Relevant bibliographies by topics / Spatial quality

Academic literature on the topic 'Spatial quality'

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Published: 4 June 2021
Last updated: 19 February 2022

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Journal articles on the topic "Spatial quality"

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Odeh, Inakwu O. A. "Spatial Data Quality." Geoderma 116, no. 3-4 (October 2003): 395–98. http://dx.doi.org/10.1016/s0016-7061(03)00115-0.

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Dondu, Mustafa, Nedim OzdemiR, Mesut Perktash, and Elmina Gadirova. "SPATIAL ANALYSIS AND EVALUATION OF WATER QUALITY OF GOKOVA BAY." JOURNAL OF BIOLOGY AND ECOLOGY 2, no. 2 (February 28, 2020): 51–55. http://dx.doi.org/10.26739/2181-0575-2020-2-9.

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Praat, J. P., A. F. Bollen, and A. D. Mowat. "CHARACTERISING SPATIAL VARIATION IN QUALITY." Acta Horticulturae, no. 753 (October 2007): 305–16. http://dx.doi.org/10.17660/actahortic.2007.753.38.

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Stöglehner, Gernot. "Conceptualising Quality in Spatial Planning." Raumforschung und Raumordnung 77, no. 1 (February 28, 2019): 1–15. http://dx.doi.org/10.2478/rara-2019-0002.

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AbstractQuality discourses help to legitimate professions. This article therefore addresses the crucial question of how quality can be framed in spatial planning. Based on the context of spatial planning in Austria, this article introduces a normative framework for quality in spatial planning that considers the four dimensions of content, planning methodology, planning process and legal compliance, and shows howthese four dimensions are interlinked. Furthermore, it discusses how quality can be enhanced by concerted governmental action and further education for planners. It is argued that planners might need to adopt a new role as 'teachers' in planning processes to facilitate societal learning processes in order to raise the quality of planning. Finally, it is concluded that the quality debate in spatial planning can be useful to calibrate expectations of planners and society to directly influence sustainable spatial development through spatial planning, to communicate achievements in planning, to raise awareness for sustainable spatial development, and to improve legal frameworks, planning methodology, and planners' training and further education.
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Skakic, Dusan, and Igor Dzincic. "Quality characteristics of spatial furniture." Bulletin of the Faculty of Forestry, no. 99 (2009): 135–45. http://dx.doi.org/10.2298/gsf0999135s.

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The quality of products represents one of the key aims of any modern organized production. In the production practice, it is essential to establish the optimal relationship between quality, production economy and delivery deadlines. Furniture quality is evaluated by three levels and they are: basic quality, high quality and especially high quality. The results presented in this paper are based on the sample measurements of chairs and tables during 2007 and 2008 at the Institute for Furniture Quality Control.
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Sedano, Elisabeth. "‘Sensor’ship and Spatial Data Quality." Urban Planning 1, no. 2 (June 24, 2016): 75–87. http://dx.doi.org/10.17645/up.v1i2.608.

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This article describes a Los Angeles-based website that collects volunteered geographic information (VGI) on outdoor advertising using the Google Street View interface. The Billboard Map website was designed to help the city regulate signage. The Los Angeles landscape is thick with advertising, and the city efforts to count total of signs has been stymied by litigation and political pressure. Because outdoor advertising is designed to be seen, the community collectively knows how many and where signs exist. As such, outdoor advertising is a perfect subject for VGI. This paper analyzes the Los Angeles community's entries in the Billboard Map website both quantitatively and qualitatively. I find that members of the public are well able to map outdoor advertisements, successfully employing the Google Street View interface to pinpoint sign locations. However, the community proved unaware of the regulatory distinctions between types of signs, mapping many more signs than those the city technically designates as billboards. Though these findings might suggest spatial data quality issues in the use of VGI for municipal record-keeping, I argue that the Billboard Map teaches an important lesson about how the public's conceptualization of the urban landscape differs from that envisioned by city planners. In particular, I argue that community members see the landscape of advertising holistically, while city agents treat the landscape as a collection of individual categories. This is important because, while Los Angeles recently banned new off-site signs, it continues to approve similar signs under new planning categories, with more in the works.
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Raines, Gary L. "Elements of spatial data quality." Computers & Geosciences 23, no. 1 (February 1997): 135. http://dx.doi.org/10.1016/s0098-3004(97)87525-5.

