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Development of a New Ground Truth Database for Global Urban Area Mapping from a Gazetteer
Center for Spatial Information Science, The University of Tokyo, 435 General Research Building, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8568, Japan
National Institute of Advanced Industrial Science and Technology, Tsukuba Central 2, Umezono 1-1-1, Tsukuba, Ibaraki 305-8568, Japan
* Author to whom correspondence should be addressed.
Received: 13 April 2011; in revised form: 21 May 2011 / Accepted: 31 May 2011 / Published: 3 June 2011
Abstract: We developed a ground truth database for urban areas from the Global Rural-Urban Mapping Project (GRUMP) Settlement Points gazetteer of populated place names by visually interpreting 3,734 urban points on satellite images, thus acquiring 2,144 urban and 1,388 non-urban data points. Our database contained many more urban data points than the existing databases, which had only 0 to 11 ground truth data points. We used our database in combination with the Degree Confluence Project database to assess the accuracy of eight satellite-derived urban area maps, among which the MODIS Terra + Aqua Land Cover Type Yearly L3 Global 500 m SIN Grid was the most accurate (84% overall accuracy; kappa coefficient, 0.63). Moreover, the most recently published maps were not necessarily the most accurate. We compared the accuracy assessment results of our database with those of another database and found that ours detected more errors of commission but included less chance agreement.
Keywords: global urban area mapping; ground truth; gazetteer
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Miyazaki, H.; Iwao, K.; Shibasaki, R. Development of a New Ground Truth Database for Global Urban Area Mapping from a Gazetteer. Remote Sens. 2011, 3, 1177-1187.
Miyazaki H, Iwao K, Shibasaki R. Development of a New Ground Truth Database for Global Urban Area Mapping from a Gazetteer. Remote Sensing. 2011; 3(6):1177-1187.
Miyazaki, Hiroyuki; Iwao, Koki; Shibasaki, Ryosuke. 2011. "Development of a New Ground Truth Database for Global Urban Area Mapping from a Gazetteer." Remote Sens. 3, no. 6: 1177-1187.