# Precision Farming in Hilly Areas: The Use of Network RTK in GNSS Technology
## 1 Introduction  
Precision agriculture has provided a remarkable positive contribution to the primary sector globally at various levels [1; 2; 3; 4]. Unlike conventional agricultural methods, it can adapt crop yields by considering the local variability of the physical, chemical, and biological characteristics of soils, as well as the application time through the development of technological and computer support [5; 6; 7]. Precision agriculture employs machines equipped with \"intelligent systems\", which can measure production factors in relation to the real needs of a plot and of different homogeneous areas within it [8]. According to [9], several goals can be achieved, such as: (i) enhancing yields with the same total inputs; (ii) reducing inputs with equal yield; (iii) increasing yields by reducing inputs at the same time. Furthermore, when applied to conservative soil methods, the principles of precision agriculture can (i) maintain environmental benefits, (ii) improve corporate income, and (iii) rationalize the use of machines [10; 11]. Analyzing precision farming from environmental, economic, and management points of view, several positive impacts emerge, which should not be underestimated [10; 12; 13; 14]. Focusing on economic benefits, an overall optimization of crop interventions can be detected, together with a quantitative reduction of distributed chemicals [13] and an improved operational and safety capacity for operators in their workplace. It should also be stressed that the above-mentioned economic benefits can also be derived from two reasons: firstly, for the probable growth in costs of the production factors; secondly, on the other hand, for the likely reduction in the cost of purchasing technical equipment, which occurs as demand and technological evolution rise. The modern approach to precision agriculture is based on flexible customized and equipped technology solutions with extensive interoperability. This method is essential as it is able to managethe wide variability of usage conditions in typical Italian farms, which are characterized by their (often highly fragmented) land capital [15; 16; 17; 18; 19]. The diffusion of highly-innovative techniques, favored by their adaptability to each agricultural reality, would substantially contribute to the modern transformation of productive processes in the Italian primary sector [20]. Nowadays, the use of a service platform for product data capture related to production is widely available in several areas through local devices. The latter include sensors, automatic guidance systems with Global Navigation Satellite Systems (GNSS), and central processing systems. Specifically, GNSS technology, as a European global navigation satellite system, ensures greater positioning accuracy and reliability compared to GPS, as it is designed to provide real-time positioning services [21; 22; 23]. The use of the signals of GNSS was initially anticipated in the late 1980s [24; 25] and experimentally confirmed in the early 1990s [26]. Regardless of this initial approach to GNSS techniques, the initial efforts to evaluate soil moisture from reflectivity dimensions arise in 2003 [27]. GNSS, such as the Global Positioning System (GPS) technology, has grown and developed as a controlling atmospheric remote sensing tool able to provide precise observations of atmospheric parameters. The success of GPS has stimulated additional progress of GNSS technology. Nevertheless, these two systems can be defined as complementary [28]. An additional value of these kind of technologies is that they can perform in all weather conditions. This feature of GNSS offers useful information also during cloudy and rainy days, which are still uncertain blocks to radar systems and low Earth orbiting satellites [29]. Potential technical enhancements must be set in the background of processing power and sophisticated technology previously incorporated into GPS receivers [13]. These devices (as GNSS technology) permit land mapping.