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, 183-198.
Homer, C., C. Huang, L. Yang, B. Wylie, and M. Coan. 2004. Development of a 2001 national land cover database for the United States. Photogrammetric Engineering & Remote Sensing 70 (7):829-840.
Huang, C., Kim, S., Altstatt, A., Song, K., Townshend, J.R.G., Davis, P., Rodas, O., Yanosky, A., Clay, R., Tucker, C.J. & Musinsky, J. (2009). Assessment of Paraguay’s Forest Cover Change Using Landsat Observations. Global and Planetary Change, 67, 1-12.
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, 183-198.
Huang, C., Thomas, N., Goward, S.N., Masek, J., Zhu, Z., Townshend, J.R.G. & Vogelmann, J.E. (2010). Automated masking of cloud and cloud shadow for forest change analysis. International Journal of Remote Sensing, 31, 5449-5464.
Remote Sensing Land Change Monitoring
A Framework for High-Resolution Estimation of Terrestrial Carbon Stocks and Dynamics
Ecosystem Disturbance and Fire: Patterns, Trends, and Greenhouse Gas Consequences
The primary goal of this project is to develop improved understanding of ecosystem disturbances and their carbon consequences. Specifically, we will develop methods for reconstructing the history of ecosystem disturbances and for continuously monitoring on-going disturbances. We will also evaluate the severity, causes, and carbon consequences of disturbances. For the second objective we will focus on fire disturbances as mapped through the Monitoring Trends and Burn Severity (MTBS) project. The following are the specific goals of the proposed project:
Using Landsat Global Land Survey Data to Measure and Monitor Worldwide Urbanization
The specific objectives of this project are to:
1) Use the Landsat GLS data set, as processed by GLCF to surface reflectance, to develop high quality, high spatial resolution, baseline measurements of global % impervious cover for the ca. 2000 and 2010 time periods.