Projecting Land use change with neural network and GIS in northern Melbourne for 2014–2050
Bibliographic Data
| ID | 8382154 |
|---|---|
| Authors | Mohammad Rahim Rahnama (0000-0002-4851-6327, Ferdowsi University of Mashhad, corresponding author), Ray Wyatt (Deakin University) |
| Year | 2021 |
| Volume | 52 |
| Issue | 2 |
| Pages | 149-170 |
| Publication date | 2021-04-03 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Australian Geographer (JOURNAL) |
| Journal identifiers | ISSN: 0004-9182 • E-ISSN: 1465-3311 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/00049182.2021.1920088 |
| OpenAlex | W3161918072 |
| Language | EN |
| Citations received | 1 |
| References cited | 32 |
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 km2 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 km2) in 2014 to 38.53% (934.50 km2) in 2019, that of forest and agricultural-grassland decreased from 62.86% (1,524.01 km2) in 2014 to 57.76% (1,400.99 km2) in 2019. Similarly, the simulation results show that residential and industrial–commercial land use will increase to 42.86% (1,037.139 km2) and 44.53% (1,079.99 km2) 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 km2) to 51.76% (1255.49 km2). Spatial changes will occur mostly in the north and northwest of the Melbourne
Archaeology · Artificial neural network · Cartography · Civil engineering · Environmental planning · Environmental resource management · Geographer · Geographic information system · Geography · Land use · Physical geography · Regional science · Remote sensing · Artificial Intelligence · Computer Science · Engineering · Environmental Science · Geographic Information Systems Studies · Land Use and Ecosystem Services · Remote Sensing and Land Use
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| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |