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Understanding Completeness and Diversity Patterns of OSM-Based Land-Use and Land-Cover Dataset in China

School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China
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ISPRS Int. J. Geo-Inf. 2020, 9(9), 531; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9090531
Received: 2 July 2020 / Revised: 20 August 2020 / Accepted: 31 August 2020 / Published: 4 September 2020
OpenStreetMap (OSM) data are considered essential for land-use and land-cover (LULC) mapping despite their lack of quality. Most relevant studies have employed an LULC reference dataset for quality assessment, but such a reference dataset is not freely available for most countries and regions. Thus, this study conducts an intrinsic quality assessment of the OSM-based LULC dataset (i.e., without using a reference LULC dataset) by examining the patterns of both its completeness and diversity. With China chosen as the study area, an OSM-based LULC dataset of the country was first generated and validated by using various accuracy measures. Both its completeness and diversity patterns were then mapped and analyzed in terms of each prefecture-level division of the country. The results showed the following: (1) While the overall accuracy was as high as 82.2%, most complete regions of China were not mapped well owing to a lack of diverse LULC classes. (2) In terms of socioeconomic factors and the number of contributors, higher correlations were noted for diversity patterns than completeness patterns; thus, the diversity pattern is a better reflection of socioeconomic factors and the spatial patterns of contributors. (3) Both the completeness and the diversity patterns can be combined to better understand an OSM-based LULC dataset. These results indicate that it is useful to consider diversity as a supplement for intrinsically assessing the quality of an OSM-based LULC dataset. This analytical method can also be applied to other countries and regions. View Full-Text
Keywords: OpenStreetMap; LULC mapping; data quality; intrinsic quality assessment; completeness; diversity OpenStreetMap; LULC mapping; data quality; intrinsic quality assessment; completeness; diversity
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MDPI and ACS Style

Wang, S.; Zhou, Q.; Tian, Y. Understanding Completeness and Diversity Patterns of OSM-Based Land-Use and Land-Cover Dataset in China. ISPRS Int. J. Geo-Inf. 2020, 9, 531. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9090531

AMA Style

Wang S, Zhou Q, Tian Y. Understanding Completeness and Diversity Patterns of OSM-Based Land-Use and Land-Cover Dataset in China. ISPRS International Journal of Geo-Information. 2020; 9(9):531. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9090531

Chicago/Turabian Style

Wang, ShuZhu, Qi Zhou, and YuanJian Tian. 2020. "Understanding Completeness and Diversity Patterns of OSM-Based Land-Use and Land-Cover Dataset in China" ISPRS International Journal of Geo-Information 9, no. 9: 531. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9090531

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