基于GEE平台的广州市主城区不透水面时间序列提取

doi:10.12082/dqxxkx.2020.190047

Abstract

Abstract:

For assessing urbanization level and urban environment, the mapping of impervious surface has become a research hotspot. Compared with single-phase imagery, time series mapping can depict temporal trends, which is of great significance for monitoring urban expansion. Based on the Google Earth Engine platform, this paper calculated BCI and NDVI using Landsat TOA data from 2000 to 2017, and determined their thresholds by an adaptive iteration method to extract the initial impervious surface. Then, Temporal Consistency Check (TCC) was performed to make the time series of impervious surface more reasonable. Results show that: (1) Adding NDVI to both BCI and TCC improved the quality of impervious surface mapping. (2) The average accuracy of impervious surface mapping in this paper was 90.4%, and the average Kappa coefficient was 0.812. (3) The impervious surface area of Guangzhou downtown nearly doubled from 2000 to 2017 with a decreasing growth rate. (4)The newly developed impervious surface mainly concentrated on the relatively backward outskirts of Guangzhou downtown. (5) Elevation, road density, and shopping mart density were the main factors influencing the expansion of impervious surface.

Key words: Guangzhou Downtown, impervious surface, Google Earth Engine, Landsat, BCI, NDVI, Adaptive iterative method, temporal consistency check

LI Peilin, LIU Xiaoping, HUANG Yinghuai, ZHANG Honghui. Mapping Impervious Surface Dynamics of Guangzhou Downtown based on Google Earth Engine[J].Journal of Geo-information Science, 2020, 22(3): 638-648.DOI:10.12082/dqxxkx.2020.190047

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类别	自变量	q值
自然环境因子	高程	0.2432
	坡度	0.1602
	到水体的距离	0.0044
交通因子	道路密度	0.1918
	到地铁站的距离	0.0601
	到公交站的距离	0.1591
服务设施因子	购物场所密度	0.1785
	餐饮场所密度	0.1371
	医疗机构密度	0.1165
	学校密度	0.1282

Mapping Impervious Surface Dynamics of Guangzhou Downtown based on Google Earth Engine

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