Decreasing Rice Cropping Intensity in Southern China from 1990 to 2015

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.

Phenology-Based Rice Paddy Mapping Using Multi-Source Satellite Imagery and a Fusion Algorithm Applied to the Poyang Lake Plain, Southern China

“…Our study found that the multiple cropping indices were approximately 150%. Jiang et al (2018Jiang et al ( , 2019 noted that the planting area of double-cropping rice and multiple cropping indices considerably decreased in southern China, especially in the Poyang Lake plain and Hubei and Hunan plain [6,47]. They employed NLCD data to generate rice paddy masks.…”

Using the Bayesian Network to Map Large-Scale Cropping Intensity by Fusing Multi-Source Data

“…The proposed CII is a new indicator which can be use to map cropping intensity at a finer scale compared with the existing researches [10,[12][13][14]. The modeled CII is a fractional image at the sub-pixel level, which is a kind of interval measurement.…”

“…Most of the existing studies have defined cropping intensity as cropping frequency (single cropping or double cropping, etc.) [4,[7][8][9][10][11][12][13][14][15] or MCI (multiple crop indexes) [16][17][18][19][20][21][22]. Cropping frequency is a hard division of crop pattern that can lead to much information loss.…”

A Data-Intensive Approach to Address Food Sustainability: Integrating Optic and Microwave Satellite Imagery for Developing Long-Term Global Cropping Intensity and Sowing Month from 2001 to 2015

“…Occasional, unpredicted failure to harvest due to disasters may have led to a reduced intensity in some years. Several studies have investigated the increasing and decreasing crop-intensity phenomenon [62,63]. Figure 6 shows the result obtained for the average cropping intensity of the dominant crop in the three year groups.…”

“…The adjustment strategy can reduce errors, which could be identified by boundary analyses between Bangladesh and India, and showed a contrast difference in the boundary of the two countries, as shown in Figure 8. Further, South Asia and Southeast Asia showed high spatial variation and complexity in the sowing months as water resources were available throughout the year [62,66]. In contrast, the northern regions, such as Europe and the US, have similar climate conditions, and hence their period of cultivation is This indicates how increasing food demand in the Asia region has led to the increased development of irrigation system that have increased the number of cultivation periods in one year [64].…”