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A water distribution network (WDN) is a dynamic system in which the demand is a nonstationary process. On the other hand, most of the successful data-driven fault detection and isolation (FDI) methods have been developed by assuming static models and stationary processes. A demand model for the WDN is formed by a periodic signal plus a stochastic variable. This model allows the transformation of data such that a stationary and extended space of data can be obtained as it is demonstrated here. This proposition is the principal contribution of this work. To illustrate the advantages of the proposal, three well-known data-driven FDI algorithms are applied for the leak detection of the Hanoi distribution network: principal component analysis (PCA), independent component analysis (ICA), and support vector data description (SVDD). The leaks were emulated with different outflow magnitudes in all nodes. As a performance index, the fault detection rate is used, and the results indicate an improvement in the general index of approximately 75% when data are periodically transformed according to the proposal.

Summary A short review is given of the history of soil surveys in South America. This is followed by a description of a soil survey of 13,000,000 hectares in the Llanos Orientales of Colombia. The experience obtained can be useful for an inventory of soil resources in South America. Conclusions are: 1. Photo-mosaics should form an essential part of the equipment. 2. The scale of the aerial photography should not be larger than 1 : 40,000. Surface features not visible on that scale can be mapped more cheaply by using small aircraft. 3. The inclusion of a geomorphologist in any project of large size is highly recommended. 4. The units on a general soil map, irrespective of the taxonomic units used in defining them, should be landscape-elements, and related to units of agricultural systems in use or to be introduced. 5. In recommending land use, a better understanding of the mentality of the rural communities in developing countries is needed to create the greatest impact on the existing agriculture.

Summary Interpretation of aerial photographs is of great value in virtually all types of hydrologic studies. These investigations range in scope from rapid reconnaissance studies based only or largely upon aerial photographs to highly detailed studies that include field work. Single and stereoscopic pairs of vertical aerial photographs, oblique aerial photographs, aerial mosaics, index aerial mosaics, and single and stereoscopic ground photographs all are of value in some phases of hydrologic studies. Infrared film is superior to panchromatic film for certain purposes. Photogrammetric techniques for measuring vertical and horizontal distances on stereoscopic pairs of vertical aerial photographs have wide application in hydrologic studies. Remote-sensing techniques involving infrared imagery and microwave systems are of value in certain hydrologic studies, but much remains to be learned regarding their full value.

Digital PCR (dPCR) has been reported to be more precise and sensitive than real-time quantitative PCR (qPCR) in a variety of models and applications. However, in the majority of commercially available dPCR platforms, the dynamic range is dependent on the number of partitions analysed and so is typically limited to four orders of magnitude; reduced compared with the typical seven orders achievable by qPCR. Using two different biological models (HIV DNA analysis and KRAS genotyping), we have demonstrated that the RainDrop Digital PCR System (RainDance Technologies) is capable of performing accurate and precise quantification over six orders of magnitude thereby approaching that achievable by qPCR.

In this short paper an analysis is performed of the prospects for digital close-range photogrammetry with respect to current and future applications and equipment. While much progress has been made in the past decade, an expansion of photogrammetric methods is likely in the future to feed the rising demand for high-precision three-dimensional measurement.

On the basis of direct observations in the optically excellent stereo model of the Wild B9 Aviograph, an instrument based on rigorous geometrical solutions, the author determines reliably not only the total forest area for the selected district but also the distribution within this area according to the exposures, elevations, and ground inclinations. It is of special significance that the observations were made in a model of very small scale (1 : 50,000) by shortened procedure, i.e., without mapping, with the aid of a dot grid consisting of ordinary graph paper positioned on the drafting surface of the Aviograph. The convenient guiding of the pricking device along the system of intersections is considered an advantage of the B9 Aviograph for the survey described. The derived area-list facilitates the site classification that would serve as a reliable basis for forest inventories using statistical methods (sample plots) for stratified forest districts. Area determination for large forest regions is likely to warrant the use of systematically distributed, isolated fields of dots.

To understand and model public health emergencies, epidemiologists need data that describes how humans are moving and interacting across physical space. Such data has traditionally been difficult for researchers to obtain with the temporal resolution and geographic breadth that is needed to study, for example, a global pandemic. This paper describes Colocation Maps, which are spatial network datasets that have been developed within Facebook’s Data For Good program. These Maps estimate how often people from different regions are colocated: in particular, for a pair of geographic regions x and y, these Maps estimate the probability that a randomly chosen person from x and a randomly chosen person from y are simultaneously located in the same place during a randomly chosen minute in a given week. These datasets are well suited to parametrize metapopulation models of disease spread or to measure temporal changes in interactions between people from different regions; indeed, they have already been used for both of these purposes during the COVID-19 pandemic. In this paper, we show how Colocation Maps differ from existing data sources, describe how the datasets are built, provide examples of their use in compartmental modeling, and summarize ideas for further development of these and related datasets. We also conduct the first large-scale analysis of human colocation patterns across the world. Among the findings of this study, we observe that a pair of regions can exhibit high colocation despite few people moving between them. We also find that although few pairs of people are colocated for many days over the course of a week, these pairs can contribute significant fractions of the total colocation time within a region or between pairs of regions.

[EN] Image-based and range-based solutions can be used for the acquisition of valuable data in medicine. However, most of these methods are not valid for non-static patients. Cranial deformation is a problem with high prevalence among infants and image-based solutions can be used to assess the degree of deformation and monitor the evolution of patients. However, it is required to deal with infants normal movement during the assessment in order to avoid sedation. Some high-end multiple-sensor image-based solutions allow the achievement of accurate 3D data for medical applications under unpredicted dynamic conditions in consultation. In this paper, a novel, single photogrammetric smartphone-based solution for cranial deformation assessment is presented. A coded cap is placed on the infant's head and a guided smartphone app is used by the user to acquire the information, that is later processed on a server to obtain the 3D model. The smartphone app is designed to guide users with no knowledge of photogrammetry, computer vision or 3D modelling. The processing is fully automatic offline. The photogrammetric tool is also non-invasive, reacting well with quick and sudden infant's movements. Therefore, it does not require sedation. This paper tackles the accuracy and repeatability analysis tested both for a single user (intrauser) and multiple non-expert user (interuser) on 3D printed head models. The results allow us to confirm an accuracy below 1.5 mm, which makes the system suitable for clinical practice by medical staff. The basic automatically-derived anthropometric linear magnitudes are also tested obtaining a mean variability of 0.6 +/- 0.6 mm for the longitudinal and transversal distances and 1.4 +/- 1.3 mm for the maximum perimeter., This project is funded by Instituto de Salud Carlos III and European Regional Development Fund (FEDER), project number PI18/00881, and by Generalitat Valenciana, grant number ACIF/2017/056.

Time has consistently been regarded as the missing dimension from our renderings of space, having a significant impact on how we interpret and represent past interaction. Nowhere is this more keenly felt than in discussion of maritime mobility. This paper outlines an innovative approach to mapping maritime spaces by taking into account the performance of Bronze Age sailing ships in different weather conditions and the subsequent time of sailing journeys. The use of cartograms is demonstrated to be invaluable for reconceptualisation of maritime space and rethinking maritime connectivity in the past. This marks a step-change in approach, which has implications for regions beyond the case study area (eastern Mediterranean). The results presented in this paper foreground meaningful differences in maritime connectivity between Egypt and the Levant during the earlier Bronze Age than are easily realised through traditional static representations. This demonstrates the significance of developing alternative representations of space/time for archaeology.

