Karen G. Schleeweis
Ogden, UT 84401-2450
- Support LANDFIRE forest structure and vegetation mapping with FIA data.
- Characterize disturbance regimes and forest disturbances for the USFS Resource Planning Act (RPA) Assessment.
- Use spatial patterns and metrics to give context to forest plots, pixels and trends.
- Characterize the implications and impacts of data quality and quantity, from FIA and imaged data, on forest structure mapping across enivornmental gradients and for multiple applications.
Annual Forest History Mapping across CONUS – I had the good fortune to be part of a research collaboration spanning multiple federal agencies and Universities that lasted over a decade: the NAFD (North American Forest Dynamics) study, a core project of the NASA North American Carbon Program (NACP).
I was able to serve multiple roles through this project's life cycle including collaborative coder on the NASA JPL supercomputers, research support, project coordinator and independent researcher. The study contributed techniques and CONUS wide data across a diverse set of topics supporting forest history modeling and mapping while creating national statistical annual estimates and maps of forest change (this only lists the projects pubs i contributed to directly):
- Insights into Natural Resource Applications from time-series forest history and Disturbance Regimes maps (Gong et al. 2022; Riitters et al. 2020; Huang et al., 2009)
- Mapping attribution of causal agents in forest change events (Schleeweis et al. 2020; Schroeder et al. 2017; Schleeweis et al. 2013)
- Mapping intensity of forest disturbance events (Lu et al. 2022; Tao et al. 2019)
- Mapping the timing and location of forest mortality events (Zhao et al. 2019; Goward et al. 2016; Masek et al. 2013)
- High volume image processing and QA (Zhao et al. 2019; Schleeweis et al. 2016; Huang et al. 2009)
- Validation of time-series maps (Zhao et al. 2019; Thomas et al. 2011)
A geographer at heart, I get excited about the relevance of spatial relationships and landscape heterogeniety in natural resource applications. Research interests include cartography, visualization, biogeography, spatial pattern analysis, scaling, forest disturbance regimes, and domain breaks of drivers and constraints within forest dynamics. I have been lucky to collaborate with teams that integrate geospatial techniques, using FIA plot data, image time-series, geostatistics, GIS and large volume data computing, to characterize forest trends as they relate to questions of natural resource monitoring and management.
I currently serve as the FIA liason for LANDFIRE, a USDA Forest Service and USGS joint program, that produces over 28+ National geospatial layers for wildfire decision support. To read more about the LANDFIRE program and FIA a 15 year interagency partnership follow this link to the StoryMap .
I currently serve as the FIA science team lead for the National Land Cover Database (NLCD) tree canopy cover product. The Forest Service is a member of the Multi-Resolution Land Characteristics Consortium (MRLC) and is responsible for producing the tree canopy dataset for the United States using Landsat imagery and maintaining the consortium's product cycle.
In order for the Forest Inventory and Analysis program to continue its efficacy, continue to learn and improve, and advance forest inventory science, we need to refine existing and develop new techniques. It is perhaps more important than ever to share the most recent information on the status of and trends in our forests in an engaging and and meaningful manner across a diverse range of audiences. Working on techniques development and technology transfer methods advances these goals and can benefit the broader forest science community.
The FIA program fills critical forest information needs for a variety of customers in state government, the timber industry, environmental organizations, and many more. As a neutral provider of data, FIA seeks to constantly improve the inventories efficiency and utility in order to maximize the return on taxpayer dollars. Integrating geospatial and remote sensing technologies into inventory processes aids in achieving this objective.
