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Combining studies of animal visual systems with exact imaging of their visual environment can get us a step closer to understand how animals see their “Umwelt”. Here, we have combined both methods to better understand how males of the speckled wood butterfly, Pararge aegeria, see the surroundings of their perches. These males are well known to sit and wait for a chance to mate with a passing females, in sunspot territories in European forests. We provide a detailed description of the males' body and head posture, viewing direction, visual field and spatial resolution, as well as the visual environment. Pararge aegeria has sexually dimorphic eyes, the smallest interommatidial angles of males are around 1°, those of females 1.5°. Perching males face the antisolar direction with their retinal region of the highest resolution pointing at an angle of about 45° above the horizon; thus, looking at a rather even and dark background in front of which they likely have the best chance to detect a sunlit female passing through the sunspot. Supplementary Information The online version contains supplementary material available at 10.1007/s00359-021-01520-3.

For better detecting the spatial-temporal change mode of individual susceptible-infected-symptomatic-treated-recovered epidemic progress and the characteristics of information/material flow in the epidemic spread network between regions, the epidemic spread mechanism of virus input and output was explored based on individuals and spatial regions. Three typical spatial information parameters including working unit/address, onset location and reporting unit were selected and SARS epidemic spread in-out flow in Beijing was defined based on the SARS epidemiological investigation data in China from 2002 to 2003 while its epidemiological characteristics were discussed. Furthermore, by the methods of spatial-temporal statistical analysis and network characteristic analysis, spatial-temporal high-risk hotspots and network structure characteristics of Beijing outer in-out flow were explored, and spatial autocorrelation/heterogeneity, spatial-temporal evolutive rules and structure characteristics of the spread network of Beijing inner in-out flow were comprehensively analyzed. The results show that (1) The outer input flow of SARS epidemic in Beijing concentrated on Shanxi and Guangdong provinces, but the outer output flow was disperse and mainly includes several north provinces such as Guangdong and Shandong. And the control measurement should focus on the early and interim progress of SARS breakout. (2) The inner output cases had significant positive autocorrelative characteristics in the whole studied region, and the high-risk population was young and middle-aged people with ages from 20 to 60 and occupations of medicine and civilian labourer. (3) The downtown districts were main high-risk hotspots of SARS epidemic in Beijing, the northwest suburban districts/counties were secondary high-risk hotspots, and northeast suburban areas were relatively safe. (4) The district/county nodes in inner spread network showed small-world characteristics and information/material flow had notable heterogeneity. The suburban Tongzhou and Changping districts were the underlying high-risk regions, and several suburban districts such as Shunyi and Huairou were the relatively low-risk safe regions as they carried out minority information/material flow. The exploration and analysis based on epidemic spread in-out flow help better detect and discover the potential spatial-temporal evolutive rules and characteristics of SARS epidemic, and provide a more effective theoretical basis for emergency/control measurements and decision-making.

Street greening is an important part of urban landscape, and Green view index (GVI) has an important influence on the comfort of street space environment. In this paper, we analyze the GVI of street space based on big data of street view photos and neural network algorithm. By collecting about 25,000 street view photos from Tencent map, we synthesize the panoramic projection photos of equal area. The image segmentation is achieved by training models through DeeplabV3 + network framework, and then the GVI after image recognition is calculated by OpenCV. The spatial distribution of GVI on the street space is analyzed by means of GIS and other means. In this paper, four spatial regression models are applied to analyze the influencing factors of GVI in the context of urbanization development from three perspectives: historical planning, economic and social. A negative correlation between road class and GVI distribution was obtained. When analyzing the influence of different POI distributions on GVI, it was found that the distribution of hospitals and subway stations was significantly correlated with GVI, and the presence of hospitals in neighborhoods would increase the GVI of surrounding streets. The presence of subway stations, on the other hand, decreases the green visibility of the surrounding streets. This study contributes to the development of human-centered planning and design and provides scientific guidance for the construction and renovation of green space in streets by targeting and optimizing the distribution of specific social facilities in the area.

This paper makes an attempt to review historical and recent seismicity in Delhi and presents updated seismic hazard map of Delhi integrated with ward-wise classified population data. Earthquakes are not destructive unless other factors that enhance the damage prevail. Population density and types or quality of buildings in an area are two such important factors that affect the risk during any hazards, particularly an earthquake. This paper presents the details of the seismic hazard analysis for Delhi with the latest available information on earthquakes and seismic sources within 300 km radius around the city, using state-of-the-art deterministic approach. Ten different attenuation relationships developed for the active tectonic region were considered in the present study. They were ranked using log-likelihood method. Ward-wise population maps along with classified population maps were developed based on the 2011 census data. Hazard contour map and population maps are presented in this paper to revisit the seismic risk prevailing in the region. An attempt was made to overlay the hazard map with population maps showing the distribution of various classes of the population that reflects the seismic risk exposure to different wards of Delhi.

In this paper, we present a systematic analysis of large-scale human mobility patterns obtained from a passive Wi-Fi tracking system, deployed across different location typologies. We have deployed a system to cover urban areas served by public transportation systems as well as very isolated and rural areas. Over 4 years, we collected 572 million data points from a total of 82 routers covering an area of 2.8 km2. In this paper we provide a systematic analysis of the data and discuss how our low-cost approach can be used to help communities and policymakers to make decisions to improve people’s mobility at high temporal and spatial resolution by inferring presence characteristics against several sources of ground truth. Also, we present an automatic classification technique that can identify location types based on collected data.

This research paper aims to model Mass Movements Susceptibility (MMS) in the province of Tétouan. First, we identified the characteristics and spatial mapping of the different types of MM (collapse, mudflows, and complex landslides) by means of the interpretation of satellite images and from fieldwork. Subsequently, we selected the predictive parameters controlling the occurrence of MM e.g. lithology, land use, fault density, hydrographic network density, slope degrees, slope aspects, and elevation. We used the heuristic method for Modeling Mass Movements Susceptibility (MMMS). The choice of this method compared to other methods (fractal, factorial, and neurons) is justified by the possibilities of intervention and the judgment of the expert who relies on the ground truth to select the parameters, to identify the classes, and to assign the weights to each one; unlike to other methods with steps that are done automatically and randomly. The results of the validation of the susceptibility map correspond to 70% compared to the field data and it includes five susceptibility classes (not susceptible, low, moderate, high, and very high). Indeed, the originality of this paper relies on the fact that the creation of our susceptibility map will eventually indicate the areas of roads, dwellings, the extension of urbanization, and dams, which are located in areas at risk of MM. Our map is also a powerful decision-making tool to conduct management plans and to guide the selection of sites to build new projects; which help mitigate the socio-economic impacts usually encountered when mass movements in Tétouan province are triggered.

