Representation Of Spatial Information Research Articles

Short Take: Story-mapping Experiences

This short take presents story-mapping as a research technique that incorporates multiple methods and data sources to build visual narratives of individual and collective experiences. The goals of story-mapping are the following: (1) iteratively synthesize the collection, analysis, and representation of spatial, visual, and textual information as a narrative; (2) enable meaningful participation of research participants; and (3) generate a visually compelling product that facilitates dissemination. This article details the motivation, methods, and procedures for story-mapping based on research from Nepal’s Kathmandu Valley, which investigated the water-related practices, feelings, and observations of people who secure water for their families.

Monitoring the Construction Project by 4D Application of GIS

Construction technology is more important for project management, as it influences on construction schedules and monitoring. The construction commerce requires a very perfect preparation of planning, development of schedule and monitoring the construction process of the plan exertion which permits the complete optimization of the rate, spell and incomes. The paper promoting the 4D GIS concepts and integration technique and representation of non-spatial and spatial information’s such by means of drawing, resource, and prepared schedules in same GIS environment. s Instead of using the older, traditional methods of auto CAD drawings and schedule sheets, one can integrate them on a stage to create a 4D view of the project using GIS. The project presenting a 4D application of GIS in construction technology and management, by introducing Microsoft project (MSP) and ARCGIS or ARCMAP, which integrates schedules, 3D model of Building plan and resources composed through 4 Dimensional skill to deliver 3Dimensional + 1 Dimensional =4Dimensional Graphical picturing ability for monitoring the construction project site. In this project a G+1 building has been selected for the research in which all the working drawing are converted into 3D plan and according to it schedules are prepared in MSP software then they are imported into ArcGIS environment to get 4D output. This 4D output provides better visualization of construction work progress by which the engineers can trace the technical error of the project by taking better decision and can monitor the delay of work to reduce the cost overrun of project and rework can be avoided by early notification.

A Geoinformatics-based Framework for Surface Water Quality Mapping and Monitoring

The management of water systems must be sustainable, something that requires systematic and comprehensive monitoring. However, the attempts to obtain a comprehensive water quality monitoring (WQM) program in developing countries are challenged due to the lack of an integrated framework and limited resources. At present, the Philippines has no systematized technical and operational monitoring approach, poor coordination and data collection system, and weak law enforcement. On the other hand, Geoinformatics promises a more convenient and cost-effective WQM to complement the traditional method. The goal of this study is to demonstrate how to maximize the use of Geonformatics in developing methods and models to address the lack of spatial trends, timely monitoring, and integrated monitoring framework that could lead to a sustainable WQM system. Results of this study showed that satellite images can be utilized to derive empirical models to estimate WQ parameters. The validation results showed that the estimated WQ values using the RS-based models have no significant difference when compared with the actual WQ values. Also, the WQ maps derived using Geographic Information System (GIS) were proven useful in providing better representation and analysis of spatial and temporal information that can provide a comprehensive and cost-effective reference for WQ monitoring and assessment.

Qualitatively correct bintrees: an efficient representation of qualitative spatial information

We outline our work on using bintrees as an efficient representation for qualitative information about spatial objects. Our approach represents each spatial object as a bintree satisfying the exact same qualitative relationships to other bintree representations as the corresponding spatial objects. We prove that such correct bintrees always exist and that they can be constructed as a sum of local representations, allowing a practically efficient construction. Our representation is both efficient, with respect to storage space and query time, and can represent many well-known qualitative relations, such as the relations in the Region Connection Calculus and Allen’s Interval Algebra.

The place cell activity is information-efficient constrained by energy

Spatial representation is a crucial function of animal’s brain. However, there is still no uniform explanation of how the spatial code is formed in different dimensional spaces to date. The main reason why place cell exhibits unique activity pattern is that the animal needs to retrieve and process spatial information. In this paper, we constructed a constrained optimization model based on information theory to explain the place field formation across species in different dimensional spaces. We proposed the following question that, using only limited amount of neural energy, how to organize the spiking locations (place field) in the available environment to obtain the most efficient spatial information representation? We solved this conditional functional extremum problem by variational techniques. The results showed that on the condition of limited neural energy, the place field will comply with a Gaussian-form distribution automatically to convey the largest amount information per spike. We also found that the animal’s natural habitat property and locomotion experience statistics affected the symmetry of spatial representation in different dimensions. These findings not only reconcile the argument of whether the spatial codes of place cell are isotropic, but also provide an explanation of place field formation by an information-theoretic approach. Furtherly, this research revealed the energy economical and information efficient properties underlie the spatial representation system of the brain.

