## 4 Adoption of the Remote Sensing Information by End Users  
Table 7 illustrates an overview of the current remote sensing application for pasture monitoring and end users' level of adoption from this review. Studies have shown that farmers, governments, scientists, and spatial consultants are the main stakeholders in the workflow of remote sensing technology (Table 7). For example, the Queensland Government Australia developed an online \"FORAGE\" ([[http://www.longpaddock.qld.gov.au/forage/](http://www.longpaddock.qld.gov.au/forage/)]([http://www.longpaddock.qld.gov.au/forage/](http://www.longpaddock.qld.gov.au/forage/)); accessed on 7 February 2021) system to support grazing management and provide site-specific information [214; 215]. The customised FORAGE system has provided pasture and climate parameters on land condition and stocking management to 1700 users. \begin{table}
\begin{tabular}{p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt}} \hline \hline
**Remote Sensing Data** & **Main Focus** & **End user/s** & **Country of Adoption** & **Economic Cost** & **Year** & **Inference** & **Reference** \\ \hline Perspective article: (satellite) & \multirow{2}{*}{Pasture degradation} & Government, pastoralist & Australia and China & Nil & 2020 & Researchers should partner with end users. & [27] \\ \hline Perspective article (satellite) & \multirow{2}{*}{Pasture biomass determination.} & \multirow{2}{*}{Farmers} & \multirow{2}{*}{New Zealand} & \multirow{2}{*}{Nil} & \multirow{2}{*}{2020} & Value proposition farmers would adopt satellite data. & & \\ \cline{3-4}  & & & & & & Cloud-based running sensing utilisation where spatial resolution & [193] \\ \hline Perspective article (satellite) & \multirow{2}{*}{Pasture management focusing on precision agriculture.} & \multirow{2}{*}{Farmers} & United Kingdom and Ireland & \multirow{2}{*}{Nil} & \multirow{2}{*}{2019} & Improvement quality through & \\ \cline{3-4}  & & & & & & (unitrients). & \\ \hline NDVI derived from MODIS & \multirow{2}{*}{Pasture quality.} & \multirow{2}{*}{Farmers} & Altai Mountain (Russia, Mongolia, China and Kazakhstan). & \multirow{2}{*}{Free} & \multirow{2}{*}{2019} & Integrate farmers ground-based pasture management with satellite data. & & \\ \cline{3-4}  & & & & & & & ground-based pasture management with satellite data. & \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Summary of current remote sensing information and forms of adoption by end users. [PERSON] et al. [216] acknowledged the low adoption of the remote sensing of pasture monitoring despite increased research and development (R&D) in the past decade. They suggested that there is a need for vendors/researchers to properly understand the \"value proposition\" of the end users and integrate this into the workflow of the remote sensing technology. An earlier representative study reported by [216] provides an empirical analysis of the current approach to pasture monitoring from interview and survey perspectives. The survey involved 500 New Zealand dairy farmers on the methods used to derive pasture measurement. Fifty-two percent used the visual approach, 45% used a technology-based scheme (RPM, C-Dax), and 3% used neither. Further technology analysis suggested that 32% depend on RPM, 11% use C-Dax, 1% use satellite, and 1% use the contractor. Therefore, although decision support tools are essential, the value of the premium that end users (e.g., farmers) place on pasture monitoring is not entirely sure; hence, the value proposition seems ambiguous to persuade non-users to consider the technology [216].