A substantially updated version of the correlation table showing chronostratigraphical subdivisions of late Cenozoic geological time, spanning the last 2.7 million years is presented. It provides scientists, students, professionals and the general public with a ready reference to stratigraphical terms and schemes in use in different areas for similar periods. The updates comprised the status of Quaternary chronostratigraphic subdivision, the combined age-modelled geomagnetic and isotope records from ocean drilling records, and revised regional correlation schemes, notably for eastern Europe. The paper describes the chart in its 2019 QI-500 form and contains sections on its types of usage and formal subdivision status, besides reference and description of the contents of the various columns. The paper also describes and discusses the resolution of correlations in younger and older parts of the last 2.7 Ma.

Tracking Earth’s past helps us to move from hindsight to foresight in seeking landscape sustainability, a pursuit aided by modern mapping capabilities but hindered by a dearth of historical landscape information. To fill the data gap and exemplify the use of old maps for land-use change sciences, we combined an old paper-based US civil war map and modern aerial photos to derive land-use history and landscape dynamics at fine scales for a region near Chancellorsville, USA, from 1867 to 2014. We also tested how advanced algorithms—object-based image analysis and Random Forests (RF)—could aid in data processing. Automatic classification of the scanned 1867 paper map proved difficult, but its manual digitization could benefit from object-based image segmentation. Classifying digital aerial images was more accurate via the object-based than pixel-based method, but only if the images were segmented appropriately. In the object-based classification, spectral-based features were much more important and useful than shape/geometry features for land-cover discrimination, as ranked by RF. During the 147 years, 32% of the region changed in land type. Settlement and roads increased in extent by 1850% and 691%, respectively, and woodland decreased by 19%. These changes fragmented the landscape, altered the hydrological regime, and affected river morphology. The utility of old maps exemplified here provides an impetus for leveraging extant old maps or historical records to support land-use and global change research. Our study also connotes the importance of preserving and geotagging current non-traditional data, such as photos, videos, and citizen science data, that can serve as a baseline to document future landscape change.

The land classification system called ‘Local Climate Zone’ (LCZ), developed by Stewart and Oke (2012), deals with the physical properties like surface cover and surface structure of the city which introduces a logical approach in studying urban heat island. Indian cities are characterized by the heterogeneous type of built forms. The primary task of mapping LCZ in such cities poses difficulty due to its complex urban form and data insufficiency. This paper aims at resolving the issues pertaining to the identification and classification of LCZ by taking a case of Nagpur city from India. The paper explains the various stages involved in the mapping and the issues confronted while delineating the LCZs. It explains the integration of various secondary data to generate LCZ map at 1 km, 500 m and 250 m. 21 LCZs are found in Nagpur including standard 7 built types and 7 natural types of LCZ. Additional 7 LCZ subclasses were observed as a result of mixing of two or more classes of built type LCZ. The paper explains typical features of the LCZ map of Nagpur and concludes with the discussion on the effectiveness of mapping method adopted for preparation of LCZ maps.

In this paper, we do a critical review of statistical methods for landslide susceptibility assessment and associated terrain zonations. Landslide susceptibility is the likelihood of a landslide occurring in an area depending on local terrain conditions, estimating "where" landslides are likely to occur. Since the first attempts to assess landslide susceptibility in the mid-1970s, hundreds of papers have been published using a variety of approaches and methods in different geological and climatic settings. Here, we critically review the statistically-based landslide susceptibility assessment literature by systematically searching for and then compiling an extensive database of 565 peer-review articles from 1983 to 2016. For each article in the literature database, we noted 31 categories/sub-categories of information including study region/extent, landslide type/number, inventory type and period covered, statistical model used, including variable types, model fit/prediction performance evaluation method, and strategy used to assess the model uncertainty. We present graphical visualisations and discussions of commonalities and differences found as a function of region and time, revealing a significant heterogeneity of thematic data types and scales, modelling approaches, and model evaluation criteria. We found that the range of thematic data types used for susceptibility assessment has not changed significantly with time, and that for a number of studies the geomorphological significance of the thematic data used is poorly justified. We also found that the most common statistical methods for landslide susceptibility assessment include logistic regression, neural network analysis, data-overlay, index-based and weight of evidence analyses, with an increasing preference towards machine learning methods in the recent years. Although an increasing number of studies in recent years have assessed the model performance, in terms of model fit and prediction performance, only a handful of studies have evaluated the model uncertainty. Adopting a Susceptibility Quality Level index, we found that the quality of published models has improved over the years, but top-quality assessments remain rare. We identified a clear geographical bias in susceptibility study locations, with many studies in China, India, Italy, South Korea and Turkey, and only a few in Africa, South America and Oceania. Based on previous literature reviews, the analysis of the information collected in the literature database, and our own experience on the subject, we provide recommendations for the preparation, evaluation, and use of landslide susceptibility models and associated terrain zonations.

This paper presents a part of an ethnoarchaeological research whose main objective is the development of methodological and conceptual instruments to advance the study of prehistoric hunter-gatherer societies. We have proposed ethnoarchaeological experimentation in order to contrast the relationship between spatial organization and social relationships for evaluate the resolution level of intra-site analysis combining the use of social categories (deriving from the socioeconomic analysis of an ethnographic documented Hunter-Gatherer society) with the systematic record recovered in a site of the same society, both from a quantitative and qualitative approach. The processes of formation of the Tunel VII site have been differentiated from the interpretation of refitting analysis and spatial distribution maps and the detailed analysis of zooarchaeological data. However, the results presented in this paper have to be contrasted with an integrated analysis of lithic and bone technology remains in order to analyse the overall distribution of by-products from production and consumption activities. Moreover, results concerning the structure of spatial data point to the need to test spatial interpolation methods designed to overcome the geostatistical restriction on the homogeneity of the surface.

This paper presents a random forest classification approach for identifying and mapping three types of lowland native grassland communities found in the Tasmanian Midlands region. Due to the high conservation priority assigned to these communities, there has been an increasing need to identify appropriate datasets that can be used to derive accurate and frequently updateable maps of community extent. Therefore, this paper proposes a method employing repeat classification and statistical significance testing as a means of identifying the most appropriate dataset for mapping these communities. Two datasets were acquired and analysed; a Landsat ETM+ scene, and a WorldView-2 scene, both from 2010. Training and validation data were randomly subset using a k-fold (k = 50) approach from a pre-existing field dataset. Poa labillardierei, Themeda triandra and lowland native grassland complex communities were identified in addition to dry woodland and agriculture. For each subset of randomly allocated points, a random forest model was trained based on each dataset, and then used to classify the corresponding imagery. Validation was performed using the reciprocal points from the independent subset that had not been used to train the model. Final training and classification accuracies were reported as per class means for each satellite dataset. Analysis of Variance (ANOVA) was undertaken to determine whether classification accuracy differed between the two datasets, as well as between classifications. Results showed mean class accuracies between 54% and 87%. Class accuracy only differed significantly between datasets for the dry woodland and Themeda grassland classes, with the WorldView-2 dataset showing higher mean classification accuracies. The results of this study indicate that remote sensing is a viable method for the identification of lowland native grassland communities in the Tasmanian Midlands, and that repeat classification and statistical significant testing can be used to identify optimal datasets for vegetation community mapping.

Mangrove forests grow in the estuaries of 124 tropical countries around the world. Because in-situ monitoring of mangroves is difficult and time-consuming, remote sensing technologies are commonly used to monitor these ecosystems. Landsat satellites have provided regular and systematic images of mangrove ecosystems for over 30 years, yet researchers often cite budget and infrastructure constraints to justify the underuse this resource. Since 2001, over 50 studies have used Landsat or ASTER imagery for mangrove monitoring, and most focus on the spatial extent of mangroves, rarely using more than five images. Even after the Landsat archive was made free for public use, few studies used more than five images, despite the clear advantages of using more images (e.g. lower signal-to-noise ratios). The main argument of this paper is that, with freely available imagery and high performance computing facilities around the world, it is up to researchers to acquire the necessary programming skills to use these resources. Programming skills allow researchers to automate repetitive and time-consuming tasks, such as image acquisition and processing, consequently reducing up to 60% of the time dedicated to these activities. These skills also help scientists to review and re-use algorithms, hence making mangrove research more agile. This paper contributes to the debate on why scientists need to learn to program, not only to challenge prevailing approaches to mangrove research, but also to expand the temporal and spatial extents that are commonly used for mangrove research.

