Journal articles: '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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Batista Lopes, Cláudia, María Eduarda Pereira, Carlos Vale, Ana Isabel Lillebo, Miguel Ângelo Pardal, and Armando Costa Duarte. "Assessment of spatial environmental quality status in Ria de Aveiro (Portugal)." Scientia Marina 71, no. 2 (June 30, 2007): 293–304. http://dx.doi.org/10.3989/scimar.2007.71n2293.

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Fajarwati, Septi Dwi, Asma Irma Setianingsih, and Muzani Muzani. "ANALISIS KONDISI LAMUN (SEAGRASS) DI PERAIRAN PULAU PRAMUKA, KEPULAUAN SERIBU." Jurnal SPATIAL Wahana Komunikasi dan Informasi Geografi 13, no. 1 (March 2, 2015): 22–32. http://dx.doi.org/10.21009/spatial.131.03.

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ABSTRACT This research aims to analyze the condition of seagrass ecosystem to see water quality data of the seagrass habitat and percentage cover of seagrass in the waters of the Pramuka Island, Seribu Islands. The research was conducted over two months from October to November 2014.This research used a descriptive method with field survey approach. The population in this study is the seagrass in Waters Pramuka Island. Determining the location with purposive sampling of the sampling is divided into three stations is North, East and South. Data collection techniques include primary data and secondary data. Primary data is data of seagrass (type, percentage cover and density of seagrass) and data of seagrass habitat environmental parameters (water temperature, current speed, brightness, depth, salinity, substrate, TSS, DO, pH) were obtained by direct measurement in the field, while secondary data include the general state of the research sites. Data analysis techniques used in this study using analysis of community structure of seagrass and water quality analysis. The results showed that seagrass species found in the Pramuka Island there are 6 types of seagrass Cymodocea rotundata, Cymodocea serrulata, Enhalus acoroides, Halophila ovalis, Halodule uninervis, Thalassia hemprichii. Conditions of seagrass in the waters of the Pramuka Island included into the category of less healthy-poor seagrass. At station 1 percentage by 31% classified seagrass less healthy conditions, while the other two stations are stations 2 and 3 belong to the category of the poor condition of seagrass, with each percentage cover of seagrass 19.4% and 20.3%. Of all water quality parameters measured, all the parameters are still in normal circumstances, but there are some parameters whose value is high at some stations TSS and pH value is high at station 2 with a value of TSS 18 mg/l and a pH value of 8.2. Water quality and seagrass communities in station 1 is still in good condition for the growth of seagrass, because at this station is an unspoiled area away from human activity, while the stations 2 and 3 have undergone changes in community structure of seagrass because at this station has several anthropogenic activities that disrupt the lives of seagrass, mostly from human activities such as domestic sewage and hoarding/reclamation, which affects the condition of seagrass at station 2 and 3 are poor seagrass. Keyword: Seagrass, Water Quality, Pramuka Island

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Brekke, Kurt R., Luigi Siciliani, and Odd Rune Straume. "Price and quality in spatial competition." Regional Science and Urban Economics 40, no. 6 (November 2010): 471–80. http://dx.doi.org/10.1016/j.regsciurbeco.2010.06.003.

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Baker, L. R. "Digital cameras: spatial image quality matters." Imaging Science Journal 53, no. 1 (March 2005): 38–45. http://dx.doi.org/10.1179/136821905x26890.

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Lindau, Alexander, Vera Erbes, Steffen Lepa, Hans-Joachim Maempel, Fabian Brinkman, and Stefan Weinzierl. "A Spatial Audio Quality Inventory (SAQI)." Acta Acustica united with Acustica 100, no. 5 (September 1, 2014): 984–94. http://dx.doi.org/10.3813/aaa.918778.

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Jetten, Victor, Gerard Govers, and Rudi Hessel. "Erosion models: quality of spatial predictions." Hydrological Processes 17, no. 5 (2003): 887–900. http://dx.doi.org/10.1002/hyp.1168.

