Cultivated Land Resources and Land Use

Spatial and Temporal Variation of Cropland at the Global Level from 1992 to 2015

  • TAN Minghong , 1, 2, * ,
  • LI Yuanyuan 3
  • 1. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
  • 2. International College, University of Chinese Academy of Sciences, Beijing 100049, China
  • 3. State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
*Corresponding author: TAN Minghong, E-mail:

Received date: 2018-10-19

  Accepted date: 2018-12-28

  Online published: 2019-05-30

Supported by

National Natural Science Foundation of China (91325302).


All rights reserved


Correlated increases in population and demand for food over recent decades have caused remarkable changes in cropland area globally. Utilizing the latest data product provided by the European Space Agency (ESA), this paper analyzes annual trends and spatiotemporal variations in cropland area and discusses cropland conversion, losses, and increases globally between 1992 and 2015 at a 300 m resolution. The results show that the global area of cropland increased rapidly between 1992 and 2004, more slowly between 2004 and 2012, and began to decrease gradually since 2012. First, an increasing trend in cropland area has been maintained solely in Africa; all other regions are characterized by decreasing trends in later periods despite different transition points and change rates. A reduction in cropland area frequently emerged earlier in high-income countries. Second, increase rates in cropland area have largely decreased in recent years while the overall rate of loss has remained almost the same. Hotspot areas of global cropland increases are mainly concentrated around the edge of the Amazon forest, Eurasian Steppe, and Sahara Desert. These hotspot areas of global cropland loss shifted from Europe to Asia while built-up areas have expanded at the expense of cropland.

Cite this article

TAN Minghong , LI Yuanyuan . Spatial and Temporal Variation of Cropland at the Global Level from 1992 to 2015[J]. Journal of Resources and Ecology, 2019 , 10(3) : 235 -245 . DOI: 10.5814/j.issn.1674-764X.2019.03.001

1 Introduction

United Nations projections indicate that global population is likely to increase steadily, from 7.38 billion people in 2014 to 11.18 billion people by 2100 (United Nation, 2017). At the same time, food consumption per capita is experiencing rapid growth, largely resulted from increases in income per capita (Delgado, 2003; Davis et al., 2017; FAO, 2017). This correlated increase in population and consumption creates huge food production pressures (Foley et al., 2011; Saxena et al., 2018) and will mean that global food demands are certain to increase for at least another 40 years (Godfray et al., 2010).
Croplands are the basis of food production; however, in recent decades, the global area of cropland has experienced rapid changes. In some areas, croplands expanded to meet the increasing demands for food caused by population growth and rises in living standards (Ramankutty and Foley, 1999; Foley et al., 2005). At the same time, cropland has been converted into other land use types. First, many mountain areas are characterized by cropland abandonment (Li and Li, 2016), since massive numbers of people have moved into urban areas in search of enhanced employment opportunities and higher incomes, which has led to concomitant reductions in the rural labor force. It has been estimated that between 385 million hectares and 472 million hectares of cropland were abandoned globally between 1700 and 2000 (Campbell et al., 2008), especially in Europe and North America (Lasanta et al., 2017; Voicu et al., 2017). Second, as demonstrated by the Environment Kuznets curve (Dinda, 2004; Meyfroidt and Lambin, 2009), people tend to exhibit a continually stronger desire to improve their environment as economic level increases. In light of this, some countries have adopted measures to protect their ecological environment; examples of such measures include the Chinese Grain for Green program, Conservation Reserve Program in the United States, and land fallowing that has been implemented in the European Union (Lasanta et al., 2017). Third, with economic development and urbanization, urban land has increasingly expanded and encroached upon cropland (Tan et al., 2005; Pandey and Seto, 2015; Vliet et al., 2017). Furthermore, urban expansion is expected to take place on fertile cropland that is 1.77 times more productive than the global average (Bren d’Amour et al., 2017).
It is therefore essential to understand spatiotemporal changes in cropland area to guarantee food security; such studies are also critical for predicting cropland changes and evaluating ecosystems and environments (Tolessa et al., 2017). Some studies have focused on cropland changes at the regional scale (Wardlow and Egbert, 2008; Wang and Qiu, 2017). The Food and Agriculture Organization (FAO) collects statistical data from member countries. However, these are not spatially accurate enough and hard to reconcile with standard cropland definitions at the global scale. Remote sensing (RS) data has been increasingly utilized to document changes in global land use (Friedl et al., 2010). Leff et al. (2004) and Ramankutty et al. (2008) used RS data to study global changes in agriculture at a 10 km spatial resolution. Pittman et al. (2010) estimated crop extents globally using high-resolution MODIS data at 250 m spatial resolution. Cao et al. (2016) mapped global cultivated land in 2000 and 2010 at a 30 m spatial resolution. Global cropland maps are becoming finer and finer in scale, however, a temporal series for this land use type remains lacking and global-level dynamics are insufficient. In addition, using multiple data sources can provide both high spatial and temporal resolution, but uncertainties and inconsistencies remain that are hard to calibrate over different year ranges, areas, and land use definitions (Lepers et al., 2005; Yao et al., 2017). Thus, it is necessary to analyze cropland changes at the global scale using spatially and temporally detailed information from a relatively consistent data product.
This paper utilizes the continuous and comparable data available from the European Space Agency (ESA) to address three issues: global changes in cropland area between 1992 and 2015, the key characteristics of these changes, and identifying consistent features underlying these changes. These are important for projecting cropland changes, evaluating ecosystems services and guaranteeing food security.

