Search Results (4)

Accurate grading of remote sensing image interpretation is crucial for improving image classification and screening efficiency. Through extensive research, the General Image Quality Equation (GIQE) based on the National Imagery Interpretability Rating Scale (NIIRS) has been developed. However, poor reliability and low accuracy issues remain due to the failure to consider human visual characteristics. This paper introduces the Target Task Performance (TTP) criterion as a key parameter to reflect the cascading degradation factors of human visual perception characteristics and system imaging links, which improves the reliability of the model. A New Optimized Remote Sensing Image Quality Equation (NORSIQE), which effectively predicted the interpretability of image information, is constructed. Using 200 sets of test data, the quantitative relationship between key parameters (GSD, TTP, and SNR) of the NORSIQE and the subjective NIIRS level is obtained by a least squares regression fit, and the determination coefficient of the model is as high as 0.916. The model is evaluated for accuracy using 120 sets of validation data, showing an 87% improvement compared to the GIQE4. This method provides theoretical support for the development of new methods for remote sensing image quality evaluation and the design of payloads for remote sensing imaging systems. Full article

Currently, hydrogen generation via photocatalytic water splitting using semiconductors is regarded as a simple environmental solution to energy challenges. This paper discusses the effects of the doping of noble metals, Ir (3.0 at.%) and Ni (1.5–4.5 at.%), on the structure, morphology, optical properties, and photoelectrochemical performance of sol-gel-produced SnO₂ thin films. The incorporation of Ir and Ni influences the position of the peaks and the lattice characteristics of the tetragonal polycrystalline SnO₂ films. The films have a homogeneous, compact, and crack-free nanoparticulate morphology. As the doping level is increased, the grain size shrinks, and the films have a high proclivity for forming Sn–OH bonds. The optical bandgap of the un-doped film is 3.5 eV, which fluctuates depending on the doping elements and their ratios to 2.7 eV for the 3.0% Ni-doped SnO₂:Ir Photoelectrochemical (PEC) electrode. This electrode produces the highest photocurrent density (J_ph = 46.38 mA/cm²) and PEC hydrogen production rate (52.22 mmol h⁻¹cm⁻² at −1V), with an Incident-Photon-to-Current Efficiency (IPCE% )of 17.43% at 307 nm. The applied bias photon-to-current efficiency (ABPE) of this electrode is 1.038% at −0.839 V, with an offset of 0.391% at 0 V and 307 nm. These are the highest reported values for SnO₂-based PEC catalysts. The electrolyte type influences the J_ph values of photoelectrodes in the order J_ph(HCl) > J_ph(NaOH) > J_ph(Na₂SO₄). After 12 runs of reusability at −1 V, the optimized photoelectrode shows high stability and retains about 94.95% of its initial PEC performance, with a corrosion rate of 5.46 nm/year. This research provides a novel doping technique for the development of a highly active SnO₂-based photoelectrocatalyst for solar light-driven hydrogen fuel generation. Full article

Nanosatellites are increasingly being used in space-related applications to demonstrate and test scientific capability and engineering ingenuity of space-borne instruments and for educational purposes due to their favourable low manufacturing costs, cheaper launch costs, and short development time. The use of CubeSat to demonstrate earth imaging capability has also grown in the last two decades. In 2017, a South African company known as Space Commercial Services launched a low-orbit nanosatellite named nSight-1. The demonstration nanosatellite has three payloads that include a modular designed SCS Gecko imaging payload, FIPEX atmospheric science instrument developed by the University of Dresden and a Radiation mitigation VHDL coding experiment supplied by Nelson Mandela University. The Gecko imager has a swath width of 64 km and captures 30 m spatial resolution images using the red, green, and blue (RGB) spectral bands. The objective of this study was to assess the interpretability of nSight-1 in the spatial dimension using Landsat 8 as a reference and to recommend potential earth observation applications for the mission. A blind image spatial quality evaluator known as Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) was used to compute the image quality for nSight-1 and Landsat 8 imagery in the spatial domain and the National Imagery Interpretability Rating Scale (NIIRS) method to quantify the interpretability of the images. A visual interpretation was used to propose some potential applications for the nSight1 images. The results indicate that Landsat 8 OLI images had significantly higher image quality scores and NIIRS results compared to nSight-1. Landsat 8 has a mean of 19.299 for the image quality score while nSight-1 achieved a mean of 25.873. Landsat 8 had NIIRS mean of 2.345 while nSight-1 had a mean of 1.622. The superior image quality and image interpretability of Landsat could be attributed for the mature optical design on the Landsat 8 satellite that is aimed for operational purposes. Landsat 8 has a GDS of 30-m compared to 32-m on nSight-1. The image degradation resulting from the lossy compression implemented on nSight-1 from 12-bit to 8-bit also has a negative impact on image visual quality and interpretability. Whereas it is evident that Landsat 8 has the better visual quality and NIIRS scores, the results also showed that nSight-1 are still very good if one considers that the categorical ratings consider that images to be of good to excellent quality and a NIIRS mean of 1.6 indicates that the images are interpretable. Our interpretation of the imagery shows that the data has considerable potential for use in geo-visualization and cartographic land use and land cover mapping applications. The image analysis also showed the capability of the nSight-1 sensor to capture features related to structural geology, geomorphology and topography quite prominently. Full article

Image quality is important for taking full advantage of satellite data. As a common indicator, the National Imagery Interpretability Scale (NIIRS) is widely used for image quality assessment and provides a comprehensive representation of image quality from the perspective of interpretability. The ZY-3 (Ziyuan-3) satellite is the first civil high resolution mapping satellite in China, which was established in 2012. So far, there has been no reports on adopting NIIRS as the common indicator for the quality assessment of that satellite image data. This lack of a common quality indicator results in a gap between satellite data users around the world and those in China regarding the understanding of the quality and usability of ZY-3 data. To overcome the gap, using the general image-quality equation (GIQE), this study evaluates the ZY-3 sensor-corrected (SC) panchromatic nadir (NAD) data in terms of the NIIRS. In order to solve the uncertainty resulting from the exceeding of the ground sample distance (GSD) of ZY-3 data (2.1 m) in GIQE (less than 2.03 m), eight images are used to establish the relationship between the manually obtained NIIRS and the GIQE predicted NIIRS. An adjusted GIQE is based on the relationship and verified by another five images. Our study demonstrates that the method of using adjusted GIQE for calculating NIIRS can be used for the quality assessment of ZY-3 satellite images and reveals that the NIIRS value of ZY-3 SC NAD data is about 2.79. Full article