Precise Yield Estimation through Improvised CASA Model by Development of Soil and Atmospheric Constants (Sᵮ) and (Aþ)
Precise Yield Estimation through Improvised CASA Model by Development of Soil and Atmospheric Constants (Sᵮ) and (Aþ)
Rao Mansor Ali Khan* and Syed Amer Mahmood
Figure 1:
(a) Map of Punjab, Pakistan; (b) Investigation site (c) Spatial extent of the study area.
Figure 2:
Flowchart of methodology.
Figure 3:
Variations recorded in LAI on various dates with a temporal resolution of five days throughout the WGP.
Figure 5:
Variations in (n/N) throughout the WGP.
Figure 6:
Variations in Go for the complete WGP.
Figure 7:
Variation in λE and H throughout WGP.
Figure 8: Variation in W throughout the WGP.
Figure 9: Variations in LUE throughout the WGP.
Figure 10:
Variations in ‘f’ throughout the WGP.
Figure 11:
Variation in biomass throughout the WGP.
Figure 12:
Spatio temporal variations in PAR (Wm−2), NDVI, APAR (Wm−2) and biomass generation (g/m2).
Figure 13: Variation in BC values throughout WGP.
Figure 14: Variation in CO values throughout WGP.
Figure 15: Variation in NO2 values of different atmospheric pollutants.
Figure 16: Variation in O3 values throughout WGP.
Figure 18:
(A) Wheat yields spatial distribution; (B) Wheat cultivation mask; (C) Integration of yield distribution with wheat cultivation mask.
Equation 1-5
Equation 12-16
Equation 5-11
Equation 17-19
Figure 4:
Variations in extraterrestrial radiation (Ra); clear sky radiation (Rso); actual incoming radiation (Rs); net radiation (Rn); net longwave radiation (Rnl) and net shortwave radiation (Rns) throughout the WGP.
Figure 17:
Variation in SO2 values throughout WGP.
November 2022
Vol.38, Iss. 5, Pages 1-396