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Acre, Fernanda, and Annemie Wyckmans. "Dwelling renovation and spatial quality." International Journal of Sustainable Built Environment 4, no. 1 (June 2015): 12–41. http://dx.doi.org/10.1016/j.ijsbe.2015.02.001.

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Dubin, Robin A. "Spatial autocorrelation and neighborhood quality." Regional Science and Urban Economics 22, no. 3 (September 1992): 433–52. http://dx.doi.org/10.1016/0166-0462(92)90038-3.

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Li, Deren, Jingxiong Zhang, and Huayi Wu. "Spatial data quality and beyond." International Journal of Geographical Information Science 26, no. 12 (December 2012): 2277–90. http://dx.doi.org/10.1080/13658816.2012.719625.

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Dissertations / Theses on the topic "Spatial quality"

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He, Ying Surveying &amp Spatial Information Systems Faculty of Engineering UNSW. "Spatial data quality management." Publisher:University of New South Wales. Surveying & Spatial Information Systems, 2008. http://handle.unsw.edu.au/1959.4/43323.

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The applications of geographic information systems (GIS) in various areas have highlighted the importance of data quality. Data quality research has been given a priority by GIS academics for three decades. However, the outcomes of data quality research have not been sufficiently translated into practical applications. Users still need a GIS capable of storing, managing and manipulating data quality information. To fill this gap, this research aims to investigate how we can develop a tool that effectively and efficiently manages data quality information to aid data users to better understand and assess the quality of their GIS outputs. Specifically, this thesis aims: 1. To develop a framework for establishing a systematic linkage between data quality indicators and appropriate uncertainty models; 2. To propose an object-oriented data quality model for organising and documenting data quality information; 3. To create data quality schemas for defining and storing the contents of metadata databases; 4. To develop a new conceptual model of data quality management; 5. To develop and implement a prototype system for enhancing the capability of data quality management in commercial GIS. Based on reviews of error and uncertainty modelling in the literature, a conceptual framework has been developed to establish the systematic linkage between data quality elements and appropriate error and uncertainty models. To overcome the limitations identified in the review and satisfy a series of requirements for representing data quality, a new object-oriented data quality model has been proposed. It enables data quality information to be documented and stored in a multi-level structure and to be integrally linked with spatial data to allow access, processing and graphic visualisation. The conceptual model for data quality management is proposed where a data quality storage model, uncertainty models and visualisation methods are three basic components. This model establishes the processes involved when managing data quality, emphasising on the integration of uncertainty modelling and visualisation techniques. The above studies lay the theoretical foundations for the development of a prototype system with the ability to manage data quality. Object-oriented approach, database technology and programming technology have been integrated to design and implement the prototype system within the ESRI ArcGIS software. The object-oriented approach allows the prototype to be developed in a more flexible and easily maintained manner. The prototype allows users to browse and access data quality information at different levels. Moreover, a set of error and uncertainty models are embedded within the system. With the prototype, data quality elements can be extracted from the database and automatically linked with the appropriate error and uncertainty models, as well as with their implications in the form of simple maps. This function results in proposing a set of different uncertainty models for users to choose for assessing how uncertainty inherent in the data can affect their specific application. It will significantly increase the users' confidence in using data for a particular situation. To demonstrate the enhanced capability of the prototype, the system has been tested against the real data. The implementation has shown that the prototype can efficiently assist data users, especially non-expert users, to better understand data quality and utilise it in a more practical way. The methodologies and approaches for managing quality information presented in this thesis should serve as an impetus for supporting further research.
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Yang, Ting Surveying &amp Spatial Information Systems Faculty of Engineering UNSW. "VISUALISATION OF SPATIAL DATA QUALITY FOR DISTRIBUTED GIS." Awarded by:University of New South Wales. School of Surveying and Spatial Information Systems, 2007. http://handle.unsw.edu.au/1959.4/27434.

