Browsing by Author "Jayawardena, CL"

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item: Conference-Full-text
Analysis of beachrock samples along Southern and Western coasts of Sri Lanka by spectroscopic methods
(Department of Earth Resources Engineering, 2019-08) Edirisooriya, KVUI; Thilakarathna, MADP; Vijitha, T; Dassanayake, ABN; Jayawardena, CL; Dissanayake, DMDOK; Samaradivakara, GVI
Beachrocks are sedimentary structures commonly observed where there is warm sea water in tropical and subtropical regions as a result of cementation by CaCCb of coastal sediments in the tidal zone. Comprehensive studies have been carried out to determine the formation mechanisms of beachrocks specially Japan to improve an alternative countermeasure against erosion by man-made rocks. When focusing on formation mechanism of beachrocks elemental and mineralogical composition is vital. Considering this important application, we used spectroscopic techniques to understand composition of beachrocks in southern coastal region between Ahangama to Kaikawala and Uswetakeiyawa in the western coastal region of Sri Lanka. The presence of minerals in beach rock samples in southern coast were identified by FT-IR spectroscopic technique. The constituents of minerals present in the beach rocks are further confirmed by XRD technique. Elemental concentrations of beach rock samples have been analyzed using technique of WDXRF spectrometry. Uswetakeiyawa beachrock was mainly analyzed by using EDX in SEM. Beachrocks in southern coasts is comprise higher percentage of Aragonite which is the polymorph of CaCCb, frequently founded in most of the sites in the world. Further the composition shown similarities with Indian (Tiruchendru) and Japan (Okinawa) beachrock occurrences. Comparative to the composition of southern coast beachrock, XRD analysis did not indicate any CaC03 polymorphs Uswetakeyyawa, beachrocks. Instead it indicated the presence of Kutnohorite (Ca(Mn,Mg,Fe)(C03)2).
item: Conference-Full-text
Analysis of physical and mineralogical properties of aggregate on strength and durability of asphalt concrete
(Department of Earth Resources Engineering, 2018-08) Lakshan, LPS; De Silva, SHSN; Kapilaratne, RDMCLB; Chaminda, SP; Jayawardena, CL; Abeysinghe, AMKB; Samaradivakara, GVI
Asphalt is made by mixing aggregates, filler and binder materials together according to pre-determined ratios. Out of the total asphalt weight, 94% to 95% consists of aggregate. It is not surprising that the performance of asphalt concrete mixtures is influenced by the properties of their aggregate blends, such as gradation, shape (angularity and elongation), texture (roughness) and mineralogy. In asphalt concrete, numerous studies have related gradation, shape, and texture of the aggregate to durability , workability , shear resistance, tensile strength, stiffness, fatigue response, rutting susceptibility, and optimum binder content of the mixtures. However, a few has described about the influence of mineralogy on characteristics of asphalt. This research has been carried on to make an effort to fill that gap between the aggregate mineralogical properties and the characteristics of asphalt concrete. Under the research, a number of representative aggregate samples were collected from different quarry sites which are currently used in the process of manufacturing asphalt all over the country. The samples were subjected to a series of tests in order to determine both physical and mineralogical properties. Marshall stability and flow values of the asphalt mixtures were determined to assess the properties of asphalt made using the collected aggregates. Finally, using test results, an analysis was conducted followed by the conclusions made using the test results, a set of recommendations were proposed.
