# Image Interpretability of nSight-1 Nanosatellite Imagery for Remote Sensing Applications
## 1 Introduction
[PERSON] [11] note that CanX-2 effectively acquired total column measurements of carbon dioxide and GNSS radio occultation measurements. Since the turn of this decade, the development of nanosatellites commonly known as CubeSats has been gaining traction in South Africa [12]. Cape Peninsula University of Technology's (CPUT) French South African Institute of Technology (F'SATI) pioneered the development and launch of South Africa's first CubeSat known as ZACUBE-1 (codenamed TshepisoSAT) that was launched on 21 November 2013. While ZACUBE-1 was primarily aimed at ionospheric studies and carries an HF beacon as its primary instrument, it has onboard a low-resolution wide swath imager as a secondary payload. As a follow-on mission, CPUT developed a second CubeSat known as ZACUBE-2 that carries onboard a medium resolution matrix imager and a number of communication subsystems aimed at providing AIS(Automated Information Service) and VDES (VHF Data Exchange Service) data to support maritime domain awareness services [12; 13]. In 2017, another South African company developed a nanosatellite known as nSight-1 that was launched as part of the European Commission-funded international QB50 constellation [14]. The nanosatellite was developed over 6 months by the Space Commercial Services (SCS) Aerospace Group in partnership with South African space industry partners [15]. nSight-1 weighs 2.5 kg and has a volume of \(10\times 10\times 20\) cm\({}^{3}\)[14; 15]. It has three onboard payloads that include a modular designed SCS Gecko imaging payload, FIPEX atmospheric science instrument supplied by University of Dresden and a Radiation mitigation VHDL coding experiment supplied by Nelson Mandela University [16]. Gecko imaging payload consists of a 30-meter resolution colour red, green, and blue (RGB)'snapshot' camera with an integrated data storage and image processing system. The imaging payload uses a matrix sensor in snapshot mode that captures RGB images at 5 frames per second. nSight-1 nanosatellite orbits the earth at an altitude of 400 km with a 50-degree inclination. The imaging payload produces RGB images with Bayer patterns that are downlinked through low bandwidth telemetry radio subsystem. Whereas CubeSats have demonstrated their capability to capture satellite data at a variety of spatial, spectral, radiometric, and temporal resolutions, little is known about their image quality and usability for key land use and land cover mapping applications. Image quality is a major parameter driving the utilization of satellite data. Many studies emphasize the significance of spatial data quality indicators. The growing interest in data quality is partly due to the proliferation of digital services that utilize remote sensing data [17; 18]. The Quality Assurance for Earth Observation (QA4 EO) initiative points out that all data and derived products must have a Quality Indicator based on a statistically derived value that must be unequivocal and universal in terms of its definition and derivation [18]. Quality indicators could be objectively derived from measurement and calculations or subjectively from expert judgement. Many global missions such as NASA and USGS's Landsat series missions, ESA's Sentinel mission, and NASA's MODIS Aqua and Terra satellite missions are well radiometrically calibrated and their image quality parameters are well documented. In sharp contrast, the image quality parameters for many small satellites are unknown or at least are not in the public domain. In many instances, satellite imagery from most CubeSats is not radiometrically calibrated, limiting the usage of such data in mainstream remote sensing applications. A variety of image quality assessment methods have been developed to assess satellite image quality in terms of spatial and spectral consistency of data.