Abstract
ABSTRACT Urbanization in China has been rapid over the past three decades causing substantial replacement of the natural landscape by built-up land. In this paper, we present a comparison of Sentinel-2A MSI (S2A) and Landsat-8 OLI (L8) data in the retrieval of five built-up indices, namely Urban Index (UI), Normalized Difference Built-up Index (NDBI), Index-based Built-up Index (IBI) and two visible based indices, i.e. VgNIR-BI and VrNIR-BI. All the built-up indices maps water-masked were classified into built-up and non-built-up land using Otsu’s method. Simultaneously, the support vector machine (SVM) algorithm was employed to classify the two imageries into three respective classes. The accuracy assessment results show that all built-up indices had higher Overall Accuracy for S2A (up to 98.14% for VrNIR-BI) and L8 (up to 98.42% for VrNIR-BI) imageries compared to SVM. The percentage differences demonstrate that L8 estimates higher built-up area compared to S2A between 1.48% and 8.45% via the built-up indices and 13.40% compared to the SVM. Cross-checking with the Statistical Yearbook, S2A is superior to L8 in built-up land mapping capability, especially utilizing built-up indices. The difference caused by spatial resolution and spectral response functions should be taken into consideration in synergistic scientific application.
Highlights
The world is urbanizing rapidly, and the urbanization process has replaced a substantial amount of natural landscape by built-up land
The results indicate that the area of built-up lands derived from Landsat-8 have been over-estimated by these indices in the study area, while the opposite is true for Sentinel-2A (Table 2, Figure 7, Figure 8)
Sentinel-2A MSI is the super-spectral instrument of the European Space Agency (ESA) with a spatial resolution ranging from 10 m × 10 m to 60 m × 60 m with 13 spectral bands, which is an additional data continuity applied to monitor the global land surface with Landsat and SPOT missions
Summary
The world is urbanizing rapidly, and the urbanization process has replaced a substantial amount of natural landscape by built-up land The accelerating trend is self-evident in the urbanized density and the spatial sprawl expansion of urbanized areas, triggering the changes from natural landscape to impervious surfaces (Sun, Chen, Jia, Yao, & Wang, 2016). The spatial distribution and temporal dynamics of built-up land play a significant role in ecosystem services and global environment change. As for urbanization, it is essential to derive land-use/cover maps from remote-sensing imageries (Antrop, 2007; Radoux et al, 2016). The increase in impervious surface in urban area has led to the degradation of the environment (Carlson & Arthur, 2000) and the decrement of natural resources (Kaufmann et al, 2007)
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