Geotechnical maps provide preliminary knowledge of sub-surface parameters which help in hazard identification, planning of detailed investigations, mitigation measures, and design for engineering projects. Maps consisting of zones with generalized stratigraphy for an entire area provide uncertain information which may lead to overlooking subsurface geotechnical hazards. In contrast, continuous contour plots consider spatial variation with depth. The purpose of this paper is to make efficient SPT N-value digital maps and soil type maps classified using Unified Soil Classification System (USCS) that indicate N value and soil type at unsampled locations in Islamabad, Pakistan. The geostatistical Kriging approach is unprecedently applied to Islamabad (Pakistan) to develop the contours. The proposed methodology involves integrating geotechnical data with contouring software Surfer 18. Data from fifty geotechnical investigation reports were used to create contour plots of twelve soil types and SPT N values at 3, 5, 10, 15, 20, and 25 ft depth intervals. In addition, a map indicating the depth of groundwater was also developed. The geotechnical contour maps presented in this paper are the first of their kind for Islamabad and lie consistent with geological generalizations of the region. A coefficient of correlation of 0.88 was found for SPT N-values. The output will serve as a supplement for site characterization and hazard identification for future projects.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Many connectivity metrics have been used to measure the connectivity of a landscape and to evaluate the effects of land-use changes and potential mitigation measures. However, there are still gaps in our understanding of how to accurately quantify landscape connectivity. A number of metrics only measure between-patch connectivity, i.e. the connectivity between different habitat patches, which can produce misleading results. This paper demonstrates that the inclusion of within-patch connectivity is important for accurate results. The behavior of two metrics is compared: the Connectance Index (CONNECT), which measures only between-patch connectivity, and the effective mesh size (meff), which includes both within-patch and between-patch connectivity. The connectivity values of both metrics were calculated on a set of simulated landscapes. Twenty cities were then added to these landscapes to calculate the resulting changes in connectivity. We found that when using CONNECT counter-intuitive results occurred due to not including within-patch connectivity, such as scenarios where connectivity increased with increasing habitat loss and fragmentation. These counter-intuitive results were resolved when using meff. For example, landscapes with low habitat amount may be particularly sensitive to urban development, but this is not reflected by CONNECT. Applying misleading results from metrics like CONNECT can have detrimental effects on natural ecosystems, because reductions in within-patch connectivity by human activities are neglected. Therefore, this paper provides evidence for the crucial need to consider the balance between within-patch connectivity and between-patch connectivity when calculating the connectivity of landscapes.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

In this paper, a spatial approach to the Galician megalithic complex (NW Iberian Peninsula) is presented, focusing on first instance on a study of the intensity of sites using a kernel density analysis. This aims to define particular zones with important concentration of sites. The study of five environmental variables selected from literature is carried out in the second part of the paper, analysing whether there is a spatial dependence of the intensity of megaliths on first-order covariates. Finally, approximations to point-pattern analysis, such as nearest neighbour distances or grouping analysis, indicate that we are facing a clustered phenomenon with specific geographic meanings. The results allow us to propose that certain environmental affordances may have determined the locational decisions, debating (from a quantitative point of view) parts of a widely discussed but yet unsystematic academic debate.

Delineation of flood risk hotspots can be considered as one of the first steps in an integrated methodology for urban flood risk management and mitigation. This paper presents a step-by-step methodology in a GIS-based framework for identifying flooding risk hotspots for residential buildings. This is done by overlaying a map of potentially flood-prone areas [estimated through the topographic wetness index (TWI)], a map of residential areas [extracted from a city-wide assessment of urban morphology types (UMT)], and a geo-spatial census dataset. The novelty of this paper consists in the fact that the flood-prone areas (the TWI thresholds) are identified through a maximum likelihood method (MLE) based both on inundation profiles calculated for a specific return period (TR), and on information about the extent of historical flooding in the area of interest. Furthermore, Bayesian parameter updating is employed in order to estimate the TWI threshold by employing the historical extent as prior information and the inundation map for calculating the likelihood function. For different statistics of the TWI threshold, the map of potentially flood-prone areas is overlaid with the map of residential urban morphology units in order to delineate the residential flooding risk urban hotspots. Overlaying the delineated urban hotspots with geo-spatial census datasets, the number of people affected by flooding is estimated. These kind of screening procedures are particularly useful for locations where there is a lack of detailed data or where it is difficult to perform accurate flood risk assessment. In fact, an application of the proposed procedure is demonstrated for the identification of urban flooding risk hotspots in the city of Ouagadougou, capital of Burkina Faso, a city for which the observed spatial extent of a major flood event in 2009 and a calculated inundation map for a return period of 300 years are both available.

Over the past five decades, archaeologists have proposed a wide range of methods for the study of spatial organization within hunter-gatherer sites. Many of these methods sought to identify the spatial location of activities based on patterns of behavior observed in ethnographic contexts. While this resulted in productive observations at certain sites, many of these methods were tailored to specific situations and thus could not be applied to a wide range of sites. For example, open-air sites rarely contain preserved bone or features, such as hearths, which were central components to identifying characteristics of site structure. In addition, many of these methods often did not take into consideration the temporal dynamics of the occupation, i.e., that many sites were formed through subsequent occupations of differing duration. This paper proposes the use of two related methods that assume many assemblages are the result of more than one occupation. The methods target the distribution of lithic artifacts, the most ubiquitously preserved of archaeological materials, and accounts for the potential that the final resting place of artifacts was the result of both intentional and unintentional movement by humans and a host of biological and geological processes. The main goal of this paper is to use an understanding of how these processes influenced the formation of site structure to estimate the relative number and duration of occupations for each site in the sample. These new methods will be presented and explained through the study of seven open-air Middle Paleolithic sites in France but are applicable to a wide range of hunter-gatherer sites.

