Sentence examples for sensing variables from inspiring English sources

As a sensor-dependent solution, the estimation is refined in the domain of sensing variables.

To map SOC stock, we used geographically weighted regression (GWR) and regression kriging (RK) methods and a large set of soil samples, in which nine topographic and remote sensing variables were observed.

Assuming that the localized sensing variables are sent to the FU, the dominant fusion model has its origins in the distributed detection theory: the parallel fusion technique [23] combines the observations to improve the detection performance.

We used 2 types of satellite remote sensing variables in this analysis: the Vegetation Continuous Fields (VCF) product and the Normalized Difference Vegetation Index (NDVI).

We used a set of moderately high-resolution (∼1 km) climate and satellite remote sensing variables to characterize the often sharp habitat transitions in Ecuador (Data S1; Table S1).

The NDVI is a satellite remote sensing variable that quantifies the concentrations of green leaf vegetation on the ground, providing an integrated estimate of vegetation health and a means of monitoring changes in vegetation over time.

Remotely sensed variables showed to be better predictors for spatial grain yield estimation than soil variables.

Techniques that combine information on land and atmospheric properties with remotely sensed variables would allow improved prediction for a number of hydrological variables.

Results showed little association between knee joint position sense variables and measures of pain and disability (r values <0.24, most p>0.05).

Soil and remotely sensed variables were evaluated in bi- and multivariate autoregressive state-space analysis to predict spring barley grain yield.

We also examined the relative importance of these remotely sensed variables in predicting nesting guild distributions of ground/understory nesters, mid-upper canopy nesters, and cavity nesters.