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Dr. Anmin Fu is a Senior Engineer in Academy of Forest Inventory and Planning (Alias: Satellite Forestry Centre), State Forestry Administration.
 
Anmin Fu received a Ph.D. degree in Geography at the Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing, China, in 2010. His research interests are land cover and land use change, biophysical parameters inversion using multiple-sensor data, and carbon cycle in forest ecosystem.
 

Research Interests and History:

In the study of forest remote sensing, he focused on boreal forest monitoring using remote sensing data, as the topic of his PhD Dissertation. It mainly engaged in [1] forest cover and its changes ( fires and deforestation ) in the Northeast of Eurasia; [2] forest parameters inversion under integrating multi-sensors (GLAS, MODIS and TM/ETM+, PALSAR); [3] assessment of forest carbon stocks and its changes in northeast of Eurasia. In this period, he mainly taken on two missions: software platform for application and analysis of remote sensing image (National 863 Programs, 2004.07-2005.09 ), and mapping forest biomass and analyzing its changes in boreal forests of Northeastern Eurasia by multi-sensor synergy (NASA. Project, 2006.02-2008.07 ).
 
Currently, he focuses on application design and demonstration for payloads (Laser Altimeter instrument, Multi-angle imaging spectro-radiometer instrument, Ultra-Spectrometer instrument) onboard Terrestrial Ecosystem Carbon (TEC) Satellite. It consists of [1] forest volume and vegetation fluorescence inversion; [2] ground-airborne-spaceborne observation experiment in forest ecosystems; [3] ground validation of satellite data and forest inversion product; [4] forest carbon stock assessment at regional, national and global scales. Two programs are in processing: Design and demonstration for major technology indexes of payloads onboard TEC Satellite (CNSA project, 2015.01-2018.01); Application design and demonstration (forest LAI, height and fluorescence) for payloads onboard TEC Satellite (CNSA project & SFA project, 2016.01-now)
 
In the study of land degradation assessment, he focused on producing national-scale land degradation map at arid region of China. Multi-sensor data (TM / ETM + / OLI and MODIS) was used in long-term vegetation monitoring; Data from meteorological satellites (FY-3, GMS) was used in energy- water balance monitoring ; The interaction status between human and land was assessed, under the background of global climate changes. Research programs include: Land degradation and its recovery monitoring using satellite images (Research Projects of Forestry Public Welfare Industry in China, 2012.01-2016.12); Vegetation change in arid region of China 2000-2010 (SFA project, 2014.01-2017.12); Application of energy and water balance model in the arid region of China with FY satellite images (948 program, 2009.01-2012.12); Assessment of sandstorm risk and its pattern (Research projects of forestry public welfare industry in China), 2008.06-2012.12).
 
In the geomatics engineering of remote sensing, he has taken charge of two national-scale projects to process digital orthophoto map (DOM) covering the area of 4000 000 km2 in the North of China. The two was completed in 2009 (TM / ETM +, 30m) and 2013 (ZY-3, 2.5m), respectively. The two missions are: 2.5 m DOM images processing project for the 5th National Desertification and Land Desertification Monitoring (2013.01- 2014.06); 30 m DOM images processing project for the 4th National Desertification and Land Desertification Monitoring (2009.01-2010.03).
 

Education:

  • B.S. degree in Geography, Northeast Normal University, 1998
  • M.S. & Ph.D. degree in Remote Sensing, Institute of Remote Sensing Applications, Chinese Academy of Sciences, 2010

 

Selected Publications:

  • [1] Fu, A., Fu, R., Sun, T., & Kong, X. (2014). Sensitivity of vegetation toward precipitation in dry land of China using satellite images. Paper presented at the Earth Observation and Remote Sensing Applications (EORSA), 2014 3rd International Workshop on.
  • [2] Fu, A., Sun, G., Cai, Y., & Ni, W. (2006). Disturbance Detection and Assessment with MODIS Imagery in Boreal Forest Ecosystem. Paper presented at the Geoscience and Remote Sensing IEEE International Symposium.
  • [3] Fu, A., Sun, G., & Guo, Z. (2009). Estimating forest biomass with GLAS samples and MODIS imagery in Northeastern China. Paper presented at the MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications.
  • [4] Fu, A., Sun, G., Guo, Z., & Wang, D. (2010). Forest Cover Classification With Modis Images In Northeastern Asia. IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing, 3(2), 178 – 189.
  • [5] Fu, A., Sun, G., Guo, Z., & Wang, D. (2010). Forest Changes Detection in the Northeastern Asia Using MODIS Imagery. Acta Scientiarum Naturalium Universitatis Pekinensis, 46(5),835-843.
  • [6] Chi, H., Sun, G., Huang, J., Guo, Z., Ni, W., & Fu, A. (2015). National Forest Aboveground Biomass Mapping from ICESat/GLAS Data and MODIS Imagery in China. Remote Sensing, 7(5), 5534-5564.
  • [7] Sun, G., Ranson, K. J., Masek, J., Guo, Z., Pang, Y., Fu, A., & Wang, D. (2008). Estimation of Tree Height and Forest Biomass from GLAS Data(Silvilaser). Journal of Forest Planning, 13, 157-164.
  • [8] CAI, Y., Sun, G., Pang, Y., Liu, D., Dong, Y., & Fu,A. (2006).Post process of forest parameters retriving for remote sensing. Geomatics &Spatial Information Technology, (5), 33-34.
  • [9] Chen, F., Niu, Z., & Fu, A. (2006).Study on lower spatial resolution image simulation of field survey data. Acta Scientiarum Naturalium Universitatis Pekinensis ,42(4), 478-483.
  • [10] Chen, F., Niu, Z., Qin, Y., & Fu, A. (2007).Simulation of an image with subsection of spectral band using an image with wider spectral band. Opo-Electronic Engineering,34(5), 89-96.
  • [11] Dong, Y., Sun, G., Pang, Y., & Fu, A. (2005). A comparitive study of some atmospheric correction methods.Remote sensing for land & resource, (2), 16-19.