Mapping regional spatial patterns of coral reef geomorphology provides the primary information to understand the constructive processes in the reef ecosystem. However, this work is challenged by the pixel-based image classification method for its comparatively low accuracy. In this paper, an object-based image analysis (OBIA) method was presented to map intra-reef geomorphology of coral reefs in the Xisha Islands, China using Landsat 8 satellite imagery. Following the work of the Millennium Coral Reef Mapping Project, a regional reef class hierarchy with ten geomorphic classes was first defined. Then, incorporating the hierarchical concept and integrating the spectral and additional spatial information such as context, shape and contextual relationships, a large-scale geomorphic map was produced by OBIA with accuracies generally more than 80%. Although the robustness of OBIA has been validated in the applications of coral reef mapping from individual reefs to reef system in this paper, further work is still required to improve its transferability.

Rainfall-triggered landslides have posed significant threats to human lives and property each year in China. This paper proposed a meteorological-geotechnical early warning system GRAPES-LFM (GRAPES: Global and Regional Assimilation and PrEdiction System; LFM: Landslide Forecast Model), basing on the GRAPES model and the landslide predicting model TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope-Stability Model) for predicting rainfall-triggered landslides. This integrated system is evaluated in Dehua County, Fujian Province, where typhoon Bilis triggered widespread landslides in July 2006. The GRAPES model runs in 5 km×5 km horizontal resolution, and the initial fields and lateral boundaries are provided by NCEP (National Centers for Environmental Prediction) FNL (Final) Operational Global Analysis data. Quantitative precipitation forecasting products of the GRAPES model are downscaled to 25 m×25 m horizontal resolution by bilinear interpolation to drive the TRIGRS model. Results show that the observed areas locate in the high risk areas, and the GRAPES-LFM model could capture about 74% of the historical landslides with the rainfall intense 30mm/h. Meanwhile, this paper illustrates the relationship between the factor of safety (FS) and different rainfall patterns. GRAPES-LFM model enables us to further develop a regional, early warning dynamic prediction tool of rainfall-induced landslides.

Correction to: Nature Ecology & Evolutionhttps://doi.org/10.1038/s41559-016-0003, published online 9 January 2017. In the version of this Article originally published, the values of two of the functions used to calculate the multifunctionality index were incorrect. In particular, the values of phosphatase activity and inorganic phosphorus were a copy of total phosphorus and beta glucosidade activity, respectively, in the database due to translocation of columns in an intermediate step for the calculation of multifunctionality. This mistake results in the overall values of the multifunctionality index (which is calculated as the average of Z-score values of all functions) to be slightly different from those reported in the paper. The main changes resulting from using the correct dataset are: (i) there is less evidence for two multifunctionality states than previously shown, although this variable is still clearly bimodal, (ii) the two multifunctionality states co-occur over a shorter gradient of aridity values (0.75–0.80) than the ones shown in the original manuscript (0.60–0.80) and (iii) some of the relationships between functions shown in Fig. 3 have changed and now in the low-multifunctionality states there are more connections between functions. Despite these changes, the main results and conclusions from the original paper remained consistent after correcting our mistake. As stated and discussed in the original manuscript, there are two multifunctionality states in global drylands, the co-occurrence of which is preceded by an abrupt decrease of the power law range (PLR). Plant cover is the best predictor for linear changes in multifunctionality but only spatial patterns can detect shifts between these two multifunctionality states, which highlights the potential use of spatial patterns as early warning signals. Despite the changes observed in the relationships between some of the functions studied, the functions related to the C and N cycles exhibited fewer connections in high- than in low-multifunctionality states (as was originally discussed in the paper).

A geodemographic classification provides a set of categorical summaries of the built and socio-economic characteristics of small geographic areas. Many classifications, including that developed in this paper, are created entirely from data extracted from a single decennial census of population. Such classifications are often criticised as becoming less useful over time because of the changing composition of small geographic areas. This paper presents a methodology for exploring the veracity of this assertion, by examining changes in UK census-based geodemographic indicators over time, as well as a substantive interpretation of the overall results. We present an innovative methodology that classifies both 2001 and 2011 census data inputs utilising a unified geography and set of attributes to create a classification that spans both census periods. Through this classification, we examine the temporal stability of the clusters and whether other secondary data sources and internal measures might usefully indicate local uncertainties in such a classification during an intercensal period.

This paper describes three datasets of seamless bathymetry and coastal topography for Sydney Harbour (Port Jackson), Botany and Bate Bays, and the Hawkesbury River. The datasets used to form these compilations were the most recent and highest quality available to the authors and were originally collated using the software ESRI ArcGIS. The original compilation of this data was undertaken to support tsunami modelling research by the authors of this paper. Before processing, all data were adjusted and/or reprojected to conform to the vertical datum Australian Height Datum (AHD) and horizontal projection WGS84 UTM zone 56. Data resolution and density was highly variable and grid resolutions of the final datasets were selected as the highest resolutions possible using the most sparse data in the compilation in question. For areas where no data were available, the ESRI ArcGIS interpolation tool, Topo to Raster, was used to provide a best estimate. These dastasets of three important Australian waterways provide a useful tool for coastal research and scientific interest.

