MEMBANGUN MODEL SAWAH LESTARI DAN MODEL PREDIKSI PERUBAHANNYA MENGGUNAKAN CELLULAR AUTOMATA DI KABUPATEN KLATEN PROVINSI JAWA TENGAH

• Main Authors: , Arief Ika Uktoro, , Dr. Suharyadi, M. Sc.
• Format: Theses and Dissertations NonPeerReviewed
• Published: [Yogyakarta] : Universitas Gadjah Mada 2013
• Subjects: ETD
• Online Access: https://repository.ugm.ac.id/119901/; http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=59907
• Institution: Universitas Gadjah Mada

Sustainable rice paddy fields are defined by rules and regulations. Sustainable rice paddy fields protection is an integral part in the arrangement of space. The trend of reduction sustainable paddy reduction could threat food security isn�t addressed immediately. One solutions to addrass this problem is to map the sustainable rice area and its change prediction. The objectives of this research : 1) Build a model of sustainable rice based on QuickBird imagery and ALOS AVNIR-2, 2) Examines the sustainable wetland change 2006 to 2009, and 3) to predict sustainable wetland changes in 2015. The model is developed by overlay three parameters: paddy land suitability map, productivity and irrigation, with paddy field existing map. The study of Sustainable rice paddy fields change by overlay sustainable rice map in 2006 and 2009, which be analyzed the constriction or additions. Predicted changes in paddy fields sustainable use cellular automata markov chain. This research use two modified cellular automata�s scenario. The first scenario work using the density of built up area, accessibility and land value zone. The second scenario used spatial plans map. The results showed that accuration model of built sustainable rice area is 98.5%. Its compared to existing data on the Department of Agriculture and Bappeda district of Klaten. The second results showed that the reduction of sustainable paddy fileds during the period 2006 to 2009 are 24 hectares per year. The last result show that the prediction accuracy on the scenario I is 45.68% and is 41.37% in scenario II.