Allocentric spatial performance higher in early-blind and sighted adults than in retinopathy-of-prematurity adults

The question as to whether people totally blind since infancy process allocentric or ‘external’ spatial information like the sighted has caused considerable debate within the literature. Due to the extreme rarity of the population, researchers have often included individuals with Retinopathy of Prematurity (RoP – over oxygenation at birth) within the sample. However, RoP is inextricably confounded with prematurity per se. Prematurity, without visual disability, has been associated with spatial processing difficulties. In this experiment, blindfolded sighted and two groups of functionally totally blind participants heard text descriptions from a survey (allocentric) or route (egocentric) perspective. One blind group lost their sight due to retinopathy of prematurity (RoP – over oxygenation at birth) and a second group before 24 months of age. The accuracy of participants’ mental representations derived from the text descriptions were assessed via questions and maps. The RoP participants had lower scores than the sighted and early blind, who performed similarly. In other words, it was not visual impairment alone that resulted in impaired allocentric spatial performance in this task, but visual impairment together with RoP. This finding may help explain the contradictions within the existing literature on the role of vision in allocentric spatial processing.

APPLICATION OF AN IMPUTATION METHOD FOR GEOSPATIAL INVENTORY OF FOREST STRUCTURAL ATTRIBUTES ACROSS MULTIPLE SPATIAL SCALES IN THE LAKE STATES, U.S.A.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

Detecting outliers and asserting consistency in agriculture ground truth information by using temporal VI data from modis.

Collecting ground truth data is an important step to be accomplished before performing a supervised classification. However, its quality depends on human, financial and time ressources. It is then important to apply a validation process to assess the reliability of the acquired data. In this study, agricultural infomation was collected in the Brazilian Amazonian State of Mato Grosso in order to map crop expansion based on MODIS EVI temporal profiles. The field work was carried out through interviews for the years 2005-2006 and 2006-2007. This work presents a methodology to validate the training data quality and determine the optimal sample to be used according to the classifier employed. The technique is based on the detection of outlier pixels for each class and is carried out by computing Mahalanobis distances for each pixel. The higher the distance, the further the pixel is from the class centre. Preliminary observations through variation coefficent validate the efficiency of the technique to detect outliers. Then, various subsamples are defined by applying different thresholds to exclude outlier pixels from the classification process. The classification results prove the robustness of the Maximum Likelihood and Spectral Angle Mapper classifiers. Indeed, those classifiers were insensitive to outlier exclusion. On the contrary, the decision tree classifier showed better results when deleting 7.5% of pixels in the training data. The technique managed to detect outliers for all classes. In this study, few outliers were present in the training data, so that the classification quality was not deeply affected by the outliers.

Learning about knowledge management for improving environmental impact assessment in a government agency: The Western Australian experience

How does knowledge management (KM) by a government agency responsible for environmental impact assessment (EIA) potentially contribute to better environmental assessment and management practice? Staff members at government agencies in charge of the EIA process are knowledge workers who perform judgement-oriented tasks highly reliant on individual expertise, but also grounded on the agency`s knowledge accumulated over the years. Part of an agency`s knowledge can be codified and stored in an organizational memory, but is subject to decay or loss if not properly managed. The EIA agency operating in Western Australia was used as a case study. Its KM initiatives were reviewed, knowledge repositories were identified and staff surveyed to gauge the utilisation and effectiveness of such repositories in enabling them to perform EIA tasks. Key elements of KM are the preparation of substantive guidance and spatial information management. It was found that treatment of cumulative impacts on the environment is very limited and information derived from project follow-up is not properly captured and stored, thus not used to create new knowledge and to improve practice and effectiveness. Other opportunities for improving organizational learning include the use of after-action reviews. The learning about knowledge management in EIA practice gained from Western Australian experience should be of value to agencies worldwide seeking to understand where best to direct their resources for their own knowledge repositories and environmental management practice. (C) 2011 Elsevier Ltd. All rights reserved.

