Browsing by Subject "Land-Cover Classification"

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    Regional dust emission thresholds from croplands in central South Africa
    (2026) Adesuyi, Ayodeji; Eckardt, Frank
    The continuous, pronounced supply of fine dust material originating from extensive agricultural farmland poses a major threat to topsoil quantity, quality, and sustainable food production, as well as other impacts on Earth's systems. The increase in dust emission in these agricultural areas is primarily attributed to surface dryness resulting from rising temperatures caused by climate change, global warming, and land degradation. The need to account for the surface variability is crucial to our comprehension of dust emission processes. The Free State and North West provinces have been identified as significant sources of agricultural dust in South Africa. This study uses an observation approach to characterise and examine physical surface controls (drought, soil moisture, vegetation, and surface roughness) that promote dust emission, using satellite remote sensing data, as well as to establish the dust event observations on eight 1-degree tiles of agricultural farmland, also referred to as the Main Emission Region (MER). Time series data for drought, soil moisture, vegetation, crop type data and surface roughness data were generated and examined over 11 years from 2006 to 2016, to analyse the spatial-temporal variation of the datasets, which corresponds to the dust event observation available. The study employed a descriptive statistical method to examine the temporal variations of the datasets as indicators of the likelihood of potential dust emissions. From the drought and soil moisture dataset, the monthly Standardised Precipitation Index (SPI), Standardised Precipitation Evapotranspiration Index (SPEI) and soil moisture index (SMI) were generated. The surface roughness data (Albedo: MCD43A1) was analysed and modelled using Chappell's “Albedo approach”, to obtain the best aerodynamic roughness (uS*/Uh). A supervised decision tree land cover classification technique was used to extract the land cover classes, while the vegetation crop type data was already classified. Findings from the study indicate that dry conditions for SPI, SPEI and SMI are highest in October and November, while surface roughness is lowest in August in the MER. The months of August, September, October, and November were identified as high dust emission months. The seasonal variation indicates dry conditions in most seasons, which corresponds with dust seasons, except for a slightly insignificant wet condition observed in summer and the prolonged drought or dry condition years matched with high to medium dust emission years. During these latter years, it was discovered that there was a decline in maize cover (1.2–0.6 million hectares) and an increase in fallow land (140–790 thousand hectares), especially between 2015 and 2016. This study created a combined threshold that categorised the indicators into low, medium, and high dust emission thresholds. Individual thresholds for dust production were also established. Should we have these values, the likelihood of dust emission increases with the availability of dust.