Xiaolin Zhu
Xiaolin Zhu
Department of Land Surveying and Geo-Informatics,The Hong Kong Polytechnic University
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Zitiert von
Zitiert von
Plant phenology and global climate change: Current progresses and challenges
S Piao, Q Liu, A Chen, IA Janssens, Y Fu, J Dai, L Liu, XU Lian, M Shen, ...
Global change biology 25 (6), 1922-1940, 2019
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 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
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
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
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
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
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
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
An Improved Flexible Spatiotemporal DAta Fusion (IFSDAF) method for producing high spatiotemporal resolution normalized difference vegetation index time series
M Liu, W Yang, X Zhu, J Chen, X Chen, L Yang, EH Helmer
Remote sensing of environment 227, 74-89, 2019
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
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
Automatic detection of individual oil palm trees from UAV images using HOG features and an SVM classifier
Y Wang, X Zhu, B Wu
International Journal of Remote Sensing 40 (19), 7356-7370, 2019
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
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), 2015
The effects of border control and quarantine measures on the spread of COVID-19
MP Hossain, A Junus, X Zhu, P Jia, TH Wen, D Pfeiffer, HY Yuan
Epidemics 32, 100397, 2020
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