Projecting Land use change with neural network and GIS in northern Melbourne for 2014–2050. Issue 2 (3rd April 2021)

• Record Type: Journal Article
• Authors: Rahnama, Mohammad Rahim; Wyatt, Ray
• Is Part Of: Australian geographer. Volume 52:Issue 2(2021)
• Page Start: 149
• Page End: 170
• Publication Date: 2021-04-03
• Subjects: Driver variables -- land use -- Markov chain model -- Melbourne -- Multilayer Perceptron -- neural network -- projecting; Geography -- Periodicals; Australia -- Description and travel -- Periodicals; 910
• DOI: 10.1080/00049182.2021.1920088
• Languages: English
• ISSNs: 0004-9182

Abstract

ABSTRACT: Melbourne is one of the most livable cities in the world and it is expected to become a global city of opportunities by 2050. These features along with some of the challenges Melbourne will face with in the future, necessitate land use change simulations. Therefore, land use changes in north Melbourne with an area of 2, 425.42 km 2 during 2014–2019 and its future changes until 2030 and 2050 have been simulated. Landsat 8 Operational Land Imager (OLI) and Multilayer Perceptron (MLP) neural networks were used along with Markov chain model in ArcGIS and TerrSet software. Results showed that while proportions of residential and industrial–commercial land uses increased from 35.90% (870.70 km 2 ) in 2014 to 38.53% (934.50 km 2 ) in 2019, that of forest and agricultural-grassland decreased from 62.86% (1, 524.01 km 2 ) in 2014 to 57.76% (1, 400.99 km 2 ) in 2019. Similarly, the simulation results show that residential and industrial–commercial land use will increase to 42.86% (1, 037.139 km 2 ) and 44.53% (1, 079.99 km 2 ) by 2030 and 2050, respectively. In the same period, forest and grassland-agricultural land uses are respectively expected to decline from 53.53% (1298.53 km 2 ) to 51.76% (1255.49 km 2 ). Spatial changes will occur mostly in the north and northwest of the Melbourne.