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Measurement and Scaling of Carbon Dioxide (CO2) Exchanges in Wheat Using Flux-Tower and Remote Sensing
Authors:N. R. Patel  V. K. Dadhwal  S. K. Saha
Affiliation:(1) Agriculture & Soils Division, Indian Institute of Remote Sensing, National Remote Sensing Centre, ISRO, Dehradun, 248001, India;(2) National Remote Sensing Centre, ISRO, Hyderabad, 500 625, India;(3) Agriculture & Soils Division, Indian Institute of Remote Sensing, National Remote Sensing Centre, ISRO, Dehradun, 248001, India;(4) Indian Institute of Remote Sensing, National remote Sensing Centre, ISRO, Dehradun, 248001, India
Abstract:The present study investigates the characteristics of CO2 exchange (photosynthesis and respiration) over agricultural site dominated by wheat crop and their relationship with ecosystem parameters derived from MODIS. Eddy covariance measurement of CO2 and H2O exchanges was carried out at 10 Hz interval and fluxes of CO2 were computed at half-hourly time steps. The net ecosystem exchange (NEE) was partitioned into gross primary productivity (GPP) and ecosystem respiration (R e) by taking difference between day-time NEE and respiration. Time-series of daily reflectance and surface temperature products at varying resolution (250–1000 m) were used to derive ecosystem variables (EVI, NDVI, LST). Diurnal pattern in Net ecosystem exchange reveals negative NEE during day-time representing CO2 uptake and positive during night as release of CO2. The amplitude of the diurnal variation in NEE increased as LAI crop growth advances and reached its peak around the anthesis stage. The mid-day uptake during this stage was around 1.15 mg CO2 m−2 s−1 and night-time release was around 0.15 mg CO2 m−2 s−1. Linear and non-linear least square regression procedures were employed to develop phenomenological models and empirical fits between flux tower based GPP and NEE with satellite derived variables and environmental parameters. Enhanced vegetation index was found significantly related to both GPP and NEE. However, NDVI showed little less significant relationship with both GPP and NEE. Furthemore, temperature-greenness (TG) model combining scaled EVI and LST was parameterized to estimate daily GPP over dominantly wheat crop site. (R 2 = 0.77). Multi-variate analysis shows that inclusion of LST or air temperature with EVI marginally improves variance explained in daily NEE and GPP.
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