Pedology and digital soil mapping (DSM)

Pedology focuses on understanding soil genesis in the field and includes soil classification and mapping. Digital soil mapping (DSM) has evolved from traditional soil classification and mapping to the creation and population of spatial soil information systems by using field and laboratory observations coupled with environmental covariates. Pedological knowledge of soil distribution and processes can be useful for digital soil mapping. Conversely, digital soil mapping can bring new insights to pedogenesis, detailed information on vertical and lateral soil variation, and can generate research questions that were not considered in traditional pedology. This review highlights the relevance and synergy of pedology in soil spatial prediction through the expansion of pedological knowledge. We also discuss how DSM can support further advances in pedology through improved representation of spatial soil information. Some major findings of this review are as follows: (a) soil classes can be mapped accurately using DSM, (b) the occurrence and thickness of soil horizons, whole soil profiles and soil parent material can be predicted successfully with DSM techniques, (c) DSM can provide valuable information on pedogenic processes (e.g. addition, removal, transformation and translocation), (d) pedological knowledge can be incorporated into DSM, but DSM can also lead to the discovery of knowledge, and (e) there is the potential to use process‐based soil–landscape evolution modelling in DSM. Based on these findings, the combination of data‐driven and knowledge‐based methods promotes even greater interactions between pedology and DSM.Highlights Demonstrates relevance and synergy of pedology in soil spatial prediction, and links pedology and DSM. Indicates the successful application of DSM in mapping soil classes, profiles, pedological features and processes. Shows how DSM can help in forming new hypotheses and gaining new insights about soil and soil processes. Combination of data‐driven and knowledge‐based methods recommended to promote greater interactions between DSM and pedology.

Neural Representation of Spatial Layout and Relational Information among Multiple Objects

Neural Representation of Spatial Layout and Relational Information among Multiple Objects

Representation of Spatial and Feature Information in the Monkey Dorsal and Ventral Prefrontal Cortex

The primate prefrontal cortex (PFC) is critical for executive functions including working memory, task switching and response selection. The functional organization of this area has been a matter of debate over a period of decades. Early models proposed segregation of spatial and object information represented in working memory in the dorsal and ventral PFC, respectively. Other models emphasized the integrative ability of the entire PFC depending on task demands, not necessarily tied to working memory. An anterior-posterior hierarchy of specialization has also been speculated, in which progressively more abstract information is represented more anteriorly. Here we revisit this debate, updating these arguments in light of recent evidence in non-human primate neurophysiology studies. We show that spatial selectivity is predominantly represented in the posterior aspect of the dorsal PFC, regardless of training history and task performed. Objects of different features excite both dorsal and ventral prefrontal neurons, however neurons highly specialized for feature information are located predominantly in the posterior aspect of the ventral PFC. In accordance with neuronal selectivity, spatial working memory is primarily impaired by inactivation or lesion of the dorsal PFC and object working memory by ventral inactivation or lesion. Neuronal responses are plastic depending on task training but training too has dissociable effects on ventral and dorsal PFC, with the latter appearing to be more plastic. Despite the absence of an overall topography, evidence exists for the orderly localization of stimulus information at a sub-millimeter scale, within the dimensions of a cortical column. Unresolved questions remain, regarding the existence or not of a functional map at the areal and columnar scale, and the link between behavior and neuronal activity for different prefrontal subdivisions.

Local motion adaptation enhances the representation of spatial structure at EMD arrays.

Neuronal representation and extraction of spatial information are essential for behavioral control. For flying insects, a plausible way to gain spatial information is to exploit distance-dependent optic flow that is generated during translational self-motion. Optic flow is computed by arrays of local motion detectors retinotopically arranged in the second neuropile layer of the insect visual system. These motion detectors have adaptive response characteristics, i.e. their responses to motion with a constant or only slowly changing velocity decrease, while their sensitivity to rapid velocity changes is maintained or even increases. We analyzed by a modeling approach how motion adaptation affects signal representation at the output of arrays of motion detectors during simulated flight in artificial and natural 3D environments. We focused on translational flight, because spatial information is only contained in the optic flow induced by translational locomotion. Indeed, flies, bees and other insects segregate their flight into relatively long intersaccadic translational flight sections interspersed with brief and rapid saccadic turns, presumably to maximize periods of translation (80% of the flight). With a novel adaptive model of the insect visual motion pathway we could show that the motion detector responses to background structures of cluttered environments are largely attenuated as a consequence of motion adaptation, while responses to foreground objects stay constant or even increase. This conclusion even holds under the dynamic flight conditions of insects.