The content of this paper refers to the modelling of the geographic environment impact on the off-road vehicles movement in raster format. The common influences of relief slope, micro-relief forms, soils, vegetation, hydrology, built-up areas, meteorological factors, etc. on the vehicle speed deceleration are calculated. To determine the impact of various geographic environment types on the vehicle movement, many field tests and laboratory analysis were provided using military and rescue vehicles. Modelling principle of cross-country vehicle mobility in raster format is based on the idea that each geographic factor "F" located at given elementary terrain area and affecting vehicle speed has its own value of deceleration coefficient Ci. The value of this coefficient expresses the fact of how many times (or percent) a certain geographic factor will decelerate the vehicle speed. The final vehicle deceleration is calculated using synthesis of corresponding raster cells in elementary terrain area in which the influences of geographic factors on vehicle speed are constant. The ArcGIS software suite was used for building the cross-country movement (CCM) database and constructing the CCM map. The database, which has been developed for selected vehicles by the Military Geographical Service of the Czech Armed Forces, should serve as a military geographical support tool during the military and civil operations to improve vehicle navigation. Obsah tohoto příspěvku se týká modelování vlivu geografického prostředí na pohyb terénních vozidel v rastrovém formátu. Jsou vypočítány společné vlivy reliéfního svahu, mikroreliéfních forem, půd, vegetace, hydrologie, zastavěných ploch, meteorologických faktorû apod. na zpomalení rychlosti vozidla. K určení dopadu různých geografických typů prostředí na pohyb vozidel bylo provedeno mnoho terénních zkoušek a laboratorní analýzy pomocí vojenských a záchranných vozidel. Princip modelování mobility mobilních vozidel v rastru je založen na myšlence, že každý geografický faktor "F", který se nachází v dané oblasti a ovlivňuje rychlost vozidla, má svou vlastní hodnotu zpomalovacího koeficientu Ci. Hodnota tohoto koeficientu vyjadřuje, kolikrát (nebo procentuálně) určitý geografický faktor zpomaluje rychlost vozidla. Konečné zpomalení vozidla se vypočte pomocí syntézy odpovídajících rastrových buněk v základní ploše terénu, ve které jsou vlivy geografických faktorů na rychlost vozidla konstantní. Softwarová sada ArcGIS byla použita pro vytváření databáze průchodnosti - cross-country movement (CCM) a pro sestavení mapy CCM. Databáze, která byla vyvinutá pro vybraná vozidla Vojenskou geografickou službou Armády ČR, by měla sloužit jako nástroj vojenské geografické podpory během vojenských a civilních operací s cílem zlepšit navigaci vozidel. The content of this paper refers to the modelling of the geographic environment impact on the off-road vehicles movement in raster format. The common influences of relief slope, micro-relief forms, soils, vegetation, hydrology, built-up areas, meteorological factors, etc. on the vehicle speed deceleration are calculated. To determine the impact of various geographic environment types on the vehicle movement, many field tests and laboratory analysis were provided using military and rescue vehicles. Modelling principle of cross-country vehicle mobility in raster format is based on the idea that each geographic factor "F" located at given elementary terrain area and affecting vehicle speed has its own value of deceleration coefficient Ci. The value of this coefficient expresses the fact of how many times (or percent) a certain geographic factor will decelerate the vehicle speed. The final vehicle deceleration is calculated using synthesis of corresponding raster cells in elementary terrain area in which the influences of geographic factors on vehicle speed are constant. The ArcGIS software suite was used for building the cross-country movement (CCM) database and constructing the CCM map. The database, which has been developed for selected vehicles by the Military Geographical Service of the Czech Armed Forces, should serve as a military geographical support tool during the military and civil operations to improve vehicle navigation.

Due to the important role in theory of reliability, forensic science, study of risk analysis, actuarial science, survival analysis, and many other areas of applied probability, the study of inactivity time and its higher order and partial moments has received considerable attention from many authors. In the present paper we give some further insight on the subject. We provide characterization of some continuous distributions based on higher order moments of inactivity time. It is shown that the distribution function can be obtained uniquely through the higher order moments of inactivity time. Furthermore, we study some characterizations based on partial moments of the inactivity time.

Compared to the urban sprawl in western countries, China’s version varies, although it retains a dispersed development pattern, which is an important feature. A new framework is provided in this paper to allow for a deeper understanding of China’s spatio-temporal sprawl patterns along its urban fringes. In this framework, Shannon’s entropy analysis and discontinuity index have been employed to quantify the spatial patterns of urban sprawl. Furthermore, a new approach, Spatial Change Frequency Analysis (SCFA), has been proposed in this paper to analyze the temporal patterns of urban sprawl related to individual pixel based on multi-temporal Landsat TM images. With two indicators, namely Spatial Change Frequency (SCF) and Spatial Change Intensity (SCI), this approach appears to effectively reveal the abnormal land use changes in the urban fringes. Jiangning District of Nanjing City, Jiangsu Province, a fast growing urban area, was selected as the study area due to its unique characteristics of urban fringes. The results indicate that the effectiveness of urban land-use planning and implementation of land-use planning policies play important roles in mitigating the negative effects of urban sprawl. Finally, some suggestions are proffered to support sustainable development at the urban fringes of Nanjing City.

This paper presents a promising approach to modeling the building resistance in the seismic rehabilitation process. The damage index model (DIM) can be interactively utilized into the Geographical Information Systems (GIS) in order to compute parameters and to analyze data for a quality management purpose. It can perform an easy accessibility of the data to evaluate buildings for earthquake mitigation and preparedness. This research article intended to introduce a software program by using an integration system to design and to dissect the data for evaluating a building resistance against earthquakes. This paper promises a new integrated system for rapid evaluation of buildings, further a city planning by combination of GIS, civil engineering and industrial engineering upon the Federal Emergency Management Agency (FEMA) accompanied by seismic data, structure, parcel, material type, foundation, ceiling, wall, floor, the interior and the exterior. This software has been programmed based on the Damage Index (DI) algorithm that was developed by Pirasteh et al. (Int J Geoinformatics 5(4): 34–41, 2009). Later, based on the proposed algorithm or model the essential parameters have been adopted in Matrix laboratory (MATLAB) environment to yield a new software program for the meliorating earthquake mitigation and preparedness processes. This software program can identify vulnerability of the buildings ranking from 1 to 100. In addition, this paper recommends establishing a scientific procedure in determining the vulnerability of the buildings for earthquake preparedness within a GIS environment. However, this software program can amend in detecting weak structures for rehabilitation.

