## 5 Discussion
### Limitation of Proposed Regression Models  
The main limitation of the proposed system is that it can only be applied in the areas classified as natural areas. No suitable models have been obtained which can monitor with an acceptable error the areas covered by grass in the golf course, the green areas, and the fairways. It is possible to have mathematical models for these cases, but the R\({}^{2}\) of these models is around 24%, and we assume that the errors are too high. Thus, we focused on the models for the natural areas within a golf course. Moreover, the application of the generated models can be applied to other areas with natural vegetation. Two key aspects cause the lack of models with appropriate R\({}^{2}\) and MAEs.  
On the one hand, there is a variability of soil moisture (from 6 to 19% approximately) in the greens, which is not correlated with changes in the grass. This is caused because the daily irrigation ensures that the plants h an optimum vigor. The soil of the greens is sandy soil, which causes very fast drainage of water, which, together with the evapotranspiration, produces a fast decrease of soil moisture. This decrease of soil moisture is not related to the grass status, which neglects the correct detection of the soil moisture by observing grass coverage in this specific environment. Moreover, high spatial variability of soil moisture inside the green can be identified, as shown in [36].  
On the other hand, in the fairways, we have a similar case. The grass coverage neglects the estimation of soil moisture because regardless of the instantaneous soil moisture value, the grass coverage aspect is stable in time. In this case, the situation is worsening than in the greens since the soil has lower homogeneity in the fairways, and it is formed by natural soil with an amendment of sand; an example of the heterogeneity of its soil moisture can be seen in [37; 38]. Moreover, the grass coverage in the fairways is far less homogeneous than in the greens, both in the temporal and spatial gradient. Regarding the temporal variability, an example can be seen in [6]. In the greens, the grass is kept at a given height, and they are moved periodically, ensuring the same grass height along the green and along the time. In the fairways, we do not have this homogeneity.  
Regarding the use of NDV and related indexes to evaluate the soil moisture in greens and fairway areas of the golf course, as shown in [12], recently published results show no correlation between NDVI and soil moisture. Although [39] showed a clear correlation between NDVI and soil moisture in grasses with different water stress, Ref. [40] indicated that there is no correlation when no continuous stress is applied. The authors set in [40] that this is because in short periods of time, even though the soil moisture decreases after irrigating, the NDVI remains uniform. Moreover, they highlight the difficulties of obtaining data that prove the decrease of soil moisture in a short period of time due to the high heterogeneity of soil.  
Finally, the MAEs of the verification process is higher than the MAEs of the calibration. The increase of MAEs in the verification might be caused by changes in the land coverage, which are not considered in the initial model. Therefore, it will be necessary to gather and analyze more data along the year to estimate if the proposed soil moisture model should be reformulated to include other seasons. Another option is to generate specific models for each season or period.