item: Conference-Full-text
Applicability of a neural network model for forecasting ground vibrations in opencast mining
(Department of Earth Resources Engineering, 2018-08) Dassanayake, SM; Dushyantha, NP; Jayawardena, CL; Abeysinghe, AMKB; Samaradivakara, GVI
Ground vibration and air-blast over pressure are two significant undesirables, among many environmental risks, in open-pit mining . Gaining control over the ground vibrations generated by rock blasts had been difficult mainly due to the complexities involved with local geology and properties of the blast. Accordingly, existing empirical equations are only capable of making vague approximations on the vibration frequencies based on site-specific parameters and attenuation factor. Therefore, the available models cannot be generalized to different geo-mining environments to obtain sufficiently reliable forecasts for ground vibration and airblast overpressure. Hence, this study attempts to employ an Artificial Neural Network (ANN) based feed-forward back-propagation algorithm to train a model, using a supervised learning technique to forecast possible ground v i b r a t i on frequencies. The main in-put parameters included in the model are noise level, number of boreholes per single blast, depth and diameter of a borehole, charge per hole, number of delays of the Electric Detonators (ED) in a single blast, burden and spacing. Airblast overpressure and the ground vibration levels will be the output by ANN model. The model was validated using 50 datasets, which were obtained from a quarry site. After adequate training, the model can determine Peak Particle Velocity (PPV) and frequency of Ground Vibrations (GV) for new input parameters with a statistically significant confidence level.
item: Conference-Full-text
Applicability of tunnel muck as an alternative for fine aggregates in cement concrete
(Department of Earth Resources Engineering, University of Moratuwa, 2021-12) Ariyasena, HHS; Sampath, BA; Wickramasooriya, MDJP; Dissanayake, DMDOK; Jayawardena, CL
One of the recent applications of Tunnel boring Machines (TBM) in Sri Lanka is Uma Oya Multipurpose Development Project (UOMDP). During rainy periods, the washed tunnel muck particles sediment in low agricultural lands forming infertile soil. It mainly affects the agricultural sector in the respective area of the country. Therefore, it appears that there is a need to study the reuse of the tunnel muck as an alternative for sand which is a very expensive construction material these days, or any other field as a useful material in an effective manner. The objective of this study is to determine the applicability of tunnel muck as an alternative for sand in concrete as fine aggregate. The material properties of tunnel muck were analysed. Water absorption and workability were higher in the concrete mixed with tunnel muck because the tunnel muck particles are finer than normal sand particles. It was observed that there was a slight decrease in the compressive strength of the concrete casted with tunnel muck. However, the compressive strength could be increased with higher cement content in the concrete. Furthermore, the mix designs with adjusted values were proposed for the concrete mixed with tunnel muck as fine aggregates.
item: Conference-Full-text
Application of GPR to identify carbonate rock cavities related to ground subsidence in Matale, Sri Lanka
(Department of Earth Resources Engineering, 2018-08) De Silva, MSTL; Chiyamvarnan, K; Niroshini, R; Abeysinghe, AMKB; Jayawardena, CL; Abeysinghe, AMKB; Samaradivakara, GVI
Cavity formation within the rocks result in ground subsidence in the regions where carbonate rocks are predominantly present. Identification of ground subsidence potential areas and the probability of such incidents is a challenge without detailed information about the subsurface. Dorakumbura in Matale, Sri Lanka is one such area which faced multiple ground subsidence incidents that demands the investigation of subsurface profile. This study uses Ground Penetrating Radar (GPR) to locate the subsurface cavities in order to create a cavity profile for the Dorakumbura area using 1D and 2D trace analysis of the radargrams. Cavities were identified and analyzed and the results reveal the existence of cavities mostly below the depth of 15 m. Comparison of GPR survey results with the well log data in the region was equivalent. The same methodology is expected to be used in similar regions to identify the presence of cavities which can result in future ground subsidence. It can also assist in suitable site selection without ground subsidence hazards, for the construction and development activities in regions underlying carbonate rocks in Sri Lanka.
