Gaofei Yin

Dr. Gaofei Yin


Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

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

Representative Publications

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1 June 2019 in ISPRS Journal of Photogrammetry and Remote Sensing
Verified
Journal Article
Open access
Lei MaLei Ma
Lei Ma
YLYu Liu
Yu Liu
XZXueliang Zhang
Xueliang Zhang
YYYuanxin Ye
Yuanxin Ye
GYGaofei Yin
Gaofei Yin
Brian Alan JohnsonBrian Alan Johnson
Brian Alan Johnson

1 February 2019 in Remote Sensing of Environment
Verified
Journal Article
Closed access
Wei ZhaoWei Zhao
Wei Zhao
Si-Bo DuanSi-Bo Duan
Si-Bo Duan
ALAinong Li
Ainong Li
GYGaofei Yin
Gaofei Yin

1 May 2018 in Remote Sensing of Environment
Verified
Journal Article
Closed access
Baodong XuBaodong Xu
Baodong Xu
JLJing Li
Jing Li
Taejin ParkTaejin Park
Taejin Park
Qinhuo LiuQinhuo Liu
Qinhuo Liu
YZYelu Zeng
Yelu Zeng
RMRanga Myneni
Ranga Myneni

5 October 2023 in ISPRS Journal of Photogrammetry and Remote Sensing
Verified
Journal Article
Closed access
ZCZhiwen Cai
Zhiwen Cai
Qiong HuQiong Hu
Qiong Hu
XZXinyu Zhang
Xinyu Zhang
JYJingya Yang
Jingya Yang
HWHaodong Wei
Haodong Wei
Zhihua ShiZhihua Shi
Zhihua Shi

1 February 2018 in Forests
Verified
Journal Article
Open access
PDF file
Baodong XuBaodong Xu
Baodong Xu
Taejin ParkTaejin Park
Taejin Park
Kai YanKai Yan
Kai Yan
CCChi Chen
Chi Chen
Yelu ZengYelu Zeng
Yelu Zeng
RMRanga Myneni
Ranga Myneni
The operational Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) algorithm has been successfully implemented for Visible Infrared Imager Radiometer Suite (VIIRS) observations by optimizing a small set of configurable parameters in Look-Up-Tables (LUTs). Our preliminary evaluation showed reasonable agreement between VIIRS and MODIS LAI/FPAR retrievals. However, there is a need for a more comprehensive investigation to assure continuity of multi-sensor global LAI/FPAR time series, as the preliminary evaluation was spatiotemporally limited. In this study, we use a multi-year (2012–2016) global LAI/FPAR product generated from VIIRS and MODIS to evaluate for spatiotemporal consistency. We also quantify uncertainty of the product by utilizing available ground measurements. For both consistency and uncertainty evaluation, we account for variations in biome type and temporal resolution. Our results indicate that the LAI/FPAR retrievals from VIIRS and MODIS are consistent at different spatial (i.e., global and site) and temporal (i.e., 8-day, seasonal and annual) scales. The estimate of mean discrepancy (−0.006 ± 0.013 for LAI and −0.002 ± 0.002 for FPAR) meets the stability requirement for long-term LAI/FPAR Earth System Data Records (ESDRs) from multi-sensors as suggested by the Global Climate Observing System (GCOS). It is noteworthy that the rate of retrievals from the radiative transfer-based main algorithm is also comparable between two sensors. However, a relatively larger discrepancy over tropical forests was observed due to reflectance saturation and an unexpected interannual variation of main algorithm success was noticed due to instability in input surface reflectances. The uncertainties/relative uncertainties of VIIRS and MODIS LAI (FPAR) products assessed through comparisons to ground measurements are estimated to be 0.60/42.2% (0.10/24.4%) and 0.55/39.3% (0.11/26%), respectively. Note that the validated LAI were only distributed in low domains (~2.5), resulting in large relative uncertainty. Therefore, more ground measurements are needed to achieve a more comprehensive evaluation result of product uncertainty. The results presented here generally imbue confidence in the consistency between VIIRS and MODIS LAI/FPAR products and the feasibility of generating long-term multi-sensor LAI/FPAR ESDRs time series.

1 September 2018 in Remote Sensing of Environment
Verified
Journal Article
Closed access
GYGaofei Yin
Gaofei Yin
ALAinong Li
Ainong Li
WSWu Shengbiao
Wu Shengbiao
WFWeiliang Fan
Weiliang Fan
YZYelu Zeng
Yelu Zeng
Qinhuo LiuQinhuo Liu
Qinhuo Liu