AggieAir: Towards Low-cost Cooperative Multispectral Remote Sensing Using Small Unmanned Aircraft Systems

Abstract

This chapter focuses on using small low-cost unmanned aircraft systems (UAS) for remote sensing of meteorological and related conditions over agricultural fields or environmentally important land areas. Small UAS, including unmanned aerial vehicle (UAV) and ground devices, have many advantages in remote sensing applications over traditional aircraftor satellite-based platforms or ground-based probes for many applications. This is because small UAVs are easy tomanipulate, cheap tomaintain, and remove the need for human pilots to perform tedious or dangerous jobs. Multiple small UAVs can be flown in a group and complete challenging tasks such as real-time mapping of large-scale agriculture areas. The purpose of remote sensing is to acquire information about the Earth’s surface without coming into contact with it. One objective of remote sensing is to characterize the electromagnetic radiation emitted by objects (James, 2006). Typical divisions of the electromagnetic spectrum include the visible light band (380− 720nm), near infrared (NIR) band (0.72− 1.30μm), and mid-infrared (MIR) band (1.30− 3.00μm). Band-reconfigurable imagers can generate several images from different bands ranging from visible spectra to infra-red or thermal based for various applications. The advantage of an ability to examine different bands is that different combinations of spectral bands can have different purposes. For example, the combination of red-infrared can be used to detect vegetation and camouflage and the combination of red slope can be used to estimate the percent of vegetation cover (Johnson et al., 2004). Different bands of images acquired remotely through UAS could be used in scenarios like water management and irrigation control. In fact, it is difficult to sense and estimate the state of water systems because most water systems are large-scale and need monitoring of many factors including the quality, quantity, and location of water, soil and vegetations. For the mission of accurate sensing of a water system, ground probe stations are expensive to build and can only provide data with very limited sensing range (at specific positions and second level temporal resolution). Satellite photos can cover a large area, but have a low resolution and a slow update rate (30-250 meter or lower spatial resolution and week level temporal resolution). Small UAVs cost less money but can provide more accurate information (meter or centimeter spatial