西南交通大学教师主页 zhangguodong--Home-- An RTM-driven machine learning approach for estimating high resolution FAPAR from Landsat 5/7/8/9 surface reflectance

Current position: Home > Research > Paper Publications

Paper Publications

An RTM-driven machine learning approach for estimating high resolution FAPAR from Landsat 5/7/8/9 surface reflectance

Impact Factor:4.7

Journal:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Translation or Not:no

Included Journals:SCI

Next One:Time series high-resolution land surface albedo estimation based on the ensemble Kalman filter algorithm

zhangguodong

Lecturer (higher education)

Gender:Male Education Level:PhD graduate Alma Mater:武汉大学 Degree:Doctor of engineering Status:在岗 School/Department:地球科学与工程学院 Business Address:四川省成都市西南交通大学犀浦校区4号楼4222室

Home

Receive Honor

Research

Teaching

Awards and Honours

Enrollment

Student Information

My Album

Blog

Paper Publications

An RTM-driven machine learning approach for estimating high resolution FAPAR from Landsat 5/7/8/9 surface reflectance