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Yiu, Man Lung, Hua Lu, Nikos Mamoulis, and Michail Vaitis. "Ranking Spatial Data by Quality Preferences." IEEE Transactions on Knowledge and Data Engineering 23, no. 3 (March 2011): 433–46. http://dx.doi.org/10.1109/tkde.2010.119.

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Wu, C. Victor, and Barbara P. Buttenfield. "Spatial data quality and its evaluation." Computers, Environment and Urban Systems 18, no. 3 (May 1994): 153–65. http://dx.doi.org/10.1016/0198-9715(94)90022-1.

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Vizzari, Marco. "Spatial modelling of potential landscape quality." Applied Geography 31, no. 1 (January 2011): 108–18. http://dx.doi.org/10.1016/j.apgeog.2010.03.001.

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Müller, Sven, and Knut Haase. "Local revenue response to service quality: spatial effects in seasonal ticket revenue data." European Journal of Marketing 49, no. 9/10 (September 14, 2015): 1391–416. http://dx.doi.org/10.1108/ejm-10-2013-0531.

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Purpose – This paper aims to consider spatial effects in the analysis of the relationship of revenue and service quality. When firms’ customers are located in spatially dispersed areas, it can be difficult to manage service quality on a geographically small scale because the relative importance of service quality might vary spatially. Moreover, standard approaches discussed so far in the marketing science literature usually neglect spatial effects, such as spatial dependencies (e.g. spatial autocorrelation) and spatial drift (spatial non-stationarity). Design/methodology/approach – The authors propose a comprehensive but intelligible approach based on spatial econometric methods that cover spatial dependencies and spatial drift simultaneously. In particular, they incorporate the spatial expansion method (spatial drift) into spatial econometric models (e.g. spatial lag model). Findings – Using real company data on seasonal ticket revenue (dependent variable) and service quality (independent variables) of a regional public transport service provider, the authors find that the elasticity for the length of the public transport network is between 0.2 and 0.5, whereas the elasticity for the headway is between −0.2 and 0.6, for example. The authors control for several socio-economic, socio-demographic and land-use variables. Practical implications – Based on the empirical findings, the authors show that addressing spatial effects of service data can improve management’s ability to implement programs aimed at enhancing seasonal ticket revenue. Therefore, they derive a spatial revenue response function that enables managers to identify small-scale areas that are most efficient in terms of increasing revenue by service improvement. Originality/value – The paper addresses the need to account for spatial effects in revenue response functions of public transport companies.

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Acre, Fernanda, and Annemie Wyckmans. "Spatial quality determinants for residential building renovation: A methodological approach to the development of spatial quality assessment." International Journal of Sustainable Building Technology and Urban Development 5, no. 3 (July 3, 2014): 183–204. http://dx.doi.org/10.1080/2093761x.2014.923793.

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* Ramamoorthy.P, *. Ramamoorthy P., Rammohan V. Rammohan.V, and Subramani T. Subramani.T. "Spatial analysis of groundwater quality in Varahanadi Watershed, Tamil Nadu, using GIS techniques." International Journal of Scientific Research 3, no. 3 (June 1, 2012): 141–45. http://dx.doi.org/10.15373/22778179/march2014/46.

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Alberti, Simon. "Molecular mechanisms of spatial protein quality control." Prion 6, no. 5 (November 2012): 437–42. http://dx.doi.org/10.4161/pri.22470.

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Meijer, M., L. A. E. Vullings, J. D. Bulens, F. I. Rip, M. Boss, G. Hazeu, and M. Storm. "SPATIAL DATA QUALITY AND A WORKFLOW TOOL." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-3/W3 (August 19, 2015): 55–59. http://dx.doi.org/10.5194/isprsarchives-xl-3-w3-55-2015.

