# Design of an Integrated Remote and Ground Sensing Monitor System for Assessing Farmland Quality
## 1 Introduction  
Farmland is a basic resource required for ensuring human survival. However, the quality of farmland dictates the quantity and quality of the extracted crops, which, in turn, affect the quality and health of human life [1, 2]. As such, farmland quality monitoring is a key task required for farmland protection [3]. Presently, farmland quality monitoring is predominantly conducted via laboratoryanalyses. However, the development of science and technology has provided new monitoring methods uniquely suited for assessing temporal and spatial changes in farmland quality. Among these, high-resolution remote sensing data obtained by unmanned aerial vehicles (UAVs) and long-term ground sensing data obtained by wireless sensor networks (WSNs), like soil moisture data obtained from three different depths, meteorological data and so on, are two key monitoring methods with substantial potential for conducting farmland quality monitoring [4; 5; 6; 7]. Moreover, the respective spatial and temporal benefits provided by these separate methods has generated considerable interest in the integration of the data collected by these two types of monitoring systems into a single farmland quality monitoring system [8; 9; 10; 11; 12; 13; 14]. One key component required for effectively integrating the data collected by UAVs and WSNs is the development of a suitable method for transmitting the data collected by a WSN to the UAV as it passes over the monitored region. Currently, three data transmission methods have been developed for this purpose, which include point-to-point transmission, the flat routing protocol, and the clustering routing protocol. Point-to-point data transmission utilizes a static star topology, where the sensor nodes of the WSN located on the ground do not communicate with each other, but rather send their data to a sink node in a passing UAV directly [15; 16; 17; 18; 19; 20; 21; 22]. This data transmission method adopts a simple network structure that is easy to build. However, the UAV must traverse every sensor node in the WSN to collect all the available data, which results in an irregular UAV flight route that increases flight time and consumes a greater proportion of available battery energy. Moreover, the irregular flight route can result in the wasteful overlap of remote sensing images, which further reduces the monitoring efficiency. Accordingly, point-to-point data transmission is only suitable for use under conditions where the density of sensor nodes is low. The flat routing protocol is a dynamic routing protocol in which all sensor nodes in the WSN are treated as equivalent and serve the same function [23]. Here, sensor nodes send their data to route nodes at fixed locations according to a number of possible flat routing protocols, such as directed diffusion (DD) or sensor protocol for information via negotiation (SPIN), and then only the route nodes send their data to the sink node in the passing UAV directly [24; 25; 26]. This method has been employed to good effect in a number of UAV-WSN applications. For example, [PERSON] et al. [27] adopted the flat routing protocol in a UAV-WSN system designed to monitor isolated vineyards separated by substantial distances. Here, several sensor nodes and a single route node were deployed in each vineyard based on the flat routing protocol. Hence, the UAV was required to fly over the route nodes of the isolated vineyards only. While this method can greatly streamline the flight path of a UAV, and thereby reduce its flight time and energy consumption, the sensor nodes of the WSN suffer from unbalanced energy consumption during data transmission, owing to their varying distances from the single route node. Moreover, the streamlined flight route of the UAV over the route nodes only reduces the coverage of UAV imaging. Accordingly, the flat routing protocol is most suitable for conditions where the sensor nodes are separable into several groups.