## 3 Technologies of Monitoring in Montado
### Precision Agriculture
#### 3.2.3 Pasture Monitoring  
Solar radiation interacting with plant tissues, or their canopies is reflected, absorbed, or transmitted. The spectral characteristics of these components are determined by the properties of tissues or plant canopies, and the reflected light can be used to assess the plant's biophysical and biochemical properties [110]. Furthermore, according to [PERSON] and [PERSON] [110], a low reflectance intensity from plant leaves is in the visible wavelength (400 to 700 nm), which implies a high absorbance. On the contrary, a high reflectance in the near infrared region (700 to 1100 nm) is due to the plant's low absorption of light. The use of remote and proximal sensors to evaluate cultures involves the relationship between the measurement of multispectral reflectance, plant temperature, photosynthesis, and evapotranspiration [91]. However, the application of the sensor becomes difficult in permanent pastures where there are trees, irregular plant spacing, morphology, and color compared to crops where there is only a single pattern [89]. The application of remote sensing techniques to monitor production systems where, in addition to crops, there is grazing is difficult due to the great complexity of these systems [43]. [PERSON] et al. [7] state that multispectral images, which come from remote sensors, have the potential to quickly estimate the quality of the pasture in the field without the need for cutting, collection, and laboratory analysis. According to [PERSON] et al. [78], the most consistent correlations between data obtained by multispectral sensors and field observations, concern the rainy season. Remote sensing, particularly hyperspectral imaging, has been described as an auspicious non-destructive tool for determining the nutrient concentration in vegetation [43]. According to [PERSON] [111] using hyperspectral sensors to estimate pasture quality has produced satisfactory results. According to [PERSON] et al. [43], applying technologies with sensors in pasture and grazing systems is challenging since these systems have significant spatial and temporal variability. However, according to those authors, nearby sensors with higher spatial and temporal resolution can overcome some of these challenges. On the other hand, pasture products have a low economic value that limits the use of new technologies [81], sometimes requiring a very high initial investment. Although proximal sensors monitor only a point or a reduced area, they differ from satellite images' scope. If they are mounted on a mobile platform, they have the potential to provide continuous data and capture rapid changes in the proportions of photosynthetically active radiation [78]. In this way, they constitute an essential database for making better decisions [78]. Optical sensors that can be mounted on vehicles are included in the category of proximity sensors [107]. Optical sensors are divided into passive (use natural light) and active (have their own light source), the latter being able to work in any light condition, including at night [81]. Generally, the information collected by the optical sensors is transformed into vegetation indices [112]. Currently, the agricultural producer has easy access to satellite images, at a low cost and with much important information regarding the crops and soil of their farms [6]. Thus, it becomes possible to continuously monitor pasture biomass based on multispectral satellite images with a high spatial resolution, which is very useful in decision making by agricultural managers [57]. According to [PERSON] et al. [56], the accurate and real-time estimation of pasture quality is crucial for the more informed adoption of management practices, such as applying fertilizers based on pasture needs. According to [PERSON] et al. [43], satellite remote sensing constitutes an interesting perspective due to the response scale, process speed, and low cost.