scholarly journals A REGRESSION MODEL OF SPATIAL ACCURACY PREDICTION FOR OPENSTREETMAP BUILDINGS

2020 ◽  
Vol V-4-2020 ◽  
pp. 39-47
Author(s):  
I. Maidaneh Abdi ◽  
A. Le Guilcher ◽  
A-M. Olteanu-Raimond
Keyword(s):  
Regression Model ◽  
Spatial Data ◽  
Reference Data ◽  
Spatial Accuracy ◽  
Machine Learning Methods ◽  
Data Matching ◽  
Data Quality Assessment ◽  
Intrinsic Quality ◽  
Abstract Data

Abstract. Data quality assessment of OpenStreetMap (OSM) data can be carried out by comparing them with a reference spatial data (e.g authoritative data). However, in case of a lack of reference data, the spatial accuracy is unknown. The aim of this work is therefore to propose a framework to infer relative spatial accuracy of OSM data by using machine learning methods. Our approach is based on the hypothesis that there is a relationship between extrinsic and intrinsic quality measures. Thus, starting from a multi-criteria data matching, the process seeks to establish a statistical relationship between measures of extrinsic quality of OSM (i.e. obtained by comparison with reference spatial data) and the measures of intrinsic quality of OSM (i.e. OSM features themselves) in order to estimate extrinsic quality on an unevaluated OSM dataset. The approach was applied on OSM buildings. On our dataset, the resulting regression model predicts the values on the extrinsic quality indicators with 30% less variance than an uninformed predictor.

Traditional vs. Machine-Learning Techniques for OSM Quality Assessment

2019 ◽  
pp. 469-487
Author(s):  
Musfira Jilani ◽  
Michela Bertolotto ◽  
Padraig Corcoran ◽  
Amerah Alghanim
Keyword(s):  
Machine Learning ◽  
Data Quality ◽  
Quality Assessment ◽  
Spatial Data ◽  
Current Data ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
Data Quality Assessment ◽  
Expensive Process

Nowadays an ever-increasing number of applications require complete and up-to-date spatial data, in particular maps. However, mapping is an expensive process and the vastness and dynamics of our world usually render centralized and authoritative maps outdated and incomplete. In this context crowd-sourced maps have the potential to provide a complete, up-to-date, and free representation of our world. However, the proliferation of such maps largely remains limited due to concerns about their data quality. While most of the current data quality assessment mechanisms for such maps require referencing to authoritative maps, we argue that such referencing of a crowd-sourced spatial database is ineffective. Instead we focus on the use of machine learning techniques that we believe have the potential to not only allow the assessment but also to recommend the improvement of the quality of crowd-sourced maps without referencing to external databases. This chapter gives an overview of these approaches.

Traditional vs. Machine-Learning Techniques for OSM Quality Assessment

2017 ◽  
pp. 47-64
Author(s):  
Musfira Jilani ◽  
Michela Bertolotto ◽  
Padraig Corcoran ◽  
Amerah Alghanim
Keyword(s):  
Machine Learning ◽  
Data Quality ◽  
Quality Assessment ◽  
Spatial Data ◽  
Current Data ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
Data Quality Assessment ◽  
Expensive Process

Nowadays an ever-increasing number of applications require complete and up-to-date spatial data, in particular maps. However, mapping is an expensive process and the vastness and dynamics of our world usually render centralized and authoritative maps outdated and incomplete. In this context crowd-sourced maps have the potential to provide a complete, up-to-date, and free representation of our world. However, the proliferation of such maps largely remains limited due to concerns about their data quality. While most of the current data quality assessment mechanisms for such maps require referencing to authoritative maps, we argue that such referencing of a crowd-sourced spatial database is ineffective. Instead we focus on the use of machine learning techniques that we believe have the potential to not only allow the assessment but also to recommend the improvement of the quality of crowd-sourced maps without referencing to external databases. This chapter gives an overview of these approaches.

