Implications of Alternative Field-Sampling Designs on Landsat-Based Mapping of Stand Age and Carbon Stocks in Oregon Forests

Empirical models relating forest attributes to remotely sensed metrics are widespread in the literature and underpin many of our efforts to map forest structure across complex landscapes. In this study we compared empirical models relating Landsat reflectance to forest age across Oregon using two alternate sets of ground data: one from a large (n 1500) systematic forest inventory and another from a smaller set of plots (n 50) deliberately selected to represent pure conditions along predefined structural gradients. Models built with the smaller set of targeted ground data resulted in lower plot-level mapping error (root mean square error) and higher apparent explanatory power (R 2 ) than those built with the larger, more widely distributed inventory data. However, in two of the three ecoregions considered, predictions derived from models built with the smaller ground data set displayed a bias relative to those built with the larger but noisier inventory data. A modeling exercise, wherein mapped forest age was translated into carbon, demonstrated how nonlinear ecological models can magnify these prediction biases over landscapes. From this study, it is clear that for mapping purposes, inventory data are superior to project-specific data sets if those data sets are not representative of the full region over which mapping is to be done. FOR .S CI. 56(4):405-416.

[1]  M. D. Nelson,et al.  Mapping U.S. forest biomass using nationwide forest inventory data and moderate resolution information , 2008 .

[2]  Warren B. Cohen,et al.  Modelling forest cover attributes as continuous variables in a regional context with Thematic Mapper data , 2001 .

[3]  M. Schlerf,et al.  Remote sensing of forest biophysical variables using HyMap imaging spectrometer data , 2005 .

[4]  Jerry F. Franklin,et al.  The Structure of Natural Young , Mature , and Old-Growth Douglas-Fir Forests in Oregon and Washington , 2010 .

[5]  Erkki Tomppo,et al.  Using coarse scale forest variables as ancillary information and weighting of variables in k-NN estimation: a genetic algorithm approach , 2004 .

[6]  W. Salas,et al.  Secondary Forest Age and Tropical Forest Biomass Estimation Using Thematic Mapper Imagery , 2000 .

[7]  W. Cohen,et al.  Estimating the age and structure of forests in a multi-ownership landscape of western Oregon, U.S.A. , 1995 .

[8]  R. Hall,et al.  Modeling forest stand structure attributes using Landsat ETM+ data: Application to mapping of aboveground biomass and stand volume , 2006 .

[9]  R. McRoberts,et al.  Remote sensing support for national forest inventories , 2007 .

[10]  J. Means.  Use of Large-Footprint Scanning Airborne Lidar To Estimate Forest Stand Characteristics in the Western Cascades of Oregon , 1999 .

[11]  Steven W. Running,et al.  Comparisons of land cover and LAI estimates derived from ETM+ and MODIS for four sites in North America: a quality assessment of 2000/2001 provisional MODIS products , 2003 .

[12]  Limin Yang,et al.  COMPLETION OF THE 1990S NATIONAL LAND COVER DATA SET FOR THE CONTERMINOUS UNITED STATES FROM LANDSAT THEMATIC MAPPER DATA AND ANCILLARY DATA SOURCES , 2001 .

[13]  C. T. Dyrness,et al.  Natural Vegetation of Oregon and Washington , 1988 .

[14]  W. Cohen,et al.  Lidar Remote Sensing of the Canopy Structure and Biophysical Properties of Douglas-Fir Western Hemlock Forests , 1999 .

[15]  Maosheng Zhao,et al.  A Continuous Satellite-Derived Measure of Global Terrestrial Primary Production , 2004 .

[16]  S. Running,et al.  Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data , 2002 .

[17]  D. Turner,et al.  Integrating Remote Sensing and Ecosystem Process Models for Landscape- to Regional-Scale Analysis of the Carbon Cycle , 2004 .

[18]  E. Tomppo,et al.  Satellite image-based national forest inventory of finland for publication in the igarss'91 digest , 1991, [Proceedings] IGARSS'91 Remote Sensing: Global Monitoring for Earth Management.

[19]  W. Cohen,et al.  An improved strategy for regression of biophysical variables and Landsat ETM+ data. , 2003 .

[20]  E. Crist.  A TM Tasseled Cap equivalent transformation for reflectance factor data , 1985 .

