Abstract
It is necessary to develop a sustainable food production system to ensure future food security around the globe. Cropping intensity and sowing month are two essential parameters for analyzing the food–water–climate tradeoff as food sustainability indicators. This study presents a global-scale analysis of cropping intensity and sowing month from 2000 to 2015, divided into three groups of years. The study methodology integrates the satellite-derived normalized vegetation index (NDVI) of 16-day composite Moderate Resolution Imaging Spectroradiometer (MODIS) and daily land-surface-water coverage (LSWC) data obtained from The Advanced Microwave Scanning Radiometer (AMSR-E/2) in 1-km aggregate pixel resolution. A fast Fourier transform was applied to normalize the MODIS NDVI time-series data. By using advanced methods with intensive optic and microwave time-series data, this study set out to anticipate potential dynamic changes in global cropland activity over 15 years representing the Millennium Development Goal period. These products are the first global datasets that provide information on crop activities in 15-year data derived from optic and microwave satellite data. The results show that in 2000–2005, the total global double-crop intensity was 7.1 million km2, which increased to 8.3 million km2 in 2006–2010, and then to approximately 8.6 million km2 in 2011–2015. In the same periods, global triple-crop agriculture showed a rapid positive growth from 0.73 to 1.12 and then 1.28 million km2, respectively. The results show that Asia dominated double- and triple-crop growth, while showcasing the expansion of single-cropping area in Africa. The finer spatial resolution, combined with a long-term global analysis, means that this methodology has the potential to be applied in several sustainability studies, from global- to local-level perspectives.
Highlights
Researchers worldwide have been focusing on how to find a better approach to increasing food production in a more sustainable manner, as the food balance is predicted to exhibit a negative trend over the decade due to increasing global demand [1,2]
We explored the potential integration of the satellite-derived normalized vegetation index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS) and land-surface-water coverage (LSWC) from The Advanced Microwave Scanning Radiometer (AMSR-E/2) to analyze the crop-phenology information
We developed a 1-km long-term analysis of cropping intensity and sowing month in three groups of years by using integration time-series MODIS NDVI and AMSR-E/2 LSWC datasets
Summary
Researchers worldwide have been focusing on how to find a better approach to increasing food production in a more sustainable manner, as the food balance is predicted to exhibit a negative trend over the decade due to increasing global demand [1,2]. The crop calendar is defined as the times at which farmers are sowing and harvesting crops, and cropping intensity refers to the number of cropping cycles per year [11] These two important parameters allow researchers to consider the volume of food production, water demand, and emissions, and the time required to accommodate dramatic changes in production demand. The latest study that used these parameters was a scenario modeling of global agriculture redistribution by Davis et al [23] These studies show that improving cropping-intensity and calendar products will benefit future research and support strategic policies. There are three existing approaches to estimating these crop-activity parameters: census-based, model simulation, and remote sensing The limitations of these approaches, considered below, point to the need for more research in order for SDGs to be met
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