2 Materials and methods

In 2017, the ESA released its most recent land cover classification (ESA-LCCS) dataset, comprising annual records encompassing the period between 1992 and 2015. These annual land cover datasets include AVHRR data from NOAA collected between 1992 and 1999, SPOT-VGT data from CNES collected between 1999 and 2013, and MERIS and PROBA-V data from the ESA collected between 2003 and 2015. The ESA-LCCS encompasses 22 main land cover types with a spatial resolution of 300 m.
The qualitative assessment results show good agreement between the ESA-LCCS maps and other reference maps with different spatial resolution in various regions of the world. According to the data assessment and validation definitions developed by the Working Group on Calibration and Validation, a subgroup of the Committee on Earth Observation Satellites, the overall accuracy of ESA-LCCS is 75.4% with the error matrix validation, and the accuracy values for cropland are high, about 90%, when compared to GlobCover2009 data (ESA, 2017). Land cover data for the year 2011 with a spatial resolution of 30 m for the United States were obtained from the U.S. National Land Cover Database 2011 (NLCD) (Homer et al., 2015). For China, the land use map for the year 2010 with a spatial resolution of 30 m was obtained from the Resources and Environment Data Center of the Chinese Academy of Science (EDC- CAS). An outdoor survey and random sample check verified that the average interpretation accuracy of the map was greater than 90% (Liu et al., 2014). These data for the two countries were produced by visual interpretation of Landsat Thematic Mapper (TM) images. The FAO provides long- term land use dataset of member countries, by collecting data from national sources, validating and harmonizing them (FAO, 2017). This dataset is regarded as the main authoritative source of information on land use and widely used for various purposes. In this study, the three datasets were used for comparison with the cropland from ESA dataset.
To obtain the area of cropland of countries, land cover maps for each year were firstly created using the Albers equal area projection. This was done using the software of ArcGIS 10.2. Then, a statistic was made for each country with the tool of Zonal Statistics of the ArcGIS software, and conversion of land use types was operated with the Conversion tool of the software.