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Nowadays a substantial trend occurs that vast amounts of geospatial data are supplied, managed, and processed over distributed GIS. It is important to provide users with the capability of visualising spatial data quality information in a meaningful way for distributed GIS, since it will significantly enhance user understanding of data quality and aid them in assessing the data fitness for their application requirements. This thesis investigates the issue of visualisation of spatial data quality for distributed GIS. Based on a review of core concepts associated with spatial data quality, metadata standards, and major research areas related to data quality, the limitations of current data quality presentation are highlighted. To overcome some of these limitations, the research topic of this thesis is proposed, namely, adding visualisation functionality to the presentation of spatial data quality to convey uncertainty information to users in an interactive and graphical manner. Based on a review of the theories on visualisation and the frameworks developed for visualisation of spatial data quality in literature, an extended framework is developed incorporating several aspects of visualisation such as contexts, contents, and techniques, where the hierarchical nature of data quality and error models are two main parts of the visualisation contents. A brief framework of visualisation of spatial data quality for distributed GIS is proposed, where data storage with quality information and web services for visualising data quality are two key components. To satisfy a series of requirements for representing spatial data quality, a new object-oriented data model is proposed based on the review of developments of data models. This data model can specifically deal with the hierarchical nature of data quality and error propagation, recognising data quality as a dynamic process. Further, The implementation of the data model using GML and SVG is discussed. The details of a web service for visualising spatial data quality are addressed. After proposing the requirements on building a system for spatial data quality visualisation for distributed GIS, the design of a prototype visualisation system for distributed GIS is addressed in detail. The prototype visualisation system for spatial data quality is developed and implemented with an example data set, where SVG and JavaScript are used to illustrate how various graphic methods such as animation, data quality filters, and colour gradients can be used for distributed GIS. In addition to the visualisation of positional accuracy at the feature level, in this pilot system, the hierarchical structure of data quality information is also presented. Limitations of the research in this thesis are also addressed. However, in general, this research is of great significance for the contributions made to a relatively new research area in terms of theories, procedures, and software developments.
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Mohamed-Ghouse, Mohamed Zaffar Sadiq. "Modeling spatial variation of data quality in databases /." Connect to thesis, 2008. http://repository.unimelb.edu.au/10187/3544.

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Li, Yang. "The spatial data quality analysis in the environmental modelling." Thesis, University of East London, 2001. http://roar.uel.ac.uk/1305/.

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The spatial data quality analysis is essential in environmental modelling for efficiently addressing the environmental change. As the complexity of data sets and the modelling capability of computer systems increase, the need to address the quality of both data and models is increasingly important. Integration with environmental modelling, the spatial data quality analysis and the geocomputation paradigm have been three important areas of GIS research. In this research they are brought together in the context of coastal oil spill modelling. The research covers the issues of measurement, modelling and management of spatial data quality. Coupling GIS and environmental modelling, the systematic solution is developed for coastal oil spill modelling which is representative of complex environmental models. The procedures of geospatial data quality analysis were implemented not only with existing GIS funLionality but also with various Geocomputation techniques. Spatial data quality analyses of inputs and model performances, which include sensitivity analyses, error propagation analyses and fitness-for-use analyses, were carried out for the coastal oil spill modelling. The results show that in coastal oil spill modelling, a better understanding and improvement of spatial data quality can be achieved through such analyses. The examples illustrate both the diversity of techniques and tools required when investigating spatial data quality issues in environmental modelling. The evidence of feasibility and practicality are also provided for these flexible analysis approaches. An overall methodology is developed at each stage of a project; with particular emphasis at inception to ensure adequate data quality on which to construct the models. Furthermore, the coupling strategy of GIS and environmental modelling is revised to include a geo-data quality analysis (GQA) engine. With growing availability of proprietary and public domain software suitable for spatial data quality analysis, GQA engines will be formed with the evolution of such software into tightly-coupled collection of tools external to GIS. The GQA engine would itself be tightly-coupled with GIS and environmental models to form a modelling framework.
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Ralphs, Martin P. "Towards the evaluation and management of spatial data quality." Thesis, University of East London, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.282737.

