By Jamal Jokar Arsanjani, Alexander Zipf, Peter Mooney, Marco Helbich
This edited quantity offers a set of classes discovered with, and examine performed on, OpenStreetMap, the objective being to advertise the project’s integration. The respective chapters tackle a) state of the art and state of the art ways to information caliber research in OpenStreetMap, b) investigations on realizing OpenStreetMap members and the character in their contributions, c) picking out styles of contributions and individuals, d) functions of OpenStreetMap in numerous domain names, e) mining value-added wisdom and knowledge from OpenStreetMap, f) obstacles within the research OpenStreetMap information, and g) integrating OpenStreetMap with advertisement and non-commercial datasets. The booklet deals an excellent chance to give and disseminate a couple of state-of-the-art advancements and purposes within the box of geography, spatial records, GIS, social technological know-how, and cartography.
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Extra resources for OpenStreetMap in GIScience: Experiences, Research, and Applications
2013), completeness is the major criterion for using OSM datasets as it is an indicator of how much of the whole has been mapped. Although measuring the degree of completeness for polyline and point features in OSM datasets requires a reference dataset, the completeness for LU features within a certain area can be measured 48 J. Jokar Arsanjani et al. even without having any reference dataset. Because every piece of the land should have an attribute, so the total coverage area is the maximum area to be mapped.
In brief, people interpret and integrate remote sensing images along with their personal information and their GPS-enabled device records. This sort of information has been called Volunteered Geographic Information (VGI): (Goodchild 2007). Among the CMPs, OSM is a unique platform in collecting LU features, because OSM has been so far a pioneer CMP due to attracting a huge amount of public attention and contributions (Ramm et al. 9 million users until December, 2014 and continue to grow as outlined by Jokar Arsanjani et al.
Consequently, the confusion matrices for the selected cities were designed for the most optimal pixel size applicable for every city at 15 m. 2 Degree of Data Completeness This measure for each city is shown in Fig. 4, which indicates that Berlin has reached the highest degree of completeness, and Frankfurt has the lowest degree of completeness. This value is much higher than the reported value for the Portugal continent at 3 % by Estima and Painho (2013) and conﬁrms how greatly completeness index varies and how heterogeneous the quantity of contributions is.