Global cropland intensification surpassed expansion between 2000 and 2010: A spatio-temporal analysis based on GlobeLand30
Graphical abstract
A spatial map of nine patterns that characterize different combinations of cropland change and intensification
Introduction
Croplands dominate 38% of the earth's terrestrial surface, and almost 30% of global net primary production is appropriated for human use (Zabel et al., 2019; Foley et al., 2011). Ending hunger is considered a key target in the UN Sustainable Development Goals (Fujimori et al., 2019). Although the total global crop production has doubled over the past half-century, the demand for food production is markedly increasing due to the world's population growth, dietary changes, biofuel consumption and environmental damages, creating substantial pressure for agricultural land systems in the next decades (Cole et al., 2018; Schierhorn et al., 2014).
Crop production can be increased through two strategies, i.e., cropland expansion and intensification. Cropland expansion is a more primitive and straightforward way to improve crop production, by bringing in new land (e.g., forest and grassland) for farming (Wu et al., 2014). However, due to excessive land reclamation for natural ecosystems, this strategy could adversely impact habitats, biodiversity and climate (Pei et al., 2015; Foley et al., 2011). Cropland intensification is often defined as a process of increasing the utilization or productivity of existing cropland to maximize agricultural productivity. It is usually achieved by diverse agricultural management practices, including the use of multiple cropping and intercropping systems; the use of improved cultivars; the increased use of irrigation; and the application of fertilizers, pesticides and mechanization (Pei et al., 2015; Wu et al., 2014; Xiang et al., 2019). Although cropland intensification has dramatically increased in recent decades, it also incurs negative environmental consequences, such as greenhouse gas emissions and water and soil pollution (Tilman et al., 2011; Petersen and Snapp, 2015). The question of which strategy is better for crop production as well as environmental protection has been debated for many years (Byerlee et al., 2014). Since individual countries differ greatly in food demand, developmental targets and environmental conditions, the preference for using either intensification or expansion to raise crop production largely varies across space and time. Understanding the reason for such preference difference among different regions and evaluating the consequences of different strategies for boosting crop production require accurate information about global extents of cropland expansion and intensification (See et al., 2015; Dias et al., 2016; Kuhling et al., 2016).
The spatial extent of global cropland is available from global land cover products such as GLC-2000, MODIS-C6 and GlobCover, with spatial resolutions ranging from 300 m to 1 km (Fritz et al., 2015; Lu et al., 2017). Despite the extensive use of these cropland data products, their coarse spatial resolution restricts the mapping accuracy of cropland, especially in regions with a heterogeneous agricultural landscape (Chen et al., 2015; Gong et al., 2013). Moreover, most existing global datasets represent only snapshots in time and cannot be used to depict the cropland dynamics (Cao et al., 2014). Therefore, global cropland products with improved spatial resolution and temporal information are desirable for a more precise estimation and analysis of global cropland expansion. For cropland intensification, substantial progress in mapping indicators, including yield gaps, fertilizer use, field size (Fritz et al., 2015), net primary production (Niedertscheider et al., 2016), and the extent of irrigated agriculture (Estel et al., 2016), has been made in recent decades. However, these individual indicators can describe cropland intensification only from one specific standpoint rather than a comprehensive perspective. Furthermore, existing studies on cropland intensification focused mostly on plot or regional scales, while few studies have characterized the spatial pattern of cropland intensification at the global scale. Although it is widely acknowledged that cropland expansion and intensification often coincide, recent studies have evaluated only one aspect, and their integrated analysis at the global scale has been explored to a lesser degree (Zabel et al., 2019).
In view of this knowledge gap, this study aims to characterize and analyze the spatio-temporal patterns of cropland expansion and intensification at the global scale using spatially explicit maps of land cover. The recent release of GlobeLand30—the first global land cover datasets at a 30 m resolution—provides an alternative to achieve this goal. Based on GlobeLand30 data for 2000 and 2010, the spatial distribution, expansion and loss of cropland area were firstly characterized and calculated for different spatial units. Cropland intensification here was defined as improved yield as a result of intensive agricultural activities and was quantified for each country according to estimated cropland area and crop production from FAO statistics. We finally mapped the coupled patterns of different combinations of cropland expansion and intensification worldwide and calculated the correlations between these two strategies and crop production to determine their contributions to improving global crop production between 2000 and 2010. The specific objectives of this study were to address the following questions:
- 1)
What were the spatial patterns of global cropland change and intensification?
