# Image Interpretability of nSight-1 Nanosatellite Imagery for Remote Sensing Applications
## 4 Results and Discussion
While the blue spectral band is prone to substantial atmospheric scattering and absorption, it is useful for mapping land use, water bodies and vegetation characteristics. The green band reacts to the green reflectance of healthy vegetation and accentuates peak vegetation, is therefore quite valuable for assessing plant vigour. nSight-1's red band is located in the red chlorophyll absorption region and is valuable for vegetation discrimination and delineation of geological and soil boundaries. Radiometric resolution is a major factor that influences the visual quality of satellite imagery. [PERSON] [45] highlights that the radiometric resolution of a sensor is indicative of the fidelity with which the imager can distinguish subtle differences in reflectance and is a function of the sensor signal-to-noise ratio. The optical design of the nSight-1 Gecko imager includes a 2 Mega Pixel RGB sensor unit and the Bayer-pattern filter that positively influences the quality of images captured by the nanosatellite. While the raw images for nSight-1 are captured at 12 bits, the images are downsampled to 8-bit colour images by standard discrete cosine transform lossy 8-bit RGB JPEG compression techniques due to capacity constraints imposed by the onboard computer and satellite power. A radiometric resolution of 8 bits impacts on the visual image quality of nSight-1 nanosatellite data as it controls the actual information contained in the images and shows the sensitivity of the sensor due to small differences in reflected energy. Modern earth observation satellites such as Landsat 8 and Sentinel-2 have radiometric resolutions of 16 bits and older sensors such as Landsat 7 are scaled to 8-bit. Radiometric calibration as not been done to make the data analysis-ready for quantitative time series based remote sensing applications that require accurate Top of the Atmosphere Reflectance or Surface Reflectance values such as trend analysis of vegetation vigour using vegetation indices. Lack of radiometrically calibrated images could be addressed in future nSight missions by installing an onboard radiometric calibration device on the imager. Calibration and validation of the imagery could also be achieved through alternative methods such as vicarious calibration and image cross-calibration. Improving the radiometric data quality will ensure the interoperability of the imagery with different data sources. The potential for radiometric calibration of CubeSat data has been demonstrated by [PERSON] [46]. Using calibrated CubeSat data from Planetlabs, [PERSON] [47; 48] showed the feasibility of cross-calibration and interoperability of CubeSat data with data from prominent missions such as Landsat 8, Sentinel-2, and MODIS for deriving vegetation parameters such as normalized vegetation index (NDVI) and leaf area index (LAI). Practical uses for nSight-1 imagery shown in the study include urban demarcation, forestry delineation, mapping of structural geology features, agriculture field boundary extraction, water body mapping, and coastline mapping and assessment, land degradation and soil erosion assessments, drainage morphometric analysis of fluvial systems, wetlands monitoring, maritime ship surveillance, mapping of major roads, general land use, and land cover mapping. A range of nSight-1 applicationshas been identified in this study. Visual analysis of nSight-1 images over croplands shows that the images are valuable in supporting food security through the generation crop maps. The images could also be used as a base data source for the extraction of agricultural field boundaries. Images of Delano, USA and Loskop, South Africa reveal rectangular and concentric cropped and fallow agricultural fields. Field boundary information is critical in agricultural field inventories and crop yield estimations. Water is a scarce resource and the frequent monitoring of water body surfaces is important to support effective water resources management.