Xiaolin Zhu
Xiaolin Zhu
Department of Land Surveying and Geo-Informatics,The Hong Kong Polytechnic University
Verified email at polyu.edu.hk - Homepage
Cited by
Cited by
An enhanced spatial and temporal adaptive reflectance fusion model for complex heterogeneous regions
X Zhu, J Chen, F Gao, X Chen, JG Masek
Remote Sensing of Environment 114 (11), 2610-2623, 2010
A simple and effective method for filling gaps in Landsat ETM+ SLC-off images
J Chen, X Zhu, JE Vogelmann, F Gao, S Jin
Remote sensing of environment 115 (4), 1053-1064, 2011
Influences of temperature and precipitation before the growing season on spring phenology in grasslands of the central and eastern Qinghai-Tibetan Plateau
M Shen, Y Tang, J Chen, X Zhu, Y Zheng
Agricultural and Forest Meteorology 151 (12), 1711-1722, 2011
A flexible spatiotemporal method for fusing satellite images with different resolutions
X Zhu, EH Helmer, F Gao, D Liu, J Chen, MA Lefsky
Remote Sensing of Environment 172, 165-177, 2016
Disaggregation of remotely sensed land surface temperature: Literature survey, taxonomy, issues, and caveats
W Zhan, Y Chen, J Zhou, J Wang, W Liu, J Voogt, X Zhu, J Quan, J Li
Remote Sensing of Environment 131, 119-139, 2013
Improving forest aboveground biomass estimation using seasonal Landsat NDVI time-series
X Zhu, D Liu
ISPRS Journal of Photogrammetry and Remote Sensing 102, 222-231, 2015
Fusing Landsat and MODIS data for vegetation monitoring
F Gao, T Hilker, X Zhu, M Anderson, J Masek, P Wang, Y Yang
IEEE Geoscience and Remote Sensing Magazine 3 (3), 47-60, 2015
Plant phenology and global climate change: Current progresses and challenges
S Piao, Q Liu, A Chen, IA Janssens, Y Fu, J Dai, L Liu, X Lian, M Shen, ...
Global change biology 25 (6), 1922-1940, 2019
A new geostatistical approach for filling gaps in Landsat ETM+ SLC-off images
X Zhu, D Liu, J Chen
Remote sensing of Environment 124, 49-60, 2012
A modified neighborhood similar pixel interpolator approach for removing thick clouds in Landsat images
X Zhu, F Gao, D Liu, J Chen
IEEE Geoscience and Remote Sensing Letters 9 (3), 521-525, 2011
Accurate mapping of forest types using dense seasonal Landsat time-series
X Zhu, D Liu
ISPRS Journal of Photogrammetry and Remote Sensing 96, 1-11, 2014
Spatiotemporal fusion of multisource remote sensing data: literature survey, taxonomy, principles, applications, and future directions
X Zhu, F Cai, J Tian, TKA Williams
Remote Sensing 10 (4), 527, 2018
An improved method for producing high spatial-resolution NDVI time series datasets with multi-temporal MODIS NDVI data and Landsat TM/ETM+ images
Y Rao, X Zhu, J Chen, J Wang
Remote Sensing 7 (6), 7865-7891, 2015
Blending MODIS and Landsat images for urban flood mapping
F Zhang, X Zhu, D Liu
International journal of remote sensing 35 (9), 3237-3253, 2014
An improved image fusion approach based on enhanced spatial and temporal the adaptive reflectance fusion model
D Fu, B Chen, J Wang, X Zhu, T Hilker
Remote sensing 5 (12), 6346-6360, 2013
Modeling tree root diameter and biomass by ground-penetrating radar
XH Cui, J Chen, JS Shen, X Cao, XH Chen, XL Zhu
Science China Earth Sciences 54 (5), 711-719, 2011
NDVI and vegetation phenology dynamics under the influence of sunshine duration on the Tibetan plateau
H Wang, D Liu, H Lin, A Montenegro, X Zhu
International Journal of Climatology 35 (5), 687-698, 2015
A hybrid color mapping approach to fusing MODIS and Landsat images for forward prediction
C Kwan, B Budavari, F Gao, X Zhu
Remote Sensing 10 (4), 520, 2018
An automatic method for screening clouds and cloud shadows in optical satellite image time series in cloudy regions
X Zhu, EH Helmer
Remote sensing of environment 214, 135-153, 2018
Estimating tree-root biomass in different depths using ground-penetrating radar: Evidence from a controlled experiment
X Cui, L Guo, J Chen, X Chen, X Zhu
IEEE Transactions on Geoscience and Remote Sensing 51 (6), 3410-3423, 2012
The system can't perform the operation now. Try again later.
Articles 1–20