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author See, Linda
Georgieva, Ivelina
Duerauer, Martina
Kemper, Thomas
Corbane, Christina
Maffenini, Luca
Gallego, Javier
Pesaresi, Martino
Sirbu, Flavius
Ahmed, Rekib
Blyshchyk, Kateryna
Magori, Brigitte
Blyshchyk, Volodymyr
Melnyk, Oleksandr
Zadorozhniuk, Roman
Mandici, Marian-Traian
Su, Yuan-Fong
Rabia, Ahmed Harb
Pérez-Hoyos, Ana
Vasylyshyn, Roman
Pawe, Chandra Kant
Bilous, Svitlana
Kovalevskyi, Serhii B.
Kovalevskyi, Sergii S.
Bordoloi, Kusumbor
Bilous, Andrii
Panging, Kripal
Bilous, Valentyn
Prestele, Reinhard
Sahariah, Dhrubajyoti
Deka, Anjan
Nath, Nityaranjan
Neves, Rui
Myroniuk, Viktor
Karner, Mathias
Fritz, Steffen
author_facet See, Linda
Georgieva, Ivelina
Duerauer, Martina
Kemper, Thomas
Corbane, Christina
Maffenini, Luca
Gallego, Javier
Pesaresi, Martino
Sirbu, Flavius
Ahmed, Rekib
Blyshchyk, Kateryna
Magori, Brigitte
Blyshchyk, Volodymyr
Melnyk, Oleksandr
Zadorozhniuk, Roman
Mandici, Marian-Traian
Su, Yuan-Fong
Rabia, Ahmed Harb
Pérez-Hoyos, Ana
Vasylyshyn, Roman
Pawe, Chandra Kant
Bilous, Svitlana
Kovalevskyi, Serhii B.
Kovalevskyi, Sergii S.
Bordoloi, Kusumbor
Bilous, Andrii
Panging, Kripal
Bilous, Valentyn
Prestele, Reinhard
Sahariah, Dhrubajyoti
Deka, Anjan
Nath, Nityaranjan
Neves, Rui
Myroniuk, Viktor
Karner, Mathias
Fritz, Steffen
author_sort See, Linda
collection PubMed
description Several global high-resolution built-up surface products have emerged over the last five years, taking full advantage of open sources of satellite data such as Landsat and Sentinel. However, these data sets require validation that is independent of the producers of these products. To fill this gap, we designed a validation sample set of 50 K locations using a stratified sampling approach independent of any existing global built-up surface products. We launched a crowdsourcing campaign using Geo-Wiki (https://www.geo-wiki.org/) to visually interpret this sample set for built-up surfaces using very high-resolution satellite images as a source of reference data for labelling the samples, with a minimum of five validations per sample location. Data were collected for 10 m sub-pixels in an 80 × 80 m grid to allow for geo-registration errors as well as the application of different validation modes including exact pixel matching to majority or percentage agreement. The data set presented in this paper is suitable for the validation and inter-comparison of multiple products of built-up areas.
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spelling pubmed-87768812022-02-04 A crowdsourced global data set for validating built-up surface layers See, Linda Georgieva, Ivelina Duerauer, Martina Kemper, Thomas Corbane, Christina Maffenini, Luca Gallego, Javier Pesaresi, Martino Sirbu, Flavius Ahmed, Rekib Blyshchyk, Kateryna Magori, Brigitte Blyshchyk, Volodymyr Melnyk, Oleksandr Zadorozhniuk, Roman Mandici, Marian-Traian Su, Yuan-Fong Rabia, Ahmed Harb Pérez-Hoyos, Ana Vasylyshyn, Roman Pawe, Chandra Kant Bilous, Svitlana Kovalevskyi, Serhii B. Kovalevskyi, Sergii S. Bordoloi, Kusumbor Bilous, Andrii Panging, Kripal Bilous, Valentyn Prestele, Reinhard Sahariah, Dhrubajyoti Deka, Anjan Nath, Nityaranjan Neves, Rui Myroniuk, Viktor Karner, Mathias Fritz, Steffen Sci Data Data Descriptor Several global high-resolution built-up surface products have emerged over the last five years, taking full advantage of open sources of satellite data such as Landsat and Sentinel. However, these data sets require validation that is independent of the producers of these products. To fill this gap, we designed a validation sample set of 50 K locations using a stratified sampling approach independent of any existing global built-up surface products. We launched a crowdsourcing campaign using Geo-Wiki (https://www.geo-wiki.org/) to visually interpret this sample set for built-up surfaces using very high-resolution satellite images as a source of reference data for labelling the samples, with a minimum of five validations per sample location. Data were collected for 10 m sub-pixels in an 80 × 80 m grid to allow for geo-registration errors as well as the application of different validation modes including exact pixel matching to majority or percentage agreement. The data set presented in this paper is suitable for the validation and inter-comparison of multiple products of built-up areas. Nature Publishing Group UK 2022-01-20 /pmc/articles/PMC8776881/ /pubmed/35058477 http://dx.doi.org/10.1038/s41597-021-01105-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) applies to the metadata files associated with this article.
spellingShingle Data Descriptor
See, Linda
Georgieva, Ivelina
Duerauer, Martina
Kemper, Thomas
Corbane, Christina
Maffenini, Luca
Gallego, Javier
Pesaresi, Martino
Sirbu, Flavius
Ahmed, Rekib
Blyshchyk, Kateryna
Magori, Brigitte
Blyshchyk, Volodymyr
Melnyk, Oleksandr
Zadorozhniuk, Roman
Mandici, Marian-Traian
Su, Yuan-Fong
Rabia, Ahmed Harb
Pérez-Hoyos, Ana
Vasylyshyn, Roman
Pawe, Chandra Kant
Bilous, Svitlana
Kovalevskyi, Serhii B.
Kovalevskyi, Sergii S.
Bordoloi, Kusumbor
Bilous, Andrii
Panging, Kripal
Bilous, Valentyn
Prestele, Reinhard
Sahariah, Dhrubajyoti
Deka, Anjan
Nath, Nityaranjan
Neves, Rui
Myroniuk, Viktor
Karner, Mathias
Fritz, Steffen
A crowdsourced global data set for validating built-up surface layers
title A crowdsourced global data set for validating built-up surface layers
title_full A crowdsourced global data set for validating built-up surface layers
title_fullStr A crowdsourced global data set for validating built-up surface layers
title_full_unstemmed A crowdsourced global data set for validating built-up surface layers
title_short A crowdsourced global data set for validating built-up surface layers
title_sort crowdsourced global data set for validating built-up surface layers
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8776881/
https://www.ncbi.nlm.nih.gov/pubmed/35058477
http://dx.doi.org/10.1038/s41597-021-01105-4
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