Volcanic geological maps provide significant data for volcanic hazard assessment, exploration of mineral-energetic resources, physical volcanology and petrological studies, as well as geophysical models. However, the lack of consensus about the best graphic representation of volcanic geological maps and the most efficient organizational structure of spatial data contained in these maps, has resulted in a variability of representations and data storage. Here we propose some guidelines to unify the representation of composite volcanoes geological maps that may facilitate the communication within a particular country and across political boundaries by reaching a common language. In this paper, we share the advances obtained in Colombia by the Servicio Geologico Colombiano (Colombian Geological Survey), through searching for improved cartographic strategies and efficient representations of mapped volcanogenic units in the North-Andean setting. The main objective of this paper is to provide a guideline for the digital representation of Pliocene-Holocene composite volcanoes geological maps, applicable elsewhere, that displays a comprehensive presentation based on an accurate and qualified geodatabase package. This contribution offers: (i) a catalogue of symbols for the representation of geological and geomorphological elements; (ii) a catalogue of colors and patterns for the representation of the different lithostratigraphic units; (iii) a graphic distribution prototype for the information within the resulting map sheet, and (iv) a geodatabase structure with its corresponding catalogue of objects. With this initiative, we aim to begin an international collaborative effort on reaching a common understanding of best practices in the representation and systematic digital organization of thematic maps of composite volcanoes.

Local climate zone (LCZ) mapping is an emerging field in urban climate research. LCZs potentially provide an objective framework to assess urban form and function worldwide. The scheme is currently being used to globally map LCZs as a part of the World Urban Database and Access Portal Tools (WUDAPT) initiative. So far, most of the LCZ maps lack proper quantitative assessment, challenging the generic character of the WUDAPT workflow. Using the standard method introduced by the WUDAPT community difficulties arose concerning the built zones due to high levels of heterogeneity. To overcome this problem a contextual classifier is adopted in the mapping process. This paper quantitatively assesses the influence of neighbourhood information on the LCZ mapping result of three cities in Belgium: Antwerp, Brussels and Ghent. Overall accuracies for the maps were respectively 85.7 ± 0.5, 79.6 ± 0.9, 90.2 ± 0.4%. The approach presented here results in overall accuracies of 93.6 ± 0.2, 92.6 ± 0.3 and 95.6 ± 0.3% for Antwerp, Brussels and Ghent. The results thus indicate a positive influence of neighbourhood information for all study areas with an increase in overall accuracies of 7.9, 13.0 and 5.4%. This paper reaches two main conclusions. Firstly, evidence was introduced on the relevance of a quantitative accuracy assessment in LCZ mapping, showing that the accuracies reported in previous papers are not easily achieved. Secondly, the method presented in this paper proves to be highly effective in Belgian cities, and given its open character shows promise for application in other heterogeneous cities worldwide.

In this paper, the levels of residential segregation of immigrants in Sweden during the years 1990, 1997, 2005, and 2012 are calculated. This paper applies a novel method for calculating segregation that is multi-scalar and addresses the modifiable areal unit problem (MAUP). The level of segregation is evaluated for each populated location by identifying the population that includes the k-nearest neighbours. The share of immigrants in this assessment population is then compared to the share in the reference population that comprises the K-nearest neighbours. One of the strengths of this method is the possibility to modify the reference population, thus making it possible to measure the difference in the results due to the size of the reference population. This study demonstrates that the results can considerably differ depending on which reference population is used. Furthermore, this study indicates that using different reference areas can produce completely different trends over time, such as decreasing or increasing segregation. The results demonstrate a general increase in segregation between 1990 and 1997, followed by a more complex pattern from 1997 to 2012. The segregation values are presented for all populated locations in Sweden, and population-weighted means are calculated for the whole of Sweden, in addition to the Stockholm, Malmo, and Gothenburg metropolitan areas.

The New Human Condition (NHC) is perhaps the largest cognitive challenge in history to human intelligence and agency and concerns our species' ability to cope with the consequences and responsibilities of being the major driver of planetary change in the twenty-first century ( Palsson et al., 2013 , Holm et al., 2015 ). But despite long held assumptions about intra-disciplinary engagements between its “human” and “physical” branches, geography's weakness as a discipline is that it has yet to gather sufficient momentum to collectively shape and implement practical and sustainable climate change policies and actions (Castree, 2014a). However, by considering together the heuristic values of the concepts of the Anthropocene and Planetary Boundaries, the Anglo-American sphere of geography recognizes in either ironic, or unconscious manners that a new strand of environmental determinism (discredited by geographical thought and practice in the early twentieth century) has re-emerged to elide the role of human agency and broadly dominate the discussion of climate change. Mike Hulme (2011, 247) states that “climate determinism” is “a form of analysis and prediction in which climate is first extracted from the matrix of interdependencies that shape human life within the physical world”. Within this discourse it is often the biophysical sphere that is employed to explain the course of human behavior; consequently, this dominating perspective threatens to skew our predictions and understandings of future societies, cultures, climates and destinies. Climate change will certainly constrain human agency, but it also creates the potential for geography to play to its intra and inter disciplinary strengths and begin discussing and addressing human-environmental dilemmas in practical and realistic ways; and secondly, seize the climate change crisis as an opportunity to study where, why and for whom global environmental change matters. Firstly, this paper considers a theoretical balance between the NHC, the Anthropocene and Planetary Boundaries as a way forward for geography to begin addressing the common dilemma of climate change. Within this consideration it engages Anne Buttimer's geographical translation of Martin Heidegger's lebenswelt as a dimension of the NHC. Secondly, the paper discusses how GeoHumanities and GIScience integrations with phenomenology, the digital and environmental humanities and social media generated “Big-Data” can explore the perceptual scales and scopes of the NHC/Anthropocene/Planetary Boundaries conceptual triad. Lastly, it argues that such integrations are salient to the study of emerging Smart City Lifeworlds as a means to engage the increasing urban agencies of global climate change driven by the vagaries of the human condition.

In this paper, the problem of establishing contact of robots with a planar surface having unknown stiffness and position is considered. Given a free-space controller that achieves tracking of a position and orientation reference trajectory, a novel, continuous on time controller is designed, capable of establishing and maintaining contact. Additionally, the proposed control scheme guarantees the satisfaction of certain pre-defined bounds regarding the maximum overshoot, the minimum convergence rate and the maximum steady-state error for the contact force, the position, and the orientation tracking errors. Moreover, all remaining closed-loop signals are kept bounded. Simulation studies on a 6-DOF robot, clarify and verify the theoretical findings.

