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Articles

The impact of object size on the thematic accuracy of landcover maps

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Pages 1029-1037 | Received 15 Mar 2013, Accepted 30 Nov 2013, Published online: 05 Feb 2014

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Shiran Song, Jianhua Liu, Yuan Liu, Guoqiang Feng, Hui Han, Yuan Yao & Mingyi Du. (2020) Intelligent Object Recognition of Urban Water Bodies Based on Deep Learning for Multi-Source and Multi-Temporal High Spatial Resolution Remote Sensing Imagery. Sensors 20:2, pages 397.
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Isaac Kyere, Thomas Astor, Rüdiger Graß & Michael Wachendorf. (2019) Multi-Temporal Agricultural Land-Cover Mapping Using Single-Year and Multi-Year Models Based on Landsat Imagery and IACS Data. Agronomy 9:6, pages 309.
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Hugo Costa, Diana Almeida, Francisco Vala, Filipe Marcelino & Mário Caetano. (2018) Land Cover Mapping from Remotely Sensed and Auxiliary Data for Harmonized Official Statistics. ISPRS International Journal of Geo-Information 7:4, pages 157.
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J. Velázquez, J. Gutiérrez, A. Hernando, A. García-Abril, M.A. Martín & P. Irastorza. (2018) Measuring mosaic diversity based on land use map in the region of Madrid, Spain. Land Use Policy 71, pages 329-334.
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A. Hernando, J. Velázquez, R. Valbuena, M. Legrand & A. García-Abril. (2017) Influence of the resolution of forest cover maps in evaluating fragmentation and connectivity to assess habitat conservation status. Ecological Indicators 79, pages 295-302.
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Julien Radoux & Patrick Bogaert. (2017) Good Practices for Object-Based Accuracy Assessment. Remote Sensing 9:7, pages 646.
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Hugo Costa, Giles M. Foody & Doreen S. Boyd. (2017) Using mixed objects in the training of object-based image classifications. Remote Sensing of Environment 190, pages 188-197.
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