scholarly journals Comparing Urban Impervious Surface Identification Using Landsat and High Resolution Aerial Photography

2013 ◽  
Vol 5 (10) ◽  
pp. 4942-4960 ◽  
Author(s):  
Tammy Parece ◽  
James Campbell
Keyword(s):  
High Resolution ◽  
Aerial Photography ◽  
Impervious Surface ◽  
Urban Impervious Surface

The Spatiotemporal Evolution of Urban Impervious Surface for Chengdu, China

2021 ◽  
Vol 87 (7) ◽  
pp. 491-502
Author(s):  
Mujie Li ◽  
Zezhong Zheng ◽  
Mingcang Zhu ◽  
Yue He ◽  
Jun Xia ◽  
...  
Keyword(s):  
Neural Networks ◽  
Growth Rate ◽  
Urban Area ◽  
Landsat Imagery ◽  
Impervious Surface ◽  
Kappa Coefficient ◽  
Spatiotemporal Evolution ◽  
Urban Impervious Surface ◽  
The Past ◽  
Secondary Industry

The spatiotemporal evolution of an impervious surface (IS) is significant for urban planning. In this paper, the IS was extracted and its spatiotemporal evolution for the Chengdu urban area was analyzed based on Landsat imagery. Our experimental results indicated that convolutional neural networks achieved the better performance with an overall accuracy of 98.32%, Kappa coefficient of 0.98, and Macro F1 of 98.28%, and the farmland was replaced by IS from 2001 to 2017, and the IS area (ISA) increased by 51.24 km2; that is, the growth rate was up to 13.8% in sixteen years. According to the landscape metrics, the IS expanded and agglomerated into large patches from small fragmented ones. In addition, the gross domestic product change of the secondary industry was similar to the change of ISA between 2001 and 2017. Thus, the spatiotemporal evolution of IS was associated with the economic development of the Chengdu urban area in the past sixteen years.

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