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Remote Sens. 2017, 9(8), 815;

Validation of Automatically Generated Global and Regional Cropland Data Sets: The Case of Tanzania

Ecosystems Services and Management Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg A-2361, Austria
Department of Geographical Sciences, University of Maryland, College Park, Maryland, MD 20742, USA
Author to whom correspondence should be addressed.
Academic Editors: Jun Chen, Xiaohua Tong, Lijun Chen, Chuanrong (Cindy) Zhang and Prasad S. Thenkabail
Received: 20 April 2017 / Revised: 20 July 2017 / Accepted: 7 August 2017 / Published: 9 August 2017
(This article belongs to the Special Issue Validation on Global Land Cover Datasets)
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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. View Full-Text
Keywords: land cover; validation; cropland; Geo-Wiki; agricultural monitoring land cover; validation; cropland; Geo-Wiki; agricultural monitoring

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Laso Bayas, J.C.; See, L.; Perger, C.; Justice, C.; Nakalembe, C.; Dempewolf, J.; Fritz, S. Validation of Automatically Generated Global and Regional Cropland Data Sets: The Case of Tanzania. Remote Sens. 2017, 9, 815.

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