In this paper, I examine the role that strategic analysis has played on antitrust and discuss new analytical venues. In order to accomplish this goal, the paper presents two directions. Initially, I undertake a review of the current debate between antitrust and strategy. I argue that much of the contemporary discussion on the subject is founded on traditional economic approaches to strategy, what leads to the disregard of the role of firm heterogeneity in competitive dynamics. In the second part of the paper, I sketch an approach to antitrust based on the resource-based view of strategy. This approach is particularly useful in examining the conditions of market rivalry, being a complement – not necessarily a substitute – to the traditional antitrust economic analysis. Resumo Neste artigo, é examinado o papel que a análise estratégica tem desempenhado no antitruste e são discutidos novos caminhos. A fim de alcançar este objetivo, o trabalho apresenta duas direções. Inicialmente, realiza-se a revisão do debate atual sobre a relação entre antitruste e estratégia. Defende-se que grande parte da discussão contemporânea sobre o assunto se baseia em abordagens econômicas tradicionais de estratégia, o que leva à desconsideração do papel da heterogeneidade da firma na dinâmica competitiva. Na segunda parte do artigo, é esboçada uma abordagem de antitruste fundamentada na visão baseada em recursos. Esta abordagem é particularmente útil para examinar as condições de rivalidade do mercado, sendo um complemento – e não necessariamente um substituto – à análise econômica antitruste tradicional. Resumen En este artículo se evalúa el papel que el análisis estratégico ha jugado en la defensa de la competencia y se discuten nuevos caminos. Para ello, se presentan dos direcciones. Inicialmente, se lleva a cabo una revisión del actual debate sobre la relación entre la defensa de la competencia y la estrategia. Se argumenta que gran parte de la discusión contemporánea sobre el tema se basa en los enfoques económicos tradicionales de estrategia, lo que lleva a ignorar el papel de la heterogeneidad de la organización en la dinámica competitiva. En la segunda parte del artículo, se describe un enfoque de antimonopolio que se apoya en la visión basada en recursos. Este enfoque es particularmente útil para examinar las condiciones de competencia del mercado, y puede complementar – y no necesariamente reemplazar – el análisis económico antitrust tradicional.

This paper deals with the problem of parity space-based fault detection (FD) for linear discrete time-varying systems. In order to simultaneously ensure the performance of FD and avoid the heavy computational burden of high dimensional parity space, the techniques of stationary wavelet transform (SWT) on residual signals are applied in the paper. Based on this, the design of residual generators can be formulated as generalized optimization problems and a recursive algorithm is developed to a feasible solution of parity vectors. Furthermore, a bank of residual signals are generated at multiscales. The significant advantage of the SWT based parity space approach is the improvement of FD performance with low parity space order and an easy online realization. Finally, a numerical example is given to demonstrate the effectiveness of the proposed approach.

Plastic greenhouses (PGs) are an important agriculture development technique to protect and control the growing environment for food crops. The extensive use of PGs can change the agriculture landscape and affects the local environment. Accurately mapping and estimating the coverage of PGs is a necessity to the strategic planning of modern agriculture. Unfortunately, PG mapping over large areas is methodologically challenging, as the medium spatial resolution satellite imagery (such as Landsat data) used for analysis lacks spatial details and spectral variations. To fill the gap, the paper proposes a new plastic greenhouse index (PGI) based on the spectral, sensitivity, and separability analysis of PGs using medium spatial resolution images. In the context of the Landsat Enhanced Thematic Mapper Plus (ETM+) imagery, the paper examines the effectiveness and capability of the proposed PGI. The results indicate that PGs in Landsat ETM+ image can be successfully detected by the PGI if the PG fraction is greater than 12% in a mixed pixel. A kappa coefficient of 0.83 and overall accuracy of 91.2% were achieved when applying the proposed PGI in the case of Weifang District, Shandong, China. These results show that the proposed index can be applied to identifying transparent PGs in atmospheric corrected Landsat image and has the potential for the digital mapping of plastic greenhouse coverage over a large area.

Topographic maps are among the most commonly used map types, however, their complex and information-rich designs depicting natural, human-made and cultural features make them difficult to read. Regardless of their complexity, spatial planners make extensive use of topographic maps in their work. On the other hand, various studies suggest that map literacy among the development planning professionals in South Africa is not very high. The widespread use of topographic maps combined with the low levels of map literacy presents challenges for effective development planning. In this paper we address some of these challenges by developing a specialized task taxonomy based on systematically assessed map literacy levels; and conducting an empirical experiment with topographic maps to evaluate our task taxonomy. In such empirical studies if non-realistic tasks are used, the results of map literacy tests may be skewed. Furthermore, experience and familiarity with the studied map type play a role in map literacy. There is thus a need to develop map literacy tests aimed at planners specifically. We developed a taxonomy of realistic map reading tasks typically executed during the planning process. The taxonomy defines six levels tasks of increasing difficulty and complexity, ranging from recognising symbols to extracting knowledge. We hypothesized that competence in the first four levels indicates functional map literacy. In this paper, we present results from an empirical experiment with 49 map literate participants solving a subset of tasks from the first four levels of the taxonomy with a topographic map. Our findings suggest that the proposed taxonomy is a good reference for evaluating topographic map literacy. Participants solved the tasks on all four levels as expected and we therefore conclude that the experiment based on the first four levels of the taxonomy successfully determined the functional map literacy of the participants. We plan to continue the study for the remaining levels, repeat the experiments with a group of map illiterate participants to confirm that the taxonomy can also be used to determine map illiteracy.

The physical landscape is the mosaic resulting from a wide spectrum of environmental components. The landforms define the variety, or diversity, of the geomorphological component: the geomorphodiversity. Landforms are usually represented in thematic maps where the scale and the graphic solutions are widely heterogeneous. Since geomorphological maps are not always easy to obtain and standardize, topography might be used as a proxy to infer the morphological signature. To recognize, evaluate, and in some cases promote the geomorphodiversity of an area, a numerical assessment is preferable. Through the use of quantitative approaches, indexes can be defined which quantitatively characterize the physical landscape in a discretized space consisting of continuous and regular cells. In this approach each cell is labelled with an algebraic value, which increases with the diversity degree. In this paper a quantitative index for geomorphodiversity is estimated stressing the topographic variables derived from Digital Elevation Models in a GIS environment. The resulting index is the sum of the variety of each terrain parameter taken into account. The areas characterized by the highest value of geomorphodiversity index show a good correspondence with well-known situations in the region where not always the geological heritage is properly acknowledged. The areas characterized by the lowest value of geodiversity correspond to the center of some intermountain basins of the region. Being the index strictly related to the topographic variety, this result is quite obvious but not easily predictable since in some flat areas the index is higher. Comparing the results with the geomorphological map of the area performs a validation procedure for the method. A positive correlation is found between the index calculated and the presence/absence of landforms. The paper shows that the index is a useful and simple tool for the identification, analysis and promotion of the geological heritage.

Many deltas, including the Mississippi River Delta, have been losing land at fast rates compromising the safety and sustainability of their ecosystems. Knowledge of delta vulnerability has raised global concern and stimulated active interdisciplinary research as deltas are densely populated landscapes, rich in agriculture, fisheries, oil and gas, and important means for navigation. There are many ways of looking at this problem which all contribute to a deeper understanding of the functioning of coastal systems. One aspect that has been overlooked thus far, yet fundamental for advancing delta science is connectivity, both physical (how different portions of the system interact with each other) as well as conceptual (pathways of process coupling). In this paper, I propose a framework called Delta Connectome for studying connectivity in river deltas based on different representations of a delta as a network. After analyzing the classic network representation as a set of nodes (e.g., bifurcations and junctions or regions with distinct physical or statistical behavior) and links (e.g., channels), I show that from connectivity considerations the delta emerges as a leaky network that continuously exchanges fluxes of matter, energy, and information with its surroundings and evolves over time. I explore each network representation and show through several examples how quantifying connectivity can bring to light aspects of deltaic systems so far unexplored and yet fundamental to understanding system functioning and informing coastal management and restoration. This paper serves both as an introduction to the Delta Connectome framework as well as a review of recent applications of the concepts of network and connectivity to deltaic systems within the Connectome framework.