- University of Maryland, College Park, Ph.D. Geography, Remote Sensing and GIS for Natural Resource Applications, 2012
- University of Maryland, Baltimore County, Bachelor Of Science, Geography, 2006
- International Association for Landscape Ecology, Current
- Schleeweis, Karen G.; Moisen, Gretchen G.; Schroeder, Todd A.; Toney, Chris ; Freeman, Elizabeth A.; Goward, Samuel N.; Huang, Chengquan ; Dungan, Jennifer L.. 2020. US National Maps Attributing Forest Change: 1986-2010
- Schleeweis, Karen; Goward, Samuel N.; Huang, Chengquan; Dwyer, John L.; Dungan, Jennifer L.; Lindsey, Mary A.; Michaelis, Andrew; Rishmawi, Khaldoun; Masek, Jeffery G.. 2016. Selection and quality assessment of Landsat data for the North American forest dynamics forest history maps of the US
- Tao, Xin ; Huang, Chengquan ; Zhao, Feng ; Schleeweis, Karen ; Masek, Jeffrey ; Liang, Shunlin. 2019. Mapping forest disturbance intensity in North and South Carolina using annual Landsat observations and field inventory data
- Schroeder, Todd A.; Schleeweis, Karen G.; Moisen, Gretchen G.; Toney, Chris; Cohen, Warren B.; Freeman, Elizabeth A.; Yang, Zhiqiang; Huang, Chengquan. 2017. Testing a Landsat-based approach for mapping disturbance causality in U.S. forests
- Moisen, Gretchen G.; Meyer, Mary C.; Schroeder, Todd A.; Liao, Xiyue; Schleeweis, Karen G.; Freeman, Elizabeth A.; Toney, Chris. 2016. Shape selection in Landsat time series: A tool for monitoring forest dynamics
- Schleeweis, Karen; Goward, Samuel N.; Huang, Chengquan; Masek, Jeffrey G.; Moisen, Gretchen; Kennedy, Robert E.; Thomas, Nancy E.. 2013. Regional dynamics of forest canopy change and underlying causal processes in the contiguous US
- Gong, Weishu ; Huang, Chengquan ; Houghton, Richard A.; Nassikas, Alexander ; Zhao, Feng ; Tao, Xin ; Lu, Jiaming ; Schleeweis, Karen. 2022. Carbon fluxes from contemporary forest disturbances in North Carolina evaluated using a grid-based carbon accounting model and fine resolution remote sensing products
- Lu, Jiaming ; Huang, Chengquan ; Tao, Xin ; Gong, Weishu ; Schleeweis, Karen. 2022. Annual forest disturbance intensity mapped using Landsat time series and field inventory data for the conterminous United States (1986-2015)
- Rishmawi, Kaldoun ; Huang, Chengquan ; Schleeweis, Karen ; Zhan, Xiwu. 2022. Integration of VIIRS observations with GEDI-Lidar measurements to monitor forest structure dynamics from 2013 to 2020 across the conterminous United States
- Lister, Andrew J.; Andersen, Hans ; Frescino, Tracey ; Gatziolis, Demetrios ; Healey, Sean ; Heath, Linda S.; Liknes, Greg C.; McRoberts, Ronald ; Moisen, Gretchen G.; Nelson, Mark ; Riemann, Rachel ; Schleeweis, Karen ; Schroeder, Todd A.; Westfall, James ; Wilson, B. Tyler.. 2020. Use of Remote Sensing Data to Improve the Efficiency of National Forest Inventories: A Case Study from the United States National Forest Inventory
- Riitters, Kurt ; Schleeweis, Karen ; Costanza, Jennifer. 2020. Forest Area Change in the Shifting Landscape Mosaic of the Continental United States from 2001 to 2016
- Zhao, Feng ; Huang, Chengquan ; Goward, Samuel N.; Schleeweis, Karen ; Rishmawi, Khaldoun ; Lindsey, Mary A.; Denning, Elaine ; Keddell, Louis ; Cohen, Warren B.; Yang, Zhiqiang ; Dungan, Jennifer L.; Michaelis, Andrew. 2018. Development of Landsat-based annual US forest disturbance history maps (1986-2010) in support of the North American Carbon Program (NACP)
- Schroeder, Todd A.; Moisen, Gretchen G.; Schleeweis, Karen; Toney, Chris; Cohen, Warren B.; Yang, Zhiqiang; Freeman, Elizabeth A.. 2015. Using an empirical and rule-based modeling approach to map cause of disturbance in U.S
