The Heureka Research Programme - Mistra

the mean and variance of total stand volume estimates correspond closely tothe mean and variance obtained by the NFI after the calibration, althoughthe original kNN estimates had considerably less variance (Gilichinsky etal. 2009). It has also been found that the accuracy for total stand volumeincreased after the matching as compared to the accuracy of the originalkNN estimates.The possibility to improve the accuracy of kNN estimates of forest parametersby using TWI, mapped clear cuttings, and other types of ancillary datain combination with satellite data in the estimation was tested. The resultsshow that the estimation accuracy for variables such as stand volume wasslightly improved when adding information on cuttings and tree species inthe kNN estimation, as compared to only using satellite data. However, theestimation accuracy was not improved by including TWI.Fulfillment of objectivesThe research and development regarding the kNN method, including calibrationof the estimates, and the use of post-stratification based on remotelysensed data has been successful. However, the development of the methodshas taken much longer than initially anticipated. It was also intended that asegmentation algorithm should be developed and implemented. Unfortunately,it was not possible to finalize this part within the Heureka program.The implementation of a segmentation algorithm will therefore be finalizedwithin SLU’s environmental monitoring and assessment program.ReferencesScientific articlesSeibert, J. Stendahl, J. & Sörensen R. 2007. Topographical influence on soil properties inboreal forest soils. Geoderma 141; 139–148.Tomppo, E., Olsson, H., Ståhl, G., Nilsson, M., & Katila, M. 2007. Creation of forest databases by combining National Forest Inventory Field Plots and Remote Sensing Data.Remote Sens. of Environ. 112:1982-1999.Gilichinsky, M., Heiskanen, J., Wallerman, J., Egberth, M., & Nilsson, M. 2009. Histogrammatching for post-processing of stem volume estimates imputed from forest inventoryand satellite data. Submitted to Remote Sensing of Environment.Lyon, S.W. Sörensen, R. Stendahl, & J. Seibert, J. 2009. Using landscape characteristics todefine an adjusted distance metric for improving kriging interpolations. Manuscript inpress.Nilsson, M., Holm, S., Wallerman, J., Reese, H. & Olsson, H. 2009. Estimating annualcuttings using multi-temporal satellite data and field data from the Swedish NFI. InternationalJournal of Remote Sensing, 30: 5109–5116.Reese, H., Nilsson, M., & Olsson, H. 2009. Comparison of Resourcesat-1 AWiFS andSPOT-5 data over managed boreal forests. International Journal of Remote Sensing, 30:4957–4978.70