This paper is concerned with the implementation and realisation of a Worldwide Electronic Navigational Charts Database (WEND), adopted by the International Hydrographic Organization (IHO) and its members in supporting marine navigation. It identifies the issue of gaps and overlaps between adjoining Electronic Navigational Charts (ENCs) and explores its consequences to the operation of Electronic Chart Display and Information Systems (ECDIS) and the fulfilment of International Maritime Organization (IMO) chart carriage requirements. As the ENCs production is directly dependent on states’ cartographic competences, this paper delves into the coastal states’ jurisdiction in accordance with international law of the sea, and in particular the United Nations Convention on the Law of the Sea, and ΙΗΟ and IMO instruments. Through a case study on recently produced ENCs in the Mediterranean and more specifically in the Aegean Sea, this paper documents the necessity to respect states’ cartographic competences in realising the WEND concept and cautions that, otherwise, new and extended overlaps emerge, which pose a risk to the safety of navigation, and, at the same time, become means through which states may promote their geopolitical aspirations as to jurisdiction over certain marine areas.

Improved data on crop type and crop area from satellite imagery are invaluable for agronomy managers and are crucial for balancing agricultural expansion and forest degradation. However, large-scale maps of crop type and crop area using satellite imagery are not easily available in some regions, especially Brazil. Reasons for this include limited ground truth data, inadequate spatial and temporal satellite data availability, computational challenges, lack of cropland data and field boundaries. In this paper, we attempted to overcome some of these obstacles by using an ensemble of approaches to generate crop classification maps for Brazil. In order to compensate for the lack of abundant ground truth data in Brazil, we combined extensive field data and satellite input features from the United States with available field data and satellite input features from Brazil to train crop classification model for Brazil. Before applying the crop classification model for Brazil, we classified cropland areas using harmonic functions and delineated field boundaries using a supervised deep learning approach. Cropland masking and field boundary delineation allowed field-level mapping of crop type and crop area. Applying the crop classification model for Brazil in the states of Mato Grosso and Goias gave a true positive accuracy of 88% in the 2017/2018 summer growing season for soybean classification, 95% in the 2018 safrinha growing season for corn classification, and 86% in the 2018/2019 summer growing season for soybean classification. Our crop area estimates also showed a good agreement (correlation of 0.95 and mean absolute error of 0.64) with state-scale statistical data provided by the Companhia Nacional de Abastecimento (CONAB) in both summer and safrinha growing seasons adding further confidence to the results. These results suggest that extensive data from one geography can be used to train machine learning models in conjunction with limited field data from another geography. Accuracy assessments support the portability of crop classification model for Brazil with reasonable accuracy spatially, as tested in the state of Parana, and temporally, to the following year. The approaches and datasets presented in this paper provide building blocks for large-scale crop monitoring benefitting both public and private sectors.

Protected areas (PAs) are crucial to the conservation of biodiversity and ecosystem services. Moreover, the creation, management, and efficiency of PAs are associated with the historical geography (the type of PA and number of PAs over the years), bioclimatic sufficiency, and informetric factors (number of papers and number of hits on the internet). These variables vary across the PA network, and combining these factors can help to understand biases of PAs and the future direction to preserve the Brazilian Cerrado biodiversity. In this paper, we evaluated the historical geography, bioclimatic representation, and informetric factors of the Brazilian Cerrado PAs. Although the number of PAs and the cumulative area of PAs has increased significantly, we detected that some new PAs are overlapping other PAs. The overlapping was not idiosyncratic, where some PAs categorized overlapped more than others. The number of papers and hits of PAs on the internet showed a positive correlation and asymmetric distribution, where most PAs had few papers/hits. The bioclimatic variables registered in PAs did not contemplate all bioclimatic variabilities found in the Cerrado. Thus, new areas are fundamental to increase the sufficiency of the PA network and to conserve the Cerrado biome. Our summarized analysis revealed that some variables showed a positive correlation, for example, age, area, number of papers, number of hits, and some PA categories. Finally, our results indicated concordance of some biases, e.g., historical geography and informetric factors. Besides, we recommend the addition of new PAs to increase the sufficiency of the Cerrado PA network.

The paper analyses migration flows with the purpose of defining functional regions at a micro level. It proposes an innovative approach to the processing of migration data. It includes a reflection on local level migration analysis in relation to local labour markets, and it is inspired by time geographical concepts and research into human spatial behaviour. Relevant identified migration flows are those that occur when a migrant only changes the place of permanent residence, and does not necessarily need to change workplace or most of the localities within a daily timespace context. The paper uses these migration data to delineate local migration areas (daily spatial systems) of the Czech Republic through the application of a standard rule-based procedure of functional regional taxonomy.

When we consider the relationship with the urban soundscape, this aural 'moment' is intrinsically intertwined with the body as part of the making of place. How can attending to the making of place through sound unveil an emotional cartography or the city? This paper will address these questions by exploring the processes that bind sound, emotion and place together. Elaborating on Nancy's (2007) concept of listening as methexis (participation) and LaBelle's (2010) idea of the moment of sound as a participatory event, this paper presents two extended vignettes taken from empirical research in London's East End, which used interviews and audio walks to examine sensory engagements with everyday urban spaces. It distinguishes an approach to the production of place that integrates aural perception, affect and emotion. It concludes outlining the importance of being re-acquainted with our ensounded body in order to explore geography from the sentient body to generate a fluid cartography that evolves at the same speed the soundscape does, making an argument for the importance of an embodied listening while strengthening the affective and emotional aspects of the urban soundscape. Cuando consideramos la relación con el paisaje sonoro urbano, este "momento" auditivo está intrínsecamente entrelazado con el cuerpo como parte de la creación del lugar. ¿De qué manera la atención a la creación del lugar a través del sonido revela una cartografía emocional o la ciudad? Este documento abordará estas cuestiones explorando los procesos que unen sonido, emoción y lugar juntos. Elaborando el concepto de Nancy (2007) de escuchar como metexis (participación) y la idea de LaBelle (2010) del momento del sonido como un evento participativo, este artículo presenta dos viñetas ampliadas tomadas de investigación empírica en el East End de Londres, que utilizó entrevistas y recorridos de audio para examinar los compromisos sensoriales con los espacios urbanos cotidianos. Distingue un enfoque de la producción del lugar que integra la percepción auditiva, el afecto y la emoción. Concluye subrayando la importancia de volver a familiarizarse con nuestro ensoñado cuerpo para explorar la geografía del cuerpo consciente para generar una cartografía fluida que evoluciona a la misma velocidad que el paisaje sonoro, argumentando la importancia de una escucha encarnada mientras se fortalecen los aspectos afectivos y emocionales del paisaje sonoro urbano. Quan pensem en la relació amb el paisatge sonor urbà, aquest "moment" auditiu està intrínsecament entrellaçat amb el cos com a part de la creació del lloc. De quina manera l'atenció a la creació del lloc a través del so revela una cartografia emocional o la ciutat? Aquest document abordarà aquestes qüestions explorant els processos que uneixen so, emoció i lloc junts. Elaborant el concepte de Nancy (2007) d'escoltar com a metexis (participació) i la idea de LaBelle (2010) del moment del so com a esdeveniment participatiu, aquest article presenta dues vinyetes ampliades preses d'investigació empírica en l'East End de Londres, que va utilitzar entrevistes i recorreguts d'àudio per examinar els compromisos sensorials amb els espais urbans quotidians. Distingeix un enfocament de la producció del lloc que integra la percepció auditiva, l'afecte i l'emoció. Conclou subratllant la importància de tornar a familiaritzar-se amb el nostre somiat cos per explorar la geografia del cos conscient per generar una cartografia fluïda que evoluciona a la mateixa velocitat que el paisatge sonor, argumentant la importància d'una escolta encarnada mentre s'enforteixen els aspectes afectius i emocionals del paisatge sonor urbà.

