In this study, a cross-calibration approach was applied to combine RADARSAT-2 and RapidEye sensors for biomass monitoring over corn fields. First, RapidEye and RADARSAT-2 sensors were compared in terms of biomass estimation. Then the estimated biomass from RADARSAT-2 was cross-calibrated with respect to the biomass estimated from RapidEye. Combination of the optical and cross-calibrated Synthetic Aperture Radar (SAR) derived biomass was proposed to have higher temporal resolution biomass maps. Vegetation indices including normalized difference vegetation index (NDVI), red-edge triangular vegetation index (RTVI), simple ratio (SR) and red-edge simple ratio (SRre) were used for modeling of biomass estimation from RapidEye. Water Cloud Model (WCM) was also used for biomass estimation from RADARSAT-2. Data collected during SMAP Validation Experiment 2012 (SMAPVEX12) field campaign was used for validation. The results demonstrate that the accuracies of biomass estimations from RapidEye and RADARSAT-2 are close. For RapidEye, the highest accuracies derived from RTVI index with correlation coefficient (R) of 0.92 and Root Mean Square of (RMSE) of 118.18 gr/m 2 . The R values derived from RADARSAT-2 is 0.83 and its RMSE is 171.93 gr/m 2 . After cross-calibration of the biomass derived from RADARSAT-2 versus those derived from RapidEye, the RMSE of estimates dropped by 18.86 gr/m 2 .

, , ,
38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
Department of Geography and Environmental Studies

Hosseini, M. (Mehdi), McNairn, H. (Heather), Mitchell, S, Davidson, A. (Andrew), & Robertson, L.D. (Laura DIngle). (2018). Combination of optical and SAR sensors for monitoring biomass over corn fields. In International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 5952–5955). doi:10.1109/IGARSS.2018.8518998