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Although by many perceived as important, spatial data quality has hardly ever been taken centre stage unless something went wrong due to bad quality. However, we think this is going to change soon. We are more and more relying on data driven processes and due to the increased availability of data, there is a choice in what data to use. How to make that choice? We think spatial data quality has potential as a selection criterion. <br><br> In this paper we focus on how a workflow tool can help the consumer as well as the producer to get a better understanding about which product characteristics are important. For this purpose, we have developed a framework in which we define different roles (consumer, producer and intermediary) and differentiate between product specifications and quality specifications. A number of requirements is stated that can be translated into quality elements. We used case studies to validate our framework. This framework is designed following the fitness for use principle. Also part of this framework is software that in some cases can help ascertain the quality of datasets.

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Yılmaz, C., and Ç. Cömert. "ONTOLOGY BASED QUALITY EVALUATION FOR SPATIAL DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-3/W3 (August 19, 2015): 95–99. http://dx.doi.org/10.5194/isprsarchives-xl-3-w3-95-2015.

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Many institutions will be providing data to the National Spatial Data Infrastructure (NSDI). Current technical background of the NSDI is based on syntactic web services. It is expected that this will be replaced by semantic web services. The quality of the data provided is important in terms of the decision-making process and the accuracy of transactions. Therefore, the data quality needs to be tested. This topic has been neglected in Turkey. Data quality control for NSDI may be done by private or public “data accreditation” institutions. A methodology is required for data quality evaluation. There are studies for data quality including ISO standards, academic studies and software to evaluate spatial data quality. ISO 19157 standard defines the data quality elements. Proprietary software such as, 1Spatial’s 1Validate and ESRI’s Data Reviewer offers quality evaluation based on their own classification of rules. Commonly, rule based approaches are used for geospatial data quality check. In this study, we look for the technical components to devise and implement a rule based approach with ontologies using free and open source software in semantic web context. Semantic web uses ontologies to deliver well-defined web resources and make them accessible to end-users and processes. We have created an ontology conforming to the geospatial data and defined some sample rules to show how to test data with respect to data quality elements including; attribute, topo-semantic and geometrical consistency using free and open source software. To test data against rules, sample GeoSPARQL queries are created, associated with specifications.

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Susilowati, Y., Y. Kumoro, and W. H. Nur. "Integrated water quality modelling for spatial planning." IOP Conference Series: Earth and Environmental Science 483 (June 13, 2020): 012041. http://dx.doi.org/10.1088/1755-1315/483/1/012041.

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Claeys, Peter, and Fabio Manca. "A missing spatial link in institutional quality." Applied Economics Letters 18, no. 3 (February 2011): 223–27. http://dx.doi.org/10.1080/13504850903559542.

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McGRANAGHAN, MATTHEW. "A Cartographic View of Spatial Data Quality." Cartographica: The International Journal for Geographic Information and Geovisualization 30, no. 2-3 (October 1993): 8–19. http://dx.doi.org/10.3138/310v-0067-7570-6566.

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Zandbergen, Paul A. "Geocoding Quality and Implications for Spatial Analysis." Geography Compass 3, no. 2 (February 10, 2009): 647–80. http://dx.doi.org/10.1111/j.1749-8198.2008.00205.x.

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Delavar, Mahmoud R., and Rodolphe Devillers. "Spatial Data Quality: From Process to Decisions." Transactions in GIS 14, no. 4 (August 2010): 379–86. http://dx.doi.org/10.1111/j.1467-9671.2010.01224.x.

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Morenikeji, Wole, Emmanuel Umaru, Halilu Pai, Solomon Jiya, Owoeye Idowu, and B. M. Adeleye. "Spatial analysis of housing quality in Nigeria." International Journal of Sustainable Built Environment 6, no. 2 (December 2017): 309–16. http://dx.doi.org/10.1016/j.ijsbe.2017.03.008.

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Borsekova, Kamila, Karima Kourtit, and Peter Nijkamp. "Smart development, spatial sustainability and environmental quality." Habitat International 68 (October 2017): 1–2. http://dx.doi.org/10.1016/j.habitatint.2017.08.001.

