Abstract:
Crop biomass and residue production are major components of cropland carbon
dynamics that can be estimated using yield data from ground-based surveys. In the
USA, surveyed yield data are available at county level and have been widely used
for various research, economic and policy purposes, in addition to biomass estimation.
However, survey data may be unavailable for certain times and/or locations
and thus biomass estimates using remotely sensed data might be used to fill in
any missing biomass data for estimating residue production and carbon dynamics
in croplands. Compared to ground-based surveys, remotely sensed data are collected
on a regular schedule and may also provide more spatially resolved data. We
analysed composite biweekly Normalized Difference Vegetation Index (NDVI)
data obtained using the Advanced Very High Resolution Radiometer (AVHRR)
sensor and crop aboveground biomass (AGBM) estimated from available countylevel
yield data reported by the National Agricultural Statistics Service (NASS) for
three crops (corn, soybean and oats) during 1992, 1997 and 2002. The aim of the
study was to explore the relationships between NDVI and crop biomass to complete
the missing biomass data in counties where no NASS-reported yields are
available for biomass estimation.
AGBM was estimated from Pathfinder biweekly NDVI, using canonical correlation
analysis (CCA) and best subset multiple regressions incorporating canonical
variates fromNDVI time series. Cross-validation ofmodel estimates was performed
by randomly splitting the dataset into training and application subsets, simulating a
10–40% range of missing values. NDVI and crop biomass in Iowa during a given
year were well correlated, with coefficient of determination (R2) values . 0.8 in
most cases. Using the available (training) data from a single year or a combination
of years to derive models for filling the missing (validation) data within the same
time period yielded a mean estimated biomass with , 1% relative error and bias.
However, models applied to out-of-sample years had lower (,0.4) R2 values for the
relationships between biomass and NDVI, although the mean residuals were low.
