## 1 Introduction  
Agriculture is an important industry to the national economy in Spain, Italy, France, Switzerland, and other countries around the world. In the case of Spain, the primary forms of property holding are large estates and tiny land plots. According to the 2009 National Agricultural Census ([[http://www.ine.es/jaxi/Tabla.htm?path=/t01/p042/ccaa_prov/l0/&file=010101.px&L=0](http://www.ine.es/jaxi/Tabla.htm?path=/t01/p042/ccaa_prov/l0/&file=010101.px&L=0)]([http://www.ine.es/jaxi/Tabla.htm?path=/t01/p042/ccaa_prov/l0/&file=010101.px&L=0](http://www.ine.es/jaxi/Tabla.htm?path=/t01/p042/ccaa_prov/l0/&file=010101.px&L=0))), 64% of the agricultural terrain was held in properties of 5 or more hectares. Those farms are located in those zones which are mainly devoted to permanent crops: orchards, olive groves, citric groves, and vineyards. However, only in the area of Valencia (Spain), there are more than 100,000 small farms with an exploitation area lower than 1 hectare. This represents 50% of the total number of farms located in Valencia and 20% of the small farms located in Spain. The agricultural industry is suffering diverse problems which are causing the progressive leave of fields, groves, and orchards in Spain. The main problems are the ageing of the agricultural active population, the low incorporation of young people, and the financial crisis suffered in early 2010. The bitter campaign for the Spanish citrus sector in 2019, where the average price has been around 35% lower than previous campaigns, is accelerating the abandonment of small citrus groves in Valencia. This drives to an undesirable scenario where the active and the abandoned farms coexist. A small active grove next to abandoned ones is more prone to being affected by plagues or, even, wildfires. Thus, more effective maintenance tasks are needed. One possible solution to minimize costs is to automatize maintenance and surveillance tasks. This can be done by teams of robots in large farms. In most large farms, the structure and the distribution of elements (e.g., citric trees) are homogeneous and well known. In contrast, in those areas where the small farms are located, the structure and distribution depend on the owners (see Figure 1), who usually are not technology-friendly and do not have digital information about their farms. Thus, to ease the operation of maintenance robots in such kinds of farms, a procedure to automatically retrieve information about where they have to operate is needed. Remote sensing can be used to extract information about the farm. [PERSON] et al. [1] introduced a manual methodology for citrus grove mapping using infrared aerial imagery. However, access to aerial imagery is often limited and using dedicated satellite imagery is not widely used for navigation tasks. As the authors of Reference [2] stated, multispectral remote imagery can provide accurate weed maps but the operating costs might be prohibitive. This paper introduces a proof-of-concept where we target the combination of public satellite imagery along with parcel information provided by governmental institutions. In particular, the system uses the maps and orthophotos provided by _SIGPAC_ (Sistema de Informacion Geografica de parcelas agricolas) to minimize operational costs. The proposed approach in the present paper is similar to the system introduced in Reference [3] with some differences. First, it uses public open data. Second, our system adopts only a binarization of the remote image instead of using classifiers because determining the kind of tree or grove is not critical. Third, the orange tree lines are also determined in the proposed mapping. The remaining of this paper is organized as follows. Section 2 shows some related and state-of-the-art works in this field. Section 3 describes the algorithms to extract satellite imagery and the mask of the parcel where the path planning is to be determined.