[21]  W. Cohen,et al.  Estimating structural attributes of Douglas-fir/western hemlock forest stands from Landsat and SPOT imagery , 1992 .

[22]  David O. Wallin,et al.  Two Decades of Carbon Flux from Forests of the Pacific Northwest , 1996 .

[23]  Brent N. Holben,et al.  Extracting forest age in a Pacific Northwest Forest from thematic mapper and topographic data , 1996 .

[24]  W. Cohen,et al.  Lidar remote sensing of above‐ground biomass in three biomes , 2002 .

[25]  S. VAN TUY,et al.  Disturbance and climate effects on carbon stocks and fluxes across Western Oregon USA , 2004 .

[26]  Albert R. Stage,et al.  Most Similar Neighbor: An Improved Sampling Inference Procedure for Natural Resource Planning , 1995, Forest Science.

[27]  Michael A. Lefsky,et al.  Combining lidar estimates of aboveground biomass and Landsat estimates of stand age for spatially extensive validation of modeled forest productivity , 2005 .

[28]  Warren B. Cohen,et al.  Scaling net ecosystem production and net biome production over a heterogeneous region in the Western United States , 2007 .

[29]  W. Cohen,et al.  Modelling forest cover attributes as continuous variables in a regional context with Thematic Mapper data , 2001 .

[30]  Michael C. Wimberly,et al.  Mapping wildland fuels and forest structure for land management: a comparison of nearest neighbor imputation and other methods , 2009 .

[31]  Dai Limin,et al.  Estimation of forest volumes by integrating Landsat TM imagery and forest inventory data , 2006 .

[32]  S. Running,et al.  8 – Generalization of a Forest Ecosystem Process Model for Other Biomes, BIOME-BGC, and an Application for Global-Scale Models , 1993 .

[33]  Janet L. Ohmann,et al.  Predictive mapping of forest composition and structure with direct gradient analysis and nearest- neighbor imputation in coastal Oregon, U.S.A. , 2002 .

[34]  W. Cohen,et al.  CARBON FLUXES ACROSS REGIONS: OBSERVATIONAL CONSTRAINTS AT MULTIPLE SCALES , 2006 .

[35]  W. Cohen,et al.  North American forest disturbance mapped from a decadal Landsat record , 2008 .

[36]  B. Law,et al.  Carbon dynamics of Oregon and Northern California forests and potential land-based carbon storage. , 2009, Ecological applications : a publication of the Ecological Society of America.

[37]  Gretchen G. Moisen,et al.  Comparing five modelling techniques for predicting forest characteristics , 2002 .

[38]  Dirk Pflugmacher,et al.  Regional Applicability of Forest Height and Aboveground Biomass Models for the Geoscience Laser Altimeter System , 2008, Forest Science.

[39]  Michael A. Wulder,et al.  Estimating Time Since Forest Harvest Using Segmented Landsat ETM+ Imagery , 2004 .

[40]  William A. Bechtold,et al.  The enhanced forest inventory and analysis program - national sampling design and estimation procedures , 2005 .

[41]  Michael J. Oimoen,et al.  The National Elevation Dataset , 2002 .

[42]  Russell G. Congalton,et al.  Assessing the accuracy of remotely sensed data : principles and practices , 1998 .

[43]  J. Wickham,et al.  Completion of the 2001 National Land Cover Database for the conterminous United States , 2007 .

[44]  J. Randerson,et al.  Terrestrial ecosystem production: A process model based on global satellite and surface data , 1993 .

[45]  Rick L. Lawrence,et al.  Land use and land cover change in the greater yellowstone ecosystem: 1975-1995 , 2003 .

[46]  Warren B. Cohen,et al.  Patterns of forest regrowth following clearcutting in western Oregon as determined from a Landsat time-series , 2007 .

[47]  David P. Turner,et al.  A Carbon Budget for Forests of the Conterminous United States , 1995 .

[48]  A. I. Gitelman,et al.  Variability in net primary production and carbon storage in biomass across Oregon forests—an assessment integrating data from forest inventories, intensive sites, and remote sensing , 2005 .

[49]  J. Omernik.  Ecoregions of the Conterminous United States , 1987 .

[50]  B. E. L Aw,et al.  Disturbance and climate effects on carbon stocks and fluxes across Western Oregon USA , 2004 .