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Khalil, Arya Farid. "Temporal and Spatial Analysis of Water Quality Time Series." University of Akron / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=akron1446027770.

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Näkne, Henrik. "Video Quality Metric improvement using motion and spatial masking." Thesis, Uppsala universitet, Avdelningen för visuell information och interaktion, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-275114.

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Objective video quality assessment is of great importance in video compression and other video processing applications. In today's encoders Peak Signal to Noise Ratio or Sum of Absolute Differences are often used, though these metrics have limited correlation to perceived quality. In this paper other block-based quality measures are evaluated with superior performance on compression distortion when evaluating correlation with Mean Opinion Scores. The major results are that Block-based Visual Information Fidelity with optical flow and intra-frame Gaussian weighting outperforms PSRN, VIF, and SSIM. Also, a block-based weighted Mean Squared Error method is proposed that performs better than PSRN and SSIM, however not VIF and BB-VIF, with the advantage of high locality, which is useful in video encoding. The previously mentioned weighting methods have not been evaluated with SSIM, which is proposed for further studies.
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Woodward, Tim. "Variation in 'Hayward' kiwifruit quality characteristics." The University of Waikato, 2007. http://hdl.handle.net/10289/2640.

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Quantify the magnitude, sources and distribution of variation in fruit quality traits within kiwifruit populations and identify opportunities for the management of this variation. Near-infrared (NIR) grading was used as a tool for monitoring fruit quality, and measurements combined with orchard/vine information to investigate opportunities for the management of the variation in fruit quality traits with a particular focus on fruit DM. NIR enabled non-destructive assessment of the quality characteristics of individual fruit from 96 commercial orchards, comprising 550 fruit-lines, across four consecutive seasons, resulting in a dataset of measurements made on 146.7 million individual fruit. The distribution of quality traits within fruit populations and the relationships between quality traits were examined. The spatial component of variation in fruit quality was investigated to assess the potential for zonal management practices. Finally, the effects of growth temperatures on fruit quality were studied. Significant variation in fruit quality was observed between-seasons, between-orchards, and between-vines within an orchard. From comparison of CVs between quality traits, cropload was more variable than fruit weight which varied more than fruit DM, independent of the production scale considered (between-orchard or between-vine). Across a hierarchy of fruit populations (individual vine, fruit-line and orchard), the majority of fruit quality distributions demonstrated significant deviations from normality. However, departures from normality can be tolerated for estimation of the proportion of fruit with specific quality criteria. The sources of variation in fruit weight and DM populations were investigated at both a between-orchard scale and a within-orchard scale. Between-orchard variation was significant, however, the majority of variation occurred within-fruitlines, within-orchards and within seasons. The within-fruitline component of variation was investigated separately. Both between-vine and within-vine variation were significant, but within-vine variation was dominant. The focus of management should be on reducing variation occurring within-fruitlines within-orchards, which is largely attributable to variation occurring within the individual vine. Higher croploads per vine have negative consequences for fruit weight but variable effects on DM. Increasing croploads reduce both FW and DW allocations for each fruit, therefore the effect of cropload on DM is dependent on the relative reductions in FW and DW. The DW allocations to fruit are not limited by DW production, at least up to the croploads observed in this study (≤65 fruit m-2). The potential for zonal management was investigated. Variation in fruit quality characteristics between-orchards across the Te Puke growing region, and between-vines within an individual orchard area were investigated using geostatistics. A spatial component to variation was identified both between-orchard and between-vine. However, the effect of spatial variation was diluted by that of non-spatial variation and therefore, zonation between orchards or between areas within-orchards should not be where the effort in managing variation is concentrated. Orchard altitude correlated with some aspects of fruit quality. Mean fruit weight declined 0.5g and within-orchard variation in fruit weight declined 0.25 units with a 25m increase in orchard altitude. Mean fruit DM was independent of orchard altitude and within-orchard variability in DM declined 0.023 units per 25m increase in orchard altitude. Differences in orchard altitude equated with differences in growth temperatures. Warm spring and cool summer temperatures favour the growth of high DM fruit. The effects of spring temperatures on canopy development and maturation were investigated to elucidate potential physiological mechanisms for temperatures effects on fruit growth. Higher spring growth temperatures increased the rate of total leaf area development and promoted development of leaf photosynthesis. Higher spring growth temperatures favoured a more positive carbon balance, which has beneficial effects on the development of fruit quality characteristics. Post-harvest, the traditional practice of grading fruit into count sizes generally also segregates for DM, and large count size fruit will often have higher DM than small sized fruit. Between fruit populations, a positive correlation was identified between fruit DM and acidity; therefore, segregation of the inventory by DM will also segregate for acidity. High DM fruit are also more acidic with a higher, more favourable brix/acid ratio when ripe. It is recommended that fruit DM status be managed in the inventory, not by maturity area as is the current practice, but by groups of similar count sizes within maturity areas.
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Beaton, Duncan. "Integration of data description and quality information using metadata for spatial data and spatial information systems." Thesis, University of Newcastle Upon Tyne, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.321263.

