Comparison of country-level cropland areas between ESA-CCI land cover maps and FAOSTAT data

• Published in: International journal of remote sensing 2018-10, Vol.39 (20), p.6631-6645
• Main Authors: Liu, Xiaoxuan, Yu, Le, Li, Wei, Peng, Dailiang, Zhong, Liheng, Li, Le, Xin, Qinchuan, Lu, Hui, Yu, Chaoqing, Gong, Peng
• Format: Article
• Language: English
• Subjects: Agricultural land; Climate change; Climate models; Climate studies; Continental interfaces, environment; Data; Datasets; Economics; International organizations; Land cover; Modelling; Object recognition; Ocean, Atmosphere; Organizations; Products; Remote sensing; Resolution; Satellites; Sciences of the Universe; Sensing techniques; Spatial resolution; Temporal variations; Time series
• ISSN: 0143-1161; 1366-5901
• DOI: 10.1080/01431161.2018.1465613

Long-term time series of spatially explicit cropland maps are essential for global crop modelling and climate change studies. The spatial resolution and temporal continuity of global cropland maps have been improving and several global data sets are released recently. Here, we calculated country-level cropland areas from the annual land-cover (LC) maps produced by the European Space Agency Climate Change Initiative (ESA-CCI) project and from the Food and Agricultural Organization of the United Nations statistical data (FAOSTAT) from 1992 to 2014. Because these two data sets used different approaches for generating the cropland data, we further quantified the consistency/difference in cropland areas and temporal changes between both products. Using log-transformed the time-averaged country-level cropland areas, a good linear relationship was found between these two products across different countries. However, only 8% of countries (mostly Organization for Economic Co-operation and Development countries) showed cropland area difference smaller than 1% between ESA-CCI and FAOSTAT. The cropland areas (without mosaic cropland types) from ESA-CCI are lower than the areas from FAOSTAT in 26% of countries but higher in 66% of countries. The magnitude of the latter difference (i.e. higher estimates of ESA-CCI than FAOSTAT) would be further amplified if crop intensity was taken into account. In addition, opposite temporal trends of cropland areas were found between these two data sets in 41% of countries. Although there are uncertainties in ESA-CCI LC maps, resulting from remote-sensing techniques such as mixed pixels, spectral similar objects, and same subject with different spectrum, the long time series and relatively high resolution of this product help us to understand the differences between satellite-based and inventory-based data sets and thus identify the possible strategies to improve the accuracy of satellite-based LC products.