Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

imagery Earth & Environmental Sciences
Landsat Earth & Environmental Sciences
remote sensing Earth & Environmental Sciences
vegetation Earth & Environmental Sciences
Ecosystems Engineering & Materials Science
land cover Earth & Environmental Sciences
China Agriculture & Biology
Monitoring Engineering & Materials Science

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Projects 2004 2017

Research Output 2000 2017

  • 2960 Citations
  • 23 h-Index
  • 47 Article
  • 2 Conference contribution
  • 1 Review article

A photosynthesis-based two-leaf canopy stomatal conductance model for meteorology and air quality modeling with WRF/CMAQ PX LSM

Ran, L., Pleim, J., Song, C., Band, L., Walker, J. T. & Binkowski, F. S. Feb 16 2017 In : Journal of Geophysical Research. 122, 3, p. 1930-1952 23 p.

Research output: Research - peer-reviewArticle

stomatal conductance
meteorology
land surface
photosynthesis
air quality
4 Citations

Natural disasters and economic development drive forest dynamics and transition in China

Zhang, K., Song, C., Zhang, Y. & Zhang, Q. Mar 1 2017 In : Forest Policy and Economics. 76, p. 56-64 9 p.

Research output: Research - peer-reviewArticle

forest dynamics
natural disaster
economic development
Natural disasters
China
4 Citations

Reanalysis of global terrestrial vegetation trends from MODIS products: Browning or greening?

Zhang, Y., Song, C., Band, L. E., Sun, G. & Li, J. Mar 15 2017 In : Remote Sensing of Environment. 191, p. 145-155 11 p.

Research output: Research - peer-reviewArticle

vegetation index
MODIS
vegetation
trend
product
4 Citations

Consistent classification of landsat time series with an improved automatic adaptive signature generalization algorithm

Dannenberg, M. P., Hakkenberg, C. R. & Song, C. 2016 In : Remote Sensing. 8, 8, 691

Research output: Research - peer-reviewArticle

Landsat
time series
land cover
wetland
hay
7 Citations

Development of a coupled carbon and water model for estimating global gross primary productivity and evapotranspiration based on eddy flux and remote sensing data

Zhang, Y., Song, C., Sun, G., Band, L. E., McNulty, S., Noormets, A., Zhang, Q. & Zhang, Z. Jun 15 2016 In : Agricultural and Forest Meteorology. 223, p. 116-131 16 p.

Research output: Research - peer-reviewArticle

evapotranspiration
eddy
remote sensing
productivity
carbon