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Berg, Jan. "Systematic evaluation of perceived spatial quality in surround sound systems /." Luleå : School of Music, Division of Sound Recording, 2002. http://epubl.luth.se/1402-1544/2002/17/index.html.

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Books on the topic "Spatial quality"

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Fisher, Peter F., and Michael F. Goodchild. Spatial Data Quality. Edited by Wenzhong Shi. Abingdon, UK: Taylor & Francis, 2002. http://dx.doi.org/10.4324/9780203303245.

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Devillers, Rodolphe, and Robert Jeansoulin, eds. Fundamentals of Spatial Data Quality. London, UK: ISTE, 2006. http://dx.doi.org/10.1002/9780470612156.

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Oort, Pepijn van. Spatial data quality: From description to application. Delft: NCG, Nederlandse Commissie voor Geodesie, 2005.

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Knox, Nichola Maria. Observing temporal and spatial variability of forage quality. Enschede: ITC, 2010.

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Yang, Li. The spatial data quality analysis in the environmental modelling. London: University of East London, 2001.

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Talhofer, Václav, Šárka Hošková-Mayerová, and Alois Hofmann. Quality of Spatial Data in Command and Control System. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-94562-0.

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Oyebanji, J. Oluwole. Social indicators and quality of life in Nigeria: A spatial analysis. Lagos State, Nigeria: Educational Professional & Scientific Publications, 1987.

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Dill, Robert W. Data warehousing and data quality for a Spatial Decision Support System. Monterey, Calif: Naval Postgraduate School, 1997.

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Dupont, Jacques. Réseau spatial de surveillance de l'acidité des lacs du Québec. [Québec]: Gouvernement du Québec, Ministère de l'environnement, 1990.

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Dupont, Jacques. Réseau spatial de surveillance de l'acidité des lacs du Québec . [Québec]: Direction de la qualité des cours d'eau, Ministère de l'environnement du Québec, 1993.

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Book chapters on the topic "Spatial quality"

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Plowright, Philip D. "Spatial Quality." In Making Architecture Through Being Human, 128. Abingdon, Oxon ; New York, NY : Routledge, 2020.: Routledge, 2019. http://dx.doi.org/10.4324/9780429261718-35.

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Shekhar, Shashi, and Hui Xiong. "Quality, Spatial Data." In Encyclopedia of GIS, 935. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_1062.

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Shekhar, Shashi, and Hui Xiong. "Spatial Data Quality." In Encyclopedia of GIS, 1087. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_1258.

