基于Google Earth Engine的河南省引黄受水区不透水面时空演变  

Analysis of Temporal and Spatial Evolution of Impervious Surface in Yellow River Diversion and Receiving Areas of Henan Province Based on Google Earth Engine

作　　者：王李良 张修宇[1] WANG Liliang;ZHANG Xiuyu(North China University of Water Resources and Hydropower,Zhengzhou 450046,China)

机构地区：[1]华北水利水电大学,河南郑州450045

出　　处：《人民黄河》2022年第8期76-80,86,共6页Yellow River

基　　金：河南省重大公益科技专项(201300311500);河南省科技攻关项目(212102311156);河南省水利科技攻关项目(GG202042);水利部黄河泥沙重点实验室开放课题基金项目(HHNS202005);河南省自然科学基金面上项目(222300420492)。

摘　　要：为了解决城镇化发展中不透水面增大导致的城市洪涝、热岛效应等问题,对不透水面的提取方法和时空演变特征进行研究。基于Google Earth Engine云平台和时序Landsat卫星遥感影像,采用随机森林分类法构建河南省引黄受水区1990—2020年不透水面数据集,并选取面积增长率、扩张强度等指标分析不透水面的变化特征,避免了传统提取方法耗时耗力、无法处理大量数据的缺点。结果表明:河南省引黄受水区不透水面面积呈逐年增大趋势,其中2020年不透水面面积最大,为7598 km^(2);生产总值、人口数量与不透水面面积的拟合优度分别为0.980、0.912,表明不透水面面积与生产总值和人口数量成正相关关系。In order to resolve the urban flooding and heat island effect caused by the change of impervious surface in urban development,this paper studied on the extracting methods and evolution features of impervious surface.Based on Google Earth Engine cloud platform and time series Landsat satellite remote sensing images,this paper used random forest classification method to make the impervious surface data set of the Yellow River diversion and receiving areas in Henan Province from 1990 to 2020,and chose typical indicators of the area growth rate and expansion intensity to analyze the change characteristics of impervious surface,avoiding the shortcomings of traditional extraction methods that were time-consuming and labor-intensive and a large amount of data that could not to be processed.The results show that the impervious surface area of the Yellow River diversion receiving areas in Henan Province shows a fluctuating growth trend year by year,of which the impervious surface area is the largest in 2020,i.e.7598 km^(2).The correlation coefficients between GDP and population and impervious surface area are 0.980 and 0.912 respectively,which indicates that the growth of impervious surface is positively correlated with GDP and population.

关 键 词：不透水面 面积增长率 扩张强度 Google Earth Engine 河南省引黄受水区 

分 类 号：TV213.9[水利工程—水文学及水资源]