Estimating absence locations of a species is important in conservation biology and conservation planning. For instance, using reliable absence as much as presence information, species distribution models can enhance their performance and produce more accurate predictions of the distribution of a species. Unfortunately, estimating reliable absence locations is difficult and often requires a deep knowledge of the species’ distribution and of its abiotic and biotic environmental preferences and tolerance. In this paper, we propose a methodology to reconstruct reliable absence information from presence-only information, and the conditions that those presence-only data have to meet to make this possible. Large species occurrence data collections (otherwise called occurrence datasets) contain high quality and expert-reviewed species observation records from scientific surveys. These surveys can be used to retrieve species presence locations, but they also record places where the species in their target list were not observed. Although these absences could be simply due to sampling variation, it is possible to intersect many of these reports to estimate true absence locations, i.e. those due to habitat unsuitability or geographical hindrances. In this paper, we present a method to generate reliable absence locations of this type for marine species, using scientific surveys reports contained in the Ocean Biogeographic Information System (OBIS), an authoritative species occurrence dataset. Our method spatially aggregates information from surveys focussing on the same target species. It detects absence locations for a given species as those locations in which repeated surveys (that included the species of interest in their target list) reported information only on other species. We qualitatively demonstrate the reliability of our method using distribution records of the Atlantic cod as a case study. Additionally, we quantitatively estimate its performance using another authoritative large species occurrence dataset, the Global Biodiversity Information Facility (GBIF). We also demonstrate that our approach has higher accuracy and presents complementary behaviour with respect to another method using environmental envelopes. Our process can support species distribution models (as well as other types of models, e.g. climate change models) by providing reliable data to presence/absence approaches. It can manage regional as well as global scale scenarios and runs within a collaborative e-Infrastructure (D4Science) that publishes it as-a-Service, allowing biologists to reproduce, repeat and share experimental results.

The multifractal analysis technique can reveal the details of a global and local evolution of a regional space at multiple levels and scales. Hence, the built-up land in Zhengzhou is used as an example in this paper to demonstrate multifractal analysis of its spatial pattern in 1988, 1995, 2006, and 2015, in which, based on the analysis of generalized multifractal (including atypical trend and typical evolutionary features), and through a generalized multifractal with historical evolution paradigm, to reveal the details of its evolution on multiple spatial scales. The analysis of global indicators shows that the regular change in the spatial pattern of built-up lands in Zhengzhou since the 1980s is a hierarchically fluctuating spatial system. Zhengzhou tended to expand in the low- and medium-density areas before the 2000s, and it managed to exhibit spatial agglomeration in high-density areas in the 2010s. The analysis of local indicators further shows: (1) the regular change with multifractal characteristics is only part of Zhengzhou’s evolutionary system, but it is the primary driving force; (2) the spatial evolution of built-up lands in Zhengzhou has long been dominated by chaotic states and mediocre states, but the regularity of recent evolution has increased; and (3) changes in the spatial scale of built-up lands at different times are basically synchronized, But the specific characteristics of each year are different and the complexity is increasing. However, compared with Beijing’s left-skewed and wide-regional f(a)-a(q) curves for all periods, the features of built-up lands in Zhengzhou are right-skewed and narrow-regional. The two cities have different types of evolutional features. Therefore, the spatial evolution of Beijing has some reference value for Zhengzhou, but it cannot be copied. In general, based on the spatial complexity analysis of multiple perspectives, this paper explains the overall change of spatial pattern and the basic evolution of multi-space scale in Zhengzhou in the past 30 years and verifies the feasibility of generalized multifractal in geospatial analysis.

Several studies have revealed that urban green spaces (UGSs) provide a number of environmental and social benefits for human beings. However, with the acceleration of urbanization and population growth, the problem of unevenly distributed UGSs presents a challenge for sustainable urban development. This paper classified UGSs based on a spatial design network analysis (sDNA) model and mapped the spatial distribution of the population in central Jinan. Based on this method, an equity evaluation model was established, and the spatial equity of the UGS distribution was analyzed. The results indicated that the core area of central Jinan spread from the center to the east and west along the axis, and the range of the UGS in the core area of central Jinan within a 15-minute walking distance included more than 30 % and nearly 50 % of the population at the local and city-wide scales, respectively. In addition, a correlation analysis showed that the size of the population had a significant negative correlation with UGS accessibility in the study area. The main contribution of this paper was the provision of a new way to assess equity on a more precise scale with the combination of spatial syntax and population data.

Continual advances in quantitative modelling of surface processes, combined with new spatio-temporal and geo-computational algorithms, have revolutionised the auto-classification and mapping of landform components through the automated analysis of high-quality digital elevation models (DEMs). Digital geomorphic mapping (DGM) approaches that can simplify and translate the inclusion of “human knowledge” to automatic terrain classification across a broader spectrum of terrain morphological units as well as a range of spatial scales, therefore, offer great potential for improved topographic and landscape analysis. One such approach is the mapping of landform elements using the concept of the Geomorphon (geomorphological phonotypes). The output of the geomorphon approach is the stratification of the landscape into ten unique but recognisable landform elements: peak, ridge, shoulder, spur, and slope, hollow, foot slope, valley, depression and flat. Equally appealing is the way the model self-adapts to local topography using a line-of-sight principle enabling better matching of landform elements to computational spatial scale. The purpose of this paper is to observe the effects that different pixel resolution (grain size) and digital elevation model source (DEM) would have on the replication of observed geomorphic spatial patterns and representation of terrain selected parameters within the landscape. This paper provides a comprehensive exploratory assessment of digital terrain representation and relief classification using an automated geomorphometric mapping approach, by evaluating three different digital surface models (SUDEM, SRTM, ASTER GDEM2) and different spatial resolution (30 m & 90 m) for an 11,200 ha catchment in KwaZulu-Natal, South Africa. To test the self-adapting ability of the geomorphon approach under regional conditions, we use 4750 gridded terrain samples to quantitatively analyse how the choice of terrain model and scale influence the extraction, generalisation and representation of digitally-derived terrain attributes such as slope, elevation and terrain unit feature extent. We further show how the variation in resulting terrain unit representation is limited by spatial resolution discontinuities of selected elementary soil association distribution, soil texture and soil depth. We also introduce the results of a Similarity Index used to gauge the degree of recall and precision between the different geomorphic landscape features. Finally, the findings of the regional geomorphon-soil relationships are presented in a readily interpretable and qualitative manner, providing a “quasi-landscape signature” for potential localised geomorphons. The application of the study findings may be beneficial to practitioners looking to align or refine modelled terrain classification approaches with expert perception and formalised heuristic approaches.

Highlights • A fully automated, real-time forecasting model for COVID-19 transmission to help frontline health workers and government policy makers. • Use of Artificial intelligence (AI) and Deep Learning to model Infectious diseases without loosing temporal components. • One of the early studies to use LSTM networks to predict the COVID-19 transmission. • We showed the trends of different countries and compared them with Canadian data to predict the future infections., On March 11th 2020, World Health Organization (WHO) declared the 2019 novel corona virus as global pandemic. Corona virus, also known as COVID-19 was first originated in Wuhan, Hubei province in China around December 2019 and spread out all over the world within few weeks. Based on the public datasets provided by John Hopkins university and Canadian health authority, we have developed a forecasting model of COVID-19 outbreak in Canada using state-of-the-art Deep Learning (DL) models. In this novel research, we evaluated the key features to predict the trends and possible stopping time of the current COVID-19 outbreak in Canada and around the world. In this paper we presented the Long short-term memory (LSTM) networks, a deep learning approach to forecast the future COVID-19 cases. Based on the results of our Long short-term memory (LSTM) network, we predicted the possible ending point of this outbreak will be around June 2020. In addition to that, we compared transmission rates of Canada with Italy and USA. Here we also presented the 2, 4, 6, 8, 10, 12 and 14th day predictions for 2 successive days. Our forecasts in this paper is based on the available data until March 31, 2020. To the best of our knowledge, this of the few studies to use LSTM networks to forecast the infectious diseases.

