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EN
The main objective of this study is to evaluate the changes in the hydrographic network of Słowiński National Park. The authors analysed the changes occurring in the drainage network due to limited maintenance in this legally protected natural area. To accomplish this task, elaborations prepared on the basis of aerial photographs were used: an orthophoto map from 1996, hyperspectral imaging from June 2015, and a digital terrain model based on airborne laser scanning (ALS) from June 2015. These spatial data resources enabled the digitisation of the water courses for which selected hydro-morphological features had been defined. As a result of analysing the differences of these features, a quality map was elaborated which was then subjected to interpretation, and the identified changes were quantified in detail.
EN
The Lagos Lagoon is under increased pressure from growth in human population, growing demands for natural resources, human activities, and socioeconomic factors. The degree of these activities and the impacts are directly proportional to urban expansion and growth. In the light of this situation, the objectives of this study were: (i) to estimate through satellite imagery analysis the extent of changes in the Lagos Lagoon environment for the periods 1984, 2002, 2013 and 2019 using Landsat-derived data on land cover, Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI); and (ii) to evaluate the relationship between the derived data and determine their relative influence on the lagoon environment. The derived data were subjected to descriptive statistics, and relationships were explored using Pearson’s correlation and regression analysis. The effect of land cover on LST was measured using the Contribution Index and a trend analysis was carried out. From the results, the mean LSTs for the four years were 22.68°C (1984), 24.34°C (2002), 26.46°C (2013) and 28.40°C (2019). Generally, the mean LSTs is in opposite trend with the mean NDVIs and EVIs as associated with their dominant land cover type. The strongest positive correlations were observed between NDVI and EVI while NDVI had the closest fit with LST in the regression. Built-up areas have the highest contributions to LST while vegetation had a cooling influence. The depletion in vegetative cover has compromised the biodiversity of this environment and efforts are required to reverse this trend.
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