An Efficient Approach for Historical Storage and Retrieval of Segmented Road Data in Geographic Information System for Transportation

One of the most powerful functions of Geographic Information System for Transportation (GIS-T) is Dynamic Segmentation (DS), which is used to increase the efficiency and precision of road management by generating segments based on attributes. The road segments describing transportation data are both spatially and temporally referenced. For a variety of transportation applications, historical road segments must be preserved. This study presents an appropriate approach to preserve and retrieve the historical road segments efficiently. In the proposed method, only the portions of segments of a time stamp that have been changed into new segments rather than storing the entire segments for every old time stamp are recorded .The storage of these portions is based on the type of changes. A recursive algorithm is developed to retrieve all segments for every old time stamp. Experimental results using real data of Tehran City, Iran justify the strength of the proposed approach in many aspects. An important achievement of the results is that database volume for 2006, 2007 and 2008 within the Historical Line Event Table (HLET) is reduced by 70%, 80% and 78%, respectively. The proposed method has the potential to prevent from vast data redundancy and the unnecessary storage of entire segments for each time stamp. Since the present technique is performed on ordinary plain tables that are readable by all GIS software, special software platforms to manage the storage and retrieval of historical segments are not needed. In addition, this method simplifies spatio-temporal queries.

Modelling the probability of presence of Aedes aegypti and Aedes albopictus in Iran until 2070

Objective:To determine the suitable ecological habitats of Aedes(Ae.)aegypti and Ae.albopictus in Iran due to climate change by the 2070s.Methods:All data relating to the spatial distribution of Ae.aegypti and Ae.albopictus worldwide,which indicated the geographical coordinates of the collection sites of these mosquitoes,were extracted from online scientific websites and entered into an Excel file.The effect of climatic and environmental variables on these mosquitoes was evaluated using the MaxEnt model in the current and future climatic conditions in the 2030s,2050s,and 2070s.Results:The most suitable areas for the establishment of Ae.aegypti are located in the southern and northern coastal areas of Iran,based on the model outputs.The modelling result for suitable ecological niches of Ae.albopictus shows that in the current climatic conditions,the southern half of Iran from east to west,and parts of the northern coasts are prone to the presence of this species.In the future,some regions,such as Gilan and Golestan provinces,will have more potential to exist/establish Ae.albopictus.Also,according to the different climate change scenarios,suitable habitats for this species will gradually change to the northwest and west of the country.The temperature of the wettest season of the year(Bio8)and average annual temperature(Bio1)were the most effective factors in predicting the model for Ae.aegypti and Ae.albopictus,respectively.Conclusions:It is required to focus on entomological studies using different collection methods in the vulnerable areas of Iran.The future modelling results can also be used for long-term planning to prevent the entry and establishment of these invasive Aedes vectors in the country.

The Characterization of Damage of the Pipes Made from Stainless Steel

The damage was noted during the usage of the pipe system which was made out of austenite steel 316L on the assembly line for the production of urea. In order to find out the cause of such damage, the samples of pipes were taken at the places where the most damage took place. Samples were taken in the form of film, sediment and/or sludge from inner and the outer surface of the pipes. As well as each pieces of pipes were further cut into 10 mm x 10 mm plates. The prepared samples were studied using X-ray diffraction, X-ray emission spectrometry, scanning electron microscope and microanalysis as well as a light microscope. The results implicate microstructural changes within the inner wall of the pipe which was caused by intercrystalline corrosion. Such corrosion in the investigated samples of sediment and/or sludge appeared due to the damage of the protective film during the aggressive phases,

Application of Digital Image Correlation and Geodetic Displacement Measuring Methods to Monitor Water Dam Behavior under Dynamic Load

This paper presents experiment results of the measurement conducted at the Roznew Dam power plant. For a course of starting and operating of turbo-plants, downstream face of the dam was monitored in relation to its eventual displacements on direction parallel to the construction axis. For the purpose of the experiment, geodetic measurement techniques and 2D DIC （digital image correlation） method （utilizing photographs of the object recorded with digital camera） were compared with regard to credibility, efficiency and accuracy. The vertical and horizontal displacements were monitored by tachometers measurements. The deformations in x-axis and y-axis on the wall surface was monitored by 2D DIC. It has been noticed that 2D DIC method is a surface method, continuous--not discreet. It allows for continuous observations of surface deformations, which is not possible in case of tachemetric measurements. Despite many advantages, the 2D DIC method lacks unambiguous evaluation of precision and relevance of designated displacements, which is rather significant for possibilities of utilization in technical control of large engineered objects. It should be also marked that the tachometric method is more reliable but is more laborious. Research of this type might comprise additional element for the assessment of the influence of dynamic loads, such as activating turbine water flow, onto the overall condition of the surveyed structure.

