Xinjie Liu

Mr. Xinjie Liu

Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
orcid

Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2017 in Agricultural and Forest Meteorology
Verified
Journal Article
Closed access
LLLiangyun Liu
Liangyun Liu
LGLinlin Guan
Linlin Guan
XLXinjie Liu
Xinjie Liu

1 September 2019 in Remote Sensing of Environment
Verified
Journal Article
Closed access
XLXinjie Liu
Xinjie Liu
LGLuis Guanter
Luis Guanter
LLLiangyun Liu
Liangyun Liu
ADAlexander Damm
Alexander Damm
Zbynek MalenovskyZbynek Malenovsky
Zbynek Malenovsky
JGJean Philippe Gastellu-Etchegorry
Jean Philippe Gastellu-Etchegorry

1 November 2018 in Science Bulletin
Verified
Journal Article
Open access
SDShanshan Du
Shanshan Du
LLLiangyun Liu
Liangyun Liu
XLXinjie Liu
Xinjie Liu
XZXiao Zhang
Xiao Zhang
XZXingying Zhang
Xingying Zhang
LZLianchong Zhang
Lianchong Zhang
The first Chinese Carbon Dioxide Observation Satellite Mission (TanSat), which was launched on December 21, 2016, is intended to measure atmospheric CO2 concentration. The high spectral resolution (0.044 nm) and high SNR (360 at 15.2 mW m-1 sr-1 nm-1) measurements in the region of the O2-A band of the Atmospheric Carbon dioxide Grating Spectroradiometer (AGCS) module onboard TanSat make it possible to retrieve solar-induced chlorophyll fluorescence (SIF) from TanSat observations at the global scale. This paper aims to explore the potential of the TanSat data for global SIF retrieval. A singular vector decomposition (SVD) statistical method was employed to retrieve SIF using radiance over a micro spectral window (∼2 nm) around the Fe Fraunhofer lines (centered at 758.8 nm). The global SIF at 758.8 nm was successfully retrieved with a low residual error of 0.03 mW m-1 sr-1 nm-1. The results show that the spatial and temporal patterns of the retrieved SIF agree well with the global terrestrial vegetation pattern. The monthly SIF products retrieved from the TanSat data were compared with other remote sensing datasets, including OCO-2 SIF, MODIS NDVI, EVI and GPP. The overall consistency between TanSat and OCO-2 SIF products (R2 = 0.86) and the consistency of the spatial patterns and temporal variations between the TanSat SIF and MODIS vegetation indices and GPP enhance our confidence in the potential and feasibility of TanSat data for SIF retrieval. TanSat, therefore, provides a new opportunity for global sampling of SIF at fine spatial resolution (2 km × 2 km), thus improving photosynthesis observations from space.

1 June 2017 in Ecological Indicators
Verified
Journal Article
Closed access
DPDailiang Peng
Dailiang Peng
CWChaoyang Wu
Chaoyang Wu
CLCunjun Li
Cunjun Li
XZXiaoyang Zhang
Xiaoyang Zhang
ZLZhengjia Liu
Zhengjia Liu
BFBin Fang
Bin Fang

17 January 2022 in Remote Sensing of Environment
Verified
Journal Article
Closed access
ZLZhunqiao Liu
Zhunqiao Liu
FZFeng Zhao
Feng Zhao
XLXinjie Liu
Xinjie Liu
QYQiang Yu
Qiang Yu
YWYunfei Wang
Yunfei Wang
XLXiaoliang Lu
Xiaoliang Lu

1 February 2020 in Agricultural and Forest Meteorology
Verified
Journal Article
Closed access
XLXinjie Liu
Xinjie Liu
LLLiangyun Liu
Liangyun Liu
JHJiaochan Hu
Jiaochan Hu
JGJian Guo
Jian Guo
SDShanshan Du
Shanshan Du