Ndvi From Active Optical Sensors as a Measure of Canopy Cover and Biomass

Abstract

ABSTRACT:Commercially available proximal sensors are being used in precision agriculture to provide non-destructive, real-time spatial information on 'green biomass' that may be of interest to the remote sensing community. The sensors are described as biomass sensors, but questions remain on which canopy characteristics can be best estimated by the sensor measurements. In this study Normalized Difference Vegetation Index (NDVI) measurements from active optical sensors were examined across multiple datasets, representing different active optical sensors, different years, and different sites for wheat and barley. The NDVI values were compared with spatially and temporally coincident measurements of fractional green cover and above ground biomass, expressed as dry matter in kg ha -1 . Direct comparison of NDVI measurements from the different sensors for the same plots over a range of canopy cover demonstrates differences for plot means of NDVI. Canopy fractional green cover values were well described by NDVI using a linear model. Using all of the datasets, the linear regression of fractional green cover on NDVI yielded an r 2 of 0.71 and a standard error of 0.12. NDVI measured by the sensors did not explain as much of the variance in dry matter as for fractional cover. Dry matter was related to NDVI using a non-linear model. For all sensors, sites and dates with green biomass, the model was fitted with r 2 value of 0.27, and standard error of 2133 kg ha -1 . The relationship between NDVI and dry matter was nearly linear at levels of biomass less than 1000 kg ha -1 . Results for these datasets indicate that the active optical sensors may be a useful surrogate for fractional cover, but not for above ground biomass.

Yield, growth and grain nitrogen response to elevated CO2 in six lentil (Lens culinaris) cultivars grown under Free Air CO2 Enrichment (FACE) in a semi-arid environment

“…Non-destructive measurements of canopy reflectance, from which Normalised Difference Vegetation Index (NDVI) was calculated, were taken with a CropCircle ACS-210 with GeoSCOUT GLS-400 data logger (Holland Scientific, Lincoln, NE, USA) as an indirect measurement of crop canopy development (Fitzgerald, 2010;Perry et al, 2012). These were taken approximately every week (2014) or fortnightly (2015) from the vegetative stage to the pod filling stage in 2014 and 2015.…”

Using Canopy Measurements to Predict Soybean Seed Yield

“…In addition, precise LAI measurements require plant destruction in order not to overestimate the LAI in dense canopies [19]. The NDVI can also be used to approximate fractional canopy coverage but is not a useful substitute for above-ground biomass measurements [20]. Ma et al [8] reported that plant density had no effect on the yield and NDVI relationship during the soybean reproductive growth stages.…”

Water use dynamics of dryland wheat grown under elevated CO2 with supplemental nitrogen

“…The sensor was held ~0.5 m above the crop canopy and oriented to measure a foot-print across the middle rows of the plot. The NDVI is calculated directly by the sensor, and mean values of transects from non-disturbed areas within the subplot were used as a surrogate for canopy cover (Perry et al 2012).…”