Uncovering implicit Seismogenic associated regions towards promoting urban resilience

Earthquakes pose a significant threat to urban environments,highlighting the need for enhanced seismic resilience.To improve understanding of earthquake dynamics and the interplay of seismic activity across space,this study introduces a novel approach for identifying associated regions that exhibit interdependence seismic behavior,revealing a network structure of earthquake interplays.This model was applied to earthquakes exceeding 3.0 Mw in Iran(1976–2023),using a 1°×1°grid.Monthly and seasonal timespans were evaluated to capture potential short-term and long-term interactions.The model revealed a network of interdependent seismic regions in southern and southwestern Iran,predominantly located within the Zagros belt.Notably,the strongest associations were observed between spatial units 45 and 36,located approximately 6°apart in southern Iran.These units exhibited significant association in both monthly and seasonal scenarios,with support values of 0.28 and 0.65,and average confidence values of 0.58 and 0.84,respectively.The second significant bilateral relation was detected between neighboring spatial units 22 and 36,with support values of 0.26 and 0.59,and average confidence values of 0.57 and 0.80,respectively.The recognized structure was compared to the established seismotectonic zoning.This network aligns with established seismotectonic provinces,particularly in the seasonal scenario.The model also identified potential interactions between distinct zones in the monthly scenario,highlighting areas where urban development strategies might need reevaluation.Additionally,the analysis revealed implicit causal relationships between spatial units,pinpointing areas susceptible to or influencing seismic activities elsewhere.These results contribute to a deeper understanding of crustal structure,earthquake propagation,and the potential for seismic activity to trigger earthquakes in nearby or distant areas.This knowledge is crucial for developing effective strategies to build earthquake-resilient cities.

Approximately Conformal,Equivalent and Equidistant Map Projections

If geodetic coordinates from an ellipsoid are included in the equations of a projection for mapping a sphere instead of geographical coordinates,the result will be a projection of the ellipsoid into a plane.This will slightly change the distortion distribution of the initial map projection.The question is to what extent the replacement of geographical with geodetic coordinates will affect this change.In this paper,we deal with conformal,equal-area and equidistant projections of the sphere,which we modify by using geodetic coordinates instead of geographical ones.The result will be an approximately conformal,approximately equal-area and approximately equidistant projection.It is shown that in this case the maximum distortion of the angles in approximately conformal projections will be approximately 23.09′,the maximum distortion of the area in approximately equal-area projections less than 0.7% and the maximum distortion of lengths in approximately equidistant projections less than 0.7%,therefore on the maps imperceptible.

A new model describing Forbush Decreases at Mars: combining the heliospheric modulation and the atmospheric influence

Forbush decreases are depressions in the galactic cosmic rays (GCRs) that are caused primarily by modulations of interplanetary coronal mass ejections (ICMEs) but also occasionally by stream/corotating interaction regions (SIRs/CIRs). Forbush decreases have been studied extensively using neutron monitors at Earth;recently, for the first time, they have been measured on the surface of another planet, Mars, by the Radiation Assessment Detector (RAD) on board the Mars Science Laboratory’s (MSL) rover Curiosity. The modulation of GCR particles by heliospheric transients in space is energy-dependent;afterwards, these particles interact with the Martian atmosphere, the interaction process depending on particle type and energy. In order to use ground-measured Forbush decreases to study the space weather environment near Mars, it is important to understand and quantify the energy-dependent modulation of the GCR particles by not only the pass-by heliospheric disturbances but also by the Martian atmosphere. Accordingly, this study presents a model that quantifies both at the Martian surface and in the interplanetary space near Mars the amplitudes of Forbush decreases at Mars during the pass-by of an ICME/SIR by combining the heliospheric modulation of GCRs with the atmospheric modification of such modulated GCR spectra. The modeled results are in good agreement with measurements of Forbush decreases caused by ICMEs/SIRs based on data collected by MSL on the surface of Mars and by the Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft in orbit. Our model and these findings support the validity of both the Forbush decrease description and Martian atmospheric transport models.