Present paper focuses on the development of a planning model for upgradation of rural roads keeping Pradhan Mantry Gram Sadak Yoyna (PMGSY) program as the base of this model. Database for the PMGSY roads of Gandevi block of Navasari district in Gujarat state is prepared which includes data like village data, road network & traffic data. Core network is prepared for all the villages under study which can be defined as rural network required for providing ‘basic accesses to all villages. i.e. all villages are connected nearby market centre and essential places from all weather roads. Planning model is classified in two phases. First phase is the network planning and the second phase is upgradation of roads. For the network planning utility values of the villages is calculated by using Delphi technique and on the basis of that alternative routes are decided. For the upgradation of existing roads, Pavement Condition Index (PCI) value of each road is determined and based on these values upgradation of roads are priorities. The rural road network planning methodology for PMGSY roads based on the accessibility concept is presented in this paper and implemented using Geographic Information System (GIS) technology.

The cellular automata (CA) model is an important tool in land use change studies. Swift increases in population and long-term expectations of rapid urbanization have led to extensive land use change, and normal living conditions have affected the natural resources of the land. This paper highlights and analyzes the historical urban changes in Kirkuk City, Iraq, considering repeated changes undergone by the state such change as government infrastructures, wars, and economic blockade. In this paper, an integrated model, built-in multi regression model, and multi-criteria evaluation were considered to improve the representation of CA transition rules. Environmental and socioeconomic factors were used to produce Suitable Maps (SMs). These SMs were practicalities to create factor layers and weight usage, rating method process for variance expert decision-making groups, and geographic information systems for the periods 1984, 1990, 2000, and 2010. The roots of the equation (R2) values are compared and these values are chosen to produce a good model of suitable maps. The approach used in this study provides a mechanism for monitoring suitability maps in Kirkuk. Furthermore, the model Markov CA is implemented and evaluated. The results indicate that the model, its related concepts performs sufficiency

During the last two decades, documentary data (written and iconographic sources) have been increasingly employed in geomorphologic research aiming at reconstruction of territorial distribution, temporal occurrence and social and economic impacts of various geomorphologic hazards. The goal of this paper is to broaden the previous discussion (Glade et al. The use of historical data in natural hazard assessments. Kluwer, Dordrecht, 2001) of the methodological constraints on the use of documentary data for geomorphologic hazard research. Using the interdisciplinary approach of geomorphology, historiography and medial studies, we firstly summarise the major finding of papers that have employed various types of documentary data sources to study geomorphologic hazards in different regions. In the second section, we present case studies from the Czech Republic resulting from the ongoing research project that is devoted to the assessment of the potential of documentary data to reconstruct past occurrences of and mitigation strategies for geomorphologic hazards. Finally, we discuss three main methodological issues emerging from our research: (a) problems emerging from the positivist approach to documentary data sources and the necessity for critical analyses of documentary data sources based on modern historiographic approaches, (b) constraints arising from the combination of documentary data from different spatiotemporal scales and (c) lacks in the use of documentary data to study local-based adaptation strategies to cope with geomorphologic hazards.

The GeoWeb presents an opportunity to expand the array of potential contributors describing the earth through digital geographic information. However, the adoption of user-generated geographic information has not been uniform, resulting in an uneven distribution of content and more nuanced digital divides. This paper uses a survey of Internet users to measure the gender divide in the contributions of cartographic information to the Internet and examine the impact of this divide within the context of OpenStreetMap and Google MapMaker. This paper argues that in both publicly available basemaps the gender divide results in men serving as the gatekeepers of local knowledge leading to gendered user-generated representations. As these digital basemaps are reproduced and utilized by almost every mobile application or web-based map, the gender divisions in the creators and content are endlessly reproduced.

This paper principally focuses on the morphological differences, spatial pattern and regional types of rural settlements in Xuzhou City of Jiangsu Province in China. Using satellite images of Xuzhou City taken in 2007 and 2008 and models of exploratory spatial data analysis (ESDA) and spatial metrics, the paper conducts a quantitative analysis of the morphological pattern of rural settlements, and finds significant characteristics. First, rural settlements in Xuzhou City are significantly agglomerated in terms of their spatial distribution; meanwhile, there is significant variation in the geographical density distribution. Second, the scale of rural settlements in Xuzhou City is larger than the average in Jiangsu Province, and the histogram of the scale data is more even and more like a gamma distribution. There are a significant high-value cluster in the scale distribution, and local negative correlation between the scale and density distribution of rural settlements in Xuzhou City. Third, the morphology of rural settlements in Xuzhou City shows relative regularity with good connection and integrity, but the spatial variation of the morphology is anisotropic. Finally, according to the characteristics of density, scale, and form of rural settlements, the rural settlements of Xuzhou City are divided into three types: A high-density and point-scattered type, a low-density and cluster-like type and a mass-like and sparse type. The research findings could be used as the scientific foundation for rural planning and community rebuilding, particularly in less-developed areas.

When mining large spatio-temporal datasets, interesting patterns typically emerge where the dataset is most dynamic. These dynamic regions can be characterized by a location or set of locations that exhibit different behaviors from their neighbors and the time periods where these differences are most pronounced. Examples include locally intense areas of precipitation, anomalous sea surface temperature (SST) readings, and locally high levels of water pollution, to name a few. The focus of this paper is to find and analyze the pattern of moving dynamic spatio-temporal regions in large sensor datasets. The approach presented in this paper uses a measure of local spatial autocorrelation over time to determine how pronounced the difference in measurements taken at a spatial location is with those taken at neighboring locations. Dynamic regions are analyzed both globally, in the form of spatial locations and time periods that have the largest difference in local spatial autocorrelation, and locally, in the form of dynamic spatial locations for a particular time period or dynamic time periods for a particular spatial node. Then, moving dynamic regions are identified by determining the spatio-temporal connectivity, extent, and trajectory for groups of locally dynamic spatial locations whose position has shifted from one time period to the next. The efficacy of the approach is demonstrated on two real-world spatio-temporal datasets (a) NEXRAD precipitation and (b) SST. Promising results were found in discovering highly dynamic regions in these datasets depicting several real environmental phenomenon which are validated as actual events of interest.

