Understanding the spatiotemporal change trend of global crop growth and multiple cropping system under climate change scenarios is a critical requirement for supporting the food security issue that maintains the function of human society. Many studies have predicted the effects of climate changes on crop production using a combination of field studies and models, but there has been limited evidence relating decadal-scale climate change to global crop growth and the spatiotemporal distribution of multiple cropping system.
Using long-term satellite-derived Normalized Difference Vegetation Index (NDVI) and observed climate data from 1982 to 2012, we investigated the crop growth trend, spatiotemporal pattern trend of agricultural cropping intensity, and their potential correlations with respect to the climate change drivers at a global scale. Results show that 82.97% of global cropland maximum NDVI witnesses an increased trend while 17.03% of that shows a decreased trend over the past three decades. The spatial distribution of multiple cropping system is observed to expand from lower latitude to higher latitude, and the increased cropping intensity is also witnessed globally.
In terms of regional major crop zones, results show that all nine selected zones have an obvious upward trend of crop maximum NDVI (p < 0.001), and as for climatic drivers, the gradual temperature and precipitation changes have had a measurable impact on the crop growth trend.
Propelled by a 2.3-billion global population growth and higher per capita incomes anticipated through the mid-21st century, global demand for agricultural crops is increasing and may continue to witness an upward trend for decades. Food provision serves a prerequisite for the function of human society, and cropland where food and feed are grown is the central, limiting resource for food production.
Global crop monitoring is a long-term, large-scale complicated scientific project. Fortunately, satellite remote sensing has greatly facilitated the mapping and monitoring of croplands by providing spatially explicit and temporally continuous observations. Over the past decades, a number of studies have utilized remotely sensed data to extract cropland extents, quantify crop types, estimate crop yields, and monitor crop growth trend.
Being one of the top threats for the Earth in the 21st century, the magnitude, rate, and pattern of climate change also greatly impacts on agricultural productivity. Crop growth is affected by biophysically by meteorological variables, including rising temperatures, changing precipitation regimes, and increased atmospheric carbon dioxide levels.
To address the aforementioned issues, here we employed long-term Global Inventory Modelling and Mapping Studies (GIMMS) dataset from 1982 to 2012 to provide a global crop monitoring with the following three major objectives in this article: (i) examine global crop growth trend over the past three decades; (ii) investigate spatiotemporal pattern change of multiple cropping system; and (iii) attribute the major drivers of crop growth trend within climate change scenarios.
The Normalized Difference Vegetation Index (NDVI), defined as the ratio of the difference between near-infrared and red visible reflectance to their sum, is a remotely sensed vegetation index widely used to measure vegetation greenness. Here we used the GIMMS third generation biweekly NDVI dataset derived from AVHRR sensors (NDVI3g) with a spatial resolution of 8 km from 1982 to 2012.
The CRU TS 3.0 climate dataset including monthly temperature and precipitation dataset that spanning from 1982 to 2012 was obtained from the Climate Research Unit (CRU) at the University of East Anglia. This gridded dataset with a spatial resolution 0.5° x 0.5°, was based on climate observations from more than 4000 meteorological stations.
The Palmer Drought Severity Index (PDSI), one of the most commonly used drought indices, was adopted to indicate spatiotemporal variations of drought. The monthly PDSI dataset produced by Dai et al. (Dai et al. 2004) with a spatial resolution of 2.5° x 2.5° was used in this study, which also covers the entire study period (1982-2012).
Nine major crop zones were defined for regional analysis based on the global digital crop maps developed by the Food and Agriculture Organization (FAO) of the United Nations.
