11 Campus Blvd. Ste. 200
Contact Kristofer Johnson
1. Validating a LIDAR-based Carbon Monitoring System with FIA data. High resolution biomass maps can help identify areas that have the potential to store, or lose, terrestrial carbon. This project focuses on comparing biomass maps with FIA data for the whole state of Maryland, and methods for integrating these two resources. Funded by NASA and in collaboration with the University of Maryland.
2. Comparing mapped soil carbon estimates to process-based outputs in Alaska. Alaska is relatively data-rich in terms of soil carbon observations compared to other areas in the boreal and arctic zones, yet it is still data-poor compared to other temperate and tropical areas in the world. The question remains of how soil carbon uncertainty may influence model results, especially those concerned with predicting the response of northern regions to climate change. Funded by USGS and in collaboration with the University of Alaska Fairbanks.
3. Assessing the effects of soil map quality on carbon modeling results and scaling in Mexico. The quality of soil maps used in process-based ecosystem models is not the same for all countries and may significantly impact model results. In this study, we are simulating GPP at several 9 km2 areas in Mexico and comparing the results using soil maps of different quality and resolution. Funded by NASA and in collaboration with the University of Delaware.
Other activities. Our research unit also helps coordinate training workshops where forest carbon measurement methods are presented, mostly in Mexico but also in other latin american countries.
- University of Pennsylvania, Earth Science , 2008
- Brigham Young University, Agronomy , 2004
- Brigham Young University, Agronomy , 2002
- American Geophysical Union
- Geological Society of America
- American Society of Agronomy
Featured Publications & Products
- Johnson, K.; Scatena, F. N.; Pan, Y. 2010. Short- And Long-Term Responses Of Total Soil Organic Carbon To Harvesting In A Northern Hardwood Forest.
- Johnson, K.D.; Scatena, F.N.; Johnson, A.H.; Pan, Y. 2009. Controls On Soil Organic Matter Content Within A Northern Hardwood Forest.
- Johnson, Kristofer D.; Birdsey, Richard; O Finley, Andrew; Swantaran, Anu; Dubayah, Ralph; Wayson, Craig; Riemann, Rachel. 2014. Integrating Forest Inventory And Analysis Data Into A Lidar-Based Carbon Monitoring System.
- Dai, Zhaohua; Birdsey, Richard A.; Johnson, Kristofer D.; Dupuy, Juan Manuel; Hernandez-Stefanoni, Jose Luis; Richardson, Karen. 2014. Modeling Carbon Stocks In A Secondary Tropical Dry Forest In The Yucatan Peninsula, Mexico.
- Birdsey, Richard; Angeles-Perez, Gregorio; Kurz, Werner A; Lister, Andrew; Olguin, Marcela; Pan, Yude; Wayson, Craig; Wilson, Barry; Johnson, Kristofer. 2013. Approaches To Monitoring Changes In Carbon Stocks For Redd+.
- Cole, Jason A.; Johnson, Kristopher D.; Birdsey, Richard A.; Pan, Yude; Wayson, Craig A.; McCullough, Kevin; Hoover, Coeli M.; Hollinger, David Y.; Bradford, John B.; Ryan, Michael G.; Kolka, Randall K.; Wieshampel, Peter; Clark, Kenneth L.; Skowronski, Nicholas S.; Hom, John; Ollinger, Scott V.; McNulty, Steven G.; Gavazzi, Michael J. 2013. Database For Landscape-Scale Carbon Monitoring Sites.
- Johnson, Kristofer D.; Harden, Jennifer W.; McGuire, A. David; Clark, Mark; Yuan, Fengming; Finley, Andrew O. 2013. Permafrost And Organic Layer Interactions Over A Climate Gradient In A Discontinuous Permafrost Zone.
- Johnson, Kristofer D.; Scatena, F.N.; Silver, Whendee L. 2011. Atypical Soil Carbon Distribution Across A Tropical Steepland Forest Catena.
- Johnson, Kristofer D.; Harden, Jennifer; McGuire, A. David; Bliss, Norman B.; Bockheim, James G.; Clark, Mark; Nettleton-Hollingsworth, Teresa; Jorgenson, M. Torre; Kane, Evan S.; Mack, Michelle; ODonnell, Johathan; Ping, Chien-Lu; Schuur, Edward A.G.; Turetsky, Merritt R.; Valentine, David W. 2011. Soil Carbon Distribution In Alaska In Relation To Soil-Forming Factors.
|How to Build a Better Map of Tree Biomass|
A logical way to validate biomass maps derived from remotely sensed data is to validate them with independent ground inventory estimates, but in ...