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Yang, Xichen, Quansen Sun, and Tianshu Wang. "Image quality assessment via spatial structural analysis." Computers & Electrical Engineering 70 (August 2018): 349–65. http://dx.doi.org/10.1016/j.compeleceng.2016.08.014.

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Kang, Taegu, Hyuk Lee, Ilseok Kang, and Tae-Young Heo. "A Study on Spatial Prediction of Water Quality Constituents Using Spatial Model." Journal of Korean Society on Water Environment 30, no. 4 (July 30, 2014): 409–17. http://dx.doi.org/10.15681/kswe.2014.30.4.409.

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Sugihara, Yoshinori, Akira Watanabe, and Chiaki Yoshida. "Subjective spatial frequency and picture quality estimating function I: Subjective spatial frequency." Journal of the Institute of Television Engineers of Japan 41, no. 12 (1987): 1173–76. http://dx.doi.org/10.3169/itej1978.41.1173.

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Mikhaylov, Aleksandr, Roman Grubka, Aleksey Lahin, Alexander Nedashkovskiy, and Ahmed Guitouni. "Structural and Technology Support Quality Improvement of Gear Coupling." Applied Mechanics and Materials 371 (August 2013): 3–7. http://dx.doi.org/10.4028/www.scientific.net/amm.371.3.

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In this work the question of sharing use a thermo-mechanical treatment method and forming spatial tool based on a kinematic method researches gearings, is considered. Also, the method of thermo mechanical treatment a gear couplings teeth, with the receiving a spatial teeth geometry and ensuring required physical- mechanical properties of them, is presented. For implementation of this method, the scheme of the device and the special tool is developed, which allows to fair blanking of spatially modified teeth. The design procedure a teeth tool’s geometric parameters of the line addendum modification are offered.

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Schaduw, Joshian N. W. "EVALUASI PENGELOLAAN EKOSISTEM MANGROVE PADA DAERAH PERLINDUNGAN LAUT DI DESA BLONGKO, KECAMATAN SINONSAYANG KABUPATEN MINAHASA SELATAN PROVINSI SULAWESI UTARA." Jurnal SPATIAL Wahana Komunikasi dan Informasi Geografi 16, no. 2 (September 30, 2016): 27–38. http://dx.doi.org/10.21009/spatial.162.04.

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ABSTRACT Mangrove ecosystem in Blongko village has many functions for coastal area. The aims of this research was to describe potential and the existing condition of mangrove ecosystem and also to give directive policy strategic for conservation mangrove ecosystem in this area. This research used primary and secondary data. Primary data was gathered by field observation and in-depth interview with 100 respondens by questionnary. Secondary data was gathered by unravel various literature and related institution. The development indicators was used to determine the policy strategic of sustainable mangrove ecosystem. Its was threat, factor, and constraint causing degradation mangrove ecosystem. This research got three policy strategy to carry on of sustainable mangrove ecosystem. Its was increase of human resources quality, protection and continuation of mangrove ecosystem, and low and institution reinforcement. This strategy was expected to depress degradation in mangrove ecosystem. Keywords : Coastal Area; Blongko village; Mangrove Ecosystem; Policy Strategy.

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Park, No-Wook, and Phaedon C. Kyriakidis. "A Geostatistical Approach to Spatial Quality Assessment of Coarse Spatial Resolution Remote Sensing Products." Journal of Sensors 2019 (June 19, 2019): 1–14. http://dx.doi.org/10.1155/2019/7297593.

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A geostatistical framework for spatial quality assessment framework of coarse resolution remote sensing products is presented that can account for either the scale difference or the uncertainty of reference value prediction at coarse resolutions. A set of multiple reference field realizations is first generated at a fine spatial resolution using geostatistical simulation to explore the uncertainty in the true unknown reference field. The upscaling of multiple reference field realizations to coarse resolution is then followed to match the spatial resolution of the target remote sensing product and create coarse resolution reference fields. The simulated reference values at each coarse pixel are compared to the corresponding reported value from the coarse resolution remote sensing product, yielding alternative error values, from which several location-dependent statistics such as mean error, mean absolute error, and probability of overestimation can be computed. An experiment involving monthly Tropical Rainfall Measuring Mission (TRMM) precipitation products and point-level rain gauge data over South Korea illustrates the applicability of the proposed approach. The spatially distributed error statistics are useful to identify areas with larger errors and the degree of overestimation in the study area, leading to the identification of areas with unreliable estimates within the TRMM precipitation products. Therefore, it is expected that the geostatistical assessment framework presented in this paper can be effectively used to evaluate the spatial quality of coarse resolution remote sensing products.

