Browsing by Author "Samarasuriya, C"

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item: Conference-Full-text
Analysis of bulking factor as a basis for royalty calculation in aggregate quarrying in Sri Lanka
(IEEE, 2020-07) Perera, T; Piyarathna, S; Liyanage, I; Panagoda, H; Dharmaratne, P; Samarasuriya, C; Samaradivakara, I; Weeraddana, C; Edussooriya, CUS; Abeysooriya, RP
Sri Lanka hosts a variety of mineral resources and the government grants necessary approvals required for mining. As compensation Government charges a royalty. Currently, in aggregate production in Sri Lanka, an explosivebased equation is used for royalty levy calculation which has not been scientifically established where bulking of the material is not considered. As mineral royalty levy is one of the main revenues of the state, deviations of royalty recovery will influence the economy of the country. The study is being conducted on several A grade quarries, and Total Station surveys were used to obtain 3-dimensional coordinates of the muck pile before and after blasting. These data were used to generate a 3D model of the muck pile and the bench, which was used for the bulk volume calculations with the use of the Surfer 16 software. The in-situ volume of the blasted rock was found by truck weight calculations and both the bulk volume and the In-situ volume were used for Bulking Factor calculations, and Powder Factor calculations. This research will lead to significant alterations in the royalty calculations. This approach with new technology will put the royalty calculation on a scientific putting and elevate the royalty calculation methodology.
item: Conference-Abstract
Investigating the impact of climate change on rainfalltriggered landslides in Kegalle district
(Department of Civil Engineering, 2023-09-27) Gunasinghe, L; Gunawardhana, L; Samarasuriya, C; Wijemanna, A; Mallikarachchi, C; Hettiarachchi, P; Herath, S; Fernando, L
Landslides present a significant peril to lives and economies, notably in Asia where over 18,000 deaths and $8 billion in economic losses occurred due to landslides from 1998 to 2017. These events stem from a range of factors, including steep terrain, geological features, and extreme rainfall. Rainfall, influenced by climate change, emerges as a key factor in increasing landslide vulnerability. The IPCC projects intensified rainfall and droughts due to global warming, heightening landslide risks. Recognising this, the study focuses on the Kegalle District, Sri Lanka, to investigate the impact of climate-induced shifts in rainfall patterns on landslide susceptibility. The findings aim to provide decision-makers with insights for proactive measures. The Kegalle District in Sri Lanka, a landslide-prone area, has experienced an increase in landslides despite a history of fewer occurrences. The study used the HadGEM3-GC31-LL model from CMIP6 to project potential shifts in future rainfall patterns. The baseline period selected for analysis is 1975-2015, while two Shared Socioeconomic Pathways: SSP2-4.5 and SSP5-8.5 were considered for future projections. Statistical downscaling was performed using the Long Ashton Research Station Weather Generator, and missing values (0.2%) were filled using the Multivariate Imputation by Chained Equations method. Daily rainfall data from Ratnapura station was distributed across the study area (Figure 1) using the gridded Climate Hazards group InfraRed Precipitation with Station (CHIRPS) dataset (with a grid resolution of 5 km x 5 km). A Python code generated bias-correction factors for accurate future rainfall projections. Historical landslide events categorised by the NBRO in the 2016-2021 period were correlated with days of excessive rainfall to gauge susceptibility. Figure 2 shows the average number of days with daily rainfall exceeding 73 mm during the 2016-2021 period. The minimum rainfall threshold for triggering past landslides was identified using NBRO data. The number of days above this threshold was used to define the range of days required for triggering landslides, slope failures, and cutting failures (Table 1). Figure 3 shows potential changes in these events from projected rainfall by SSP2-4.5 during the 2031- 2060 period. Results show that the extreme category (4.2-6 days/year) expands throughout the catchment area in the future compared to the observational period. Similar effects were observed in different magnitudes for both SSP scenarios in two different periods (Table 2). The findings of this research concluded that the rainfall effect on landslide susceptibility can be significant and that climate change effects could exacerbate the likelihood of landslides in the future. To enhance the accuracy of the analysis, it is recommended to incorporate additional landslide-triggering factors for the susceptibility analysis.
