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Funded Research

Integration of long term Landsat observations with DESDynI measurements for monitoring terrestrial carbon fluxes within and beyond the DESDynI mission

Huang, Chengquan (Cheng): University of Maryland (Project Lead)
Dubayah, Ralph: University of Maryland (Co-Investigator)
Goward, Samuel: University of Maryland (Co-Investigator)
Hurtt, George: University of Maryland (Co-Investigator)
Masek, Jeffrey (Jeff): NASA GSFC (Institution Lead)

Project Funding: 2009 - 2013

NRA: 2008 NASA: Terrestrial Ecology   

Funded by NASA

A key element of climate change studies is to understand past and current global carbon budget and predict its future trend. Currently this is hindered by a lack of good understanding of the various carbon pools and the fluxes among them. The primary goal of this project is to improve estimates of terrestrial carbon pools and associated fluxes using integrated assessment approaches that combine long term Landsat observations, direct structure and biomass measurements from the planned DESDynI, and ecosystem modeling. Specifically, we seek to: (1) Develop an approach for integrating age estimates and multispectral trajectories from the Landsat record with anticipated height observations from DESDynI to map height, biomass and biomass changes across the landscape through time. (2) Assess the spatial and temporal variability of biomass dynamics over the 5-year DESDynI mission length at various spatial scales to quantify expected disturbance and growth rates from which required measurement accuracies for DESDynI may be determined. (3) Integrate age structure maps from Landsat with height and biomass products developed through Landsat/DESDynI fusion to improve and validate ecosystem model estimates of terrestrial carbon flux. (4) Scale up our Landsat-DESDynI integration approach to produce spatially and temporally resolved, state level assessment of biomass dynamics for nearly four decades, and use these products to drive ecosystem model estimates of carbon flux. Our methodological approach will first relate Landsat disturbance time series products from NAFD, including age and multispectral trajectories to lidar-derived heights from ICESAT and the Laser Vegetation Imaging Sensor (LVIS). These will then be used to produce a time series of height and biomass maps for the Landsat record which will be compared with measured differences in biomass. Once validated the approach will be scaled to larger areas, namely, North Carolina and Maryland. Next, we will pick several 5 year periods from our Landsat record, and use the derived maps of height and biomass to assess real-world variability in the dynamics of each of these across various spatial scales. This will help determine the magnitude of the changes in height and biomass DESDynI can be expected to encounter, and help define its required measurement sensitivities through time and across space. Finally, we will explore methods for integrating these height and age products into the ecosystem models, in particular the Ecosystem Demography (ED) model. We will scale our approach upwards by using the ED model to predict flux over the larger areas in North Carolina and Maryland.


Ling, P., Baiocchi, G., Huang, C. 2015. Estimating annual influx of carbon to harvested wood products linked to forest management activities using remote sensing. Climatic Change. 134(1-2), 45-58. DOI: 10.1007/s10584-015-1510-3

Huang, C., Goward, S. N., Masek, J. G., Thomas, N., Zhu, Z., Vogelmann, J. E. 2010. An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks. Remote Sensing of Environment. 114(1), 183-198. DOI: 10.1016/j.rse.2009.08.017

Huang, C., Thomas, N., Goward, S. N., Masek, J. G., Zhu, Z., Townshend, J. R. G., Vogelmann, J. E. 2010. Automated masking of cloud and cloud shadow for forest change analysis using Landsat images. International Journal of Remote Sensing. 31(20), 5449-5464. DOI: 10.1080/01431160903369642

2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)

  • Impact of Forest Harvest Regimes on the Tradeoff between Roundwood Production and Carbon Sequestration   --   (Pui-Yu Ling, Caren Dymond, Weimin Xi)   [abstract]
  • Integrating Lidar Canopy Height and Landsat-based Forest Disturbance History with Ecosystem Demography Model for Carbon Change Estimation, A Case in Charles County, Maryland   --   (Maosheng Zhao, Chengquan Huang, George Hurtt, Ralph Dubayah, Justin Fisk, Anu Swatantran, Wenli Huang, Hao Tang)   [abstract]

2013 NASA Terrestrial Ecology Science Team Meeting Poster(s)

  • High-Resolution Ecosystem Modeling as part of Robust Carbon Monitoring System   --   (Maosheng Zhao, George Hurtt, Ralph Dubayah, Justin Fisk, Amanda Armstrong, Anuradha Swatantran, Naira Pinto, Oliver Rourke, Steve Flanagan, Chengquan Huang)   [abstract]
  • Forest Structure and Biomass Mapping Using Time Series Landsat Observations, Small Footprint Lidar, and Field Inventory Data in North Carolina   --   (Chengquan Huang)   [abstract]

2011 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)

  • Incorporating passive and active remote sensing data into an advanced ecosystem model to investigate the role of regional forest disturbance and recovery dynamics on the carbon cycle   --   (Katelyn Dolan, George Hurtt, Chengquan Huang, Ralph Dubayah, Justin Fisk)   [abstract]
  • Statewide Mapping of Forest Structure and Standing Biomass in North Carolina Using Small Footprint Lidar and Field Plot Data   --   (Chengquan Huang, Yong Pang, Chris Toney, Ralph Dubayah)   [abstract]

2010 NASA Terrestrial Ecology Science Team Meeting Poster(s)

  • Integration of long term Landsat observations with DESDynI measurements for monitoring terrestrial carbon fluxes within and beyond the DESDynI mission   --   (Chengquan Huang, Ralph Dubayah, George Hurtt, Jeffrey G Masek, Samuel N Goward)   [abstract]
  • Mapping Forest Height for Mississippi Using Long-term Landsat Observations and GLAS Data   --   (Ainong Li, Chengquan Huang, Hua Shi, Guoqing Sun, Zhiliang Zhu, Samuel N. Goward, Jeffrey G. Masek)   [abstract]

More details may be found in the following project profile(s):