Peilei Luo: Post-doc research scientist, working in Aerospace Information Research Institute, Chinese Academy of Sciences, Ph.D. The main research interests include vegetation quantitative remote sensing and agricultural application, active and passive remote sensing collaborative inversion of crop growth parameters and deep learning. The major softwares and programming languages used are ERDAS Imagine, & ENVI image analysis systems, ESRI ArcGIS analysis softwares, Matlab, Python, R, IDL, Java, C++/C and so on.

ACADEMIC QUALIFICATIONS

PhD. Aerospace Information Research Institute, Chinese Academy of Sciences, ChinaCartography and Geographical Information System (2017-2020)

MSc. Beijing Forestry University, ChinaForestry Information Engineering (2014-2017)

BSc. Shandong Agricultural University, ChinaRemote sensing science and technology (2010-2014)

APPOINTMENTS

2020-Present

Post-doc research scientist, Aerospace Information Research Institute, Chinese Academy of Sciences, China

PUBLICATIONS

• Luo P, Ye H, Huang W, Liao J, Jiao Q, Guo A and Qian B. Enabling Deep-Neural-Network-Integrated Optical and SAR Data to Estimate the Maize Leaf Area Index and Biomass with Limited In Situ Data[J]. Remote Sensing, 2022, 14(21): 5624. (SCI)

• Luo P, Liao J, Shen G. Combining Spectral and Texture Features for Estimating Leaf Area Index and Biomass of Maize Using Sentinel-1/2, and Landsat-8 Data[J]. IEEE Access, 2020, 8: 53614-53626.(SCI)

Zeng Y, Ning Z, Liu P, Luo P, et al. A mosaic method for multi-temporal data registration by using convolutional neural networks for forestry remote sensing applications[J]. Computing, 2020, 102(3): 795-811.(SCI)