scholarly journals OpenStreetMap land cover data quality assessment on the example of Lower Silesia Voivodship, Poland

2018 ◽  
Vol 71 ◽  
pp. 00016
Author(s):  
Jakub Łuczak
Keyword(s):  
Information System ◽  
Land Cover ◽  
Reference Data ◽  
Geographic Information ◽  
Spatial Analyses ◽  
Land Cover Data ◽  
Data Quality Assessment ◽  
The World ◽  
Lower Silesia

OpenStreetMap (OSM) is an open source, freely available spatial database, co-created by users from around the world in the idea of volunteered geographic information. The functioning of the project as an open community geographic information system is its great advantage, however, it is associated with many flaws, like heterogeneity of collected data. The presented work focuses on the assessment of completeness and quality of land cover data. The reference data used in analysis were objects stored in the Baza Danych Obiektów Topograficznych (BDOT10k), which is an element of the Polish National Geodetic and Cartographic Resource. The analysis was carried out for the area of the Lower Silesia Voivodship. Despite the achievement of quite unsatisfactory results of the analysis, OpenStreetMap project has information potential and is useful in selected spatial analyses.

scholarly journals WEB SERVICE FOR POSITIONAL QUALITY ASSESSMENT: THE WPS TIER

2015 ◽  
Vol II-3/W5 ◽  
pp. 257-262 ◽  
Author(s):  
E. M. A. Xavier ◽  
F. J. Ariza-López ◽  
M. A. Ureña-Cámara
Keyword(s):  
Quality Assessment ◽  
Spatial Data ◽  
Positional Accuracy ◽  
Advantages And Disadvantages ◽  
Spatial Data Quality ◽  
Data Quality Assessment ◽  
Specific Assessment ◽  
Accuracy Assessments ◽  
Assessment Procedures

In the field of spatial data every day we have more and more information available, but we still have little or very little information about the quality of spatial data. We consider that the automation of the spatial data quality assessment is a true need for the geomatic sector, and that automation is possible by means of web processing services (WPS), and the application of specific assessment procedures. In this paper we propose and develop a WPS tier centered on the automation of the positional quality assessment. An experiment using the NSSDA positional accuracy method is presented. The experiment involves the uploading by the client of two datasets (reference and evaluation data). The processing is to determine homologous pairs of points (by distance) and calculate the value of positional accuracy under the NSSDA standard. The process generates a small report that is sent to the client. From our experiment, we reached some conclusions on the advantages and disadvantages of WPSs when applied to the automation of spatial data accuracy assessments.

scholarly journals APPLICATION FOR MEASURING REPRESENTATIVE VARIABLES OF COLLECTIVE SPACE INTELLIGENCE

2021 ◽  
Vol XLVI-4/W2-2021 ◽  
pp. 119-122
Author(s):  
C. A. Paiva ◽  
R. G. Campos ◽  
S. P. Camboim
Keyword(s):  
Developing Countries ◽  
Spatial Data ◽  
Reference Data ◽  
Related Research ◽  
Intrinsic Parameters ◽  
Spatial Intelligence ◽  
The Subject ◽  
Voluntary Geographic Information ◽  
Official Data

Abstract. The scarcity of metrics for analysing the quality of Voluntary Geographic Information without direct comparisons with reference data makes it impossible to use this information in many areas of society. Especially in developing countries, where collaborative data can help fill the deficit of official data, studies on intrinsic parameters of quality become an alternative to conventional comparative methods for evaluating spatial data. A recurring parameter in related research is Collective Spatial Intelligence. Seeking to offer researchers on the subject a tool capable of measuring the Collective Spatial Intelligence in predefined areas, we developed a Python application that counts representative values of this intelligence in political-administrative limits. Considering that, in general, the quality of spatial data is inferred on these limits, research that seeks to explain the VGI quality without using official data as a reference can be facilitated.

