# Landsat Surface Product Validation Instrumentation:
## 1 Big MAC Overview
### Purpose
#### 1.1.2 Measurement Technologies  
The immediate purpose of BigMAC was to assess multiple measurement technologies with respect to accuracy, precision, and deployability. Both the instruments and platforms for the instruments were assessed. Perhaps the most often used instrument to measure surface reflectance in the community involved with calibration of optical remote sensing satellites is the handheld spectroradiometer. Three teams brought the following instruments to BigMAC: USGS EROS, SDSU, and RIT. Each of them used models of the ASD FieldSpec instrument, commonly referred to as an ASD. These instruments have been used for decades and are quite well understood with regard to accuracy and repeatability [14; 15]. In general, two person teams are required and the initial cost of the instrument is significant. Typically, these instruments are calibrated through observing a well-characterized reflectance panel and are then used to measure unknown surface reflectances in the visible through SWIR wavelengths. The dual spectrometer approach uses two instruments operating in tandem at the field site. One spectrometer continuously monitors the reflectance panel while the other measures the unknown target [16]. One of the difficulties when using a reflectance panel as the calibration source for the ASD is that the reflectance of the panel is transferred to the radiance measurement of the ASD. Thus, while the ASD is being used to measure the target, any changes in downwelling irradiance will cause a change in the radiance recorded by the ASD that is indicative of an illumination change and not a surface reflectance change. Simultaneous observation of the reflectance panel with a stationary ASD can be used to track illumination changes during site measurements, and these changes can be transferred to the mobile unit during post-processing. In this manner, changes in atmospheric transmission can be tracked continuously to reduce variability during the measurement of the unknown target. USGS EROS deployed a dual unit system [11; 17], while SDSU and RIT fielded single unit systems. However, the RIT instrument was primarily used to observe  
Figure 4: Colormapped thermal image of water and sand targets. Figure 3: Color image of thermal water and sand targets. the full hemispherical downwelling irradiance with a RCR to track atmospheric changes for their UAS instrumentation and Labsphere is a mirror-based demonstration. During each collection activity, the handheld radiometer teams would measure the asphalt target, followed by the row of human-made reflective targets and then collect data over the large natural alfalfa target. Collection patterns over the large target were left up to individual teams--SDSU collected north/south transects following their standard operation procedure, while USGS EROS collected along east/west transects which crossed the rows of alfalfa rather than paralleling them. In 2017, RIT established an Unmanned Aerial Systems Laboratory [18] along with a field team capable of deploying UAS-based imaging systems throughout North America. This UAS team conducts hundreds of missions annually, for studies ranging from harmful algal blooms, the detection of vegetative diseases, target detection, and the calibration of sensors. As part of the BigMAC, RIT flew four unique UAS as follows: the MX-1, SWIR, MX-2, and DJI Mavic 2 Enterprise. The MX-1 is a multi-modal sensor payload that simultaneously captures Nano hyperspectral (400-1000 nm), uncooled thermal, three-band color, and five-band multispectral imagery, as well as LiDAR and GPS/IMU data; see Figure 5A,C [19; 20]. The SWIR payload was also flown in order to extend the spectral range out to 2500 nm. The MX-1 and SWIR sensor payloads were flown on two separate DJI Matrice 600 Pro UAS platforms in tandem. The MX-2 payload consists of the same capabilities as MX-1 with the following two critical upgrades: a calibrated cooled thermal FLIR A6751 sc SLS imaging system and an UAS platform with more lifting power, the DJI Wind 8; see Figure 5B,D.