Collaborative classification of hyperspectral and visible images with convolutional neural network

Recent advances in remote sensing technology have made multisensor data available for the same area, and it is well-known that remote sensing data processing and analysis often benefit from multisource data fusion. Specifically, low spatial resolution of hyperspectral imagery (HSI) degrades the quality of the subsequent classification task while using visible (VIS) images with high spatial resolution enables high-fidelity spatial analysis. A collaborative classification framework is proposed to fuse HSI and VIS images for finer classification. First, the convolutional neural network model is employed to extract deep spectral features for HSI classification. Second, effective binarized statistical image features are learned as contextual basis vectors for the high-resolution VIS image, followed by a classifier. The proposed approach employs diversified data in a decision fusion, leading to an integration of the rich spectral information, spatial information, and statistical representation information. In particular, the proposed approach eliminates the potential problems of the curse of dimensionality and excessive computation time. The experiments evaluated on two standard data sets demonstrate better classification performance offered by this framework.

In silico Interrogation of Insect Central Complex Suggests Computational Roles for the Ellipsoid Body in Spatial Navigation.

The central complex in the insect brain is a composite of midline neuropils involved in processing sensory cues and mediating behavioral outputs to orchestrate spatial navigation. Despite recent advances, however, the neural mechanisms underlying sensory integration and motor action selections have remained largely elusive. In particular, it is not yet understood how the central complex exploits sensory inputs to realize motor functions associated with spatial navigation. Here we report an in silico interrogation of central complex-mediated spatial navigation with a special emphasis on the ellipsoid body. Based on known connectivity and function, we developed a computational model to test how the local connectome of the central complex can mediate sensorimotor integration to guide different forms of behavioral outputs. Our simulations show integration of multiple sensory sources can be effectively performed in the ellipsoid body. This processed information is used to trigger continuous sequences of action selections resulting in self-motion, obstacle avoidance and the navigation of simulated environments of varying complexity. The motor responses to perceived sensory stimuli can be stored in the neural structure of the central complex to simulate navigation relying on a collective of guidance cues, akin to sensory-driven innate or habitual behaviors. By comparing behaviors under different conditions of accessible sources of input information, we show the simulated insect computes visual inputs and body posture to estimate its position in space. Finally, we tested whether the local connectome of the central complex might also allow the flexibility required to recall an intentional behavioral sequence, among different courses of actions. Our simulations suggest that the central complex can encode combined representations of motor and spatial information to pursue a goal and thus successfully guide orientation behavior. Together, the observed computational features identify central complex circuitry, and especially the ellipsoid body, as a key neural correlate involved in spatial navigation.

36 Human parahippocampal cortex supports spatial binding in visual working memory

Objective Studies investigating the functional organisation of the medial temporal lobe (MTL) suggest that parahippocampal cortex (PHC) generates representations of spatial and contextual information used by the hippocampus in the formation of episodic memories. However, evidence from animal studies also implicates PHC in spatial binding of visual information held in working memory. This study focussed on elucidating the role of PHC in spatial binding in working memory in humans. Method We assessed a 46-year-old man (PJ), after he had recovered from bilateral medial occipitotemporal cortical mOTC strokes resulting in lesions in PHC but sparing the hippocampus, and a group of age-matched healthy controls on a series of visual working memory tasks. Results When recalling the colour of one of two objects, PJ misidentified the target when cued by its location, but not shape. When recalling the position of one of three objects, he frequently misidentified the target, which was cued by its colour. Increasing the duration of the memory delay had no impact on the proportion of binding errors, but did significantly worsen recall precision in both PJ and controls. Conclusion We conclude that PHC plays a crucial role in spatial binding during encoding of visual information in working.

