The 500-m Moderate Resolution Imaging Spectroradiometer (MODIS) burned area products, MCD45A1, MCD64A1, and a merged product were validated across six study sites in South Africa using independently-derived Landsat burned-area reference data during the fire season of 2007. The objectives of this study were to: (i) investigate the likelihood of the improved detection of small burns through an empirically-derived merged product; (ii) quantify the probability of detection by each product using sub-pixel burned area measures; and, (iii) compare the mean percent concurrence of burned pixels between the standard products over a ten-year time series in each site. Results show that MCD45A1 presented higher detection probabilities (i.e., 3.0%–37.9%) for small fractions ≤50%, whereas MCD64A1 appeared more reliable (i.e., 12.0%–89.2%) in detecting large fractions >50% of a burned MODIS pixel, respectively. Overall, the merged product demonstrated improved detection of the burned area in all fractions. This paper also demonstrates that, on average, >50% of MODIS burned pixels temporally concur between the MCD45A1 and MCD64A1 products in each site. These findings have significant implications for fire monitoring in southern Africa and contribute toward the understanding of the range and of the sources of errors present in the MODIS burned area products.

Orthomosaics derived from consumer grade digital cameras on board unmanned aerial vehicles (UAVs) are increasingly being used for biodiversity monitoring and remote sensing of the environment. To have lasting quantitative value, remotely sensed imagery should be calibrated to physical units of reflectance. Radiometric calibration improves the quality of raw imagery for consistent quantitative analysis and comparison across different calibrated imagery. Moreover, calibrating remotely sensed imagery to units of reflectance improves its usefulness for deriving quantitative biochemical and biophysical metrics. Notwithstanding the existing radiometric calibration procedures for correcting single images, studies on radiometric calibration of UAV-derived orthomosaics remain scarce. In particular, this study presents a cost- and time-efficient radiometric calibration framework for designing calibration targets, checking scene illumination uniformity, converting orthomosaic digital numbers to units of reflectance, and accuracy assessment using in situ mean reflectance measurements (i.e. the average reflectance in a particular waveband). The empirical line method was adopted for the development of radiometric calibration prediction equations using mean reflectance values measured in only one spot within a 97 ha orthomosaic for three wavebands, i.e. red, green and blue of the Sony NEX-7 camera. A scene illumination uniformity check experiment was conducted to establish whether 10 randomly distributed regions within the orthomosaic experienced similar atmospheric and illumination conditions. This methodological framework was tested in a relatively flat terrain semi-arid woodland that is invaded by Harrisia pomanensis (the Midnight Lady). The scene illumination uniformity check results showed that at a 95% confidence interval, the prediction equations developed using mean reflectance values measured from only one spot within the scene can be used to calibrate the entire 97 ha RGB orthomosaic. Furthermore, the radiometric calibration accuracy assessment results showed a correlation coefficient r value of 0.977 (p < 0.01) between measured and estimated reflectance values with an overall root mean square error of 0.063. These findings suggest that given the entire scene being mapped is experiencing similar atmospheric and illumination conditions, then prediction equations developed using mean reflectance values measured in only one spot within the scene can be used to calibrate the entire orthomosaic in semi-arid woodlands. The proposed methodological framework can potentially be tested and adapted for use in large-scale crop mapping and monitoring in precision agriculture, land-use/land-cover classification as well as plant species delimitation, particularly for mapping widespread invasive alien plants such as H. pomanensis.

A new geodetic observatory at Matjiesfontein will house a 1-metre aperture Lunar Laser Ranging (LLR) optical telescope to acquire millimetre Earth-Moon distance measurements. Large optical telescopes utilised for laser ranging observations of Earth-Moon distance, with sub-centimetre level accuracy can suffer from structural deformations induced by thermal variations, wind loadings and/or gravitational forces. These variables need to be measured to enable correction of the resulting pointing errors. This paper presents the proposed locations of temperature sensors on the composite structure of the Hartebeesthoek Radio Astronomy Observatory (HartRAO) LLR 1-metre optical telescope. Furthermore, we describe a mathematical model for (i) obtaining thermal measurements from a network of temperature sensors, (ii) interpolating the temperatures across the telescope composite structure, and (iii) predicting thermally-induced structural deformations. Currently, the available thermal simulation results of the LLR telescope tube assembly indicate isotherms with gradients of about 1°C followed by thermal deformations that vary between 2.9 µm and 40.7 µm along the optical tube axes. The physical implementation of the above mathematical model is part of the next phase of this research work coupled with experiments to derive thermally-induced pointing errors. The errors will be incorporated into the steering control software to compensate for thermally-induced misalignment of the telescope axes.