Browsing by Author "Abudu, Dan"

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    Estimating urban heat island intensity using remote sensing techniques in Dhaka City
    (International Journal of Scientific & Engineering Research, 2017-04) Parvin, Nigar Sultana; Abudu, Dan
    This study assessed the effects of urban heat island in Dhaka city, Bangladesh from 2002 to 2014 using remote sensing techniques. Land cover changes were characterized over a twelve year period with keen interested on urban expansion and the resulting impacts created by these changes on the land surface temperatures investigated. The study also compared the land surface temperature and ground station temperature data to validate the surface temperature in Dhaka. Maximum likelihood supervised classification method was used for the land cover classification resulting in a classification accuracy of 86.5% and 90.7% for 2002 and 2014 respectively. Remarkable change in land cover was observed in built-up areas which increased by 21% of the total land area from 74.12 to 135.36 square kilomentres in 2002 and 2014 respectively. Combined end member selection and linear mixture model techniques were used to estimate the surface emissivity of the land surface properties. The obtained surface emissivity together with the brightness temperatures of the thermal bands were then used to calculate the land surface temperature. Results showed that land surface temperature increased throughout the study area. Temperature ranges of 28.5°C to 35.4°C were observed in 2002 and 37.9°C to 40.1°C in 2014. The difference between ground-based temperature and the satellite derived temperatures for the ground weather station were +1.8°C and +2.7°C in 2002 and 2014 respectively. This margin of difference is attributed to sensor calibration errors. The land surface temperature increased across all land cover types over the twelve year period indicating existence and potential effects of urban heat highland in the Dhaka city. The results indicates that there is urgent need for the city authority to implement measures that must monitor and contain the resulting effects on the city population and infrastructure.
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    Reviewing the pertinence of Sentinel-1 SAR for urban land use land cover classification
    (International Journal of Scientific & Engineering Research, 2020-05) Abudu, Dan; Parvin, Nigar Sultana; Andogah, Geoffrey
    Conventional approaches for urban land use land cover classification and quantification of land use changes have often relied on the ground surveys and urban censuses of urban surface properties. Advent of Remote Sensing technology supporting metric to centimetric spatial resolutions with simultaneous wide coverage, significantly reduced huge operational costs previously encountered using ground surveys. Weather, sensor’s spatial resolution and the complex compositions of urban areas comprising concrete, metallic, water, bare- and vegetation-covers, limits Remote Sensing ability to accurately discriminate urban features. The launch of Sentinel-1 Synthetic Aperture Radar, which operates at metric resolution and microwave frequencies evades the weather limitations and has been reported to accurately quantify urban compositions. This paper assessed the feasibility of Sentinel-1 SAR data for urban land use land cover classification by reviewing research papers that utilised these data. The review found that since 2014, 11 studies have specifically utilised the datasets. The reviewed studies demonstrated that, features representing urban topography such as morphology and texture can easily and accurately be extracted from Sentinel-1 SAR and subjected to state-of-the-art classification algorithms such as Support Vector Machine and ensemble Decision Trees for accurate urban land use land cover classification. Development of robust algorithms to deal with the complexities of SAR imagery is still an active research area. Furthermore, augmentation of SAR with optical imagery is required especially for classification accuracy assessments.
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    Spatial assessment of urban sprawl in Arua Municipality, Uganda
    (The Egyptian Journal of Remote Sensing and Space Science, 2019-12) Abudu, Dan; Echima, Robert Azo; Andogah, Geoffrey
    Arua Municipality is one of the regional municipalities that has been earmarked for transformation to city status. Its population has been growing at rate of 3% per annum 1% higher than the capital, Kampala. Urbanisation provides economic opportunities. However, it also lead to emergence of unplanned urban settlements and urban sprawl. This paper applied remote sensing and geographical information system techniques to map land cover changes from 2001 to 2016, quantify urban sprawl within the period and estimate the urban growth pattern up to 2031. TerrSet’s Land Change Modeller has been used to model the urbanisation and Markov Chain matrices used to predict future changes in the urban composition. Land cover classification accuracy of 85% in 2001, 84% in 2010 and 89.2% in 2016 were obtained. From 2001 to 2016, the four land cover types considered, contributed a total of 11.5% to the composition of built-up area with agricultural land cover type contributing the most at 7.4%. Results of urbanisation analyses indicated that in 2001, 18.2% of the total area were built-up. This increased to 28.8% in 2010 and 40.9% in 2016. Urbanisation is predicted to increase to 57.4% by the year 2031. This prediction indicates that agricultural land cover will be most negatively affected at _10% loss rate while built-up areas will increase by 6%. While urbanisation continues to increase at this rate, the municipal authority must implement sustainable measures to protect agricultural lands and ecosystems against the land consuming urbanisation.