ANALISIS DAN PREDIKSI PERUBAHAN TUTUPAN LAHAN MENGGUNAKAN MODEL CELULAR AUTOMATA-MARKOV CHAIN DI DAS WAE RUHU KOTA AMBON

The geographical location of the Wae Ruhu watershed is in Sirimau District, which is the sub-district with the largest population in Ambon City and is also the center of economic, educational, and industrial activities; this creates economic and population growth that has the potential to trigger l...

Full description

Bibliographic Details
Main Authors: Heinrich Rakuasa, Melianus Salakory, Philia Christi Latue
Format: Article
Language:English
Published: Universitas Brawijaya 2022-06-01
Series:JTSL (Jurnal Tanah dan Sumberdaya Lahan)
Subjects:
Online Access:https://jtsl.ub.ac.id/index.php/jtsl/article/view/781
Description
Summary:The geographical location of the Wae Ruhu watershed is in Sirimau District, which is the sub-district with the largest population in Ambon City and is also the center of economic, educational, and industrial activities; this creates economic and population growth that has the potential to trigger land conversion around this area. This study aimed to analyze land cover changes in Ambon City in 2012, 2017, 2022 and predict land cover in 2031. This study used Cellular Automata Markov Chains modeling to predict land cover changes in 2031. The results showed that the types of land cover are built and land cover. The open area continues to increase in area, while agricultural and non-agricultural areas continue to experience a decrease in area, and water bodies do not experience a decrease or increase in area. The results of land cover predictions in 2031 showed that the built-up area is 345.79 ha, open land is 121.18 ha, agricultural land is 657.35 ha, non-agricultural land is 507.65 ha, and water bodies are 11.46 ha. The results of this study are expected to be used as a reference in making policies related to spatial planning and utilization, especially the Wae Ruhu watershed and can optimize sustainable watershed management as the first step in efforts to mitigate natural disasters.
ISSN:2549-9793