3 Results and discussions

3.1 Cropland distribution

Data from the ESA-LCCS product reveal that the 2015 global cropland area was 22.27 million km2. Cropland area in Asia includes most of this total, about 41.79%, while the second largest contributor is Africa, encompassing 19.06%. The top five ranked countries are China, India, Brazil, Russia, and the USA, collectively encompassing 42.05% of global cropland in 2015 (Fig. 1).
Fig. 1 The global distribution of cropland (in green) in 2015

3.2 Spatiotemporal changes in cropland area

The average net global cropland increase between 1992 and 2015 was 37,000 km2yr-1, corresponding to an average annual growth rate of 0.17%. A transition point is evident during this period (Fig. 2). In 2004, the pace of cropland area increase began to slow down, and in 2012, the area of cropland started to decline slightly. The average annual cropland area growth rate was 0.32% before 2004, while this rate was about 0.03% between 2004 and 2012. The global area of cropland decreased slightly subsequent to 2012 at a rate of 0.08%, a potential predictor of the decreasing trend a few years later. The process of change was not consistent with the previously published FAO data, which show that the pace of cropland area increase began to speed up after 2010 (FAO, 2017).
Fig. 2 Changes in global cropland area with two datasets between 1992 and 2015
Data at the regional level show that different areas are characterized by different trends in cropland change (Fig. 3). Notably, an increasing trend was only maintained in Africathroughout the whole study period, corroborating previously published FAO data (Cao et al., 2016). The data in this study show that average cropland area growth rates in Africa were different before and after the 2004 transition point; these values were 0.49% and 0.14%, respectively. In contrast, the area of cropland in Europe decreased between 2000 and 2004 at a rate of 0.26%, while areas in both South America and Oceania increased and then reached a consistent level. Within these data, the growth rate in South America (1.03%) was much higher than that of Oceania (0.36%) between 1992 and 2004. Asia and North America also showed a similar trend in cropland area change, an initial dramatic rise, followed by a gradual increase and then a final smooth decrease. This period of ‘gradual increase’ was much longer in Asia than North America; since 2004, the area of cropland in North America has decreased.
Fig. 3 Changes in cropland area on different continents between 1992 and 2015. The highlighted years show the transition points
Fig. 3 also compares changes in cropland area between continents. Between 1992 and 2015, Europe first reached its peak area followed by North and South America, Asia and Africa. This may be indicative of an underlying rule: stepwise reduction in cropland area from developed continents (e.g. Europe) to developing continents (e.g. Africa). The stepwise reduction may be related to the increase in food trade (Dissanayake et al., 2017). Weinzettel et al. (2013) think that rich countries often displace land use to other countries through increasing food import, which may lead to cropland reduction in developed countries.
At the country level, Fig. 4 shows that many European countries first reached their maximum cropland areas before 1998, followed by some large countries, including India, Russia, China, and the USA between 1999 and 2003. The northern part of South America mostly reached their turning points in 2004 or 2005 while those in the southern part were delayed a few years. After 2005, many African countries and Central Asian countries reached their maximum cropland areas. This order implies that the reduction in cropland area is more likely to emerge earlier in high-income countries. Among the 74 countries reaching their maximum cropland areas before 2004, the average per capita GDP in the study period is about \$21,000 while that of the 98 countries after 2004 is only about \$7,000. Low-income countries offer low-price labor force for the global market, attracting high-income countries to displace their cropland abroad (Weinzettel et al., 2013). In these low-income countries, the rapid expansion of cropland is likely to occur in areas where large-scale farming is available, such as the northern parts of Kazakhstan (Swinnen et al., 2017), northeastern China (Xin et al., 2009), and sub-Saharan Africa (Schoneveld, 2014). In these regions, agricultural production heavily depends on blue water, which increases pressure on water resources and the risk for abrupt and irreversible environment change (Alexander et al., 2015; Johanssona et al., 2016).
Fig. 4 The timing that global countries have reached maximum cropland area