Physico-Chemical Analysis of Groundwater and Effect of Climatic Change in Angul-Talcher Area

2018 ◽  
Vol 6 (12) ◽  
pp. 26
Author(s):  
Aliva Bera ◽  
D.P. Satapathy
Keyword(s):  
Water Resources ◽  
Linear Regression ◽  
Regression Model ◽  
Climatic Change ◽  
Linear Regression Model ◽  
Ann Model ◽  
Quality Of Water ◽  
Physico Chemical ◽  
Simulation Based

In this paper, the linear regression model using ANN and the linear regression model using MS Excel were developed to estimate the physico-chemical concentrations in groundwater using pH, EC, TDS, TH, HCO3 as input parameters and Ca, Mg and K as output parameters. A comparison was made which indicated that ANN model had the better ability to estimate the physic-chemical concentrations in groundwater. An analytical survey along with simulation based tests for finding the climatic change and its effect on agriculture and water bodies in Angul-Talcher area is done. The various seasonal parameters such as pH, BOD, COD, TDS,TSS along with heavy elements like Pb, Cd, Zn, Cu, Fe, Mn concentration in water resources has been analyzed. For past 30 years rainfall data has been analyzed and water quality index values has been studied to find normal and abnormal quality of water resources and matlab based simulation has been done for performance analysis. All results has been analyzed and it is found that the condition is stable. 

Valuation mapping of hazards of the crisis natural and economic situations

2017 ◽  
Vol 929 (11) ◽  
pp. 40-49
Author(s):  
N.E. Krasnoshtanova ◽  
A.K. Cherkashin
Keyword(s):  
Spatial Data ◽  
Heterogeneous Information ◽  
Secondary Use ◽  
Raster Maps ◽  
Irkutsk Region ◽  
Homogeneous Network ◽  
Surrounding Areas ◽  
Integral Assessment ◽  
Multidimensional Statistics

An innovative technique for the secondary use of cartographic information for creating assessment hazard maps of crisis natural and economic situations and an integral assessment of the sustainability economic development and the quality of live is presented. Valuation mapping was carried for the Slyudyansky district of the Irkutsk region. A database has been created for homogeneous network of plots, which contains heterogeneous information about the nature and socio-economic environment of the district. Spatial data were processed using multidimensional statistics on the base of reliability theory models. An account of the environmental correction for each plots is an important aspect of the proposed technique of assessing and creating through maps. This makes it possible to reduce the evaluation function to an invariant form common to all locations and it is used in through way to create assessment maps for natural and socio-economic objects. As a result, a series of raster maps of through thematic content was made. The map of integral hazard of emergence of economic crisis situation displays the lowest hazard values for the territories of settlements and their surrounding areas, as well as areas along roads and railways. Additionally it allocates undeveloped valley of taiga rivers, advanced for economic use, primarily for recreational purposes.

Study on Application of Oat Flour in Quick-Frozen Dumpling Production

2013 ◽  
Vol 634-638 ◽  
pp. 1532-1536
Author(s):  
Chang Xin Ji ◽  
Xiao Yan Jing ◽  
Yan Qi Liu
Keyword(s):  
Regression Model ◽  
Correlation Coefficient ◽  
Sensory Evaluation ◽  
Outward Appearance ◽  
Optimal Amount ◽  
Oat Flour ◽  
Model Equations

Quick-frozen oat dumplings were produced by adding some Oat flour in dumpling wrapper. The effect of oat flour ratio on the optimal amount of water of the bland flour, cracking ratio and edible quality of quick-frozen oat dumpling were researched. The optimal amount of water of per gram Xiang Man Yuan dumpling flour and oat flour are 0.43g and 0.63g individually. The cracking ratio of products increases with the increases of oat flour ratio. The effect of oat flour ratio on the sensory evaluation and the outward appearance score of quick-frozen oat dumplings is very significant in 1‰ level, their correlation coefficient are 0.990 and 0.994 respectively, and the regression model equations are as follows: Y=90.094－112.477X; Y=18.519－21.763X.

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