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Frank, Matthias, Franz Zotter, Hagen Wierstorf, and Sascha Spors. "Spatial Audio Rendering." In Quality of Experience, 247–60. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-02681-7_17.

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Cepuder, P., and V. aus der Schmitten. "Spatial Modeling of Nitrogen Leaching." In Water Resources Quality, 33–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-642-56013-2_3.

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Schulze Bäing, Andreas. "Spatial Analysis." In Encyclopedia of Quality of Life and Well-Being Research, 6259–61. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-0753-5_2818.

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Baker, Mark. "Planning, Spatial." In Encyclopedia of Quality of Life and Well-Being Research, 4822–25. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-0753-5_2820.

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Palermo, Pier Carlo, and Davide Ponzini. "The Quality in Spatial Development." In Spatial Planning and Urban Development, 207–12. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-8870-3_25.

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Ballatore, Andrea, and Alexander Zipf. "A Conceptual Quality Framework for Volunteered Geographic Information." In Spatial Information Theory, 89–107. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23374-1_5.

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Hou, Zemin, and Yong Qi. "Quality Preference, Congestion, and Differentiation Strategy." In Spatial Economics Volume I, 265–94. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-40098-9_11.

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Conference papers on the topic "Spatial quality"

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Lu, Chunyan, and Jing Wang. "Data quality control in eco-environmental monitoring." In Second International Conference on Spatial Information Technology, edited by Cheng Wang, Shan Zhong, and Jiaolong Wei. SPIE, 2007. http://dx.doi.org/10.1117/12.780351.

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Mittal, Anish, Anush K. Moorthy, and Alan C. Bovik. "Blind/Referenceless Image Spatial Quality Evaluator." In 2011 45th Asilomar Conference on Signals, Systems and Computers. IEEE, 2011. http://dx.doi.org/10.1109/acssc.2011.6190099.

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Hristova, Hristina, Xavier Corbillon, Gwendal Simon, Viswanathan Swaminathan, and Alisa Devlic. "Heterogeneous Spatial Quality for Omnidirectional Video." In 2018 IEEE 20th International Workshop on Multimedia Signal Processing (MMSP). IEEE, 2018. http://dx.doi.org/10.1109/mmsp.2018.8547114.

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Xi, Jingke. "Spatial Clustering Algorithms and Quality Assessment." In 2009 International Joint Conference on Artificial Intelligence (JCAI). IEEE, 2009. http://dx.doi.org/10.1109/jcai.2009.162.

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Akbar, Fikri, Nanna Suryana, and Burairah Hussin. "Quality-based spatial/spectral image transformation." In 2010 2nd International Conference on Signal Processing Systems (ICSPS). IEEE, 2010. http://dx.doi.org/10.1109/icsps.2010.5555451.

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Huignard, J. P. "Spatial Light Modulators And Their Applications." In International Topical Meeting on Image Detection and Quality, edited by Lucien F. Guyot. SPIE, 1987. http://dx.doi.org/10.1117/12.966779.

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Yu, Honghai, and Stefan Winkler. "Image complexity and spatial information." In 2013 Fifth International Workshop on Quality of Multimedia Experience (QoMEX). IEEE, 2013. http://dx.doi.org/10.1109/qomex.2013.6603194.

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Li, Hong, Cheng-Kok Koh, Venkataramanan Balakrishnan, and Yiran Chen. "Statistical Timing Analysis Considering Spatial Correlations." In 8th International Symposium on Quality Electronic Design (ISQED'07). IEEE, 2007. http://dx.doi.org/10.1109/isqed.2007.149.

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Rai, Pranjal Kumar, Sajal Maheshwari, and Vineet Gandhi. "Document Quality Estimation Using Spatial Frequency Response." In ICASSP 2018 - 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2018. http://dx.doi.org/10.1109/icassp.2018.8461951.

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Su, Ying, Lei Yang, and Zhanming Jin. "Evaluating Spatial Data Quality in GIS Database." In 2007 International Conference on Wireless Communications, Networking and Mobile Computing. IEEE, 2007. http://dx.doi.org/10.1109/wicom.2007.1463.

