Model-based inference for biomass estimation in a LiDAR sample survey in Hedmark County, Norway

In forest inventories, regression models are often applied to predict quantities such as biomass at the level of sampling units. In this paper, we propose a model-based inference framework for combining sampling and model errors in the variance estimation. It was applied to airborne laser (LiDAR) data sets from Hedmark County, Norway, where the model error proportion of the total variance was found to be large for both scanning (airborne laser scanning) and profiling LiDAR when biomass was estimated. With profiling LiDAR, the model error variance component for the entire county was as large as 71% whereas for airborne laser scanning, it was 43% of the total variance. Partly, this reflects the better accuracy of the pixel-based regression models estimated from scanner data as compared with the models estimated from profiler data. The framework proposed in our study can be applied in all types of sample surveys where model-based predictions are made at the level of individual sampling units. Especially, it should be useful in cases where model-assisted inference cannot be applied due to the lack of a probability sample from the target population or due to problems of correctly matching observations of auxiliary and target variables.

[1]  K. Steinmann,et al.  Small area estimations of proportion of forest and timber volume combining Lidar data and stereo aerial images with terrestrial data , 2013 .

[2]  Sassan Saatchi,et al.  A sample design for globally consistent biomass estimation using lidar data from the Geoscience Laser Altimeter System (GLAS) , 2012, Carbon Balance and Management.

[3]  P. Beets,et al.  The national inventory of carbon stock in New Zealand's pre-1990 planted forest using a LiDAR incomplete-transect approach , 2012 .

[4]  Terje Gobakken,et al.  Lidar sampling — Using an airborne profiler to estimate forest biomass in Hedmark County, Norway , 2012 .

[5]  Göran Ståhl,et al.  Estimating biomass in Hedmark County, Norway using national forest inventory field plots and airborne laser scanning , 2012 .

[6]  Göran Ståhl,et al.  Assessing the accuracy of regional LiDAR-based biomass estimation using a simulation approach , 2012 .

[7]  David Saah,et al.  Integration of airborne lidar and vegetation types derived from aerial photography for mapping aboveground live biomass , 2012 .

[8]  Joanne C. White,et al.  Lidar sampling for large-area forest characterization: A review , 2012 .

[9]  E. Næsset,et al.  Subalpine zone delineation using LiDAR and Landsat imagery , 2012 .

[10]  T. Nord-Larsen,et al.  Estimation of forest resources from a country wide laser scanning survey and national forest inventory data , 2012 .

[11]  Mark O. Kimberley,et al.  Airborne scanning LiDAR in a double sampling forest carbon inventory , 2012 .

[12]  Jordan Golinkoff,et al.  The use of airborne laser scanning to develop a pixel-based stratification for a verified carbon offset project , 2011, Carbon balance and management.

[13]  Ronald E. McRoberts,et al.  Probability- and model-based approaches to inference for proportion forest using satellite imagery as ancillary data , 2010 .

[14]  E. Næsset,et al.  Assessing effects of positioning errors and sample plot size on biophysical stand properties derived from airborne laser scanner data. , 2009 .

[15]  R. Nelson,et al.  Regional aboveground forest biomass using airborne and spaceborne LiDAR in Québec. , 2008 .

[16]  R. Nelson,et al.  Regression Estimation Following the Square-Root Transformation of the Response , 2008, Forest Science.

[17]  E. Næsset,et al.  Estimation of above- and below-ground biomass across regions of the boreal forest zone using airborne laser , 2008 .

[18]  Göran Ståhl,et al.  Regional Forest Inventory using an Airborne Profiling LiDAR( Silvilaser) , 2008 .

[19]  E. Næsset.  Airborne laser scanning as a method in operational forest inventory: Status of accuracy assessments accomplished in Scandinavia , 2007 .

[20]  E. Næsset.  Accuracy of forest inventory using airborne laser scanning: evaluating the first nordic full-scale operational project , 2004 .

[21]  Ross Nelson,et al.  Measuring biomass and carbon in delaware using an airborne profiling LIDAR , 2004 .

[22]  T. Gregoire,et al.  Sampling Strategies for Natural Resources and the Environment , 2004 .

[23]  E. Næsset.  Practical large-scale forest stand inventory using a small-footprint airborne scanning laser , 2004 .

[24]  Robert C. Parker,et al.  An Application of LiDAR in a Double-Sample Forest Inventory , 2004 .

[25]  J. Holmgren.  Prediction of tree height, basal area and stem volume in forest stands using airborne laser scanning , 2004 .

[26]  R. Nelson,et al.  A Multiple Resource Inventory of Delaware Using Airborne Laser Data , 2003 .

[27]  Ross Nelson,et al.  A Portable Airborne Laser System for Forest Inventory , 2003 .

[28]  Alan B. Anderson,et al.  Effect and uncertainty of digital elevation model spatial resolutions on predicting the topographical factor for soil loss estimation , 2002 .

[29]  E. Næsset.  Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data , 2002 .

[30]  E. Næsset,et al.  Estimating tree heights and number of stems in young forest stands using airborne laser scanner data , 2001 .

[31]  T. Gregoire.  Design-based and model-based inference in survey sampling: appreciating the difference , 1998 .

[32]  E. Næsset.  Estimating timber volume of forest stands using airborne laser scanner data , 1997 .

[33]  Carl-Erik Särndal,et al.  Model Assisted Survey Sampling , 1997 .

[34]  George Z. Gertner,et al.  An assessment of some nonsampling errors in a national survey using an error budget , 1992 .

[35]  Ross Nelson,et al.  Estimating forest biomass and volume using airborne laser data , 1988 .

[36]  Kirk M. Wolter,et al.  An Investigation of Some Estimators of Variance for Systematic Sampling , 1984 .

[37]  R. Royall.  On finite population sampling theory under certain linear regression models , 1970 .

[38]  Göran Ståhl,et al.  Model-assisted estimation of biomass in a LiDAR sample survey in Hedmark County, NorwayThis article is one of a selection of papers from Extending Forest Inventory and Monitoring over Space and Time. , 2011 .

[39]  Hans-Erik Andersen,et al.  STATISTICAL PROPERTIES OF MEAN STAND BIOMASS ESTIMATORS IN A LIDAR- BASED DOUBLE SAMPLING FOREST SURVEY DESIGN , 2007 .

[40]  F. Wagner,et al.  Good Practice Guidance for Land Use, Land-Use Change and Forestry , 2003 .

[41]  E. Næsset.  Effects of Differential Single- and Dual-Frequency GPS and GLONASS Observations on Point Accuracy under Forest Canopies , 2001 .

[42]  J. Means,et al.  Predicting forest stand characteristics with airborne scanning lidar , 2000 .

[43]  L. Marklund,et al.  Biomass functions for pine, spruce and birch in Sweden , 1988 .

[44]  R. Royall,et al.  Robust Estimation in Finite Populations I , 1973 .