This paper argues that cartographic calculation can be considered as a form of ‘capture’. It suggests that surveillance narratives, typically used to illustrate sovereign forms of power, can be augmented by other socio-technical approaches. Accordingly, the paper develops the idea of capture from media studies to reframe cartographic calculation in computational terms. In doing so, it engages with work in political and digital geography, arguing that the rise of digital devices, apps, platforms and services have led to the generation of huge volumes of event-based knowledges; with significant implications for the study of the calculation. It subsequently argues that cartographic calculation is not, however, solely composed of calculative practices that simply capture cartographic data, but also necessarily composed of calculative practices that add knowledge into, and proliferate renders of, the world. Two dynamics of this oscillating process – anticipation and correspondence – expose the ontogenetic tendencies of cartographic calculation. The paper draws on the use of a digital protest mapping app to exemplify these forces.

Demographic profiling of archaeological assemblages offers a window into the shifting exploitation strategies practiced by ancient societies. High resolution sex-specific age profiles, in particular, have yielded new insights into the evolution of early management practices taken during the initial stages of animal domestication (Zeder, 2001). This paper is the third in a series seeking to develop a method for constructing demographic profiles for Sus scrofa — one of the earliest major livestock species noteworthy for being independently domesticated in both Southwest and East Asia. The first paper in this series (Lemoine et al., 2014) presented a new system for constructing high resolution age profiles using patterns of dental eruption and wear. The second (Zeder et al., 2015) presented a new method for computing high resolution age profiles based on long bone fusion. Both papers used a reference assemblage of modern Eurasian wild boar for developing these new aging schemes, which were then applied to the large assemblage of S. scrofa remains from the Early Holocene age site of Hallan Cemi (c. 11,600 cal. BP) in southeastern Anatolia — an assemblage that previous researchers claimed provided evidence for early steps toward management (Redding, 2005). Here we focus on a subset of this modern reference collection consisting of 34 wild boar skeletons from Turkey, Iran, and Iraq. We employ a Logarithm Size Index scaling (LSI) technique to examine the effect of factors such as age, locality, and, sex on body size in modern wild boar. We find that even though both age and locality have an impact on body size, LSI values derived from select measurements of various different post-cranial elements can be used to classify individual osteological specimens as belonging to immature animals, and, for animals older than about eight months of age, as female or male. We test the reliability of these classifications by comparing the known demographic profiles of the modern reference population against those derived from the LSI classifications. Finally, we apply this new method to the Hallan Cemi assemblage and propose a method for adjusting LSI values to account for temporal size differences encountered between the modern and ancient populations. We also present methods for assessing the reliability of these classifications in the ancient population. We conclude by offering guidelines for the application of this new method to other archaeological assemblages of S. scrofa and other ungulate species that demonstrate strong degrees of sexual dimorphism.

Over the last quarter of a century, analyzing the pace of urbanization and urban economic growth in South Asia has become increasingly important. However, a key challenge relates to the absence of spatially disaggregated national accounts data – in particular, the absence of GDP data for sub-national administrative units and individual cities. The absence of such data limits the scope for detailed empirical analysis of spatial patterns of economic growth, particularly across individual urban settlements or cities. This paper aims to test the suitability of DMSP-OLS Nighttime Lights (NTL) data as a proxy for GDP to analyze detailed spatial patterns of urban economic growth across South Asia over the period 1999–2010. It will help to build an understanding of the nature and heterogeneity of spatial patterns of urban economic growth within the region and contribute to the development of a framework for the usage of NTL to investigate such patterns. Geographic Information System (GIS) is employed to identify the cities and urban agglomerations together with their NTL data in South Asia, and spatial statistics are used to analyze the spatial and temporal patterns of NTL growth. This paper adopts descriptive and inferential statistics to determine the quantitative relationship between NTL and population, urban size, and proximity to the coast. This paper reveals that the inter-annually calibrated NTL data is a good proxy for changes in national and sub-national GDP. In South Asia, the urban NTL hot spots are around major cities with populations between 1.3 and 2.6 million in 1999 and 0.5 to 1.3 million in 2010. Cities in the region have also become more clustered and connected forming urban agglomerations. NTL per unit of land in such clusters tends to be higher than in single cities in South Asia. India, Pakistan, and Sri Lanka tend to have higher NTL (economic) growth on average, while Nepal and Bangladesh have lower growth or declining NTL. There exists a very strong positive linear relation between distance to the coast and the total NTL within that distance, which leads to similar NTL growth rates among inland and coastal cities.

This research provides a method for modelling landscape experience that combines space, time, and landscape character. The visual landscape experience is particularly challenging to model because it involves perception that is specific to an individual, views that vary in extent, a period of time that the experience takes place, and a complex interaction of landform and land-cover, including cultural elements. Landscape experience is important to the quality of people's lives and is a substantial component of the tourism industry. To represent such experiences there is a need to develop techniques to model landscape experience. The method demonstrated is based on the landscape experience while walking a track and combines GIS viewshed analysis with a GIS generated landscape character classification. This method takes into account near and distant landscape views and weights the area that each landscape type is viewed by the length of time that it is viewed. The results produce a new metric that combines space and time and has the units of hectare-hours. This paper argues that there is a need for a unit that combines space and time so that landscape experience can be measured, compared and researched. It is proposed that this unit be called “experions” and this paper shows how such a unit can be measured using GIS. This metric measures landscape character experience rather than quality, but can be converted to quality when combined with landscape preference information.

This study compared three local cluster detection methods to identify local hotspots of human cutaneous anthrax (HCA) transmission in the country of Georgia where cases have been steadily increasing since the dissolution of the Soviet Union. Recent reports have indicated that the disease has reached historical levels in 2012 highlighting the need for better informed policy recommendations and targeted control measures. The purpose of this paper was to identify spatial clusters of HCA to aid in the implementation of targeted public health interventions. At the same time, we compared the utility of different statistical tests in identifying hotspots. We used the Getis-Ord ( G i ∗ ( d ) ) , a multidirectional optimal ecotope-based algorithm (AMOEBA) – a cluster morphology statistic, and the spatial scan statistic in SaTScan™. Data on HCA cases from 2000 to 2012 at the community level were aggregated to an 8 × 8 km grid surface and population data from the Global Rural and Urban Mapping Project (GRUMP) were used to calculate local incidence. In general, there was agreement between tests in the locations of HCA hotspots. Significant local clusters of high HCA incidence were identified in the southern, eastern and western regions of Georgia. The G i ∗ ( d ) and spatial scan statistics appeared more sensitive but less specific than the AMOEBA algorithm. The scan statistic identified larger geographic areas as hotspots of transmission. In general, the spatial scan statistic and G i ∗ ( d ) performed well for spatial clusters with lower incidence rates, whereas AMOEBA was well suited for defining local spatial clusters of higher HCA incidence. In resource constrained areas, efficient allocation of public health interventions is crucial. Our findings identified hotspots of HCA that can be used to target public health interventions such as livestock vaccination and training on proper outbreak management. This paper illustrates the benefits of evaluating statistical approaches for defining disease hotspots and highlights differences in these clustering approaches applicable beyond public health studies.