- Schleeweis, Karen; Moisen, Gretchen G.; Schroeder, Todd A.; Toney, Chris; Freeman, Elizabeth A.. 2015. On the road to national mapping and attribution of the processes underlying U.S
- Schleeweis, Karen; Huang, Chengquan; Rishmawi, Khaldoun; Zhao, Feng Aron; Masek, Jeffery G.; Houghton, Richard K.; Goward, Samuel N.. 2015. Using FIA and landsat observations to improve the spatial and temporal resolution of forest carbon estimates
- Toney, J. Chris; Schleeweis, Karen G.; Dungan, Jennifer; Michaelis, Andrew; Schroeder, Todd; Moisen, Gretchen G.. 2015. Nationwide disturbance attribution on NASA’s earth exchange: experiences in a high-end computing environment
- Schroeder, T.; Moisen, G.; Schleeweis, K.. 2014. Testing alternative response designs for training forest disturbance and attribution models
- Moisen, Gretchen G.; Schroeder, Todd A.; Schleeweis, Karen; Toney, Chris; Cohen, Warren B.; Goward, Samuel N.. 2012. Attributing causal agents to nationwide maps of forest disturbance
- Schleeweis, Karen; Goward, Samuel N.; Huang, Chengquan; Masek, Jeffrey; Moisen, Gretchen G.. 2012. Understanding trends in observations of forest disturbance and their underlying causal processes
Tao, X.; Huang, C.; Zhao, F.; Schleeweis, K.; Masek, J.; Liang, S. Mapping forest disturbance intensity in North and South Carolina using annual Landsat observations and field inventory data. Remote Sensing of Environment 2019, 221, 351-362.
Zhao, F.; Huang, C.; Goward, S.N.; Schleeweis, K.; Rishmawi, K.; Lindsey, M.A.; Denning, E.; Keddell, L.; Cohen, W.B.; Yang, Z., et al. Development of Landsat-based annual US forest disturbance history maps (1986–2010) in support of the North American Carbon Program (NACP). Remote Sensing of Environment 2018, 209, 312-326, doi:https://doi.org/10.1016/j.rse.2018.02.035.
Huang, C.; Goward, S.N.; Schleeweis, K.; Thomas, N.; Masek, J.G.; Zhu, Z.L. Dynamics of national forests assessed using the Landsat record: Case studies in eastern United States. Remote Sensing of Environment 2009, 113, 1430-1442.
Thomas, N.E.; Huang, C.; Goward, S.N.; Powell, S.; Rishmawi, K.; Schleeweis, K.; Hinds, A. Validation of North American forest disturbance dynamics derived from Landsat time series stacks. Remote Sensing of Environment 2011, 115, 19-32, doi:10.1016/j.rse.2010.07.009.
Huang, C.; Schleeweis, K.; Thomas, N.; N, G.S. Forest dynamics within and around the Olympic National Park assessed using time series Landsat observations. In Remote Sensing of Protected Lands, Wang, Y., Ed. Taylor & Francis: London, 2011; pp. 75-94.
Masek, J.G.; Goward, S.N.; Kennedy, R.E.; Cohen, W.B.; Moisen, G.G.; Schleeweis, K.; Huang, C. United States Forest Disturbance Trends Observed Using Landsat Time Series. Ecosystems 2013, 1-18.
Huang, C.; Goward, S.N.; Masek, J.G.; Gao, F.; Vermote, E.F.; Thomas, N.; Schleeweis, K.; Kennedy, R.E.; Zhu, Z.; Eidenshink, J.C., et al. Development of time series stacks of Landsat images for reconstructing forest disturbance history. International Journal of Digital Earth 2009, 195-218.
Goward, S.N., C. Huang, F. Zhao, K. Schleeweis, K. Rishmawi, M. Lindsey, J.L. Dungan, and A. Michaelis. 2015. NACP NAFD Project: Forest Disturbance History from Landsat, 1986-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1290
- Hansen, C., Yonavjak, L. Clarke,C., Minnemeyer, S., Boisrobert, L., Leach, A., Schleeweis, K. (2010) Southern Forests for the Future. World Resources Institute: Washington D.C.