The objective of this paper is to develop a GIS (Geographic Information System) database for Jiuzhaigou National Nature Reserve (Jiuzhaigou, hereafter) in China and demonstrate its application as a research tool. A cost-effective procedure was developed to compile a variety of geographical and biological data of the study area in terms of popular GIS format such as shape files. These files were further calibrated and validated using field surveys data. The developed GIS database was used to quantify the distributions of the wildlife (amphibians, mammals, and birds) using the distances of the wildlife to the centerline of the bus-tour routes. The Pearson correlation coefficient was used to quantify the correlation in space between pairs of different wildlife using the number of habitats for given space contexts. An ArcObject-based macro was developed to perform the analysis. The results showed the majority of the habitats of wildlife are located in the proximity of the tour-bus routes with an average distance ranging from 564 to 894 m depending on types of wildlife. This indicates a possibility of the disturbance to the wildlife by human activities. The correlation coefficient of the wildlife ranged from 0.36 to 0.64 depending on pairs of wildlife, indicating some correlations in space. However, due to the limited sample size, the statistical significances need to be further investigated. This paper has successfully demonstrated the use of the GIS-based database as a research tool for environmental study.

This paper is devoted to describe a new method of fuzzy logic applied to multi geohazards macro-zone maps. The basic steps are (1) compilation of macro-zone maps for each type of geohazard phenomenon. Each phenomenon is then assigned one of seven geohazard zones: very low, low, relatively low, moderate, relatively high, high, and very high; (2) definition of a membership function using a fuzzy logic algorithm to quantify the qualitative data, estimate a geohazard grade for each mesh point, and to convert qualitative maps to quantitative maps; (3) computation of the summed hazard grade for each mesh point and creation a cumulative geohazard map; and (4) compilation of a multi geohazards macro-zone map by defining a mathematical algorithm and again using fuzzy logic. The paper also describes a mechanism that takes subjective engineering judgments into account. Finally, a geohazard map with a scale of 1:25,000 (Rahdar district, Khuzestan, Iran) is compiled. This study divides the area into seven geohazard macro-zones. Zones of high and very high geohazard classification cover most of the area due to the large number of sinkholes and asymmetric subsidences, rock falls and other slop movements. Low and very low hazard zones only cover small localities.

The addition of the “News in Brief” series to our Views and News section will highlight recent significant research in the last year—from high-impact papers to emerging research fronts—and will include papers with both classic and new hot topics. This series will offer a rotating view among the major Earth Science areas, as various experts will be invited to provide a brief look around the recent research conducted in their area. This selection of research papers is left up to each expert and due to the broadness of each field is not intended to be a comprehensive overview. Links to the published work are provided in each section. David Carlson, former Director of the International Programme Office for the International Polar Year, has been invited to provide a glimpse into the latest findings in polar science. Carlson outlines selected research of global relevance hoping that readers will “discover the fascinating connections among and across these topics, and the unintended prominence of three restless partners: ocean, wind and ice”.

This paper presents rational polynomial coefficients (RPC) block adjustment model and its application as a new concept for the accuracy of environmental research, cartography and geomarketing. With the influence of information technology (IT) rapid development, Geographic Information Systems and remote sensing, the application of cartography, has gradually evolved from the form of paper into digitized and computerized data, from traditional formats such as vector maps into Satellite Image Maps (SIM). Particularly, remotely sensed images are a major data source to observe the earth and; have been extensively integrated into spatial–temporal analysis in environmental research. To effectively use high resolution satellite images for use in environmental monitor research, cartography and geomarketing, the accuracy of the satellite image photogrammetric process is an important issue. The aim of this paper is to apply the block adjustment of RPC models to evaluate the precision of satellite image for the use of environmental research, cartography and geomarketing, which is not found in previous literature. To verify the effectiveness of RPC Block Adjustment, this study also adapted Technology Acceptance Model (TAM) to develop a questionnaire for conducting the implementation investigation. The results showed the method is useful and powerful for the various applications and research.

The paper focuses on automatic extraction building stock information for quantifying physical exposure and its vulnerability from High and Very High Resolution (VHR) optical satellite imagery. We use two case studies. In Sana’a (Yemen) we use automatic techniques to extract the building stock as well as building height that is used to characterize its vulnerability. In Port-au-Prince (Haiti) – in the area affected by the 2010 earthquake -we map the building stock based on a pre-disaster imagery – and we show the added value of area based information when added to point based damage assessment from visual change interpretation of post disaster aerial images. The paper shows that VHR imagery can be used to locate and quantify the building stock and its height. This paper also shows that damages measured from changes detected from pre-and post-disaster imagery can in principle map and provide vulnerability information related to the structural fragility of the building stock., JRC.G.2-Global security and crisis management

Over the years, urban growth models have proven to be effective in describing and estimating urban development and have consequently proven to be valuable for informed urban planning decision. Therefore, this paper investigates the implementation of an urban growth Cellular automata (CA) model using a GIS platform as a support tool for city planners, economists, urban ecologists and resource managers to help them establish decision making strategies and planning towards urban sustainable development. The area used as a test case is the River Shannon Basin in Ireland. This paper investigates the spatio-temporally varying effects of urbanization using a combined method of CA and GIS rasterization. The results generated from Cellular automata model indicated that the historical urban growth patterns in the River Shannon Basin area, in considerable part, be affected by distance to district centres, distance to roads, slope, neighbourhood effect, population density, and environmental factors with relatively high levels of explanation of the spatial variability. The optimal factors and the relative importance of the driving factors varied over time, thus, providing a valuable insight into the urban growth process. The developed model for Shannon catchment has been calibrated, validated, and used for predicting the future land use scenarios for the future time intervals 2020, 2050 and 2080. By involving natural and socioeconomic variables, the developed Cellular automata (CA) model had proved to be able to reproduce the historical urban growth process and assess the consequence of future urban growth. This paper presented as a novel application to the integrated CA-GIS model using a complicated land use dynamic system for Shannon catchment. The major conclusion from this paper was that land use simulation and projection without GIS rasterization formats cannot perform a multi-class, multi factors analysis which makes high accuracy simulation is impossible.