Gaussian Radial Basis Function interpolation in vertical deformation analysis

In many deformation analyses,the partial derivatives at the interpolated scattered data points are required.In this paper,the Gaussian Radial Basis Functions(GRBF)is proposed for the interpolation and differentiation of the scattered data in the vertical deformation analysis.For the optimal selection of the shape parameter,which is crucial in the GRBF interpolation,two methods are used:the Power Gaussian Radial Basis Functions(PGRBF)and Leave One Out Cross Validation(LOOCV)(LGRBF).We compared the PGRBF and LGRBF to the traditional interpolation methods such as the Finite Element Method(FEM),polynomials,Moving Least Squares(MLS),and the usual GRBF in both the simulated and actual Interferometric Synthetic Aperture Radar(InSAR)data.The estimated results showed that the surface interpolation accuracy was greatly improved by LGRBF and PGRBF methods in comparison withFEM,polynomial,and MLS methods.Finally,LGRBF and PGRBF interpolation methods are used to compute invariant vertical deformation parameters,i.e.,changes in Gaussian and mean Curvatures in the Groningen area in the North of Netherlands.

A Context-Aware Approach for the Spatial Data Infrastructure Portal

The infrastructure of most of the practical and construction activity in communities is based on correct understanding and proper use of spatial data in GIS1?and SDI2. Optimal and efficient use of infrastructure systems of the spatial data by users, depends on how to search and access of user to proper and desired data among informative sources of various organizations. Search operation and access of users to various information of multiple sources located on Spatial Data Infrastructure Network is confusing and time-consuming due to diversity and relatively high volume of spatial information. Because there are numerous classes and subclasses of various complications on the pattern of SDI, unaware user to the pattern may be confused in select displaying the proper spatial layer. In optimum condition, the user should have access to the appropriate data type based on his status and task and environmental conditions. Making intelligent Graphical User Interface by inference based on task information user and his expertise, the appropriate information and consistent with conditions will be achieved. Selecting and displaying of spatial layers related to the technical-organizational approach of system user provides him special assistance both in terms of filtering the irrelevant data and speed of operation in access optimal information than non-selective displaying state. For this purpose, designing and employment context-aware techniques in servicing user interface of system based on recognition of the technical expertise of the user can be a good solution in data adaptive displaying and context-aware servicing to users.

Land Tenure and Land Consolidation Issues in Bosnia and Herzegovina and Croatia

Bosnia and Herzegovina and Croatia are post-war and post-socialist countries having partly common history and problems regarding land tenure and land consolidation, but, due to the different recent development, they are tackling detected problems in different manner. Internal problems regarding land ownership, privatization and corruption, together with negative consequences of globalization and economic crisis resulted in the downfall of land usage for food production having visible impact on prosperity of the nations. The expansion of farming area represents therefore one of the priorities for both countries. Without well kept and well managed land registers, and without the development of efficient land tenure mechanisms, the mentioned problems can hardly be solved, hence, both countries are paying great attention to solving these problems. Bosnia and Herzegovina fighting with the reducing size of uncultivated land, initiated the land consolidation activities on pilot locations in Oragje, Ravno and Trebinje after twenty years. Croatia has focused its activities on dealing with the issues related to the registration of state-owned agricultural land and on developing the efficient system for land tenure. For this purpose, different kinds of projects related to land registration, land consolidation, and finally the State agricultural land IT system establishment project have been executed. In this paper, an overview of the executed activities, the achieved results and detected problems is given indicating also further activities.

Combined forest and soil management after a catastrophic event

At the end of October 2018,a storm of unprecedented strength severely damaged the forests of the eastern sector of the Italian Alps.The affected forest area covers 42,500 ha.The president of one of the damaged regions asked for help from the University of Padua.After eight months of discussion,the authors of this article wrote a consensus text.The sometimes asper debate brought to light some crucial aspects:1)even experienced specialists may have various opinions based on scientific knowledge that lead to conflicting proposals for action.For some of them there is evidence that to restore a destroyed natural environment it is more judicious to do nothing;2)the soil corresponds to a living structure and every ecosystem’s management should be based on it;3)faced with a catastrophe,people and politicians find themselves unarmed,also because they rarely have the scientific background to understand natural processes.Yet politicians are the only persons who make the key decisions that drive the economy in play and therefore determine the near future of our planet.This article is an attempt to respond directly to the governor of a region who formally and prudently asked a university department called"Land,Environment,Agriculture and Forestry"for help before taking decisions;4)the authors also propose an artistic interpretation of facts(uncontrolled storm)and conclusions(listen to the soil).Briefly,the authors identify the soil as an indispensable source for the renewal of the destroyed forest,give indications on how to prepare a map of the soils of the damaged region,and suggest to anchor on this soil map a series of silvicultural and soil management actions that will promote the soil conservation and the faster recovery of the natural dynamic stability and resilience.

