File Download
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1038/s41597-021-01065-9
- Scopus: eid_2-s2.0-85118425893
- PMID: 34711845
- WOS: WOS:000712438500002
- Find via
Supplementary
- Citations:
- Appears in Collections:
Article: Annual dynamic dataset of global cropping intensity from 2001 to 2019
Title | Annual dynamic dataset of global cropping intensity from 2001 to 2019 |
---|---|
Authors | |
Issue Date | 2021 |
Publisher | Nature Research: Fully open access journals. The Journal's web site is located at https://www.nature.com/sdata/ |
Citation | Scientific Data, 2021, v. 8, article no. 283 How to Cite? |
Abstract | The cropping intensity has received growing concern in the agriculture field in applications such as harvest area research. Notwithstanding the significant amount of existing literature on local cropping intensities, research considering global datasets appears to be limited in spatial resolution and precision. In this paper, we present an annual dynamic global cropping intensity dataset covering the period from 2001 to 2019 at a 250-m resolution with an average overall accuracy of 89%, exceeding the accuracy of the current annual dynamic global cropping intensity data at a 500-m resolution. We used the enhanced vegetation index (EVI) of MOD13Q1 as the database via a sixth-order polynomial function to calculate the cropping intensity. The global cropping intensity dataset was packaged in the GeoTIFF file type, with the quality control band in the same format. The dataset fills the vacancy of medium-resolution, global-scale annual cropping intensity data and provides an improved map for further global yield estimations and food security analyses. |
Persistent Identifier | http://hdl.handle.net/10722/309004 |
ISSN | 2023 Impact Factor: 5.8 2023 SCImago Journal Rankings: 1.937 |
PubMed Central ID | |
ISI Accession Number ID |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Liu, X | - |
dc.contributor.author | Zheng, J | - |
dc.contributor.author | Yu, L | - |
dc.contributor.author | Hao, P | - |
dc.contributor.author | Chen, B | - |
dc.contributor.author | Xin, Q | - |
dc.contributor.author | Fu, H | - |
dc.contributor.author | Gong, P | - |
dc.date.accessioned | 2021-12-14T01:39:19Z | - |
dc.date.available | 2021-12-14T01:39:19Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | Scientific Data, 2021, v. 8, article no. 283 | - |
dc.identifier.issn | 2052-4463 | - |
dc.identifier.uri | http://hdl.handle.net/10722/309004 | - |
dc.description.abstract | The cropping intensity has received growing concern in the agriculture field in applications such as harvest area research. Notwithstanding the significant amount of existing literature on local cropping intensities, research considering global datasets appears to be limited in spatial resolution and precision. In this paper, we present an annual dynamic global cropping intensity dataset covering the period from 2001 to 2019 at a 250-m resolution with an average overall accuracy of 89%, exceeding the accuracy of the current annual dynamic global cropping intensity data at a 500-m resolution. We used the enhanced vegetation index (EVI) of MOD13Q1 as the database via a sixth-order polynomial function to calculate the cropping intensity. The global cropping intensity dataset was packaged in the GeoTIFF file type, with the quality control band in the same format. The dataset fills the vacancy of medium-resolution, global-scale annual cropping intensity data and provides an improved map for further global yield estimations and food security analyses. | - |
dc.language | eng | - |
dc.publisher | Nature Research: Fully open access journals. The Journal's web site is located at https://www.nature.com/sdata/ | - |
dc.relation.ispartof | Scientific Data | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.title | Annual dynamic dataset of global cropping intensity from 2001 to 2019 | - |
dc.type | Article | - |
dc.identifier.email | Chen, B: binleych@hku.hk | - |
dc.identifier.email | Gong, P: penggong@hku.hk | - |
dc.identifier.authority | Chen, B=rp02812 | - |
dc.identifier.authority | Gong, P=rp02780 | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1038/s41597-021-01065-9 | - |
dc.identifier.pmid | 34711845 | - |
dc.identifier.pmcid | PMC8553865 | - |
dc.identifier.scopus | eid_2-s2.0-85118425893 | - |
dc.identifier.hkuros | 330809 | - |
dc.identifier.volume | 8 | - |
dc.identifier.spage | article no. 283 | - |
dc.identifier.epage | article no. 283 | - |
dc.identifier.isi | WOS:000712438500002 | - |
dc.publisher.place | United Kingdom | - |