Fig. 2a is the 3-year (2010–2012) averaged switchgrass biomass
productivity estimation map for the GP. The estimated switchgrass
biomass productivity increases from the southwestern GP to the
northeastern GP, primarily due to the high temperatures with low
precipitation in the southwestern GP. Although the switchgrass
pixels used for developing the switchgrass productivity model
represent a broad range of the environmental and climate
conditions of the GP (from Texas to South Dakota and Colorado
to Missouri), the relatively small sample size (176 pixels) still may not represent the entire environmental and climate conditions of
the GP. Therefore, we applied the approach used by Gu et al., 2012a
to develop a switchgrass productivity uncertainty map for the GP
(Fig. 2b) based on the 0% and 50% extrapolation maps (Gu et al.,
2012b). As a result of the relatively few (or no) samples collected
from the west-central edge of the GP (Colorado and New Mexico)
and the northeastern part of the GP (North Dakota and Minnesota)
(Fig. 1), the high uncertainty areas are mainly located in these
regions (red color in Fig. 2b). In order to make the estimated
switchgrass productivity map more reliable, we masked out all the
areas of uncertainty from the productivity map and generated a
final switchgrass biomass productivity estimation map for the GP
(Fig. 2c). Highly productive switchgrass areas are mainly located in
the eastern part of the GP. The derived switchgrass biomass
productivity estimation map provides preliminary information to
land managers and biofuel plant investors to identify areas where
suitable switchgrass development could occur in the GP.
Fig. 2a is the 3-year (2010–2012) averaged switchgrass biomassproductivity estimation map for the GP. The estimated switchgrassbiomass productivity increases from the southwestern GP to thenortheastern GP, primarily due to the high temperatures with lowprecipitation in the southwestern GP. Although the switchgrasspixels used for developing the switchgrass productivity modelrepresent a broad range of the environmental and climateconditions of the GP (from Texas to South Dakota and Coloradoto Missouri), the relatively small sample size (176 pixels) still may not represent the entire environmental and climate conditions ofthe GP. Therefore, we applied the approach used by Gu et al., 2012ato develop a switchgrass productivity uncertainty map for the GP(Fig. 2b) based on the 0% and 50% extrapolation maps (Gu et al.,2012b). As a result of the relatively few (or no) samples collectedfrom the west-central edge of the GP (Colorado and New Mexico)and the northeastern part of the GP (North Dakota and Minnesota)(Fig. 1), the high uncertainty areas are mainly located in theseregions (red color in Fig. 2b). In order to make the estimatedswitchgrass productivity map more reliable, we masked out all theareas of uncertainty from the productivity map and generated afinal switchgrass biomass productivity estimation map for the GP(Fig. 2c). Highly productive switchgrass areas are mainly located inthe eastern part of the GP. The derived switchgrass biomassproductivity estimation map provides preliminary information toland managers and biofuel plant investors to identify areas wheresuitable switchgrass development could occur in the GP.
การแปล กรุณารอสักครู่..