Assessment of different topographic correction methods in ALOS AVNIR-2 data over a forest area

Because the removal of topographic effects is one the most important preprocessing steps when extracting information from satellite images in digital Earth applications,the problem of differential terrain illumination on satellite imagery has been investigated for at least 20 years.As there is no superior topographic correction method applicable to all areas and all images,a comparison of topographic normalization methods in different regions and images is necessary.In this study,common topographic correction methods were applied on an ALOS AVNIR-2 image of a rugged forest area,and the results were evaluated through different criteria.The results show that the simple correction methods[Cosine,Sun-Canopy-sensor(SCS),and Minnaert correction]are inefficient in exceptionally rough forests.Among the improved correction methods(SCSC,modified Minnaert,and pixel-based Minnaert),the best result was achieved using a pixel-based Minnaert approach in which a separate correction factor in various slope angles is used.Thus,this method should be considered for topographic correction,especially in forests with severe topography.

Local linear scale factors in map projections in the direction of coordinate axes

This paper explains that the terms“horizontal and vertical scales”are not appropriate in map projections theory.Instead,the authors suggest using the term“scales in the direction of coordinate axes.”Since it is not possible to read a local linear scale factor in the direction of a coordinate axis immediately from the definition of a local linear scale factor,this paper considers the derivation of new formulae that enable local linear scale factors in the direction of coordinate x and y axes to be calculated.The formula for computing the local linear scale factor in any direction defined by dx and dy is also derived.Furthermore,the position and magnitude of the extreme values of the local linear scale factor are considered and new formulas derived.

Exploring the applications of 3D proximity analysis in a 3D digital cadastre

Increasing population in urban areas and limitations of suitable lands for developing houses and urban infrastructure have led to the vertical development in cities.However,these developments are managed by a cadastral system which is mainly two-dimensional and cannot efficiently represent Rights,Restrictions,and Responsibilities(RRRs)in complex scenarios.In fact,a three-dimensional cadastre is required for efficiently registering and representing RRRs.In this paper,a 3D proximity analysis was proposed and implemented to determine RRRs and associated easement rights in non-topology-based data structures.This method can be used to investigate the surrounding spaces of a subject apartment unit or storage in a high-rise.The performance of the developed method was evaluated in a large complex high-rise in Tehran,Iran.The results confirmed that the proposed method can correctly identify the neighbor spaces in complex scenarios.

A generalized supervised classification scheme to produce provincial wetland inventory maps:an application of Google Earth Engine for big geo data processing

Wetlands are important natural resources due to their numerous ecological services.Consequently,identifying their locations and extents is imperative.The stability,repeatability,cost-effectiveness,multi-scale coverage,and proper spatial resolution imagery of satellites provide a valuable opportunity for their use in various large-scale applications,such as provincial wetland mapping.To do so,it is required to(1)process and classify big geo data(i.e.a large amount of satellite datasets)in a time-and computationally-efficient approach and(2)collect a large amount of field samples.In this study,Google Earth Engine(GEE)and machine learning algorithms were utilized to process thousands of remote sensing images and produce provincial wetland inventory maps of the three Canadian provinces of Manitoba,Quebec,and Newfoundland and Labrador(NL).Additionally,using GEE,a generalized supervised classification method is proposed to produce a regional wetland map from a large area(e.g.,a province)when lacking field samples.In fact,using the field data from only Manitoba and assuming that all wetlands in Canada have similar characteristics,the wetland maps were generated for the other two provinces.The overall classification accuracies for Manitoba,Quebec,and NL were 84%,78%,and 82%,respectively,indicating the high potential of the proposed method for aiding provincial wetland inventory systems.

