Cloud cover constitutes a major obstacle to land cover classification in the humid tropical regions when using optical remote sensing such as Landsat imagery. The advent of freely available Sentinel-1 C band synthetic aperture radar (SAR) imagery offers new opportunities for land cover classification in frequently cloud covered environments. In this study, we investigated the utility of Sentinel-1 for extracting land use land cover (LULC) information in the coastal low lying strip of Douala, Cameroon when compared with Landsat enhanced thematic mapper (TM). We also assessed the potential of integrating Sentinel-1 and Landsat. The major LULC classes in the region included water, settlement, bare ground, dark mangroves, green mangroves, swampy vegetation, rubber, coastal forest and other vegetation and palms. Textural variables including mean, correlation, contrast and entropy were derived from the Sentinel-1 C band. Various conventional image processing techniques and the support vector machine (SVM) algorithm were applied. Only four * Corresponding author. M. L. Fonteh et al. 496 land cover classes (settlement, water, mangroves and other vegetation and rubber) could be calibrated and validated using SAR imagery due to speckles. The Sentinel-1 only classification yielded a lower overall classification accuracy (67.65% when compared to all Landsat bands (88.7%)). The integrated Sentinel-1 and Landsat data showed no significant differences in overall accuracy assessment (88.71% and 88.59%, respectively). The three best spectral bands (5, 6, 7) of Landsat imagery yielded the highest overall accuracy assessment (91.96%). in the study. These results demonstrate a lower potential of Sentinel-1 for land cover classification in the Douala estuary when compared with cloud free Landsat images. However, comparable results were obtained when only broad classes were considered.
A study based on the spatial variability and contamination levels of fresh water resources by saline intrusion was conducted in the Douala coastal area. The study was aimed at highlighting the associations between major ions in ground water from which cause-effect relationships could be inferred. Water samples were collected from 19 stations. 3 stations were selected from the mangrove area and 16 stations were selected from the rest of the area partitioned into four transects (coastal transect, inner transect 1, inner transect 2 and inner transect 3). Sampling was done repeatedly during the dry season and these samples were analysed for physico-chemical parameters. Results show that the samples were acidic (pH: 4.7 -6.7). Total dissolved solids (TDS) and electrical conductivity (EC) values ranged between 70.3 -3703 mg/L and 136.4 -7333 μS/cm respectively indicating medium salt enrichment and brackish waters. High temperatures (T˚C) and low dissolved oxygen (DO) values of 26˚C -30.3˚C and 0.96 -3.9 mg/L respectively were observed and this could be interpreted as the acceleration of biological and chemical processes of ground water resources. Major ions were within the WHO limits except for Ca 2+ (20.3 -85 mg/L) and Mg 2+ (6.6 -49.6 mg/L) respectively whose concentrations were slightly higher. Ca -SO − , 26.3% Ca 2+ -Cl − and 10.5% Na + -Cl − . 89.5% of the water types had secondary salinity implying that anthropogenic sources were the source of salinity. The water was not fit for drinking. The values calculated for percentage sodium and sodium absorption ratio to determine its suitability for agricultural purposes revealed that 63.15%, 15.5%, 5.3% and 15.8% of sampled water were excellent, good, doubtful and unsuitable respectively for irrigation purposes. The need for water resource monitoring and forecasting regarding deterioration in quality is imperative before hazards of the rise in sea level arise.
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