item: Conference-Full-text
Appraisal of electrode configuration characteristics in resistivity surveying
(Department of Earth Resources Engineering, 2019-08) Kankanamge, BU; Chathuranga, SMS; Ruwanika, ILD; Palamure, PK; Abeysinghe, AMKB; Samaradivakara, GVI; Jayawardena, CL; Dissanayake, DMDOK; Samaradivakara, GVI
Non-destructive subsurface exploration methods could reveal subterranean characteristics with minimal consumption of time and resources. However, validity of such interpretations could vary depending on the appropriate use of the controllable parameters in the geophysical method, with respect to the subsurface complexities. Accordingly, this study evaluates the sub subsurface characteristics of several locations revealed by the interpretation of resistivity data to understand the performance of different electrode configurations used in resistivity surveying. The electrode spacings maintained at each configuration was also critically assessed to identify the most appropriate for a particular instance of surveying. Furthermore, subsurface profiles were computed using three different interpretation methods to identify any influences from the interpretation method on the accuracy of the resultant profile. The results reveal a strong dependency of interpretations on the array configuration and maintained electrode spacing. And it was determined a suitable electrode spacing for improved subsurface interpretation. In order to improve accuracy of interpretations, it also suggests the need of developing an upper limit for current electrode spacing (AB) of the Schlumberger Array Configuration, given the general electrode spacing is maintaining a lower limit as AB > 5 (potential electrode spacing).
item: Conference-Full-text
Assessment of rehabilitation options for environmental impacts of abandoned mines
(Department of Earth Resources Engineering, University of Moratuwa, 2021-12) Kavirathne, SR; Udayanga, RI; Keerthi, T; Gunawardana, ADTJ; Chaminda, SP; Jayawardena, CL; Dissanayake, DMDOK; Jayawardena, CL
The quarries which are abandoned ceasing operations without a proper closure plan cause negative impacts on the environment and also risk for the health and safety of society and the economy. This research focused on the environmental aspects that are affected by abandoned quarries and a sustainable methodology to design future land use. The objective of this research is to introduce a quarry rehabilitation method that is effective and has a positive impact on the environment, and applicable for abandoned quarries in Sri Lanka. In this respect, the district of Colombo has been chosen due to its importance in social and economic aspects. The research was conducted by identifying abandoned quarries through remote sensing and geographic information system technique (RS & GIS) analysis of satellite images of the concerned area. Prioritised two quarries among identified quarries for further analysis and suggested possible rehabilitation options. According to the land use analysis around the two quarries, the better rehabilitation option is to transform the lands into a vegetation area.
item: Conference Full-text
Assessment of seasonal impacts on groundwater quantity and quality in upstream of Malwathu Oya Basin
Madhushankha, JML; Madhuwan, ARB; Menan, P; Chaminda, SP; Abeysinghe, AMKB; Jayawardena, CL; ; Abeysinghe, AMKB; Dassanayake, ABN; Elakneswaran, Y
Malwathu Oya Basin which covers 2350km2 located in Anuradhapura district is considerably populated and the safety and the available quantity of water is crucial for the people. Water samples were collected from selected locations during South- West monsoon period, Second Inter monsoon period and North-East monsoon period from September 2016 to March 2017. The samples were analysed for pH, turbidity, conductivity, fluoride, chloride, magnesium and calcium as basic drinking water quality parameters. Only the shallow regolith aquifers are considered for the study. The groundwater quality variation of the area shows a considerable variation from dry season to rainy season in general water quality of the area, and is in acceptable limit for most of the basic parameters. With the seasonal changes Fluoride and Chloride content is higher than permissible limits in some areas.