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Skowronek, Janto, and Alexander Raake. "Assessment of Cognitive Load, Speech Communication Quality and Quality of Experience for spatial and non-spatial audio conferencing calls." Speech Communication 66 (February 2015): 154–75. http://dx.doi.org/10.1016/j.specom.2014.10.003.

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Marder, Christopher, and Jennifer Bernstein. "The Role of Precision in Spatial Narratives: Using a Modified Discourse Quality Index to Measure the Quality of Deliberative Spatial Data." International Journal of Humanities and Arts Computing 14, no. 1-2 (March 2020): 197–217. http://dx.doi.org/10.3366/ijhac.2020.0252.

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The importance of spatial precision in geographic information science is not limited to quantitative data. As spatial data can also exist in qualitative form, modifying a discourse quality index from the field of discourse ethics can help understand whether mentioning specific spatial locations changes the quality of spatial narratives. The discourse quality index was modified by incorporating an item into the index that detected the presence and magnitude of a spatial precision construct. The spatial narratives analyzed with this modified index were 151 public comments submitted during a public policy revision process, for a national forest plan revision at the Chugach National Forest in Alaska, USA. Analysis showed when discourse quality values underwent a comparison of means test, the values were significantly changed between comments with no spatial precision versus those considered to have spatial precision. The results suggest, preliminarily, that employing spatial precision in narratives changes discourse quality during deliberative activities. Further, the way in which people use spatial precision to communicate during a policy revision process can impact how spatial narratives are understood and valued.

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Choi, Jaewan, Junho Yeom, Anjin Chang, Younggi Byun, and Yongil Kim. "Hybrid Pansharpening Algorithm for High Spatial Resolution Satellite Imagery to Improve Spatial Quality." IEEE Geoscience and Remote Sensing Letters 10, no. 3 (May 2013): 490–94. http://dx.doi.org/10.1109/lgrs.2012.2210857.

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Schoeffler, Michael, Andreas Silzle, and Jurgen Herre. "Evaluation of Spatial/3D Audio: Basic Audio Quality Versus Quality of Experience." IEEE Journal of Selected Topics in Signal Processing 11, no. 1 (February 2017): 75–88. http://dx.doi.org/10.1109/jstsp.2016.2639325.

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Nagurney, Anna, Dong Li, and Ladimer S. Nagurney. "Spatial price equilibrium with information asymmetry in quality and minimum quality standards." International Journal of Production Economics 158 (December 2014): 300–313. http://dx.doi.org/10.1016/j.ijpe.2014.08.013.

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Hu, Xiao-Bing, Hang Li, XiaoMei Guo, Pieter H. A. J. M. van Gelder, and Peijun Shi. "Spatial Vulnerability of Network Systems under Spatially Local Hazards." Risk Analysis 39, no. 1 (March 23, 2018): 162–79. http://dx.doi.org/10.1111/risa.12986.

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Acre, Fernanda, and Annemie Wyckmans. "The impact of dwelling renovation on spatial quality." Smart and Sustainable Built Environment 4, no. 3 (November 16, 2015): 268–309. http://dx.doi.org/10.1108/sasbe-05-2015-0008.