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Reports on the topic "Spatial quality"

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Hudson, Tracy D. Spatial Light Modulators (SLMs) Surface Quality. Fort Belvoir, VA: Defense Technical Information Center, March 1993. http://dx.doi.org/10.21236/ada263249.

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Williams, R. J. Data Quality Statements for Spatial Databases. Fort Belvoir, VA: Defense Technical Information Center, July 1992. http://dx.doi.org/10.21236/ada264125.

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Mainali, Janardan. Spatial Statistical Approaches to Water Quality Modelling. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.7383.

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Raikow, David, Scott Kichman, Amanda McCutcheon, and Anne Farahi. Marine water quality in Pacific Island national parks: Temporal, spatial, and chemical patterns 2008–2015. National Park Service, January 2021. http://dx.doi.org/10.36967/nrr-2284328.

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Komppula, Birgitta, Tomi Karppinen, Henrik Virta, Anu-Maija Sundström, Iolanda Ialongo, Kaisa Korpi, Pia Anttila, Jatta Salmi, Johanna Tamminen, and Katja Lovén. Air quality in Finland according to air quality measurements and satellite observations. Finnish Meteorological Institute, September 2021. http://dx.doi.org/10.35614/isbn.9789523361409.

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In this report the current air quality in Finland has been assessed with air quality measurement data and satellite observations. The assessment of ambient air concentrations included following air impurities: NO2, NOx, PM10, PM2,5, SO2, CO, O3, benzo(a)pyrene, benzene, Pb, As, Cd ja Ni. For these pollutants air quality assessment thresholds are given in air quality legislation (2008/50/EY, 2004/107/EY). Assessment has been performed for air quality zones. The main data set included air quality measurements performed in Finland during 2015–2019. Satellite observations were used as an objective assessment tool in analysis of the spatial variation of NO2 and CO concentrations. Air quality measurements show that air quality has improved in Finland in many respects. Especially the need to monitor NO2 and PM10 with continuous measurements has decreased. Growing understanding of national benzo(a)pyrene concentrations has increased the monitoring needs. Efforts to decrease ozone levels still requires international actions. SO2, CO, benzene and heavy metal concentrations are on a low level in Finland outside industrial areas and other assessment methods than continuous monitoring can be used, and the number of continuous monitoring sites has already decreased. Satellite-based concentrations of nitrogen dioxide and carbon monoxide as well as their spatial variation in Finland were analyzed using observations from the TROPOsperic Monitoring Instrument (TROPOMI). The analysis of CO over Finland was carried out for the first time in this project. Results show that overall annual CO concentrations over Finland are low and spatial variability is small. Also, NO2 concentrations over Finland are rather low, but spatial patterns are more clearly visible. The highest NO2 concentrations are observed over the largest cities. By establishing a relationship between ground-based and satellite total column concentrations, surface concentrations of NO2 and CO were estimated from the satellite data for the zones. The satellite-based estimate for annual NO2 surface concentration over Helsinki metropolitan area is 28 μg/m3, and for the rest of Finland mostly between 10–15 μg/m3. For CO the differences between monitoring areas are small, with estimates varying between 160–164 μg/m3 or in other words about 0,16 mg/m3.
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Tait, Emma, David Gudex-Cross, and James Duncan. Standardized Spatial Datasets for Exploring the Connection Between Forest Cover and Water Quality in the Northeast. Forest Ecosystem Monitoring Cooperative, October 2020. http://dx.doi.org/10.18125/5xqty5.

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Galvis, Luis, Patrick J. Guertin, and William D. Meyer. Actionable Cultural Understanding for Support to Tactical Operations (ACUSTO): The Effect of Data Quality on Spatial Analysis Results. Fort Belvoir, VA: Defense Technical Information Center, June 2009. http://dx.doi.org/10.21236/ada522284.

