# Systematic Mapping Study on Remote Sensing in Agriculture  
[PERSON]  
1 Department of Computer Science and Systems, University of Murcia, 30100 Murcia, Spain; [EMAIL_ADDRESS] (J.A.G.-B. ); [EMAIL_ADDRESS] (B.B. ); [EMAIL_ADDRESS] (J.L.F.-A.) 2 Department of Computer Science and Software Engineering, CIT, United Arab Emirates University, Al Alin 15551, UAE; [EMAIL_ADDRESS]
3 Food Engineering and Agricultural Equipment Department, Technical University of Cartagena, 30203 Cartagena, Spain; [EMAIL_ADDRESS]
4 Correspondence: [EMAIL_ADDRESS]; Tel. : +34-868-88-8530  
[PERSON]  
2 Department of Computer Science and Software Engineering, CIT, United Arab Emirates University, Alin 15551, UAE; [EMAIL_ADDRESS]  
[PERSON]  
1 Department of Computer Science and Systems, University of Murcia, 30100 Murcia, Spain; [EMAIL_ADDRESS] (J.A.G.-B. ); [EMAIL_ADDRESS] (B.B. ); [EMAIL_ADDRESS] (J.L.F.-A.) 2 Department of Computer Science and Software Engineering, CIT, United Arab Emirates University, Alin 15551, UAE; [EMAIL_ADDRESS]  
[PERSON]  
1 Department of Computer Science and Systems, University of Murcia, 30100 Murcia, Spain; [EMAIL_ADDRESS] (J.A.G.-B. ); [EMAIL_ADDRESS] (B.B. ); [EMAIL_ADDRESS] (J.L.F.-A.) 2 Department of Computer Science and Software Engineering, CIT, United Arab Emirates University, Alin 15551, UAE; [EMAIL_ADDRESS]  
3 Food Engineering and Agricultural Equipment Department, Technical University of Cartagena, 30203 Cartagena, Spain; josealberto. GPS is closely related to GIS and RS, being used as input for both systems, i.e., GPS offers precise positioning of geospatial data and the collection of data in the field [8]. Some works have addresses PA problems from this point of view, such as solving weed management issues [9; 10; 11], but usually in conjunction with other technologies. RS has been considered by some authors as the most cost-efficient technique for monitoring and analyzing large areas in the agricultural domain [12]. It can be considered as a part of the Earth observation domain, used for capturing and analyzing information about crops and soil features acquired from sensors mounted on different types of platforms such as satellites, aircraft, or ground-based equipment. Thus, the technologies related with remote sensing in agriculture (RSA) include hardware design of the cameras and capturing vehicles, communication technologies used to transfer the images [13], and the necessary tools of image processing, computer vision and machine learning to analyze the images and additional information available [14]. The obtained information is later used in agricultural decision support systems [15]. As the number of tasks and activities involved in the efficient use of these technologies can be overwhelming (from study design to quality assurance), efforts have been done to harmonize these tasks and provide general recommendations [16]. The existing applications of RSA include almost all tasks of the cultivation process [17]: estimation of cropland parameters; drought stress and use of water resources; pathogen and disease detection; weed detection; monitoring nutrient status and growth vigor of the plants; and yield estimation. These applications are affected by a set of parameters specific for each sensor type [12]:  
* Type of platform where the sensor is mounted: in-field systems, ground vehicles, aircraft or satellites. * Wavelengths of the electromagnetic spectrum that are captured; most frequently, they include visible, infrared, ultraviolet and microwaves. * Number and width of the spectral bands captured: panchromatic (a single wide band), multispectral (a small number of broad bands), and hyperspectral (many narrow bands). * Spatial resolution, measured in meters per pixel, which can be roughly classified in high (less than 1 mm for in-field cameras), medium, and low (around 1 km in some satellites and bands). * Temporal resolution, i.e., capture frequency of the system, which can range from real-time (in-field cameras) to several weeks (in some satellites).