A national-scale land cover reference dataset from local crowdsourcing initiatives in Indonesia

Hadi, H., Yowargana, P., Zulkarnain, M.T., Mohamad, F., Goib, B.K., Hultera, P., Sturn, T., Karner, M., et al. (2022). A national-scale land cover reference dataset from local crowdsourcing initiatives in Indonesia. Scientific Data 9 (1) 10.1038/s41597-022-01689-5.

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Abstract

Here we present a geographically diverse, temporally consistent, and nationally relevant land cover (LC) reference dataset collected by visual interpretation of very high spatial resolution imagery, in a national-scale crowdsourcing campaign (targeting seven generic LC classes) and a series of expert workshops (targeting seventeen detailed LC classes) in Indonesia. The interpreters were citizen scientists (crowd/non-experts) and local LC visual interpretation experts from different regions in the country. We provide the raw LC reference dataset, as well as a quality-filtered dataset, along with the quality assessment indicators. We envisage that the dataset will be relevant for: (1) the LC mapping community (researchers and practitioners), i.e., as reference data for training machine learning algorithms and map accuracy assessment (with appropriate quality-filters applied), and (2) the citizen science community, i.e., as a sizable empirical dataset to investigate the potential and limitations of contributions from the crowd/non-experts, demonstrated for LC mapping in Indonesia for the first time to our knowledge, within the context of complementing traditional data collection by expert interpreters.

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