Representing Time and Space for the Semantic Web

Representation of temporal and spatial information for the Semantic Web often involves qualitative defined information (i.e., information described using natural language terms such as “before” or “overlaps”) since precise dates or coordinates are not always available. This work proposes several temporal representations for time points and intervals and spatial topological representations in ontologies by means of OWL properties and reasoning rules in SWRL. All representations are fully compliant with existing Semantic Web standards and W3C recommendations. Although qualitative representations for temporal interval and point relations and spatial topological relations exist, this is the first work proposing representations combining qualitative and quantitative information for the Semantic Web. In addition to this, several existing and proposed approaches are compared using different reasoners and experimental results are presented in detail. The proposed approach is applied to topological relations (RCC5 and RCC8) supporting both qualitative and quantitative (i.e., using coordinates) spatial relations. Experimental results illustrate that reasoning performance differs greatly between different representations and reasoners. To the best of our knowledge, this is the first such experimental evaluation of both qualitative and quantitative Semantic Web temporal and spatial representations. In addition to the above, querying performance using SPARQL is evaluated. Evaluation results demonstrate that extracting qualitative relations from quantitative representations using reasoning rules and querying qualitative relations instead of directly querying quantitative representations increases performance at query time.

Place cells are more strongly tied to landmarks in deep than in superficial CA1

Environmental cues affect place cells responses, but whether this information is integrated versus segregated in distinct hippocampal cell populations is unclear. Here, we show that, in mice running on a treadmill enriched with visual-tactile landmarks, place cells are more strongly controlled by landmark-associated sensory inputs in deeper regions of CA1 pyramidal layer (CA1d). Many cells in CA1d display several firing fields correlated with landmarks, mapping positions slightly before or within the landmarks. Supporting direct involvement of sensory inputs, their firing fields show instantaneous responses to landmark manipulations, persist through change of context, and encode landmark identity and saliency. In contrast, cells located superficially in the pyramidal layer have single firing fields, are context specific and respond with slow dynamics to landmark manipulations. These findings suggest parallel and anatomically segregated circuits within CA1 pyramidal layer, with variable ties to landmarks, allowing flexible representation of spatial and non-spatial information.

Volunteered Geographic Information for Disaster Management with Application to Earthquake Disaster Databank & Sharing Platform

All phases of disaster management require up-to-date and accurate information. Different in-situ and remote sensor systems help to monitor dynamic properties such as air quality, water level or inundated areas. The rapid emergence of web-based services has facilitated the collection, dissemination, and cartographic representation of spatial information from the public, giving rise to the idea of using Volunteered Geographic Information (VGI) to aid disaster management. In this study, with a brief review on the concept and the development of disaster management, opportunities and challenges for applying VGI in disaster management were explored. The challenges, including Data availability, Data quality, Data management and Legal issues of using VGI for disaster management, were discussed in detail with particular emphasis on the actual needs of disaster management practice in China. Three different approaches to assure VGI data quality, namely the classification and authority design of volunteers, a government-led VGI data acquisition framework for disaster management and a quality assessment system for VGI, respectively, were presented and discussed. As a case study, a prototype of VGI oriented earthquake disaster databank & sharing platform, an open WebGIS system for volunteers and other interested individuals collaboratively create and manage the earthquake disaster related information, was proposed, to provide references for improving the level of earthquake emergency response and disaster mitigation in China.

Spatial Navigation and the Central Complex: Sensory Acquisition, Orientation, and Motor Control.

Cockroaches are scavengers that forage through dark, maze-like environments. Like other foraging animals, for instance rats, they must continually asses their situation to keep track of targets and negotiate barriers. While navigating a complex environment, all animals need to integrate sensory information in order to produce appropriate motor commands. The integrated sensory cues can be used to provide the animal with an environmental and contextual reference frame for the behavior. To successfully reach a goal location, navigational cues continuously derived from sensory inputs have to be utilized in the spatial guidance of motor commands. The sensory processes, contextual and spatial mechanisms, and motor outputs contributing to navigation have been heavily studied in rats. In contrast, many insect studies focused on the sensory and/or motor components of navigation, and our knowledge of the abstract representation of environmental context and spatial information in the insect brain is relatively limited. Recent reports from several laboratories have explored the role of the central complex (CX), a sensorimotor region of the insect brain, in navigational processes by recording the activity of CX neurons in freely-moving insects and in more constrained, experimenter-controlled situations. The results of these studies indicate that the CX participates in processing the temporal and spatial components of sensory cues, and utilizes these cues in creating an internal representation of orientation and context, while also directing motor control. Although these studies led to a better understanding of the CX's role in insect navigation, there are still major voids in the literature regarding the underlying mechanisms and brain regions involved in spatial navigation. The main goal of this review is to place the above listed findings in the wider context of animal navigation by providing an overview of the neural mechanisms of navigation in rats and summarizing and comparing our current knowledge on the CX's role in insect navigation to these processes. By doing so, we aimed to highlight some of the missing puzzle pieces in insect navigation and provide a different perspective for future directions.