Modeling the spread of spatio-temporal phenomena through the incorporation of ANFIS and genetically controlled cellular automata: a case study on forest fire

Virtual representation and simulation of spatio-temporal phenomena is a promising goal for the production of an advanced digital earth.Spread modeling,which is one of the most helpful analyses in the geographic information system(GIS),plays a prominent role in meeting this objective.This study proposes a new model that considers both aspects of static and dynamic behaviors of spreadable spatio-temporal in cellular automata(CA)modeling.Therefore,artificial intelligence tools such as adaptive neuro-fuzzy inference system(ANFIS)and genetic algorithm(GA)were used in accordance with the objectives of knowledge discovery and optimization.Significant conditions in updating states are considered so traditional CA transition rules can be accompanied with the impact of fuzzy discovered knowledge and the solution of spread optimization.We focused on the estimation of forest fire growth as an important case study for decision makers.A two-dimensional cellular representation of the combustion of heterogeneous fuel types and density on non-flat terrain were successfully linked with dynamic wind and slope impact.The validation of the simulation on experimental data indicated a relatively realistic head-fire shape.Further investigations showed that the results obtained using the dynamic controlling with GA in the absence of static modeling with ANFIS were unacceptable.

Dynamic Spatio-Temporal Tweet Mining for Event Detection:A Case Study of Hurricane Florence

Extracting information about emerging events in large study areas through spatiotemporal and textual analysis of geotagged tweets provides the possibility of monitoring the current state of a disaster.This study proposes dynamic spatio-temporal tweet mining as a method for dynamic event extraction from geotagged tweets in large study areas.It introduces the use of a modified version of ordering points to identify the clustering structure to address the intrinsic heterogeneity of Twitter data.To precisely calculate the textual similarity,three state-of-theart text embedding methods of Word2vec,GloVe,and Fast Text were used to capture both syntactic and semantic similarities.The impact of selected embedding algorithms on the quality of the outputs was studied.Different combinations of spatial and temporal distances with the textual similarity measure were investigated to improve the event detection outcomes.The proposed method was applied to a case study related to 2018 Hurricane Florence.The method was able to precisely identify events of varied sizes and densities before,during,and after the hurricane.The feasibility of the proposed method was qualitatively evaluated using the Silhouette coefficient and qualitatively discussed.The proposed method was also compared to an implementation based on the standard density-based spatial clustering of applications with noise algorithm,where it showed more promising results.

Ontological exploration of geospatial objects in context

Structured study of spatial objects and their relationships leads to a better cognition of the geospatial information and creates the concept of context at a higher level of abstraction.This study is aimed at providing a comprehensive definition of the context for geospatial objects.A combination of binary qualitative spatial relationships(i.e.direction,distance,and topological relations)among the members of a set of spatial objects will be used accordingly.In addition,by incorporating the general concept of context,obtained from either static data(attributes in a database)or dynamic data(sensors),the compact context of spatial objects will be introduced.Our framework for presentation of the involved knowledge and conception about the objects in context is also explored using ontology and description logic because of powerful conceptualization of relationships,either spatial or non-spatial,integrally.For this purpose,the hierarchies of main structure and object properties are formed at first.The constraint and characteristics of classes,such as subclasses,equivalent classes,cardinality etc.,and object properties,such as being functional,transitive,symmetric,asymmetric,inverse functional,disjoint etc.,are discovered and presented in more detail using web ontology language in description logic mode.The implementation is then performed in the framework of semantic web and extensible markup language syntaxes.The method ultimately facilitates,spatial reasoning by effective querying in a semantic framework taking pellet reasoner and SPARQL(a recursive acronym for SPARQL Protocol and RDF Query Language).

An automatic procedure for generating burn severity maps from the satellite images-derived spectral indices

Fire,especially wildfire,which can be considered as one of the main threats to vegetation cover and animals’life,has attracted lots of attention from environmental researchers.To better manage the fire crisis and take the necessary measures to compensate for its damages,it is essential to have detailed information about the burn severity levels.Accordingly,satellite images and their spectral indices have been widely considered in the literature as powerful tools in producing burn severity information.Despite the efficiency of the previously proposed methods,the necessity of ground reference data for their thresholding step faces them with serious challenges.To address this problem,in this study,an automatic procedure based on the change-point analysis is presented for thresholding differenced normalized burn ratio(dNBR)and its another version,dNBR2.In this procedure,a mean-shift based change-point analysis is performed on the dNBR and dNBR2 images for classifying them into burn severity levels.Experiments,conducted on some parts of Alaska and California in the United States,illustrated the high efficiency of the proposed method.Moreover,as an applied experiment,the severity of the fires,occurred in 2020 in the Khaeiz protected area in Iran,was estimated and compared with local reports.