Effects of reversible inactivation of the medial septum on rat exploratory behavior in the elevated plus-maze using a test-retest paradigm

The effect of intraseptal injections of lidocaine before a first or a second session in the elevated plus-maze, in a test-retest paradigm, was investigated. In addition to gross session analyses, a minute-by-minute analysis of the sessions was used to evaluate both anxiety and memory. Lidocaine injections before the test session produced increases in the frequency of entries, time spent and distance run in the open arms without affecting activity occurring in the closed arms. During the retest session, saline- and lidocaine-treated rats exhibited increased indices of anxiety and lidocaine-treated rats exhibited decreased closed-arm entries. The minute-by-minute analysis showed a faster decrease in anxiety-related behaviors during the test session by saline- than by lidocaine-treated rats and a significant decrease in closed-arm exploration by saline-treated rats, but not by lidocaine-treated ones. Lidocaine injection before the retest session produced increases in the frequency of entries, time spent and distance run in the open arms in the second session when compared with saline-treated rats. Minute-by-minute analysis showed an increase in the time spent in the open arms by lidocaine animals at the beginning of the retest session in comparison to saline animals and a significant decrease in closed-arm exploration by both groups. These results suggest that inactivation of the medial septum by lidocaine affects the expression of unconditioned and conditioned forms of anxiety in the elevated plus-maze and, in a lesser way, the acquisition and retention of spatial information. (C) 2010 Elsevier B.V. All rights reserved.

MapScript: A map algebra programming language incorporating neighborhood analysis

Map algebra is a data model and simple functional notation to study the distribution and patterns of spatial phenomena. It uses a uniform representation of space as discrete grids, which are organized into layers. This paper discusses extensions to map algebra to handle neighborhood operations with a new data type called a template. Templates provide general windowing operations on grids to enable spatial models for cellular automata, mathematical morphology, and local spatial statistics. A programming language for map algebra that incorporates templates and special processing constructs is described. The programming language is called MapScript. Example program scripts are presented to perform diverse and interesting neighborhood analysis for descriptive, model-based and processed-based analysis.

Coupling 3D visualisation to qualitative assessment of built environment designs

Geographical information systems (GIS) coupled to 3D visualisation technology is an emerging tool for urban planning and landscape design applications. The utility of 3D GIS for realistically visualising the built environment and proposed development scenarios is much advocated in the literature. Planners assess the merits of proposed changes using visual impact assessment (VIA). We have used Arcview GIS and visualisation software: called PolyTRIM from the University of Toronto, Centre for Landscape Research (CLR) to create a 3D scene for the entrance to a University campus. The paper investigates the thesis that to facilitate VIA in planning and design requires not only visualisation, but also a structured evaluation technique (Delphi) to arbitrate the decision-making process. (C) 2001 Elsevier Science B.V. All rights reserved.

Using a cartographic modeling language to manipulate spectral satellite imagery

Land related information about the Earth's surface is commonIJ found in two forms: (1) map infornlation and (2) satellite image da ta. Satellite imagery provides a good visual picture of what is on the ground but complex image processing is required to interpret features in an image scene. Increasingly, methods are being sought to integrate the knowledge embodied in mop information into the interpretation task, or, alternatively, to bypass interpretation and perform biophysical modeling directly on derived data sources. A cartographic modeling language, as a generic map analysis package, is suggested as a means to integrate geographical knowledge and imagery in a process-oriented view of the Earth. Specialized cartographic models may be developed by users, which incorporate mapping information in performing land classification. In addition, a cartographic modeling language may be enhanced with operators suited to processing remotely sensed imagery. We demonstrate the usefulness of a cartographic modeling language for pre-processing satellite imagery, and define two nerv cartographic operators that evaluate image neighborhoods as post-processing operations to interpret thematic map values. The language and operators are demonstrated with an example image classification task.