3.3 Increases in cropland area

The data assembled in this study show that the average increase in global cropland area (new cropland) between 1992 and 2004 was 99,000 km2yr-1. This increase in area was mainly derived from forests (60.2%), shrub (16.7%), grassland (10.1%), and sparse vegetation (9.8%). In contrast, between 2004 and 2015, the average area increase was only a third of that seen during the previous time period, about 30,000 km2yr-1. During this period, the proportion of forest decreased to 52.3% while the proportion of grass and bare land increased to 17.7% (Fig. 5).
Fig. 5 Transitions in cropland proportions between 1992 and 2004 and between 2004 and 2015
The data clearly show that the largest proportions of cropland reclaimed globally between 1992 and 2004 were distributed on the southeastern edge of the Amazon forest, edge of the Eurasian Steppe, and southern margins of the Sahara Desert (Fig. 6). The area of new cropland reclaimed in Asia comprised 32.3% of the global total and was mostly converted from forest (45.2%), sparse vegetation (26.3%), and grassland (15.2%), mainly including southeastern India, Indonesia, and in other southeast Asian countries. In northwestern China cropland was mainly converted from bare areas, and in northeastern Iran and at the junction between Russia and Kazakhstan it was mainly converted from grass and sparse vegetation.
Fig. 6 Maps to show the distribution of cropland change between 1992 and 2004 and between 2004 and 2015
South America was second in this comparison, accounting for 31.7% of the total cropland increase, while Brazil, the largest country in this region, was also the nation that boasted the largest area of new cropland over the time period. At the same time, both Argentina and Bolivia also reclaimed large areas of cropland. Data show that the majority of reclaimed cropland in South America was converted from forest, as high as 86.6%, while a small amount was converted from shrub, just 12.5%.
Africa was third in this comparison, accounting for 21.9% of the total new cropland area, most of which was distributed in Nigeria, Sudan, and Mali to the south of the Sahara. New cropland in this region was largely converted from grassland and shrub, while in some Southern African countries (e.g., Tanzania, Mozambique, and Malawi) cropland was mostly converted from forests.
Previous studies also reported cropland expansion, which creates massive deforestation, grassland loss (Dissanayake et al., 2017). Chen et al. (2013) believe that cropland was substantially converted from of natural vegetation in Central Asia in the 1990s.
Compared to the first time period evaluated in this study, new cropland was distributed in Africa and Asia between 2004 and 2015 (Fig. 6). The proportions of this land use type in Asia and Africa increased by 11.9% and 8.3%, respectively, while the area in South America decreased sharply by 17.6%. Among the ten countries boasting the largest areas of new cropland, Asia includes the first six, Indonesia, China, Russia, Kazakhstan, Iran, and Malaysia. The rapid cropland expansion observed in Indonesia and Malaysia over the whole period may be related to the production of biofuels, such as oil palm (Tscharntke et al., 2012). However, data show that the loss of cropland was also significant in the two countries, which can be explained by the reduction in permanent crops (excluding oil palm) since 1990s (Wicke et al., 2011). As for cropland conversion in Asia, the proportion of forest as a source of cropland increased by 7.7% while the proportion of sparse vegetation as a source decreased by 11.5%, which indicates that cropland growth along the edge of the Eurasian Steppe slowed between 2004 and 2015. In Africa, new cropland areas were largely distributed in Nigeria, Zaire, Sudan, Algeria, Chad, and Tanzania. The proportion of grass and shrub converted to cropland remained stable during this period, while that of forest fell by 9.4% and the proportion of converted sparse vegetation increased 7.0%. Thus, in combination with the spatial distribution of new cropland, it is clear that the trend in Southern African cropland growth slowed while expansion along the northern edge of the Sahara Desert increased (Fig. 7). The area of new cropland also decreased sharply in comparison with the previous period in South America; data reveal a significant decrease in the proportion of forest converted to cropland, up to 17.8%, while the proportion of converted shrub increased by 15.2%. This implies that the reclamation of cropland at the expense of Amazonian edge forest was alleviated somewhat over this period. Previous studies have shown that tropical forests were the primary sources of new cropland in the 1980s and 1990s, and that these new areas were mainly distributed in South America, Sub-Saharan Africa, and southeast Asia (Gibbs et al., 2010). As this rapid deforestation of tropical area aroused a great degree of global concern, governments adopted a series of policies to protect their forests, including improved monitoring and the creation of a soybean moratorium in the Amazon. These measures may have significantly suppressed cropland expansion and mitigated the large-scale deforestation of tropical areas (Austin et al., 2017).
Fig. 7 Hot spot areas of cropland increases and sources: A1) Southeastern edge of the Amazon forest between 1992 and 2004; A2) southeastern edge of the Amazon forest between 2004 and 2015; B1) edge of the Eurasian Steppe between 1992 and 2004; B2) edge of the Eurasian Steppe between 2004 and 2015; C1) southern edge of the Sahara Desert between 1992 and 2004; and C2) southern edge of the Sahara Desert between 2004 and 2015.

