate-driven, disease prediction models will most likely require a mechanistically based, dynamical framework that parameterizes key processes at a variety of locations. Over the next two decades, consensus climate predictions make it possible to produce forecasts for a number of important infectious diseases that are largely independent of the uncertainty of longer-term emissions scenarios. In particular, the role of climate in the modulation of seasonal disease transmission needs to be unravelled from the complex dynamics resulting from the interaction of transmission with herd immunity and intervention measures that depend upon previous burdens of infection. Progress is also needed to solve the mismatch between climate projections and disease projections at the scale of public health interventions. In the time horizon of seasons to years, early warning systems should benefit from current developments on multi-model ensemble climate prediction systems, particularly in areas where high skill levels of climate models coincide with regions where large epidemics take place. A better understanding of the role of climate extremes on infectious diseases is urgently needed.     

Venomous snakes and climate change: ophidism as a dynamic problem

Snakebite envenoming is an important public health problem worldwide and addressing this issue has turned into a challenge for applied science. In this sense, the study of the distributional patterns of problematic snakes is central in terms of public health. Global Climate Change is affecting the distributional ranges of snakes, so that decisions regarding treatment of ophidism (poisoning by snake venom) may also change spatially and/or temporally. Here, we assessed suitable climate spaces at present conditions and estimated potential future changes in the distributions of the five southernmost venomous snakes, responsible for almost 99 % of accidents in Argentina, by implementing an ensemble of forecasts between different algorithms and scenarios for 2030 and 2080. Present suitable climate spaces showed high concordance with known distribution of the species. Future projections show moderate “north to south” displacements of the snakes’ suitable climate spaces, implying potential increments of suitable spaces in human populated areas in Argentina. Our results suggest the necessity of considering ophidism as a dynamic problem. In this regard, the analyses implemented here are useful tools in improving the assessment of snakebite envenoming in light of global climate change.     

Testing the stereoscopic precision of a large-format digital camera

The use of large-format digital cameras in aerial photogrammetry is leading to great improvements in photogrammetric production. Since they were first introduced about 10 years ago, the technological community has been testing and investigating the conditions under which this major change can be consolidated. But a certain (and understandable) bias may be noticed in the efforts that developers, researchers and clients are undertaking. Almost all of the efforts aim at checking the quality of automated measurements and very little attention has been directed to stereoscopic measurements by human operators, which, nevertheless, still represent an important task that needs to be carried out in the production chain. This paper presents the results from a number of tests (13 operators from a variety of enterprises) performed to check the stereoscopic precision of Vexcel UltraCamD camera images compared with Leica RC30 film images. The main conclusion to be drawn from the empirical data is that stereoscopic precision does not depend on the type of camera.     

Automatic estimation of olive tree dendrometric parameters based on airborne laser scanning data using alpha-shape and principal component analysis

The aim of this study is to present an automatic approach for olive tree dendrometric parameter estimation from airborne laser scanning (ALS) data. The proposed method is based on a unique combination of the alpha-shape algorithm applied to normalized point cloud and principal component analysis. A key issue of the alpha-shape algorithm is to define the α parameter, as it directly affects the crown delineation results. We propose to adjust this parameter based on a group of representative trees in an orchard for which the classical field measurements were performed. The best value of the α parameter is one whose correlation coefficient of dendrometric parameters between field measurements and estimated values is the highest. We determined crown diameters as principal components of ALS points representing a delineated crown. The method was applied to a test area of an olive orchard in Spain. The tree dendrometric parameters estimated from ALS data were compared with field measurements to assess the quality of the developed approach. We found the method to be equally good or even superior to previously investigated semi-automatic methods. The average error is 19% for tree height, 53% for crown base height, and 13% and 9% for the length of the longer diameter and perpendicular diameter, respectively.     

Quantifying the building stock from optical high-resolution satellite imagery for assessing disaster risk

This study uses high-resolution (HR) satellite imagery to quantify the stock of buildings, referred herein as building stock. The risk assessment requires information on the natural hazards and on the element at risk, that is the building stock in this article. This study combines (1) texture-based image processing to map built-up areas, (2) statistical sampling that allows locating the building samples and (3) photo-interpretation to encoding building footprints. Statistical inference is then used to quantify the building stock per class of building size. Legaspi in the Philippines is used as a case study. The results show that texture-based computer algorithms provide accurate area estimations of the built-up, that the detail of HR imagery allows the mapping of single buildings using photo-interpretation, and that a systematic sampling approach that uses building encoding and built-up maps can be used to quantify the building stock.     

The digital ‘connected’ earth: open technology for providing location-based services on degraded communication environments

In the current world, it is easy to listen that everybody and everything is connected. Over this connected world, the concept of location-based services has grown in order to provide digital services in everyplace and at every time. Nevertheless, this is not 100% true because the connection is not guaranteed for many people and in many places. These are the Degraded Communications Environments (DCE), environments where the availability of high-speed communications is not guaranteed in at least the 75% of the time. This paper works over the experience of a previous work in developing light protocols that do not need broadband for communication. This work provides an extension of these protocols for the inclusion of mobile devices as elements of the communication process and a set of libraries to allow the development of applications in DCE. The work done has involved the development of two frameworks: an Android framework that makes the incorporation of Android devices easier and a server-based framework that provides the server side for the development of the referred applications. A use case that uses these two frameworks has been developed. Finally, all technology developed is available throw a public Git repository.     

From 2D TO 3D Through Modelling Based On A Single Image

Three-dimensional modelling from single images remains an interesting topic of investigation in the research community, even though range sensors are becoming a common alternative for the generation of 3D information. The interest in single-image-based modelling is motivated by a wide spectrum of applications such as cultural heritage, civil engineering, urban planning and even criminology. In this paper a complete new production flowline is presented for modelling based on a single image. The modelling process consists of a series of familiar steps in photogrammetry and computer vision: feature extraction, vanishing point computation, camera self-calibration, 3D reconstruction and dimensional analysis. In particular, the methodology developed for single-image-based modelling takes a scientific approach combining several proven techniques with robust estimators. Finally, in order to demonstrate its capabilities, the reported examples include several real situations applied in different contexts.     

Modelling regional effects of artificial groundwater recharge in a multilayer aquifer characterized by perched water tables

This paper presents an approach to estimate the effects of a managed recharge experiment in a multilayer aquifer characterized by the presence of perched water tables in the Medina del Campo groundwater body, Douro basin, central Spain. A numerical model was developed to evaluate the effect of artificial recharge on the shallow sector of a regional-scale aquifer and on formerly active wetlands. The model was developed in the Visual MODFLOW Pro v.2011.1 environment in order to represent and analyse the regional impact of this artificial recharge event. Results suggest that the assumption of a single perched system may prove useful in regional contexts where data is limited. From a study site perspective, managed recharge is observed to increase shallow storage along the riverbanks, which is considered valuable for environmental purposes. However, downstream wetlands are unlikely to experience a significant recovery. Furthermore, only a small percentage of artificial recharge is expected to reach the deep regional aquifer. This method can be exported to settings characterized by the presence of perched aquifers and associated groundwater dependent ecosystems.