## 2 Related Work  
Drones have been utilized for remote sensing activities for different purposes in vegetated areas. [PERSON] et al. presented [10] a remote-sensing dryland vegetation quantification technique. The technique was able to employ structure-from-motion (SfM) photogrammetry of pictures taken from drones to obtain 3D models of the vegetation structure. The technique was able to identify grass tussocks with volumes of a few cm\({}^{3}\) employing canopy height models. The results showed that the technique was able to predict biomass utilizing the detected canopy volume, obtaining coefficients of determination that ranged from 0.64 to 0.95. Moreover, [PERSON] et al. [11] proposed the use of lightweight drones for the remote sensing of forests for ecological purposes. The system employed drone-derived canopy variables to detect patterns in the biodiversity of the forest. Results showed a correlation between canopy closure and stand basal area. Niche differentiation was performed utilizing edaphic and topographic variables. Lastly, the authors detected a correlation between canopy variables and light-demanding species. [PERSON] et al. [12] described the structural characteristics and the parameters of a UAV developed for its use in environmental monitoring. [PERSON] et al. [13] presented a study in which a drone was utilized to obtain vegetation indexes and thermal maps, relating the temperature of the vegetation and the soil. In order to do so, they used multispectral and thermal sensors. [PERSON] et al. [14] assured that drones could monitor the fields more frequently than the satellites. They also stated that drones could take more detailed photographs, and clouds do not hinder their vision. They also predicted that at the time when the cost of drones decreases and their technology improves, more drones would be used in the field of agriculture. Furthermore, [PERSON] et al. [15] described the process of developing a mechanism for spraying from a drone. Other authors such as [PERSON] et al. [16] made a study where they presented the best drones that can be used in monitoring and observation in agriculture so as to improve crops and prevent damage to the fields. [PERSON] et al. [17] presented a collaborative system consisting of a WSN and an aerial robot that was used for the real-time monitoring of frost in vineyards. Its solution was a mobile node that transported an aerial robot that ensured communication between the dispersed nodes and the base station of the robot. This method allowed them to overcome the limitations arising from the use of wireless networks. There are authors, such as the following, who present a classification of UAV applications in PA. [PERSON] et al. [18] present a classification of the applications of the unmanned aircraft systems (UAS) for precision agriculture. The authors define the following three niches or sectors in their classification: scouting for problems, monitoring to prevent yield loss, and planning crop management operations. [PERSON] et al. [19] review recent applications of UAVs for Precision Agriculture. [PERSON] et al. briefly review the implementation of UAVs for crop monitoring and pesticide spraying. [PERSON] et al. [20] propose a survey on techniques, applied to precision agriculture monitoring, through the use of drones equipped with multispectral, thermal, and visible cameras. For each application, the main limitations are highlighted, and the parameters that need to be considered before performing a flight are reported. Authors such as [PERSON] et al. [21] propose using an IEEE802.11n network to distribute the images captured from a UAV to their ground control station. Furthermore, fields and remote areas can hinder the progress of other activities such as cultural heritage conservation, and drones have been considered as a solution to implement systems such as the remote-sensing system for an archaeological survey of remains in mountain areas presented by [PERSON] [22].