Browsing by Author "Magidimisha, Edwin"

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    Analysis of Ceilometer LiDAR (CL51) sensor atmospheric profile images for urban environmental monitoring over Pretoria, South Africa
    (2024-12) Faniso-Mnyaka, Zimbini; Magidimisha, Edwin; Dikole, Realeboga G; Sekopa, Teboho L
    Clouds are a critical component of the atmosphere, influencing both climate and weather patterns, while their backscatter impacts human activities and lives. The CL 51 Ceilometer LiDAR is one of the advanced atmospheric sensors deployed globally to collect massive data for monitoring environmental conditions. This sensor captures data in digital format, which is subsequently converted into images. However, extracting atmospheric features, such as aerosol distribution along the sensor's path length, requires precise identification for effective analysis. In this paper, we outline the methodology for data acquisition, conversion to image format, and feature extraction of atmospheric components from the CL 51 script. We further analyse the atmospheric images derived from CL 51 seasonal data collected in Pretoria from 2014 to 2015. This analysis of CL 51 ceilometer LiDAR images will enhance our knowledge and understanding of the atmospheric aerosol profile, thereby contributing to urban environmental monitoring efforts.
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    Characterisation of submerged arc welding process using infrared imaging technique
    (South African Institution of Mechanical Engineering, 2017-09) Zondi, MC; Tekane, Yanga C; Magidimisha, Edwin; Wium, Elsmari; Gopal, Ajith K; Bemont, C
    Infrared (IR) thermography is a technique used to measure temperature distribution of heat generation in manufacturing processes such as welding. IR thermography is a non-destructive and non-contact method, which makes it favoured for the arc welding process where interference with the welding process must be avoided. In this study, IR thermography is used to record the temperature history during the submerged arc welding (SAW) process experiment; and to validate the numerical model developed to simulate the said SAW process of a multi-pass circumferential weld on pressure vessel steel. The Flir Short Wave Infrared Radiometer (FSIR) is used during SAW experiments with the ESAB welding unit. The weld pool and the surrounding area are continuously monitored and their temperature recorded using a thermal camera. The recorded temperatures are plotted against time on Temperature-Time curves to reveal the temperature profiles of each welding cycle. Comparison of the resultant temperature profiles with those of the numerical model show good agreement. It is therefore concluded that temperature measurement through thermal imaging is a suitable method to characterize the temperature history of the SAW multi-pass circumferential weld, as well as to effectively validate the numerical.
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    Detecting wildfires using unmanned aerial vehicle with near infrared optical imaging sensor
    (2023-04) Magidimisha, Edwin; Faniso-Mnyaka, Zimbini; Naidoo, Seelenthren; Nana, Muhammad A
    The severity of wildland vegetation fires is expected to grow in response to climate change. Therefore, the price of combating fires will likewise go up while still posing a serious risk to the firefighters. Various countries have invested enormous sums of money in combating fires throughout the years, and this trend is expected to continue. This provides compelling reasons for surveillance systems that can track and detect wildfires at early stages. The Optronic Sensor Systems of the Council for Scientific and Industrial Research (CSIR) in South Africa is developing a small, cost-effective Near-Infrared (NIR) optical imaging payload for tactical forest fire-fighting operations. This paper reports on the field measurement from sensors that detect NIR spectral emissions from the electronically exited alkali metal Potassium (K) emitted during the flaming phase of the biomass. The NIR sensor consists of a combination of two optical imaging systems (target and reference sensor) placed side-by-side with common (identical) field of view. The concept uses images obtained from the optical imaging systems are compared to determine the pixels which are much brighter in the target band relative to the reference band, which are defined as fire detections. This principle uses a portable imaging system consisting of two similar complementary metal oxide semiconductor (CMOS) cameras with high sensitivity within the NIR band. The fire detection is computed using the K-line ratio algorithm. The results presented in this paper show that it is possible to perform early fire detection of biomass fires using low cost NIR sensors coupled with advanced image processing algorithms.
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    Earth observation of aerosols over inland water bodies in relation to calibration and validation of sentinel 2/3
    (SPIE, 2018-10) Faniso, Zimbini; Magidimisha, Edwin
    Satellite remote sensing of inland water bodies has great potential for ensuring water quality and for obtaining reliable data which can be used for decision making. This is a rapidly evolving technology that is now widely utilized throughout the globe for providing a broad as well as detailed perspective on earth-system status and change. Inland water processes, such as eutrophication, may have a major impact on human life and can lead to environmental disasters. This study investigates the optical effect of atmospheric aerosols on remote sensing of the water-leaving radiance (Lw) at Roodeplaat dam. An in-situ measurement field campaign was performed at Roodeplaat dam (Pretoria) during the 2016 winter season, in relation to calibration and validation of Sentinel 2 and Sentinel 3 satellite data. In-situ measurements were performed simultaneously with the satellite overpasses at the dam. In-situ measurements included Aerosol Optical Thickness (AOT), water vapor column and downwelling spectral irradiance as well as the remote sensing spectral reflectance of the dam, Rrs. A radiative transfer code (Modtran) was used to predict the radiance at the Top of Atmosphere (TOA), compared to actual measurements from Sentinel 2 and 3. Sensitivity analysis demonstrated that retrieval of water-leaving radiance at small water bodies such as Roodeplaat dam was sensitive to aerosol optical properties as well as total column.
