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The study evaluates the performance of the Conformal Cubic Atmospheric Model (CCAM) when simulating an urban heat island (UHI) over the city of eThekwini, located along the southeast coast of South Africa. The CCAM is applied at a grid length of 1 km on the panel with eThekwini, in a stretched-grid mode. The CCAM is coupled to the urban climate model called the Australian Town Energy Budget (ATEB). The ATEB incorporates measured urban parameters including building characteristics, emissions, and albedo. The ATEB incorporates the land-cover boundary conditions obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite. The CCAM configuration applied realistically captured the orientation of the city and land-cover types. Simulations of meteorological variables such as temperatures and longwave radiation reproduced the spatial distribution and intensity of the UHI. Results show that the UHI is stronger during summer and weaker in all other seasons. The UHI developed because of natural factors (e.g., distribution of longwave radiation) and human factors (e.g., urban expansion, an increase in anthropogenic emissions, and additional heating). Because of the city's location along the coast, the UHI simulation could be weakened by atmospheric circulations resulting from land and sea breezes. Mitigation methods such as applying reflective paints and revegetation of the city may increase albedo and latent heat fluxes but reduce the sensible heat fluxes and weaken the UHI. However, the UHI may not be completely eliminated since natural factors and emissions constantly influence its development. Significance Statement: The outcome of this study could be particularly valuable for municipalities in their disaster management planning since the occurrence of UHIs can cause heat-related diseases such as heatstrokes and even fatalities, especially for the elderly, in cities. Increases in temperatures also lead to higher demand for air conditioners, which in the long term lead to higher demand and pressure on the electricity grid system as well as increased costs for the individual. As higher temperatures increase heatwave events, increases in anthropogenic emissions also result in degraded air quality that impacts health. UHIs impact human lives and can cause deterioration in health when individuals experience high temperatures in summer. Warmer temperatures also reduce energy demand (and in the long term assist with global environmental restoration). [ABSTRACT FROM AUTHOR]

The tree Acacia mearnsii is native to south-eastern Australia but has become an aggressive invader in many countries. In South Africa, it is a significant threat to the conservation of biomes. Detecting and mapping its early invasion is critical. The current ground-based methods to map A. mearnsii are accurate but are neither economical nor practical. Remote sensing (RS) provides accurate and repeatable spatial information on tree species. The potential of RS technology to map A. mearnsii distributions remains poorly understood, mainly due to a lack of knowledge on the spectral properties of A. mearnsii relative to co-occurring native plants. We investigated the spectral uniqueness of A. mearnsii compared to co-occurring native plant species within the South African landscape. We explored full-range (400–2500 nm), leaf and canopy hyperspectral reflectance of the species. The spectral reflectance was collected biweekly from December 23, 2016 and May 31, 2017. We conducted a time series analysis, to assess the effect of seasonality on species discrimination. For comparison, two classification models were employed: parametric interval extended canonical variate discriminant (iECVA-DA) and nonparametric random forest discriminant classifiers (RF-DA). The results of this paper suggest that phenology plays a crucial role in discriminating between A. mearnsii and sampled species. The RF classifier discriminated A. mearnsii with slightly higher accuracies (from 92% to 100%) when compared with the iECVA-DA (from 85% to 93%). The study showed the potential of RS to discriminate between A. mearnsii and co-occurring plant species. [ABSTRACT FROM AUTHOR]