Abstract
The study monitored land use change in Nansha during 2000-2018, evaluate Nansha’s urban planning by the overlay analysis of land use general planning, land use distribution, and economic data, and predicted the urban expansion in 2025 and 2035 to provide scientific information for urban planning in the future. The results showed that the built-up area rapidly expanded (78.32 km2 to 153.75 km2 in 2000-2018), and the GDP and the newly-added enterprises remarkably increased as well. Most of built-up area matched the land use planning. The urban expansion was simulated to 168.27 km2 in 2025 and to 207.04 km2 in 2035 for future land use planning.
Highlights
Remote sensing (RS) is a fast, convenient, and economical way to monitor land use in long-time series
The results showed that the built-up area rapidly expanded (78.32 km2 to 153.75 km2 in 2000-2018), and the Gross Domestic Product (GDP) and the newly-added enterprises remarkably increased as well
The study selected Nansha as the study area to explore how the land use changed during the development, and how the land use can be applied to urban planning evaluation and formulation
Summary
Remote sensing (RS) is a fast, convenient, and economical way to monitor land use in long-time series. Supervised classification, such as minimum distance classification and maximum likelihood classification, and unsupervised classification, such as IsoData and K-Means, are two main approaches to extract vegetation, water, built-up area, bare land from RS data. FLUS model can examine the complex relationship between various land use types and economic, social and environmental factors. It is suitable for simulating complex and longterm land use changes and has the advantages of convenient operation and higher accuracy compared to other models [3] [4] [5]
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