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Validation of Automatically Generated Global and Regional Cropland Data Sets: The Case of Tanzania
There is a need to validate existing global cropland maps since they are used for different purposes including agricultural monitoring and assessment. In this paper we validate three recent global products (ESA-CCI, GlobeLand30, FROM-GC) and one regional product (Tanzania Land Cover 2010 Scheme II)...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MPDI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7340490/ https://www.ncbi.nlm.nih.gov/pubmed/32704489 http://dx.doi.org/10.3390/rs9080815 |
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author | Laso Bayas, Juan Carlos See, Linda Perger, Christoph Justice, Christina Nakalembe, Catherine Dempewolf, Jan Fritz, Steffen |
author_facet | Laso Bayas, Juan Carlos See, Linda Perger, Christoph Justice, Christina Nakalembe, Catherine Dempewolf, Jan Fritz, Steffen |
author_sort | Laso Bayas, Juan Carlos |
collection | PubMed |
description | There is a need to validate existing global cropland maps since they are used for different purposes including agricultural monitoring and assessment. In this paper we validate three recent global products (ESA-CCI, GlobeLand30, FROM-GC) and one regional product (Tanzania Land Cover 2010 Scheme II) using a validation data set that was collected by students through the Geo-Wiki tool. The ultimate aim was to understand the usefulness of these products for agricultural monitoring. Data were collected wall-to-wall for Kilosa district and for a sample across Tanzania. The results show that the amount of and spatial extent of cropland in the different products differs considerably from 8% to 42% for Tanzania, with similar values for Kilosa district. The agreement of the validation data with the four different products varied between 36% and 54% and highlighted that cropland is overestimated by the ESA-CCI and underestimated by FROM-GC. The validation data were also analyzed for consistency between the student interpreters and also compared with a sample interpreted by five experts for quality assurance. Regarding consistency between the students, there was more than 80% agreement if one difference in cropland category was considered (e.g., between low and medium cropland) while most of the confusion with the experts was also within one category difference. In addition to the validation of current cropland products, the data set collected by the students also has potential value as a training set for improving future cropland products. |
format | Online Article Text |
id | pubmed-7340490 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MPDI |
record_format | MEDLINE/PubMed |
spelling | pubmed-73404902020-07-21 Validation of Automatically Generated Global and Regional Cropland Data Sets: The Case of Tanzania Laso Bayas, Juan Carlos See, Linda Perger, Christoph Justice, Christina Nakalembe, Catherine Dempewolf, Jan Fritz, Steffen Remote Sens (Basel) Article There is a need to validate existing global cropland maps since they are used for different purposes including agricultural monitoring and assessment. In this paper we validate three recent global products (ESA-CCI, GlobeLand30, FROM-GC) and one regional product (Tanzania Land Cover 2010 Scheme II) using a validation data set that was collected by students through the Geo-Wiki tool. The ultimate aim was to understand the usefulness of these products for agricultural monitoring. Data were collected wall-to-wall for Kilosa district and for a sample across Tanzania. The results show that the amount of and spatial extent of cropland in the different products differs considerably from 8% to 42% for Tanzania, with similar values for Kilosa district. The agreement of the validation data with the four different products varied between 36% and 54% and highlighted that cropland is overestimated by the ESA-CCI and underestimated by FROM-GC. The validation data were also analyzed for consistency between the student interpreters and also compared with a sample interpreted by five experts for quality assurance. Regarding consistency between the students, there was more than 80% agreement if one difference in cropland category was considered (e.g., between low and medium cropland) while most of the confusion with the experts was also within one category difference. In addition to the validation of current cropland products, the data set collected by the students also has potential value as a training set for improving future cropland products. MPDI 2017-08-09 2017 /pmc/articles/PMC7340490/ /pubmed/32704489 http://dx.doi.org/10.3390/rs9080815 Text en © 2017 The authors. http://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Laso Bayas, Juan Carlos See, Linda Perger, Christoph Justice, Christina Nakalembe, Catherine Dempewolf, Jan Fritz, Steffen Validation of Automatically Generated Global and Regional Cropland Data Sets: The Case of Tanzania |
title | Validation of Automatically Generated Global and Regional Cropland Data Sets: The Case of Tanzania |
title_full | Validation of Automatically Generated Global and Regional Cropland Data Sets: The Case of Tanzania |
title_fullStr | Validation of Automatically Generated Global and Regional Cropland Data Sets: The Case of Tanzania |
title_full_unstemmed | Validation of Automatically Generated Global and Regional Cropland Data Sets: The Case of Tanzania |
title_short | Validation of Automatically Generated Global and Regional Cropland Data Sets: The Case of Tanzania |
title_sort | validation of automatically generated global and regional cropland data sets: the case of tanzania |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7340490/ https://www.ncbi.nlm.nih.gov/pubmed/32704489 http://dx.doi.org/10.3390/rs9080815 |
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