Although simpler than process based models, state of the art shoreline evolution models based on the idea of cross-shore equilibrium still depend on at least 4 free-parameters. These dynamic equilibrium models are generally based on a kinetic equation in which shoreline change rate is proportional to the existing disequilibrium. Therefore a link between the model driving forces and their corresponding equilibrium shoreline position is necessary for their implementation. Until now this correlation has been established only empirically adding calibration parameters to the model. In this paper, an analytical correlation between the wave energy and the equilibrium shoreline position (“Equilibrium Energy Function”, EEF) is obtained from known invariant beach physical characteristics according to a theoretical bi-parabolic equilibrium beach profile (EBP). A wave driven shoreline evolution model related to cross-shore processes for the medium and long term is then developed with just one free-parameter as the combination of a kinetic equation simply proportional to the wave energy disequilibrium and the proposed analytical EEF. It is remarkable that, at the particular case of the beach of Nova Icaria, where the model has been calibrated and validated by means of two years of video monitoring, the proposed analytical EEF obtained only as a function of the so called EBP invariants fits shoreline observations as well as a calibrated EEF with precisely shoreline observation. The results at Nova Icaria of the proposed model show the same skills with just one calibration parameter than state of the art models with over 4 free-parameters. Nevertheless, observations in different sites with diverse beach characteristics and wave conditions are needed to widely validate the analytical form of the EEF and the shoreline evolution model proposed in this paper.

Spanish Abstract: En un intento de contribuir al desarrollo del derecho ambiental y de las energias renovables en America Latina, los autores sometieron una comunicacion amicus curiae a un Tribunal Federal de Primera Instancia en Argentina. El caso se refiere a una accion colectiva relativa a problemas ambientales derivados de la contaminacion atmosferica producida por una planta de produccion de biodiesel localizada en la ciudad de Cordoba (Argentina). A pesar que los requisitos que exige la Corte Suprema argentina para este tipo de presentaciones fue cumplido, el juez de primera instancia decidio declarar inadmisible el escrito, sin especificar las razones para su rechazo in limine. Los principales argumentos sometidos al Tribunal se encuentran contenidos en el trabajo que se adjunta, el cual se publica como paper en espanol English Abstract: In an attempt to contribute to the legal development of environmental law and renewable energy aspects in Latin America, the authors drafted an amicus curiae file for it submission to a First Instance Federal Tribunal in Argentina. The matter at issue is relevant as it deals with a class action which may involve serious air pollution by a biofuel-processing plant located in the city of Cordoba (Argentina). Although the Argentine Supreme Court’s requirements were met, the first instance judge decided not to admit the file without specifying any reasons for rejecting in limine the submission. The main arguments put forward are contained in the attached paper which is published in Spanish.

Soil mapping is a major goal of soil science. Soil maps rely upon accurate base maps, both for positional reference and to provide environmental data that can assist in the prediction of soil properties. This paper reviews the historical development of base maps used for soil mapping, and evaluates the dependence of soil mapping on base maps. The availability of geographic technology for producing base maps has both constrained and directed the geographic study of soil. The lack of accurate methods for determining location limited early geographic descriptions of soils to narratives, or to listings of attributes for property-based map units. The first real base maps available for soil mapping were outline maps produced in the late 18th century, fueled by governments' interests in documenting national boundaries and popular interest in world atlases. These early soil maps primarily used outline maps as a positional reference onto which soil-related thematic detail was added. Eventually, additional spatial information, in the form of topographic maps and later aerial photographs, increased the predictive role of base maps in soil mapping. In the current digital, geospatial revolution, global positioning systems and geographic information systems have nearly replaced the positional reference function of base maps. Today, base maps are more likely to be used as parameters in soil-landscape models for predicting the spatial distribution of soil properties and classes. Formerly, as a reference for spatial position, paper base maps controlled the cartographic scale of soil maps. However, this relationship is no longer true in geographic information systems. Today, as parameters for digital soil maps, base maps constitute the library of predictive variables and constrain the supported resolution of the soil map.

From 2002 to 2011, West Nile virus mosquitoes (WNV) has been ever-present in traps across Harris County, TX which contains the city of Houston. Disease-positive trap locations have peaked twice, from 2002 to 2006 and then again from 2009 onwards. This paper will examine fine scale spatial and temporal patterns in disease-positive mosquito traps for the Houston area across this time frame, using three different analytical approaches: kernel density, spatial filtering and SaTScan. The purpose of this paper is twofold. Firstly, to identify spatial and space-time clusters of WNV in order to spatially prioritize subsequent research for causative associations. Secondly, to compare the effectiveness of three methods that vary in complexity and ease of use in order to suggest a transferable methodology for mosquito control and environmental health departments across the United States with only lower level GIS skillsets. This paper also illustrates a successful ongoing academic and mosquito control collaboration with the Harris County Public Health Services Mosquito Control Division's (MCD) program.

The scientific subjects addressed in the research into badlands since the publication of Bryan and Yair's book (Bryan, R.B. and Yair, A. (Editors), 1982 Badland geomorphology and piping. Geo Books, Norwich, 408 pp.) are briefly analysed. With a steadily increasing number of papers per year, attention to some aspects, such as runoff generation, piping and the role of lithology and soils, varied, whereas the percentage of studies on erosion rates increased steadily over time. Vegetation was not a subject of research in early papers, as most of the papers dealing with vegetation were rather descriptive and published in local or limited-diffusion media, which contrasts with the present situation when about 40% of papers published in international journals about badlands address some aspect of vegetation. However, the growth in the attention paid to vegetation and erosion rates was not linked to any increase in papers dealing with badland reclamation. Badlands are now seen as a group of systems with some common features but diverse dynamics, depending mainly on climatic and lithological drivers. More attention should be paid in the future to investigating the evolution of these landforms over time, mostly through modelling studies, whereas emerging technologies foster detailed analyses that were not possible formerly. Although some badland areas determine on- and off-site environmental issues, others are spots of landscape diversity that merit protection rather than reclamation.

Street connectivity, defined as the number of (3-way or more) intersections per area unit, is an important index of built environments as a proxy for walkability in a neighborhood. This paper examines its geographic variations across the rural-urban continuum (urbanicity), major racial-ethnic groups and various poverty levels. The population-adjusted street connectivity index is proposed as a better measure than the regular index for a large area such as county due to likely concentration of population in limited space within the large area. Based on the data from the Behavioral Risk Factor Surveillance System (BRFSS), this paper uses multilevel modeling to analyze its association with physical activity and obesity while controlling for various individual and county-level variables. Analysis of data subsets indicates that the influences of individual and county-level variables on obesity risk vary across areas of different urbanization levels. The positive influence of street connectivity on obesity control is limited to the more but not the mostly urbanized areas. This demonstrates the value of obesogenic environment research in different geographic settings, helps us reconcile and synthesize some seemingly contradictory results reported in different studies, and also promotes that effective policies need to be highly sensitive to the diversity of demographic groups and geographically adaptable.

Religion and the expansion of religious sites throughout the built environment have a long and conflict-ridden history. This paper examines the development of three controversial religious sites in Israel that have developed in recent decades in an effort to better understand the kinds of political, social, and locational circumstances that cause some new sites to be regarded as spatially transgressive. The three sites examined here are the Mormon Center in Jerusalem, the Baha'i Gardens in Haifa, and the Church/Mosque in Nazareth. The study is based primarily on 75 structured, open interviews with stakeholders and decision-makers. The broader aim of the paper is to generate a better understanding of the concept of spatial transgression through systematic investigation based on the methodology of “framing.” This methodology provides a comprehensive vocabulary for perceptions, referred to as “frames,” and offers a detailed and systematic typology of frames based on the literature and the empirical data (grounded research) of the case studies. The main findings fall within the three aggregated super-frames identified in the research: “Process,” “Values,” and “Issues.” Of these, the Process super-frame was found to be dominant in all three cases. Comparing the different frames in the three cases enabled us to identify the factors that influenced the transgression process. It also facilitated a better understanding of the different “stories” involved and the concept of spatial transgression, which was found to exist on a scale ranging from low to high intensity. This paper also proposes a framing typology that may prove useful for understanding and mapping similar cases elsewhere.