Presentation + Paper
2 November 2017 Mapping agroecosystem zone using remote sensing for food security analysis in Bantul district Daerah Istimewa Yogyakarta
Author Affiliations +
Abstract
Food security is one of the most important issue for Indonesia. The huge population number and high population growing rate has made the food security a critical issue. This paper describe the application of remote sensing data to (1) map agroecosystem zones in Bantul District, Special Region of Yogyakarta, Indonesia in 2012 and (2) analyze the food security in the study area based on the resulting agro-ecosystem map. Bantul District is selected as the pilot area because this area is among the highest food crop production area in the Province. ALOS AVNIR-2 image accquired on 15 June 2010 was integrated with Indonesian Surface map (RBI map), soil types map, and slope steepness map. Population statistics data was also used to calculate the food needs. Field survey was conducted to obtain the crop field productivity information on each agro-ecosystem zone and assess the accuracy of the model. This research indicates that (1) Bantul District can be divided into three agroecosystem zones, where each zone has unique topograhic configuration and soil types composition, and (2) Bantul Distict is categorized as food secure area since the rice production in 2012 managed to cover the food needs of the people with the surplus of 33,208.6 tonnes of rice. However, when the analysis was conducted at sub-district level, there are four subdistrict with food insecurity where the food needs surpass the rice production. These sub-district are Kasihan Sub-district (-5,598.4 t), Banguntapan Sub-district (-2,483.4 t), Pajangan Sub-district (-1,039.6 t) and Dlingo Sub-district (-798.7 t).
Conference Presentation
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Sigit Heru Murti "Mapping agroecosystem zone using remote sensing for food security analysis in Bantul district Daerah Istimewa Yogyakarta", Proc. SPIE 10421, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX, 104211D (2 November 2017); https://doi.org/10.1117/12.2278011
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KEYWORDS
Computer security

Remote sensing

Agriculture

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