3.4 Losses in cropland area

The data collated in this study show that the average global cropland area loss between 1992 and 2004 was about 30,000 km2yr-1. These areas were mainly converted to forest (49.4%), settlements (34.3%), and grasslands (5.8%). In contrast, between 2004 and 2015, the average area lost remained approximately the same, about 28,000 km2yr-1; over this period, the proportion of forest decreased by 4.6% while the proportion of settlements increased by 7.7%.
Globally, about 42.7% of cropland losses between 1992 and 2004 occurred in Asia, while about 21.0% were in Europe, and 17.8% were in South America. Losses of this land use type in Eastern Europe, and the Mediterranean are also obvious, most notably in Ukraine, Germany, France, Poland, Romania, and Britain, which corroborate the results of earlier work that addressed the period between 1990 and 2006 (Terres et al., 2015; Kuemmerle et al., 2016). In contrast, Asian cropland losses were concentrated in east and southeast Asia and Northern India, while in South America, cropland losses were mainly distributed in southern Brazil. Lost cropland was mostly converted to settlements in Europe and North America, accounting for 70.5% and 52.6%, respectively, while it was mostly converted to forests in other continents. In Asia, cropland loss may be related to forest transition. For instance, in Vietnam, the national-scale reforestation began in 1992 and forest cover has grown steadily from about 24.7% in 1992 to about 38.2% in 2005 (Meyfroidt et al., 2009).
Between 2004 and 2015, global cropland losses were highest in Asia, where the proportion was 53.8%, an increase of 11.1% compared to the earlier time period. This cropland shrinkage phenomenon was most notable within this region on the Huang-Huai-Hai Plain, China, Japan, and in southeast Asian countries, such as the Philippines. In contrast, the trend toward cropland losses slowed down in Europe, where the proportion was only 7.5%. Over this time period, the proportion of lost cropland converted to settlement decreased dramatically by 19.2%, in Europe with a corresponding increase in the proportion of forests (16.2%). Interestingly, the opposite situation occurred in Asia; in this region, the proportion of cropland converted to settlements increased substantially (24.5%) while that converted to forests decreased (19.3%). Similarly, a projection thinks that about 60% of global cropland loss caused by settlement expansion will take place in Asia by 2030 (Bren d’Amour et al., 2017).
Facing the challenges of cropland loss and increasing population, some researchers have recently focused on the issue of re-cultivating abandoned cropland in the countries of the former Soviet Union, notably Russia, Ukraine, and Kazakhstan (Meyfroidt et al., 2016). Indeed, one recent calculation (Schierhorn et al., 2014) suggests that the wheat production in European Russia could be increased by 6.0 million tons if the 4.4 million hectares of cropland abandoned within the former Soviet Union since 2000 was re-cultivated. It is also possible that this region will become a hot spot area for cropland increases rather than losses in the future.

