Analysis of the Quality of the Mamasa Sub-Watershed Using the Land Cover Approach and Land Cover Projections in 2031 Andang Suryana Soma (a), Andi Alif Chaeruddin (b), and Wahyuni (a)
(a) Lecturer, Watershed Management Laboratory, Faculty of Forestry, Hasanuddin University, Makassar
(b) Student, Watershed Management Laboratory, Faculty of Forestry, University
Hasanuddin, Makassar
Abstract
Land cover can be interpreted as the biophysical cover on the earth^s surface that can be observed and is the result of regulation, activity and human treatment. In general, changes in land cover can be observed using spatial data from land cover maps from several points in different years. Changes in land cover in a watershed will directly affect the quality of the watershed. This study aims to analyze land cover changes in 2011 - 2016 and 2016 - 2021, analyze land cover change projections in 2031 and analyze watershed quality using the Percentage of Vegetation Cover approach. Land cover change analysis was carried out using the overlay analysis method, land cover change projections were carried out using the Multi Layer Perceptron method and Cellular Automata (CA) markov chain modelling in Idrisi TerrSet Software and watershed quality analysis by calculating the PPV entering the plants permanently. The results of this study note that changes in land cover in 2011 - 2016 experienced a change of 763,53 ha and in 2016 - 2021 the biggest changes was 802,69 ha. The biggest change in land cover occurred in the closure of dry land agriculture. The results of the projected land cover in 2031 as a whole have changed by 4.472,44 ha with the biggest change occurning in dry land agriculture. The results of calculating the percentage value of vegetation cover, the quality of the Mamasa sub-watershed has decreased in quality from very good to good due to a decrease in the area of permanent vegetation.
Keywords: Land Cover Change, Projection, Multi Layer Perceptron, CA Markov Chain, Watershed Quality
Topic: Topik C: Ecological risk and natural disaster