Representing Spatial Information in the Parietal Association Cortex

Several clinical studies have shown that the parietal association cortex plays an important role in spatial perception. Electrophysiological studies on behaving monkeys initiated in the 1970s have revealed the presence of neurons in the parietal association cortex whose activity is related to spatial vision. Herein, we review previous studies on non-human primates and we present an overview of the neuronal representation of spatial information in the parietal association cortex.

Peripheral Processing Facilitates Optic Flow-Based Depth Perception.

Flying insects, such as flies or bees, rely on consistent information regarding the depth structure of the environment when performing their flight maneuvers in cluttered natural environments. These behaviors include avoiding collisions, approaching targets or spatial navigation. Insects are thought to obtain depth information visually from the retinal image displacements (“optic flow”) during translational ego-motion. Optic flow in the insect visual system is processed by a mechanism that can be modeled by correlation-type elementary motion detectors (EMDs). However, it is still an open question how spatial information can be extracted reliably from the responses of the highly contrast- and pattern-dependent EMD responses, especially if the vast range of light intensities encountered in natural environments is taken into account. This question will be addressed here by systematically modeling the peripheral visual system of flies, including various adaptive mechanisms. Different model variants of the peripheral visual system were stimulated with image sequences that mimic the panoramic visual input during translational ego-motion in various natural environments, and the resulting peripheral signals were fed into an array of EMDs. We characterized the influence of each peripheral computational unit on the representation of spatial information in the EMD responses. Our model simulations reveal that information about the overall light level needs to be eliminated from the EMD input as is accomplished under light-adapted conditions in the insect peripheral visual system. The response characteristics of large monopolar cells (LMCs) resemble that of a band-pass filter, which reduces the contrast dependency of EMDs strongly, effectively enhancing the representation of the nearness of objects and, especially, of their contours. We furthermore show that local brightness adaptation of photoreceptors allows for spatial vision under a wide range of dynamic light conditions.

Виртуальные геоизображения пространственно-временных моделей окружающей среды

Abstract: The article discusses methods for visualization of multidimensional space-time (3D raster, time) environmental models. It analyzes the range of existing tools for building and rendering the 3D raster voxel spatial models and ascertain only a few designated for this purpose programs. The authors focus attention on the approach to the representation of 3D and 4D spatial information in multidimensional, volumetric, space-time digital model, each cell describes the state of the real space elementary volume at a time. This model is seen by them as the basis for an automated, self organizing, modeling computational process. The article presents a common algorithm for the generation of multidimensional space-time environmental model virtual geoimages and provides some examples for the Earth and its polar areas models, built as a part of the authors experimental work. The article describes the features of the real time virtual modeling with the use of virtual audio and video variables in a program-controlled environment and proposes some different approaches to the large multidimensional models visualization. The authors note the progress of 3D volumetric visualization methods and devices, and conclude what the global multidimensional spacetime environmental virtual model development will require to create intelligent volumetric visualizing virtual geoimages.

BIM for existing facilities: feasibility of spectral image integration to 3D point cloud data

Accurate geometrical and spatial information of the built environment can be accurately acquired and the resulting 3D point cloud data is required to be processed to construct the digital model, Building Information Modelling (BIM) for existing facilities. Point cloud by laser scanning over the buildings and facilities has been commonly used, but the data requires external information so that any objects and materials can be correctly identified and classified. A number of advanced data processing methods have been developed, such as the use of colour information to attach semantic information. However, the accuracy of colour information depends largely on the scene environment where the image is acquired. The limited number of spectral channels on conventional RGB camera often fails to extract important information about surface material, despite spectral surface reflectance can represent a signature of the material. Hyperspectral imaging can, instead, provide precise representation of spatial and spectral information. By implementing such information to 3D point cloud, the efficiency of material detection and classification in BIM should be significantly improved. In this work, the feasibility of the image integration and discuss practical difficulties in the development.