Cellular Automata Markov Method, An Approach for Rice Self-Sufficiency Projection
Dewayany Sutrisno 1  
,  
Wiwin Ambarwulan 1  
,  
Irmadi Nahib 1
,  
Turmudi Turmudi 1  
,  
Jaka Suryanta 1  
,  
Rizka Windiastuti 1  
,  
 
 
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Centre for Research, Promotion and Cooperation, Geospatial Information Agency, Jl Raya Jakarta Bogor Km 46, Cibinong Bogor City, Indonesia
CORRESPONDING AUTHOR
Dewayany Sutrisno   

Centre for Research, Promotion and Cooperation, Geospatial Information Agency, Jl Raya Jakarta Bogor Km 46, Cibinong Bogor City, 16911, Indonesia
Publish date: 2019-06-01
 
J. Ecol. Eng. 2019; 20(6):117–125
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ABSTRACT
This article discusses the ability of the Cellular Automata (CA) Markov method to project rice sufficiency by considering the conversion of massive rice fields, such as in Indonesia. The conversion of rice fields into land use for non-farming due to the rapidly growing population, industry and economic needs is increasingly affecting rice self-sufficiency. With the development of remote sensing techniques, such as CA Markov, which has been used for years in spatial change projection, there is a need to assess rice field conversion and its impact on rice field self-sufficiency. The process is not solely based on CA Markov but also includes an object-based classification method utilising multi-temporal spot image data to derive land use maps, CA Markov for rice field conversion projection and rice self-sufficiency assessment, which was developed by assessing the availability of rice, consumption and production. Using the Indramayu district as the study area, the results indicate that within the next 20 years there will be decreasing rice field area, and the impact of this on rice self-sufficiency will be 5.34 for Business as usual (BAU) and 0.47 when considering population growth. Previous research validated the results and indicated efficacy this method for rice self-sufficiency projection. Moreover, a management assessment was also conducted and indicated that to maintain rice self-sufficiency, innovation in the planting and seed systems as well as in farmers’ welfare management, such as incentives and subsidised, local food diversification systems and innovative food technique development to support food diversification, should be considered.