item: Conference-Full-text
Assessment of the effect of Aruwakkalu waste dump on surrounding water resources
(Department of Earth Resources Engineering, University of Moratuwa, 2021-12) Chirantha, D; Herath, HMDK; Chandrapala, HMNI; Chaminda, SP; Dassanayake, ABN; Jayawardena, CL; Dissanayake, DMDOK; Jayawardena, CL
In developing countries like Sri Lanka, waste management is a vital necessity. Solid waste dumps play a major role in handling waste in most countries. These solid waste dumps can cause severe environmental pollution via leachate generation and transport of toxic material along with both surface and underground water flows. The Aruwakkalu waste dump, which is the subject of the study, is a sanitary landfill situated in Puttalam district, Sri Lanka. The landfill is planned to receive and store municipal solid waste (MSW) from Colombo metropolitan area. Locations for these waste dumps must be selected strategically to minimise the risk of contamination of the surrounding environment. A distributed hydrological model was used to determine the effect of rainfall, evapotranspiration, and surface runoff on the site. It identified the direction of the water flow through the waste dump. The analyses have illustrated that the area receives lesser rainfall and a higher rate of evapotranspiration. The hydrological analysis illustrates the water flow direction from the waste dump to the outside is towards the West and away from the nearby settlement areas. The results were used to assess the effect of the waste dumpsite on the surrounding water resources.
item: Article-Abstract
Bibliometric analysis of grey literature on the Bolgoda ecosystem with special reference to theses and dissertations
(Department of Wildlife Conservation, Sri Lanka, 2023-10-18) Jayawardena, CL; Seneviratne, TM
Conservation of ecosystems such as Bolgoda is crucial in achieving sustainable development goal 11 – Make cities inclusive, safe, resilient, and sustainable. To conserve such valuable ecosystems, the importance of reviewing research has been highlighted. Grey literature such as theses and dissertations are important sources of information since they include valuable context-specific local information not published in conventional scientific publications. Hence this study attempted to carry out a bibliometric analysis of theses and dissertations related to the Bolgoda ecosystem. Keyword searches were conducted across various academic platforms and repositories, seeking records related to the Bolgoda Ecosystem up to the year 2022. Bibliographic details and subject areas were recorded, with particular attention to the frequency of the term "Bolgoda" in retrieved documents. The study identified a total of 45 theses and dissertations related to the Bolgoda ecosystem, with 11 from foreign institutions and the University of Moratuwa contributing the highest number (16) among local universities. The majority were Master of Science (MSc) theses (58%), followed by Ph.D. theses (18%), with 25 documents originating from Taught Postgraduate programs. Categorization of the research according to Millennium Ecosystem Services (MES) revealed that the majority focused on Regulating services (e.g., water), followed by Provisional services (e.g., food) and Cultural services (e.g., aesthetic and recreational). Notably, documents with restricted access had an average of 3.56 occurrences of the word "Bolgoda," while open-access documents had 20.2 occurrences. This bibliometric analysis provided a comprehensive overview of Bolgoda ecosystem-related research, highlighting a concentration on certain ecosystem services. The study emphasizes the need to expand local research into less-explored areas to effectively manage the Bolgoda ecosystem and work towards achieving sustainable development goals.
item: Conference-Full-text
Characterisation of coal fly ash for potential wastewater treatment opportunities
(Department of Earth Resources Engineering, University of Moratuwa, 2021-12) Pannilarathne, IE; Sandaruwan, MGL; Mathissan, P; Jayawardena, CL; Fernando, WAM; Dissanayake, DMDOK; Jayawardena, CL
Lakvijaya coal power plant, which is in Norochcholai, Puttalam District, Sri Lanka, is the largest coal power plant in Sri Lanka. It annually produces about 150,000 tonnes of fly ash (FA) as waste, and the management of it is a pressing concern. Various studies have been conducted to valorise FA in a useful manner without simply dumping it into the nearby lands. To this end, we propose the utilisation of FA in wastewater treatments to adsorb heavy metal ions in wastewater to promote environmental sustainability. The direct application of FA for that purpose may be questionable due to the contaminants present in the FA; however, it is reported commercially. Therefore, we attempt to initiate a preprocessed preparation route to ensure the leachate contains fewer contaminants compared to the use of raw FA. Washing is a commonly used preliminary pre-processing step, though it is not studied extensively in the literature with reference to the FA. Herein, we aimed to study the effects of the number of washing cycles and temperature on the characteristics of the FA. With the results, we could conclude that washing is an effective means of preprocessing to alleviate the contaminants of FA, en route for wastewater treatment.
