摘要
以安徽铜陵金属矿区城镇为研究区,基于Landsat-8遥感数据,采用辐射传输方程模型反演4个时期的地表温度,并以MOD11A1温度产品数据进行精度验证,开展热效应等级区划及URI指数定量评价,统计分析热度与生态地表参数的相关性。研究结果表明:(1)辐射传输模型法在无地面实测数据情况下反演地表温度精度达到0. 7℃,适用于区域热效应分析;(2)城镇人员密集场所、工业集中区存在明显的热效应现象,其中春夏秋三季城镇热效应面积比例均达到25%左右,冬季热效应不明显;(3)热度与绿度指标正相关,合理提高植被覆盖率可有效改善热效应状况;夏秋两季热度与湿度指标负相关,增加空气含水率可降低城镇热效应;热度与干度指标无明显相关性。
Based on the Landsat-8 remote sensing data,the radiation transfer equation model was used to retrieve the surface temperature of four periods in Tongling metal mining area,Anhui Province,and the precision of the data was verified by the MOD11A1 temperature product data.The thermal effect grade regionalization and the quantitative evaluation of URI index were carried out,and the correlation between heat intensity and ecological surface parameters was analyzed statistically.The results show that:① The accuracy of inversion of surface temperature by radiation transfer model method can not reach 0.7 ℃ without ground measured data,which is suitable for the analysis of regional thermal effect.② There are obvious thermal effects in the densely populated places and industrial concentration areas in cities and towns,The proportion of urban heat effect area in spring,summer and autumn reaches about 25%,while the winter heat effect is not obvious.③ The heat intensity is positively correlated with the green degree index,and a reasonable increase in vegetation coverage can effectively improve the thermal effect situation.There is a negative correlation between heat and humidity in summer and autumn.Increasing air moisture content can reduce urban heat effect,but there is no significant correlation between heat and dryness.
作者
王翔
戴晓爱
陈永俊
薛东剑
WANG Xiang;DAI Xiao-ai;CHEN Yong-jun;XUE Dong-jian(Academic of Earth Sciences,Chengdu University of Technology,Chengdu 610059,China;School of Resources and Geosciences,China University of Mining and Technology,Xuzhou 221116,China)
出处
《科学技术与工程》
北大核心
2019年第13期7-14,共8页
Science Technology and Engineering
基金
四川省教育厅高校人文社科重点项目(ZHYJ17-ZD01)
数学地质四川省重点实验室开放基金(SCSXDZ201705)
大学生创新创业训练计划项目(201810616069)资助
