Record Details

Scale considerations for integrating forest inventory plot data and satellite image data for regional forest mapping

ScholarsArchive at Oregon State University

Field Value
Title Scale considerations for integrating forest inventory plot data and satellite image data for regional forest mapping
Names Ohmann, Janet L. (creator)
Gregory, Matthew J. (creator)
Roberts, Heather M. (creator)
Date Issued 2014-08 (iso8601)
Note To the best of our knowledge, one or more authors of this paper were federal employees when contributing to this work. This is the publisher’s final pdf. The published article is copyrighted by Elsevier and can be found at: http://www.journals.elsevier.com/remote-sensing-of-environment. Supplementary Data can be found at: http://www.sciencedirect.com/science/article/pii/S003442571300343X
Abstract The integration of satellite image data with forest inventory plot data is a popular approach for mapping forest
vegetation over large regions. Several methodological choices regarding spatial scale, mostly related to spatial
resolution or grain, can profoundly influence forest maps developed from plot and imagery data. Yet often the
consequences of scaling choices are not explicitly addressed. Our objective was to quantify the effects of several
scale-related methods on map accuracy for multiple forest attributes, using a variety of diagnostics that address
different map characteristics, to help guide map developers and users. We conducted nearest-neighbor imputation
over a large region in the Pacific Northwest, USA, to investigate effects of imputation grain (single pixel or
kernel); inclusion of heterogeneous plots; accuracy assessment grain and extent; and value of k (k = 1 and
k = 5), where k is the number of nearest-neighbor plots. Spatial predictors were from rasters describing climate
and topography and a time-series of Landsat imagery. Reference data were from regional forest inventory plots
measured over two decades. All analyses were conducted at a spatial resolution of 30 m × 30 m. Effects of imputation
grain and heterogeneous plots on map accuracy were small. Excluding heterogeneous plots slightly improved
map accuracy and did not lessen the systematic agreement (AC[subscript SYS]) between our maps and observed
plot data. Accuracy assessment grain strongly influenced map accuracy: maps assessed with a multi-pixel
block were much more accurate than when assessed with a single pixel for almost all map diagnostics, but this
was an artifact of methods rather than reflecting real differences among maps. Unsystematic agreement
(AC[subscript UNS]) between our maps and plots, or random error, improved notably with increasing accuracy assessment
extent for all scaling methods, indicating that reliability of most map applications can be improved through coarsening
the map grain. Value of k strongly influenced map diagnostics. The k = 5 maps were better than k = 1
maps for local-scale accuracy, but at the cost of reduced AC[subscript SYS], and loss of variability and poor areal representation
of forest conditions over the study region. The k = 1 maps produced notably better predictions of the least
abundant forest conditions (early-successional, late-successional, and broadleaf). None of the scaling methods
were optimal for all map diagnostics. Nevertheless, given a variety of diagnostics associated with a range of
scaling options, map developers and map users can make informed choices about methods and resulting maps
that best meet their particular objectives, and we present some general guidelines in this regard. Most of our
findings are applicable to mapping with Landsat data in other forested regions with similar forest inventory
data, and to other methods for spatial prediction.
Genre Article
Topic Vegetation mapping
Identifier Ohmann, J. L., Gregory, M. J., & Roberts, H. M. (2014). Scale considerations for integrating forest inventory plot data and satellite image data for regional forest mapping. Remote Sensing of Environment, 151, 3-15. doi:10.1016/j.rse.2013.08.048

© Western Waters Digital Library - GWLA member projects - Designed by the J. Willard Marriott Library - Hosted by Oregon State University Libraries and Press