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Kwon, Jaymin, Yushin Ahn, and Steve Chung. Spatio-Temporal Analysis of the Roadside Transportation Related Air Quality (STARTRAQ) and Neighborhood Characterization. Mineta Transportation Institute, August 2021. http://dx.doi.org/10.31979/mti.2021.2010.

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To promote active transportation modes (such as bike ride and walking), and to create safer communities for easier access to transit, it is essential to provide consolidated data-driven transportation information to the public. The relevant and timely information from data facilitates the improvement of decision-making processes for the establishment of public policy and urban planning for sustainable growth, and for promoting public health in the region. For the characterization of the spatial variation of transportation-emitted air pollution in the Fresno/Clovis neighborhood in California, various species of particulate matters emitted from traffic sources were measured using real-time monitors and GPS loggers at over 100 neighborhood walking routes within 58 census tracts from the previous research, Children’s Health to Air Pollution Study - San Joaquin Valley (CHAPS-SJV). Roadside air pollution data show that PM2.5, black carbon, and PAHs were significantly elevated in the neighborhood walking air samples compared to indoor air or the ambient monitoring station in the Central Fresno area due to the immediate source proximity. The simultaneous parallel measurements in two neighborhoods which are distinctively different areas (High diesel High poverty vs. Low diesel Low poverty) showed that the higher pollution levels were observed when more frequent vehicular activities were occurring around the neighborhoods. Elevated PM2.5 concentrations near the roadways were evident with a high volume of traffic and in regions with more unpaved areas. Neighborhood walking air samples were influenced by immediate roadway traffic conditions, such as encounters with diesel trucks, approaching in close proximity to freeways and/or busy roadways, passing cigarette smokers, and gardening activity. The elevated black carbon concentrations occur near the highway corridors and regions with high diesel traffic and high industry. This project provides consolidated data-driven transportation information to the public including: 1. Transportation-related particle pollution data 2. Spatial analyses of geocoded vehicle emissions 3. Neighborhood characterization for the built environment such as cities, buildings, roads, parks, walkways, etc.
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Ahmad, Ehtisham, and Hans van Rijn. The Role of Local Governments in Driving High-Quality Growth in the People’s Republic of China. Asian Development Bank, December 2020. http://dx.doi.org/10.22617/wps200400-2.

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Over the past 25 years, the People’s Republic of China has gone through a long period of remarkable growth, lifting millions of people out of poverty. But this focus on growth has come at a cost, particularly in terms of environmental degradation, increasing socioeconomic and spatial inequalities, and the building up of fiscal liabilities at the local government level. Under the High-Quality Growth agenda, the People’s Republic of China seeks to rebalance the economy by addressing those negative side effects, and local governments will have a key role to play in the implementation of that agenda. In this paper, some critical aspects of the fiscal and institutional environment in which local governments operate are analyzed, and proposals are offered for the strengthening of local government finances.
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Cai, Yongxia, Christopher M. Wade, Justin S. Baker, Jason P. H. Jones, Gregory S. Latta, Sara B. Ohrel, Shaun A. Ragnauth, and Jared R. Creason. Implications of alternative land conversion cost specifications on projected afforestation potential in the United States. RTI Press, November 2018. http://dx.doi.org/10.3768/rtipress.2018.op.0057.1811.

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The Forestry and Agriculture Sector Optimization Model with Greenhouse Gases (FASOMGHG) has historically relied on regional average costs of land conversion to simulate land use change across cropland, pasture, rangeland, and forestry. This assumption limits the accuracy of the land conversion estimates by not recognizing spatial heterogeneity in land quality and conversion costs. Using data from Nielsen et al. (2014), we obtained the afforestation cost per county, then estimated nonparametric regional marginal cost functions for land converting land to forestry. These afforestation costs were then incorporated into FASOMGHG. Three different assumptions for land moving into the forest sector were run; constant average conversion cost, static rising marginal costs and dynamic rising marginal cost, in order to assess the implications of alternative land conversion cost assumptions on key outcomes, such as projected forest area and cropland use, carbon sequestration, and forest product output.
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