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    Flight hardware verification and validation of the K-line fire sensor payload on ZACube-2
    (SPIE, 2018-10) Cogan, D; Griffith, Derek J; Magidimisha, Edwin; Van Zyl, R
    With the launch of the ZACube-2 nanosatellite, a new technique of wildfire detection and monitoring from space will be evaluated. Potassium is an essential plant macronutrient and all vegetation biomass fires exhibit characteristic spectral ¿K-line¿ emissions in the near infrared (NIR), which can be isolated and observed with suitable optical filtering. However, as a new technique, the effectiveness of this kind of sensor from a space platform is unknown. The magnitude of the K-line emission signal seen from space is contingent on many factors, including the concentration of potassium in the biomass fuel, fire size and intensity as well as atmospheric state. The architecture and preparation of the flight model K-line sensor hardware is described, together with the approach to verification and validation of the sensor characteristics and performance on-orbit.
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    Image quality assessment methods for near-infrared wildfire imagery
    (2022-10) Faniso-Mnyaka, Zimbini; Skosana, Vusi J; Nana, Muhammad A; Magidimisha, Edwin
    Over the past two decades, there has been a surge of interest in the study of image quality assessment due to its broad applicability in many fields. Satellites and other remote sensing applications have been collecting vital data that is utilised to monitor targets or events in varying environmental conditions all over the world. Some of these collections include images of natural disasters and anthropogenic events such as wildfires, floods, and drought, among others. However, appropriate image quality assessment techniques have been lacking for image fusion and other remote sensing applications where the information is not targeting the human visual system. Currently, there are several perceptual image quality assessment methods that can be applied depending on the image sensor type. In this paper, we focus on various no-reference general and specific image quality methods that can be used to evaluate remote sensing images for fire detection. Further, we evaluate the effectiveness of the non-referential image quality techniques applied in the processing of airborne sensor images, notably those for fire detection, and correlate the effectiveness of these techniques to the accuracy of detection. In this paper Image quality assessment (IQA) methods such as entropy, BRISQUE, MUSIQ, exposure, and CPBD are analyzed along with methods for image distortion, i.e., Gaussian blur, and image enhancement such as HE, AHE, and CLAHE. Therefore, the no-reference image quality assessment investigation will contribute to the detection and correction of image quality processing issues in wildfires.
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    A UAV based system for real-time near-infrared monitoring of small-scale wildfires
    (2023) Magidimisha, Edwin; Nana, Muhammad A; Naidoo, Seelenthren; Naidoo, Shrikant V; Faniso-Mnyaka, Zimbini; Skosana, Vusi J
    Wildfires are a global threat that is becoming more severe and widespread due to climate change. These fires not only pose a significant risk to human life, firefighters, and infrastructure, but also endanger forest resources, increase greenhouse gas emissions, and cause huge economic losses. Several researchers have been working to find dedicated solutions for early wildfire detection, tracking, and firefighting assistance. Traditional methods of fire detection have mainly been from fire lookouts in towers, infrared sensors on elevated platforms, surveillance of fires from aircraft, and remote sensing from satellites. Although these techniques have been proven to work in other areas, they are unsuitable or are limited in performance due to various reasons, e.g., human accuracy, sensor field of view limiting coverage to smaller areas, sensor cost-effectiveness, and re-visit time on a satellite. To counteract the problem, a real-time wildfire monitoring system that can detect small-scale wildfire events and that can be used for tactical forest firefighting operations is proposed. The concept takes advantage of vegetation biomass combustion by-products such as the alkali element Potassium (K) that is emitted at the flaming phase of the fire. The technique is specific to the flaming phase of the fire and is not affected by the fire size. It employs two high-resolution, cost-effective complementary metal-oxidesemiconductors (CMOS) with high quantum efficiency within the near-infrared (NIR) spectrum. The sensor uses ultranarrow-band filtering and target-to-background rationing techniques for the detection of vegetation fires. The system is designed to be self-contained, having its supporting power, compact, and lightweight for easy integration on different types and sizes of unmanned aerial vehicles (UAV) to provide realtime detection and support to firefighters while airborne. UAVs can provide a low-cost alternative for the reduction of fire disasters through early detection, reporting, and real-time support for firefighters. This paper presents the experimental results of an NIR optical sensor mounted on a UAV carrier that was used to collect data while flying at low to 200m above ground at the Centurion Grassland Flying Club. The results provide evidence of the presence of K in small-scale actively burning vegetation fires observed at different angles and detectable from a UAV. The results support the use of NIR sensor payload for the detection of small-scale fires from a UAV platform.