Monday, April 09, 2018

Predicting Rice Cropping Patterns around Poyang Lake, China using a Cellular Automata Model
Normally, on this blog, the focus is on agent-based modeling and GIS. However, I am not agnostic to other modeling approaches especially cellular automata (CA) modeling (which I have written about in the past).  To this end, Rui Zhang, Qing Tian, Luguang Jiang, Shuhua Qi, Ruixin Yang and myself recently had a paper published in Land Use Policy entitled: "Projecting Cropping Patterns around Poyang Lake and Prioritizing Areas for Policy Intervention to Promote Rice: A Cellular Automata Model" In the paper we explore current land use patterns in the Poyang Lake Region (PLR) of China. Specifically, we focus on current rice production in the region and what this might look like in the future (especially the impact of farmland consolidation) by using an CA model (built on the DINAMICA EGO platform). Below you can read the abstract to our paper, along with some figures, outlining our study area, the model design and development, along with observed current day and predicted rice cropping patterns around Poyang Lake. Finally at the bottom of the post I provide the full reference and a link to the paper.

Rural households’ cropping choices are increasingly influenced by nonfarm activities across the developing world, raising serious concerns about food security locally and globally. In China, rapid urbanization has led to agricultural decline in some regions. To stimulate agriculture, the Chinese government has recently increased its effort in farmland consolidation by providing special support to large farms in an attempt to address land-use inefficiency associated with small farming operations in rural China. Focusing on the Poyang Lake Region (PLR), we develop a Cellular Automata (CA) model to explore future agricultural land use and examine the impact of farmland consolidation. PLR is an important rice production base in Jiangxi Province and China. In PLR rice can be grown once a year on a plot, called one-season rice, or twice a year on the same plot, called two-season rice. Our CA model simulates the transition between one-season and two-season rice. Emphasizing distributional differences in the region, we use the modeling results to identify five areas where rice cultivation is (i) relatively stable for one-season rice, (ii) more likely to be one-season rice, (iii) of equal probability for either type, (iv) more likely to be two-season rice, and (v) relatively stable for two-season rice. We then explore the characteristics of these areas in terms of biophysical and geographical environments to provide further insights into how the government may prioritize areas for interventions to effectively promote food production and environmental sustainability. The analysis also indicates a positive effect of farmland consolidation on promoting rice production.

Keywords: Agricultural Land Use; Cellular Automata; Food Security; Environmental Sustainability; Farmland Consolidation; China.
Poyang Lake Region. The left map shows its location in China. Rice cropping patterns shown on the right map were interpreted from Landsat images in 2013.
Model design and development

Rice cropping patterns around Poyang Lake. The map on the left is observed land use in 2013 and on the right prediction for 2033.

Full Reference:
Zhang, R., Tian, Q., Jiang, L., Crooks, A.T., Qi, S. and Yang, R. (2018), Projecting Cropping Patterns around Poyang Lake and Prioritizing Areas for Policy Intervention to Promote Rice: A Cellular Automata Model, Land Use Policy, 74: 248-260. (pdf)
As always, any thoughts or comments are most welcome.

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