Search Results (3)

Mapping the spatial and temporal dynamics of tropical herbaceous wetlands is vital for a wide range of applications. Inundated vegetation can account for over three-quarters of the total inundated area, yet widely used EO mapping approaches are limited to the detection of open water bodies. This paper presents a new wetland mapping approach, RadWet, that automatically defines open water and inundated vegetation training data using a novel mixture of radar, terrain, and optical imagery. Training data samples are then used to classify serial Sentinel-1 radar imagery using an ensemble machine learning classification routine, providing information on the spatial and temporal dynamics of inundation every 12 days at a resolution of 30 m. The approach was evaluated over the period 2017–2022, covering a range of conditions (dry season to wet season) for two sites: (1) the Barotseland Floodplain, Zambia (31,172 km²) and (2) the Upper Rupununi Wetlands in Guyana (11,745 km²). Good agreement was found at both sites using random stratified accuracy assessment data (n = 28,223) with a median overall accuracy of 89% in Barotseland and 80% in the Upper Rupununi, outperforming existing approaches. The results revealed fine-scale hydrological processes driving inundation patterns as well as temporal patterns in seasonal flood pulse timing and magnitude. Inundated vegetation dominated wet season wetland extent, accounting for a mean 80% of total inundation. RadWet offers a new way in which tropical wetlands can be routinely monitored and characterised. This can provide significant benefits for a range of application areas, including flood hazard management, wetland inventories, monitoring natural greenhouse gas emissions and disease vector control. Full article

Currently, the negative effects of unified and intensive agriculture are of growing concern. To mitigate them, the possibilities of using local but nowadays underused crop for food production should be more thoroughly investigated and promoted. The soybean is the major crop cultivated for vegetable oil production in Zambia, while the oil production from local oil-bearing plants is neglected. The chemical composition of oils and cakes of a three traditional oil plant used by descendants of the Lozi people for cooking were investigated. Parinari curatellifolia and Schinziophyton rautanenii oils were chiefly composed of α-eleostearic (28.58–55.96%), linoleic (9.78–40.18%), and oleic acid (15.26–24.07%), whereas Ochna serrulata contained mainly palmitic (35.62–37.31%), oleic (37.31–46.80%), and linoleic acid (10.61–18.66%); the oil yield was high (39–71%). S. rautanenii and O. serrulata oils were rich in γ-tocopherol (3236.18 μg/g, 361.11 μg/g, respectively). The O. serrulata oil also had a very distinctive aroma predominantly composed of p-cymene (52.26%), m-xylene (9.63%), γ-terpinene (9.07%), o-xylene (7.97), and limonene (7.23%). The cakes remaining after oil extraction are a good source of essential minerals, being rich in N, P, S, K, Ca, and Mg. These plants have the potential to be introduced for use in the food, technical, or pharmaceutical industries. Full article

Knowledge of the location and extent of surface water and inundated vegetation is vital for a range of applications including flood risk management, biodiversity monitoring, quantifying greenhouse gas emissions, and mapping water-borne disease risk. Here, we present a new tool, TropWet, which enables users of all abilities to map wetlands in herbaceous dominated regions based on simple unmixing of optical Landsat satellite imagery in the Google Earth Engine. The results demonstrate transferability throughout the African continent with a high degree of accuracy (mean 91% accuracy, st. dev 2.6%, n = 10,800). TropWet demonstrated considerable improvements over existing globally available surface water datasets for mapping the extent of important wetlands like the Okavango, Botswana. TropWet was able to provide frequency inundation maps as an indicator of malarial mosquito aquatic habitat extent and persistence in Barotseland, Zambia. TropWet was able to map flood extent comparable to operational flood risk mapping products in the Zambezi Region, Namibia. Finally, TropWet was able to quantify the effects of the El Niño/Southern Oscillation (ENSO) events on the extent of photosynthetic vegetation and wetland extent across Southern Africa. These examples demonstrate the potential for TropWet to provide policy makers with crucial information to help make national, regional, or continental scale decisions regarding wetland conservation, flood/disease hazard mapping, or mitigation against the impacts of ENSO. Full article