A research paper’s contribution exists not only in its originality and creativity but also in its continuity and development for research that follows. The reference section can play a key role to researchers who are interested in a paper’s statement or who would like to follow the study or find useful information from the paper. This section is as important as the core of a paper; however, it was easily to be ignored by the author. This comment offered information for citing original idea of methods, figures, and tables which Zhi et al. (Environ Earth Sci 74(7):6065–6075, 2015) used. It is also suggested that an author not only must be creative but also must be careful while writing in order to publish more valuable and papers more worthy of reading.

The main aim of this paper is to develop a new hybrid method to assess landslide susceptibility mapping (LSM) in neighboring provinces of Alborz Mountains in Iran. In the last centuries, this region has experienced a large number of landslides due to its location on earthquake belt, with high precipitation in some parts and having varied topography. Besides, the largest city of Iran (Tehran), a lot of important infrastructures, congested roads and a large population are located in this region. Therefore, determining the spatial outlines of the regions which are prone to future landslides is a critical issue. To reach this goal, the LSM is provided by applying a hybrid model of statistical index (Wi) and adaptive neuro-fuzzy inference system (ANFIS) in a Geographic Information System. In the first step, landslide inventory map was divided into two groups randomly. These groups are training dataset including 70 % recorded landslides and the remaining 30 % was used to test the model output. The first and second groups are used to determine the weights in model and validation of results, respectively. Then, 12 landslide conditioning factors are selected and categorized into two groups which are continuous numerical and nominal. After that, each factor is classified and the weight of each class is determined using Wi. The outputs of Wi and Wi-ANFIS were employed to determine nominal and continuous numerical data, respectively. In the Wi-ANFIS approach, the calculated weights of each class is allocated to the center of each class, and the rest weights of values are determined by ANFIS which is an artificial algorithm using training data (in this paper, the weights were calculated by Wi) in terms of predicting and interpolating. The results are evaluated using receiver operation curves including success rate curve and predicted rate curve. The validation results of the proposed hybrid method shows that the area under the curve of success rate curve and predicted rate curve are 0.90 and 0.89, respectively, which have been improved in comparison with Wi. The results pr oved that the suggested model applied in this study generated reliable LSM which can be applicable for primary land use planning and infrastructure site selection.

Background: Over the last years, the new role of Land Administration in realising the Information Infrastructure and the need to address spatial and non- spatial land related data exchange between countries emerged and since then, standard models were created and put into use. Two examples of these standards are the Land Administration Domain Model and INSPIRE's Cadastral Parcels. The former is an official international standard with a great deal of prospects; it is based on the 'people - land' relationship and has many applications apart from storingdata about properties. The latter is part of a specification framework (set of rules) describing how cadastral parcels can serve as reference for creating a European Spatial Data Infrastructure, enabling cross border dissemination ofdata. Methods: This paper provides the design of a conceptual model in conformance with both standards. Within this context a Land Administration Domain Model - compliant country profile and the INSPIRE model for Cadastral Parcels are proposed based on characteristic cases from the Hellenic Cadastre. Applying LADM brings along the collective international expertise on various aspects, which are analysed and applied for Greece: including administrative and spatial sources, supporting historical data (versioning), integration of legal (rights) and spatial data (cadastral map), including different register types (Archaeological, Urban, Rural, Forest), and allowing for an integrated 3D registration.Results: This research results in a model that can be used as a transition from the current cadastral system to a fully LADM- compliant one, taking also into account the INSPIRE directive. The paper further investigates how thedeveloped conceptual model, may be automatically converted to a technical model using Model Driven Architecture. Problematic issues and constraints are highlighted when applying the Model Driven Architecture approach and suggestions for resolving these issues are described.Conclusions: It is feasible to develop a conceptual model (country profile) which is in conformance with multiple standards, LADM and INSPIRE, because these are well aligned. Cross-boundary land administration is more than ever a very important requirement in todays’ global and European community. This is where the adoption of standards comes to play in realising the Information infrastructure.

This work addresses the use of remote sensing imagery to quantify the built environment and its spatial and temporal changes. It identifies building footprint map, building location map and built-up area map as information products that can be used to quantify physical exposure, one of the variables required in disaster risk assessments. The paper also reviews urban land use maps and urban classes in land cover maps as potential source for deriving exposure information. The paper focuses on the latest generation of satellite-borne remote sensing imaging systems that deliver high-resolution optical imagery able to resolve buildings and other three-dimensional man-made constructions. This work also reviews the semantics, the spatial unit used to define physical exposure, image processing procedures and change techniques.

In order to develop efficient strategies for risk mitigation and emergency management, planners require the assessment of both the expected hazard (frequency and magnitude) and the vulnerability of exposed elements. This paper presents a GIS-based methodology to produce qualitative to semi-qualitative thematic risk assessments for tephra fallout around explosive volcanoes, designed to operate with datasets of variable precision and resolution depending on data availability. Due to the constant increase in population density around volcanoes and to the wide dispersal of tephra from volcanic plumes, a large range of threats, such as roof collapses, damage to crops, blockage of vital lifelines and health problems, concern even remote communities. To address these issues, we have assessed the vulnerability and the risk levels for five themes relevant to tephra fallout: (1) social, (2) economic, (3) environmental, (4) physical and (5) territorial. Risk and vulnerability indices for each theme are averaged to the fourth level of administrative unit (parroquia, parish). In a companion paper, Biass and Bonadonna (this volume) present a probabilistic hazard assessment for tephra fallout at Cotopaxi volcano (Ecuador) using the advection-diffusion model TEPHRA2, which is based on field investigations and a global eruption database (Global Volcanism Program, GVP). The scope of this paper is to present a new approach to risk assessment specifically designed for tephra fallout, based on a comprehensive hazard assessment of Cotopaxi volcano. Our results show that an eruption of moderate magnitude (i.e. VEI 4) would result in the possible collapse of ∼9,000 houses in the two parishes located close to the volcano. Our study also reveals a high risk on agriculture, closely linked to the economic sector, and a possible accessibility problem in case of an eruption of any size, as tephra is likely to affect the only major road running from Quito to Latacunga (Panamerican Highway). As a result, this method fits into the ongoing effort to better characterize and evaluate volcanic risk, and more specifically the risk associated with tephra fallout. Although this methodology relies on some assumptions, it can serve as a rapid and efficient starting point for further investigations of the risk level around explosive volcanoes.

