摘要
提出融入中高空间分辨率遥感影像精确地类识别信息,以改进传统的Chen NDVI尺度转换模型的方法,并基于两个模型共同进行MODIS 250m 16D合成植被指数产品MOD13 Q1(MODIS/Terra Vegetation Indices 16-Day L3 Global 250m SIN Grid)真实性检验。研究以地类丰富的厦门市作为研究区主体,并以30m Landsat8陆地成像仪OLI(Operational Land Imager)影像作为验证数据,实践了上述方法。实验结果表明:MOD13 Q1产品总体质量较好,但是存在偏高估计的问题,尤其是对人工地物更为明显,在实际应用中应予以关注;融入精细地类信息的改进ChenNDVI模型相比较融入粗略地类信息的传统Chen NDVI模型,升尺度转换结果无显著差异,但是前者在精细、定量刻画“不同地类对NDVI尺度效应影响”方面更有优势,这对遥感地表参数尺度效应研究具有重要的启示意义。
To improve the traditional Chen NDVI scale conversion model to perform MOD13 QI validation based on the traditional and improved models,a method to integrate the accurate classifications information of medium-high spatial resolution remote sensing images is proposed in this study.The above-mentioned method is practiced by using Xiamen City as the main body of the study area and using 30 m Landsat8 OLI image as verification data which is rich in ground objects.The experimental results show that the overall quality of MOD13 Q1 products is good,but there is a problem of high estimation,especially for artificial ground objects which should be paid attention to in practical applications.Improved Chen NDVI model incorporating fine ground information is compared with the traditional Chen NDVI model with rough information,there is no significant difference in the up-scale conversion results,but the former has more advantages in the fine and quantitative description of the influence of different land types on NDVI scale effects.It has important implications for the scale effect research of remote sensing surface parameters.
作者
栾海军
牛阳
何原荣
刘光生
章欣欣
聂芹
LUAN Haijun;NIU Yang;HE Yuanrong;LIU Guangsheng;ZHANG Xinxin;NIE Qin(College of Computer and Information Engineering,Xiamen University of Technology,Xiamen 361024,China;Fujian Engineering and Research Center of Rural Sewage Treatment and Water Safety,Xiamen University of Technology,Xiamen 361024,China;Big Data Institute of Digital Natural Disaster Monitoring in Fujian,Xiamen University of Technology,Xiamen 361024,China)
出处
《测绘科学技术学报》
北大核心
2019年第1期45-50,共6页
Journal of Geomatics Science and Technology
基金
国家自然科学基金项目(41601350
41701383)
福建省自然科学基金项目(2017J05069
2017J01666
2017J01469)
“福建省农村污水处理与用水安全工程研究中心”开放课题资助(RST201809)