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Purpose – Non-technical dimensions such as spatial quality are just as relevant for energy efficiency as technical and economic dimensions in the renovation of dwellings. However, the significance of non-technical dimensions is often neglected in the energy renovation of dwellings. The purpose of this paper is to demonstrate how the renovation of dwellings for energy efficiency influences spatial quality in the MS-1 building in the neighbourhood of Arlequin, Grenoble, France. The Arlequin case study is part of the ZenN project, nearly zero energy neighbourhoods, funded by the European 7th Framework Programme (Grant Agreement No. 314363). Design/methodology/approach – The impact of the renovation on spatial quality is analysed by crossing technical measures, applied in the energy renovation of dwellings with the definition of spatial quality proposed by Acre and Wyckmans (2014). The spatial quality definition results from a literature review on quality of design and urban life, wherein works of Weber (1995) and Gehl (2010, 2011) are related to the residential use in the scales of the building and block. The impact of renovation on spatial quality is further evaluated by using the spatial quality assessment developed by Acre and Wyckmans (2015). The impact on spatial quality is observed by considering all the renovation measures, instead of only considering the measures primarily related to energy performance. This emphasises the need for a cross-disciplinary approach between technical and non-technical dimensions in the energy renovation of dwellings. Findings – The results display both negative and positive impacts of the energy renovation on spatial quality in the dwellings and emphasise the potential of non-technical dimensions in promoting renovation. The impact on spatial quality is primarily negative when only measures adopted in order to improve energy efficiency are considered in the evaluation. Originality/value – This paper consists of a novel crossing of technical and non-technical dimensions in energy renovation of dwellings. The work aligns with the current European trend of nurturing energy-deep renovation to reach Europe’s 2050 energy-efficiency targets (Buildings Performance Institute Europe (BPIE) 2011).

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Fry, Edward W. S., Sophie Triantaphillidou, Robin B. Jenkin, Ralph E. Jacobson, and John R. Jarvis. "Scene-and-Process-Dependent Spatial Image Quality Metrics." Journal of Imaging Science and Technology 63, no. 6 (November 1, 2019): 60407–1. http://dx.doi.org/10.2352/j.imagingsci.technol.2019.63.6.060407.

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Abstract Spatial image quality metrics designed for camera systems generally employ the Modulation Transfer Function (MTF), the Noise Power Spectrum (NPS) and a visual contrast detection model. Prior art indicates that scene-dependent characteristics of non-linear, content-aware image processing are unaccounted for by MTFs and NPSs measured by traditional methods. The authors present two novel metrics: the log Noise Equivalent Quanta (log NEQ) and Visual log NEQ. They both employ Scene-and-Process-Dependent MTF (SPD-MTF) and NPS (SPD-NPS) measures, which account for signal transfer and noise scene dependency, respectively. The authors also investigate implementing contrast detection and discrimination models that account for scene-dependent visual masking. Also, three leading camera metrics are revised to use the above scene-dependent measures. All metrics are validated by examining correlations with the perceived quality of images produced by simulated camera pipelines. Metric accuracy improved consistently when the SPD-MTFs and SPD-NPSs were implemented. The novel metrics outperformed existing metrics of the same genre.

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Nillesen, Anne Loes. "Water-safety strategies and local-scale spatial quality." Proceedings of the Institution of Civil Engineers - Municipal Engineer 166, no. 1 (March 2013): 16–23. http://dx.doi.org/10.1680/muen.12.00006.

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Jones, D., W. Wang, and R. Fawcett. "High-quality spatial climate data-sets for Australia." Australian Meteorological and Oceanographic Journal 58, no. 04 (December 2009): 233–48. http://dx.doi.org/10.22499/2.5804.003.

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Oliker, Nurit, Ziv Ohar, and Avi Ostfeld. "Spatial event classification using simulated water quality data." Environmental Modelling & Software 77 (March 2016): 71–80. http://dx.doi.org/10.1016/j.envsoft.2015.11.013.

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Hower, James C., Alan S. Trimble, and Cortland F. Eble. "Temporal and spatial variations in fly ash quality." Fuel Processing Technology 73, no. 1 (October 2001): 37–58. http://dx.doi.org/10.1016/s0378-3820(01)00193-x.

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Journal articles on the topic 'Spatial quality'

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