Using siting algorithms in the design of marine reserve networks

Using benthic habitat data from the Florida Keys (USA), we demonstrate how siting algorithms can help identify potential networks of marine reserves that comprehensively represent target habitat types. We applied a flexible optimization tool-simulated annealing-to represent a fixed proportion of different marine habitat types within a geographic area. We investigated the relative influence of spatial information, planning-unit size, detail of habitat classification, and magnitude of the overall conservation goal on the resulting network scenarios. With this method, we were able to identify many adequate reserve systems that met the conservation goals, e.g., representing at least 20% of each conservation target (i.e., habitat type) while fulfilling the overall aim of minimizing the system area and perimeter. One of the most useful types of information provided by this siting algorithm comes from an irreplaceability analysis, which is a count of the number of, times unique planning units were included in reserve system scenarios. This analysis indicated that many different combinations of sites produced networks that met the conservation goals. While individual 1-km(2) areas were fairly interchangeable, the irreplaceability analysis highlighted larger areas within the planning region that were chosen consistently to meet the goals incorporated into the algorithm. Additionally, we found that reserve systems designed with a high degree of spatial clustering tended to have considerably less perimeter and larger overall areas in reserve-a configuration that may be preferable particularly for sociopolitical reasons. This exercise illustrates the value of using the simulated annealing algorithm to help site marine reserves: the approach makes efficient use of;available resources, can be used interactively by conservation decision makers, and offers biologically suitable alternative networks from which an effective system of marine reserves can be crafted.

As formas simbólicas espaciais e a dinâmica da centralidade em Vitória : um esforço de análise

O presente trabalho aborda, sob a perspectiva da geografia cultural renovada, a temática das formas simbólicas no espaço urbano, tento como problematização o estudo de caso das formas simbólicas espaciais mais representativas da centralidade na Área Central de Vitória (ES). O interesse sobre o tema está associado o quadro relativamente recente no qual a Área Central de Vitória, sobretudo nas últimas duas décadas do século XX, passa a sofrer com um intenso processo de descentralização apresentando como alguns efeitos dessa dinâmica não só aparecimento de núcleos secundários de comércio e serviços afastados da Área Central, quanto também exerce um papel fundamental no que se ficou consagrado como “crise da área central”. Entretanto, se o quadro acima descrito é muito recente, por outro lado, durante o amplo período da produção do espaço urbano da capital capixaba em que a organização interna da cidade foi tributária, fundamentalmente, do processo de centralização, o Centro de Vitória foi o lócus privilegiado de materialização de formas simbólicas espaciais tipicamente associadas à centralidade intra-urbana tais como edificações que são símbolos dos poderes político, jurídico e econômico; igrejas; os monumentos, dentre outras formas simbólicas espaciais. Deste modo, a dissertação pretende investigar o advento da descentralização sobre as formas simbólicas espaciais tipicamente associadas à Área Central da capital capixaba, questionando em que medida essas formas permanecem enquanto signos de resistência simbólica a importância da área, bem como a natureza da eventual requalificação de significado ao qual foram, eventualmente, submetidas.

Preliminary clinical trial in percutaneous nephrolithotomy using a real-time navigation system for percutaneous kidney access

Background: Precise needle puncture of renal calyces is a challenging and essential step for successful percutaneous nephrolithotomy. This work tests and evaluates, through a clinical trial, a real-time navigation system to plan and guide percutaneous kidney puncture. Methods: A novel system, entitled i3DPuncture, was developed to aid surgeons in establishing the desired puncture site and the best virtual puncture trajectory, by gathering and processing data from a tracked needle with optical passive markers. In order to navigate and superimpose the needle to a preoperative volume, the patient, 3D image data and tracker system were previously registered intraoperatively using seven points that were strategically chosen based on rigid bone structures and nearby kidney area. In addition, relevant anatomical structures for surgical navigation were automatically segmented using a multi-organ segmentation algorithm that clusters volumes based on statistical properties and minimum description length criterion. For each cluster, a rendering transfer function enhanced the visualization of different organs and surrounding tissues. Results: One puncture attempt was sufficient to achieve a successful kidney puncture. The puncture took 265 seconds, and 32 seconds were necessary to plan the puncture trajectory. The virtual puncture path was followed correctively until the needle tip reached the desired kidney calyceal. Conclusions: This new solution provided spatial information regarding the needle inside the body and the possibility to visualize surrounding organs. It may offer a promising and innovative solution for percutaneous punctures.