- 2)
What were the spatial distributions of different coupled patterns of these two strategies (i.e., cropland expansion and intensification)?
- 3)
Which strategy was the dominant force in increasing global crop production between 2000 and 2010, considering the conflict between crop production and environmental protection?
Section snippets
Data collection
Cropland areas were acquired from the GlobeLand30 dataset (http://www.globallandcover.com), which is the world's first global land cover product with a spatial resolution of 30 m (Chen et al., 2014), for the years 2000 and 2010. The GlobeLand30 product was generated from Landsat TM/ETM+ and the Chinese BJ-1 and HJ-1 sensors based on the integration of pixel- and object-based methods with knowledge (POK-based) (Chen et al., 2015). This product consists of ten land cover types, among which
Estimation of cropland change
Based on the GlobeLand30 data, we aggregated the pixel-level cropland area to the country level (Ac) for the years 2000 and 2010 and then calculated the net change area (CQc) and change magnitude (CMc) for each country over the ten years. The formulas are as follows:where Ac2000 and Ac2010 represent the cropland area of a country for the years 2000 and 2010, respectively.
We also calculated the standard deviation of the cropland change area of a
Spatial distribution of global cropland
In 2010, the total cropland area of the world was 19.30 million km2, accounting for 14.31% of the world's land surface. Asia ranked first in cropland area, followed by America, contributing 36.02% and 27.26% to the world's total cropland area, respectively. In contrast, the cropland area of Oceania was the smallest. The world's top 10 countries with the largest cropland area were China, the United States, India, Russia, Brazil, Argentina, Australia, Canada, Kazakhstan and Ukraine, from high to
Discussion
In this study, we first presented the global cropland spatial distribution and its change between 2000 and 2010 based on a global land cover product with a 30-m spatial resolution. Our results not only revealed the difference in net cropland area across different spatial scales, i.e., continent, country and 1° × 1° grid, but also provided a global view of cropland area per capita. We found that some countries with large populations (e.g., China and India) do not have comparable cropland
Conclusion
In this study, we investigated the spatio-temporal patterns of global cropland expansion and intensification between 2000 and 2010 using the first 30 m global land cover dataset. In addition to analyzing the global extents of cropland change and intensification, we identified nine patterns that represented different combinations of these two strategies and also determined their contributions to improving global food production. During 2000 and 2010, global cropland increased slightly (by
CRediT authorship contribution statement
Qiong Hu: Methodology, Software, Visualization, Writing - original draft. Mingtao Xiang: Conceptualization, Methodology, Writing - review & editing. Di Chen: Validation, Methodology, Writing - review & editing. Jie Zhou: Validation, Methodology, Writing - review & editing. Wenbin Wu: Methodology, Writing - review & editing. Qian Song: Conceptualization, Methodology, Writing - review & editing.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgement
This study was financially supported by the National Natural Science Foundation of China (41901380 and 41801371), by the National Key Research and Development Program of China (2019YFA0607400) and by the Fundamental Research Funds for the Central Universities (CCNU19TD002 and CCNU20QN032).
References (44)
- et al.
Does intensification slow crop land expansion or encourage deforestation?
Global Food Security
(2014) - et al.
Global land cover mapping at 30m resolution: a POK-based operational approach
ISPRS J. Photogramm. Remote Sens.
(2015) - et al.
Urban expansion brought stress to food security in China: evidence from decreased cropland net primary productivity
Sci. Total Environ.
(2017) - et al.
Spatio-temporal analysis of agricultural land-use intensity across the Western Siberian grain belt
Sci. Total Environ.
(2016) - et al.
Chinese cropland losses due to urban expansion in the past four decades
Sci. Total Environ.
(2019) - et al.
Mapping multi-year cropping patterns in small irrigation districts from time-series analysis of Landsat TM images
Eur. J. Agron.
(2005) - et al.
What is sustainable intensification? Views from experts
Land Use Policy
(2015) - et al.
The potential of Russia to increase its wheat production through cropland expansion and intensification
Global Food Security
(2014) - et al.
Improved global cropland data as an essential ingredient for food security
Global Food Security
(2015) - et al.
Sustainable intensification in land systems: trade-offs, scales, and contexts
Curr. Opin. Environ. Sustain.
(2019)