Abstract
Assessing changes in rice cropping systems is essential for ensuring food security, greenhouse gas emissions, and sustainable water management. However, due to the insufficient availability of images with moderate to high spatial resolution, caused by frequent cloud cover and coarse temporal resolution, high-resolution maps of rice cropping systems at a large scale are relatively limited, especially in tropical and subtropical regions. This study combined the difference of Normalized Difference Vegetation Index (dNDVI) method and the Normalized Difference Vegetation Index (NDVI) threshold method to monitor changes in rice cropping systems of Southern China using Landsat images, based on the phenological differences between different rice cropping systems. From 1990–2015, the sown area of double cropping rice (DCR) in Southern China decreased by 61054.5 km2, the sown area of single cropping rice (SCR) increased by 20,110.7 km2, the index of multiple cropping decreased from 148.3% to 129.3%, and the proportion of DCR decreased by 20%. The rice cropping systems in Southern China showed a “double rice shrinking and single rice expanding” change pattern from north to south, and the most dramatic changes occurred in the Middle-Lower Yangtze Plain. This study provided an efficient strategy that can be applied to moderate to high resolution images with deficient data availability, and the resulting maps can be used as data support to adjust agricultural structures, formulate food security strategies, and compile a greenhouse gas emission inventory.
Highlights
Rice feeds more than half of the world’s population, and paddy rice areas account for approximately 12% of global cropland areas [1]
From the perspective of the conversion between double cropping rice (DCR) and single cropping rice (SCR), the most dramatic double rice shrinking and single rice expanding” (DSSE) changes occurred in the Middle-Lower Yangtze Plain, including the Hubei and Hunan Plain, the Poyang Lake
The ARCSM procedure combined the difference of Normalized Difference Vegetation Index (dNDVI) method and Normalized Difference Vegetation Index (NDVI) threshold method to monitor the distribution of rice cropping systems in Southern China, which only needs one or two Landsat images in proper phenology time windows
Summary
Rice feeds more than half of the world’s population, and paddy rice areas account for approximately 12% of global cropland areas [1]. Planting paddy rice consumes a huge amount of water resources, approximately one quarter to one third of the world’s developed freshwater resources are used for rice irrigation [2]. Due to the flooded environment caused by irrigation, paddy rice fields are important sources of methane (CH4 ) emissions, which account for more than 10% of the total CH4 flux in the atmosphere [3,4,5]. The timely and explicit mapping of spatiotemporal changes in rice cropping systems is essential for food security, greenhouse gas emissions, and water resource management [6]. The traditional method of acquiring rice cropping system distribution information relies on statistical data [7]. Statistical data can be disturbed by human factors, and it is difficult to characterize spatial variation within administrative units, which restrict their application [8]
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