item: Conference-Full-text
Characterisation of sediment deposition of Bolgoda lake using acoustic and sampling methods
(Department of Earth Resources Engineering, University of Moratuwa, 2021-12) Jayasooriya, SPND; Fernando, SFRS; Priyantha, HNL; Vijitha, AVP; Premasiri, HMR; Samaradivakara, GVI; Dissanayake, DMDOK; Jayawardena, CL
Bolgoda Lake is one of the main water resources in the western province, which has two major basins explained as Bolgoda south and north lakes. Lake sedimentation is a serious dilemma for water scarcity, productivity, and flooding effect. So, identification of sediment characteristics is most critical. The attempt of this study is to identify the sedimentation pattern, sediment type, and mineral composition of the sediment from the data collected from core sampling, grab sampling, and the bathymetric data obtained from spot depth eco sounder that combines with Magellan 510. Hence, grain size distribution (GSD), scanning electron microscope (SEM), and bathymetric surveys were utilised to recognise sediment type, heavy metal composition, and sedimentation pattern, respectively. These analyses revealed that bottom sediment has poorly sorted, very fine skewed, physical characteristics have statistical distribution and discover the sediment type as sandy silt. Also, bathymetric analysis upholds the sedimentation pattern that accumulates sediment from the left bank to the right bank of the Bolgoda lake via the water column and to identify the sediment distribution along the lake bottom.
item: Conference-Abstract
Comparative analysis of water hyacinth dynamics in North Bolgoda Lake, Sri Lanka: a classification based on high-resolution aerial imagery and satellite-imagery
(Department of Earth Resources Engineering, 2023-08-28) Dawalagala, HS; Radampola, A; Gowsigan, PT; Chaminda, SP; Dassanayake, SM; Jayawardena, CL
Water hyacinth (WH) is an invasive aquatic plant that has established its presence in tropical and subtropical regions around the globe. Its widespread existence has resulted in societal, economic, and ecological impacts that are mostly intolerable. Understanding and monitoring the spatial and seasonal dynamics of WH in the respective environments could provide insights to mitigate its environmental impact. This study attempts to identify seasonal patterns of WH within north Bolgoda Lake over four years (2019-2022). The methodology includes a pixel-based random forest (RF) classification utilising five distinct spectral indices in conjunction with raw Sentinel-2 spectral bands, operationalised through the Google Earth Engine (GEE) platform. The aerial imageries were classified using Esri ArcGIS Pro software. The outcomes of this study indicate an increase of WH proliferation during the wet season (May-November) over the dry season (December- April) with an overall accuracy of 82% for aerial imagery and 98% for satellite imagery. Data fusion techniques are proposed to overcome the limitations of employing two different forms of remote sensing data individually. Despite the challenges, this study reveals important insights into the scalability of input data to specific requirements and under restricted conditions.
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Correlations between durability, mineralogy and strength properties of limestone
(Department of Earth Resources Engineering, University of Moratuwa, 2021-12) Senarathna, TMB; Janith, SHMPK; Dassanayake, ABN; Chaminda, SP; Jayawardena, CL; Dissanayake, DMDOK; Jayawardena, CL
Durability is used to depict the obstruction of rock to weathering and the pace of events of such changes. Wetting and drying cycles cause evaluation of physical changes and slaking behaviour of rocks, and that can be appraised by the slake durability test. Correlations between durability, mineralogy, and other physical-mechanical properties are different with the rock. Physical and mechanical characteristics of High-grade limestone samples and Lowgrade limestone samples from the Aruwakkalu mine were determined according to ASTM standard methods. X-ray diffractometer (XRD) analysis and scanning electron microscope (SEM) analysis were used to determine the mineralogical contents of the studied samples. Regression analyses were performed between the slake durability index and the physicalmechanical properties of limestones to identify the best wetting and drying cycle to assess the relationships. Differences between the physical, mechanical properties, and mineralogical contents of High-grade limestone and Low-grade limestone were also identified from the laboratory test results. Finally, this study will help to understand any rock engineering problem relating to durability, mineralogy, and other physical-mechanical properties of areas with limestone.
