Accurate and reliable assessment of pasture or forage biomass remains one of the key challenges for grazing industries. Livestock managers require accurate estimates of the grassland biomass available over their farm to enable optimal stocking rate decisions. This paper reports on our investigations into the potential application of affordable Lidar (Light Detection and Ranging) systems and Active Optical (reflectance) Sensors (AOS) to estimate pasture biomass. We evaluated the calibration accuracy of the recently released Pulsed Light LidarLite™ against common AOS including the Trimble® GreenSeeker® Handheld and Holland Scientific ACS-470 Crop Circle™ in a Tall Fescue (Festuca arundinacea) pasture. We also compared the LidarLite™ sensor against a rising plate meter which has traditionally been used to assess pasture height and density. Finally, we explored the potential for integrating AOS with Lidar to improve biomass estimation accuracies. Both the plate meter and the Lidar sensor were significantly related to Total Dry Matter (P<0.01). The Lidar reported a slightly better R² (0.75) than the plate meter (0.72). Both AOSs were found to have a significant relationship with TDM (P<0.01) with the ACS-470 Crop Circle™ showing a slightly higher R² (0.88) than the GreenSeeker® Handheld (R²=0.80). A number of variable transformations and combinations of both the ACS-470 Crop Circle™, GreenSeeker® Handheld and LidarLite™ were explored. The optimal model was found to be a non-linear transformation of the mean height multiplied by the mean NDVI derived from the ACS-470 Crop Circle™. We have subsequently defined this model as the Non-Linear Height and Reflectance Index (NHRI). The relationship of the NHRI to TDM was found to be significant (P<0.01) with a R² of 0.96. Whereas this study investigated two different types of AOS, in order to develop the NHRI, future research should focus on engineering similarly affordable integrated devices which combine height and photosynthetically active biomass sensors.