ABSTRACT
Traditional techniques based on field measurements (e.g. by cutting and weighing) are the most accurate methods for collecting data on herbage biomass (Frame, 1993). However, especially on sites that are remote or difficult to access, these approaches are time-consuming, labour-intensive and difficult to implement. They are unable to represent variations in the spatial distribution of any biomass parameter in large areas. In these situations, remote sensing (RS), with its repetitive data collection and digital format, allows fast recording and processing of large quantities of data, making it the primary source for large-area biomass estimation (Kumar et al., 2015). For the monitoring of vegetation characteristics, remote sensors can be used to capture information about vegetation without necessarily making direct measurement of the parameters of interest, but simply by providing data from which the desired information can be extracted based on the characteristics observed during RS of vegetation. The main advantages of RS include (i) the ability to obtain measurements potentially from every location in time and space, (ii) the speed with which remotely sensed data can be collected and processed, (iii) the relatively low cost of many RS data types and (iv) the ability to collect data easily even in areas that are normally difficult to access on the ground.
