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Open AccessArticle

Coincidence Analysis of the Cropland Distribution of Multi-Sets of Global Land Cover Products

1
Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
2
Key Laboratory of Environment Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing 100875, China
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(3), 707; https://doi.org/10.3390/ijerph17030707
Received: 19 December 2019 / Revised: 14 January 2020 / Accepted: 21 January 2020 / Published: 22 January 2020
(This article belongs to the Section Ecology and the Environment)
Modern global cropland products have been widely used to assess the impact of land use and cover change (LUCC) on carbon budgets, climate change, terrestrial ecosystems, etc. However, each product has its own uncertainty, and inconsistencies exist among different products. Understanding the reliability of these datasets is essential for knowing the uncertainties that exist in the study of global change impact forced by cropland reclamation. In this paper, we propose a set of coincidence assessments to identify where reliable cropland distribution is by overlaying ten widely used global land cover/cropland datasets around 2000 AD. A quantitative assessment for different spatial units is also performed. We further discuss the spatial distribution characteristics of different coincidence degrees and explain the reasons. The results show that the high-coincidence proportion is only 40.5% around the world, and the moderate-coincidence and low-coincidence proportion is 18.4% and 41.1%, respectively. The coincidence degrees among different continents and countries have large discrepancies. The coincidence is relatively higher in Europe, South Asia and North America, while it is very poor in Latin America and Africa. The spatial distribution of high and moderate coincidence roughly corresponds to the regions with suitable agricultural conditions and intensive reclamation. In addition to the random factors such as the product’s quality and the year it represented, the low coincidence is mainly caused by the inconsistent land cover classification systems and the recognition capability of cropland pixels with low fractions in different products. View Full-Text
Keywords: global; cropland cover; coincidence; uncertainty; multi-products; overlay global; cropland cover; coincidence; uncertainty; multi-products; overlay
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MDPI and ACS Style

Zhang, C.; Ye, Y.; Fang, X.; Li, H.; Zheng, X. Coincidence Analysis of the Cropland Distribution of Multi-Sets of Global Land Cover Products. Int. J. Environ. Res. Public Health 2020, 17, 707.

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