Integrating LIDAR and forest inventories to fill the trees outside forests data gap
Forest inventories are commonly used to estimate total tree biomass of forest land even though they are not traditionally designed to measure biomass of trees outside forests (TOF). The consequence may be an inaccurate representation of all of the aboveground biomass, which propagates error to the outputs of spatial and process models that rely on the inventory data. An ideal approach to fill this data gap would be to integrate TOF measurements within a traditional forest inventory for a parsimonious estimate of total tree biomass. In this study, Light Detection and Ranging (LIDAR) data were used to predict biomass of TOF in all “nonforest” Forest Inventory and Analysis (FIA) plots in the state of Maryland. To validate the LIDAR-based biomass predictions, a field crew was sent to measure TOF on nonforest plots in three Maryland counties, revealing close agreement at both the plot and county scales between the two estimates. Total tree biomass in Maryland increased by 25.5 Tg, or 15.6 %, when biomass of TOF were included. In two counties (Carroll and Howard), there was a 47 % increase. In contrast, counties located further away from the interstate highway corridor showed only a modest increase in biomass when TOF were added because nonforest conditions were less common in those areas. The advantage of this approach for estimating biomass of TOF is that it is compatible with, and explicitly separates TOF biomass from, forest biomass already measured by FIA crews. By predicting biomass of TOF at actual FIA plots, this approach is directly compatible with traditionally reported FIA forest biomass, providing a framework for other states to follow, and should improve carbon reporting and modeling activities in Maryland.
KeywordsTrees outside forest Carbon management Nonforest biomass LIDAR Forest inventory
- Bechtold, W. A., & Patterson, P. L. (2005). The Enhanced Forest Inventory and Analysis Program—National Sampling Design and Estimation Procedures (p. 85). Ashville, NC: Southern Research Station, US Department of Agriculture Forest Service.Google Scholar
- Cumming, A., Twardus, D., & Nowak, D. (2008). Urban forest health monitoring: large-scale assessments in the United States. Arboriculture and Urban Forestry, 34, 341–346.Google Scholar
- De Foresta, H., Somarriba, E., Temu, A., Boulanger, D., Feuilly, H., & Gauthier, M. (2013). Towards the assessment of trees outside forests. FAO Resources Assessment Working Paper no. 183. Rome.Google Scholar
- Heath, L., Hansen, M., Smith, J., Miles, P., & Smith, W. (2008). Investigation into calculating tree biomass and carbon in the FIADB using a biomass expansion factor approach. In W. McWilliams, G. Moisen, & R. Czaplewski (Eds.), Proceedings of the FIA [Forest Inventory and Analysis] Symposium 2008. Park City, Utah ((Eds.) ed., ). Fort Collins, Colorado, USA: USDA Forest Service, Rocky Mountain Research Station.Google Scholar
- Huang, W., Satantran, A., Johnson, K., Duncanson, L., Tang, H., O’Neil Dunne, J., Hurtt, G., & Dubayah, R. (2015). Local discrepancies in continental scale biomass maps: a case study over forested and non-forested landscapes in Maryland, USA. Carbon Balance and Management, 10(19), 1–16. doi:10.1186/s13021-015-0030-9.CrossRefGoogle Scholar
- Jenkins, J., & Riemann, R. (2003). What does nonforest land contribute to the global C balance? In R. McRoberts, G. A. Reams, P. C. Van Dousen, & J. W. Mosor (Eds.), Proceedings of the third annual Forest Inventory and Analysis Symposium (p. p. 173). North Central Station: U.S. Department of Agriculture, Forest Service.Google Scholar
- Miles, P. (2014). Forest Inventory EVALIDator web-application version 1.6.0.01. St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station. [Available only on internet: http://apps.fs.fed.us/Evalidator/tmattribute.jsp].
- O’Neil-Dunne, J. P. M., MacFaden, S., Royar, A., Reis, M., Dubayah, R., & Swatantran, A. (2014). An object-based approach to statewide land cover mapping. In Proceedings of the 2014. Louisville, KY: ASPRS Annual Conference.Google Scholar
- Riemann, R. (2003). Pilot inventory of FIA plots traditionally called “Nonforest.” US Department of Agriculture, Forest Service, Northeastern Research Station.Google Scholar
- Zhang, F., Chen, J. M., Pan, Y., Birdsey, R. A., Shen, S., Ju, W., & He, L. (2012). Attributing carbon changes in conterminous U.S. forests to disturbance and non-disturbance factors from 1901 to 2010. Journal of Geophysical Research: Biogeosciences, 117(G2), n/a–n/a. doi:10.1029/2011JG001930Google Scholar