3.5 Comparison of cropland and its changes between ESA-LCCS and other datasets

There are various cropland datasets available at the country, regional, or continent levels. Here, this paper compared cropland and its changes based on different datasets. The FAO provides long-term land use data at the country, continent, and global levels. At the global level, cropland area in this study was higher than that extracted from FAO dataset for several reasons. First, in most cases, cropland area extracted from remote sensing data is often higher than that from statistical data because the former may cover small parcels of other land use types in cropland, such as small ponds, forests, and paths in farmland. Second, some countries do not update timely cropland data, which also affects the accuracy of cropland area based on the FAO dataset (FAO, 2017). For instance, during the period 2010- 2014, the area of cropland and permanent crops remained constant at 1.22×105 km2 in China. However, the change trends of cropland are similar at the global level. And, during the study period 1992-2015, global cropland areas extracted from the two datasets both showed an increasing trend at rates of about 4%.
In addition, this paper compared cropland in China and the United States at the county level, extracted from ESA-LCCS data and land use data with a spatial resolution of 30 m interpreted from Landsat Imagery (Fig. 8). The results showed that cropland from ESA-LCCS was highly consistent with cropland extracted from Landsat Imagery. In China and the United States, the R2 values were about 0.78 and 0.94, respectively. The lower value in China may be caused by the more complicated landforms; China has a large proportion of croplands in mountain areas, which increases the difficulty for mapping croplands since cropland parcels are small. The results also show that the cropland areas from the ESA-LCCS dataset for the two countries were both higher than those from land use datasets with higher resolutions. Similarly, Cao et al. (2016) mapped global cropland in 2000 and 2010 based on Landsat and MODIS data, which was slightly lower than that based on the ESA-LCCS dataset.
Fig. 8 Comparisons of cropland area at the county level between ESA-LCCS data and land use data at a spatial resolution of 30 m interpreted from Landsat Imagery: A) comparison for China using a 30 m spatial resolution land use data from the EDC-CAS and B) comparison for the United States using a 30 m spatial resolution land use data from the NLCD.
Finally, the ESA-LCCS dataset has some limitations. First, the quality of the map varies according to the region of interest. Areas including the western part of the Amazonbasin, Chili, southern Argentina, western Congo basin, Gulf of Guinea, eastern Russia, eastern coast of China, and Indonesia are affected by lower MERIS FR coverage. Second, data between 1992 and 1999 were less reliable due to relatively lower quality AVHRR data.

4 Conclusions

Data from the ESA-LCCS were used in this study to analyze spatiotemporal changes in global cropland area and transitions to other land use types between 1992 and 2015. Five main conclusions were developed.
(1) Global cropland area increased rapidly between 1992 and 2004. However, growth slowed between 2004 and 2012 before starting to gradually decrease globally.
(2) A continual increasing trend in cropland area over the last 24 years occurred solely in Africa; all other continents are characterized by an increase in cropland area followed by a slight decline. Europe was the first continent where a reduction in cropland area occurred. Subsequently, reductions occurred in North and South America, and Asia. At the country level, many European countries first reached their maximum cropland areas, followed by some large countries. After 2005, many African countries and Central Asian countries reached their maximum cropland areas. This order implies that the reduction in cropland area is more likely to emerge earlier in high-income countries.
(3) New cropland areas between 1992 and 2004 are mainly distributed on the southeastern edge of the Amazon forest in South America, edge of Eurasian Steppe in Central Asia, and southern edge of the Sahara Desert in Africa. During the subsequent period between 2004 and 2015, the global conversion rate of new cropland annually was only about one third that of the earlier period. An overall decrease in the proportion of forest converted to cropland was observed over this time period, concomitant with an increase in grassland. Land source analysis shows that this cropland expansion was successfully alleviated on the edges of the Amazonian forest and Eurasian Steppe compared to other areas. Concurrently, cropland expansion on the southern edge of the Sahara Desert has remained basically stable but has been aggravated along the northern margin.
(4) Global losses in cropland have been primarily concentrated in most areas of Europe and east Asia, converted to forests, built-up areas, and grasslands between 1992 and 2004. The occupation of built-up areas has been most marked in Europe and North America, while over the later of the two time periods considered in this work, global average cropland losses per year remained almost unchanged. The proportion of losses in Europe dropped while those in Asia increased. Excluding Europe, the proportion of cropland converted to built-up areas increased globally, especially in Asia.
(5) ESA provides a relatively consistent data product of land cover. It can be used not only to depict global changes in cropland area, but also to analyze conversions between cropland and other land cover types. Due to the conversions, cropland was experiencing a spatial shift during the study period, which may come at ever increasing environmental costs in the regions with an cropland increase.
Finally, the ESA-LCCS dataset has some limitations. First, the quality of the map varies according to the region of interest. Second, data between 1992 and 1999 were less reliable due to relatively lower quality of AVHRR data.

The authors have declared that no competing interests exist.

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