WOS: 000308329900030, Landslide hazard or susceptibility assessment is based on the selection of relevant factors which play a role on the slope instability, and it is assumed that landslides will occur at similar conditions to those in the past. The selected statistical method compares parametric maps with the landslide inventory map, and results are then extrapolated to the entire evaluated territory with a final product of landslide hazard or susceptibility map. Elements at risk are defined and analyzed in relation with landslide hazard, and their vulnerability is thus established. The landslide risk map presents risk scenarios and expected financial losses caused by landslides, and it utilizes prognoses and analyses arising from the landslide hazard map. However, especially the risk scenarios for future in a selected area have a significant importance, the literature generally consists of the landslide susceptibility assessment and papers which attempt to assess and construct the map of the landslide risk are not prevail. In the paper presented herein, landslide hazard and risk assessment using bivariate statistical analysis was applied in the landslide area between Hlohovec and Sered' cities in the south-western Slovakia, and methodology for the risk assessment was explained in detail.

The form of the urban fabric plays an important role in urban morphology which not only expresses the city’s overall morphological features, but also describes the relationships between buildings and plots, which are called patterns. The majority of morphological studies have focused on the street network pattern, the plot pattern and the building pattern or typology. In the other hand, the form of the urban fabric also reflects the city’s space character, such as street spatial outline, visual variety, and spatial typologies, which are directly related to the quality of urban space. Although these characters influence the urban design decision-taking, the current research has not reached an effective level. With a special focus on potentials for urban design, this paper proposes an account of how building position affects the street spatial pattern. Based on the viewshed analysis in GIS, the variance between the form of the urban fabric and the street viewshed pattern could be measured. The study samples were 600 meters square samples of urban fabric image selected from different cities of Europe, America, and China. This paper proposes a new kind of pattern: street spatial related line (SSRL) pattern. Through viewshed simulating it shows that there is a strong relationship between SSRL pattern and street spatial configuration, and that visual statistical diagrams could indicate the street spatial characters.

Indoor radon is an important risk factor for human health. Indeed radon inhalation is considered the second cause of lung cancer after smoking. During the last decades, in many countries huge efforts have been made in order to measuring, mapping and predicting radon levels in dwellings. Various researches have been devoted to identify those areas within the country where high radon concentrations are more likely to be found. Data collected through indoor radon surveys have been analysed adopting various statistical approaches, among which hierarchical Bayesian models and geostatistical tools are worth noting. The essential goal of this paper regards the identification of high radon concentration areas (the so-called radon prone areas) in the Abruzzo Region (Italy). In order to accurately pinpoint zones deserving attention for mitigation purpose, we adopt spatial cluster detection techniques, traditionally employed in epidemiology. As a first step, we assume that indoor radon measurements do not arise from a continuous spatial process; thus the geographic locations of dwellings where the radon measurements have been taken can be viewed as a realization of a spatial point process. Following this perspective, we adopt and compare recent cluster detection techniques: the simulated annealing scan statistic, the case event approach based on distance regression on the selection order and the elliptic spatial scan statistic. The analysis includes data collected during surveys carried out by the Regional Agency for the Environment Protection of Abruzzo (ARTA) in 1,861 random sampled dwellings across 277 municipalities of the Abruzzo region. The radon prone areas detected by the selected approaches are provided along with the summary statistics of the methods. Finally, the methodologies considered in this paper are tested on simulated data in order to evaluate their power and the precision of cluster location detection.

This paper aims to analyse and compare the loss of life that occurred during two recent floods in France. The first flood was due to a sea surge triggered by the storm called Xynthia that hit the Atlantic coast on 28 February 2010 (41 flood-related deaths). The second was a flash flood that struck the Var Department in the French Mediterranean region on 15 June 2010 (26 fatalities). After detailing the assumptions and expected outcomes of the study of disaster-related fatalities, the paper focuses on the characteristics of the victims and the circumstances of their deaths. In the first case, 71% of the victims were people aged over 60 (mainly women) who were surprised while they were sleeping and who died in or near their homes. In the case of the flash flood, the profiles of the victims were diverse as the flooding occurred in the afternoon and many people were trapped in open. The paper also highlights the factors that explain mortality. Physical factors such as water depth were determined. The relationship between the water depth and the age of victims was found to be relevant. In the case of the storm surge Xynthia, the correlation between age and water depth is positive. For the flash flood, the correlation between age and water depth was negative as male adults died in open. In the first case, the vulnerability of people was closely linked to human features such as type of housing and age that people are not directly responsible for. During flash floods, dangerous behaviour by people highlighted the role of risk-taking in loss of life. We also examined the particular case of the deaths of the children. The paper concludes by discussing the factors of vulnerability on frail population such as elderly people or marginalized. The lack of risk awareness and crisis preparedness were clearly a major factor of vulnerability.

The study described in this paper investigates the relative merits of two peer-reviewed earthquake-induced landslide models using participatory model assessment. The earthquake-induced landslide hazard models assessed are a simplified Newmark’s displacement model and a recently developed knowledge-based model. Participatory model assessment involves conducting facilitated participatory processes where the model(s) are used for aiding decisions within a socio-behavioral experiment designed for collecting data to evaluate formal hypotheses about the model(s). The paper sets out the design of the participatory model assessment—a series of workshops involving experts and potential model end-users that incorporated a roleplay site selection task. Quantitative data elicited using a set of entrance and exit questionnaires were analyzed to investigate hypotheses about the models. Participants found the knowledge-based model to be significantly more complete and more informative for their roleplay task. Overall, the two models did not yield significant differences with respect to issues such as task efficiency or task outcome satisfaction. Lastly, it was found that education level and disciplinary perspectives (of those analyzed) did not significantly affect outcomes, suggesting that a wide demographic of participants can be used for participatory model assessments. Additional research is needed to assess the models in different contexts, as well as more broadly developing a set of best practices for conducting participatory model assessments of other natural hazard and risk models intended to support decision-making.