Cellular Automata Markov Method, An Approach for Rice Self-Sufficiency Projection

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 the ones 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 the 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 the rice field conversion and its impact on the 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, the rice field area will decrease, and the impact on rice self-sufficiency will be 5.34 for Business as usual (BAU) and 0.47 when considering population growth. The previous research validated the results and indicated the efficiency of this method for rice self-sufficiency projection. Moreover, a management assessment was also conducted and indicated that in order to maintain rice self-sufficiency, innovation in the planting and seed systems as well as in farmers' welfare management, such as incentives and subsidies, local food diversification systems and innovative food technique development to support food diversification, should be considered.

Monitoring Urban Expansion and Loss of Agriculture on the North Coast of West Java Province, Indonesia, Using Google Earth Engine and Intensity Analysis

“…ere have been many published articles on the conversion of agricultural land to nonagricultural use in Indonesia, especially in Java, but generally these cover only one administrative area, usually at the regency level [26][27][28]. Meanwhile, research that covers a larger area is scarce but includes one study that focuses solely on statistical evidence to describe the issue of agricultural land conversion and its consequences for regional spatial planning in West Java's north coast [29].…”

Paddy Rice Mapping Using a Dual-Path Spatio-Temporal Network Based on Annual Time-Series Sentinel-2 Images

“…Among them, China alone accounts for 28%. In recent decades, the demand for rice has dramatically increased with population growth [6] and accelerated urbanization. Unfortunately, human activities like high emissions [7] have raised the threat to food supply [8,9], and in recent years global pandemics and regional warfare greatly increase the risk of food crisis.…”