item: Conference-Full-text
Remote sensing and gis approach to monitor the land-use and land-cover change in Kaduwela metropolitan area
(IEEE, 2022-07) Kanagasundaram, G; Dissanayake, K; Samarasuriya, C; Rathnayake, M; Adhikariwatte, V; Hemachandra, K
This article depicts the impact of Land Use and Land Cover (LULC) change using multi-temporal remotely sensed data in the Kaduwela metropolitan area located in Colombo District for the period between 1997 and 2019. To obtain information from the satellite data, the Maximum likelihood supervised classification technique and post-classification change detection strategy were applied. Besides, Spectral indices were utilized to define the ground truth. Thus, the study area was divided into four main land use/cover classes, and hence five satellite images for the years; 1997, 2007, 2014, 2017, and 2019 with low cloud cover were identified. According to the study, urban development resulted in a significant conversion of vegetation cover to the urban development of around 36 km 2 during the past 22 years. The generated map showed that between 1997 and 2019, the built-up area increased by 43.62 percent whereas vegetation cover decreased by 41.72 percent. The overall precision of the data produced ranged from 72 to 81 percent. The dramatic growth of the urban population will boost the risk of natural environmental diminishing. This study assesses the change in the LULC pattern for the previous 22 years, providing useful information for the urban planners to make sustainable environmental decisions.
item: Article-Full-text
Satellite image band ratio techniques for identifying and visualizing minerals exposure zones in the Kandy district, Sri Lanka
(Faculty of Graduate Studies, 2024) Ravanan, M; Samarasuriya, C; Dassanayake, A
Recent scientific studies are anticipating the development of novel, expeditious, and dependable methodologies for mineral exploration. This emerging need arises from the extensive depletion of major valuable mineral deposits in easily accessible regions. Furthermore, contemporary exploration strategies are increasingly focused on locating deeper mineral deposits in geologically complex and challenging terrains, where accessibility is significantly constrained [1], [2].Geophysical methodologies comprise a range of techniques utilized to acquire insights into the subsurface properties of the Earth. These methods facilitate the acquisition of data from considerable depths, with verification achieved through borehole core sampling [1]. Additionally, remote sensing data can offer valuable insights such as surface material composition and rock types, particularly in areas where vegetation cover is not comprehensive during the reconnaissance surveys [3]. Remote sensing data, including both multispectral and hyper spectral imagery used for mineral exploration does not serve as a replacement for ground truth data, but rather complements it by providing additional information about the region of interest [1],[2],[4]. The identification of potential mineral deposits is facilitated by the examination of available geological data, which includes observations such as specific mineral occurrences within distinct rock types, the distribution of geological structural features, significant alteration zones, deposits forms with high-temperature zones and hydrothermally altered areas [1], [5]. At a regional scale, diverse lithological features such as the textural properties of igneous and sedimentary rocks, structural configurations, and vegetation patterns can be effectively detected through remote sensing. These observations are instrumental in elucidating the geological and ecological framework of an area, thereby contributing to a comprehensive understanding of its natural environment. Integrating remote sensing with field observations and geospatial technologies provides a comprehensive view of landscapes, enhancing geological accuracy and supporting sustainable development. This approach aids informed land use planning and resource management, promoting efficient and sustainable natural resource utilization.
item: Article-Full-text
Stones that stand the test of time: exploring the durability and weathering of metamorphic Rocks of Sri Lanka
(2023-08) Kanagasundaram, G; Dassanayake, A; Jayawardena, C; Samarasuriya, C
Weathering and durability are the key properties of the rock to evaluate the suitability and end-use for different kinds of applications such as building and construction material and engineering structures. Weathering is simply known as the alteration or breaking down of rocks due to air, water, etc. whereas durability of rock can be defined as the ability to resist the weathering to maintain the characteristics of strength under various environmental conditions. To evaluate the strength of rock, the degree of weathering and durability can be used as main indicators[1] as the measure of strength depends on the external force resistance.
item: Article-Full-text
Unlocking the Power of Big Data: How Remote Sensing and Land Zoning Data are Revolutionizing Urban Planning
(2023-08) Senarathna, T; Kanagasundaram, G; Samarasuriya, C
Urbanization is a rapidly growing trend, and cities are facing unprecedented challenges in managing growth, ensuring sustainability, and promoting social equity. Urban planning is a complex and challenging process, as it involves the coordination of various stakeholders and the management of different resources. So, utilizing conventional methods for urban planning can lead to limited data availability, inaccurate data, and a lack of stakeholder engagement, which can affect the quality and effectiveness of the planning process for highly populated areas. There fore, with the advent of big data and remote sensing technology, urban planners now have powerful tools to tackle these challenges. Remote sensing is the use of satellites, aerial imagery, and other sensor-based technologies to gather data about the earth’s surface. Land zoning data, on the other hand, provides information about the designated use of land in each area. When combined, these two types of data can provide a comprehensive view of land use, environmental conditions, and social dynamics. One of the main benefits of remote sensing and land zoning data is their ability to provide real-time monitoring of urbanization patterns. By tracking changes in land use and environmental conditions, urban planners can make informed decisions about infrastructure development, environmental protection, and social equity. This information can also be used to anticipate future trends and respond proactively to emerging challenges.