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Critical evaluation of industrial mineral mining methods in Sri Lanka
(Department of Earth Resources Engineering, University of Moratuwa, 2021-12) Jeewandara, JTP; Senarathna, MKT; Wickramarathna, CH; Sirisena, KMW; Hemalal, PVA; Lasantha, MML; Dharmaratne, PGR; Chaminda, SP; Jayawardena, CL; Dissanayake, DMDOK; Jayawardena, CL
Sri Lanka is rich in industrial minerals, including graphite, apatite, ilmenite, rutile, quartz, feldspar, kaolin, apatite, garnet sand, mica, calcite, and dolomite. Even though lots of mining methods are used to extract such minerals, only limited studies have been carried out in Sri Lanka to evaluate mining methods by means of main mining principles, such as safety, economy, and efficiency. This study focuses on the Bogala graphite mine, a narrow vein medium depth underground mine, and Aruwakkalu limestone open pit mine. To evaluate the overhand cut and fill mining method in Bogala mine, Equivalent Linear Overbreak or Slough (ELOS), which is a useful measurement for quantifying the unplanned dilution in narrow vein mining, is used. The favourability of the underground mining method is evaluated for a particular mine site using Key Deposit Indicators (KDIs), and it provides the best suited underground mine based on characteristics of the ore body. The fracture system presence in the Bogala mine requires a good support system to ensure the safety of underground workers. The efficiency of the loading and hauling equipment in the Aruwakkalu mine site is evaluated by Match Factor (MF).
item: Conference-Abstract
Decision tree regression approach for detecting spatiotemporal changes of vegetation cover in surface water bodies
(Department of Earth Resources Engineering, University of Moratuwa, 2021-12) Dassanayake, SM; Jayawardena, CL; Dissanayake, DMDOK; Dissanayake, DMDOK; Jayawardena, CL
Surface water bodies in urban areas, such as Bolgoda lake, show complex vegetation dynamics, typically noticeable by the fluctuating vegetation cover throughout the year. Primary factors governing these fluctuations include wastewater discharge, anthropogenic activities (e.g., surface mining), invasive plant growth, and climate change. It is exceptionally challenging to physically measure and monitor these dynamics over the spatial extent of these waterbodies consistently over many years. Recent studies have explored the potentials of employing satellite imagery to quantitatively detect spatiotemporal changes of surface water vegetation cover. Such attempts have utilised vegetation detection indices, such as the normalised vegetation index (NDVI), to classify the vegetation cover with significant statistical accuracy. However, these conventional geospatial analyses require substantial computational power. They are limited to small timescales and spatial extents. This study employs the computational power of the google earth engine to address this limitation. Moreover, it integrates a machine learning classification approach, namely decision tree regression, to monitor the vegetation cover change over coarser and finer temporal resolutions using Landsat 8 hyperspectral imagery. Initially, NDVI classification was performed on 390 Landsat 8 images acquired throughout 2013-2021. Five locations, which represent different vegetation cover characteristics on the lake, were selected to generate the time series of the NDVI classified values. The results show that the vegetation cover varies at two temporal frequencies. The annual variation of the water, vegetation, and non-vegetation classes are undetectable. However, vegetation dynamics fluctuate rapidly at a finer temporal resolution (i.e., on monthly cycles). The statistically significant results claimed in this study will be further explored to support policymakers in optimising environmental resource management strategies and prioritising eco-preservation that can enhance the health and productivity of urban surface water bodies.
item: Conference-Full-text
Determination of depleted rock volume in open cast mines using photogrammetric techniques for the purpose of royalty calculation
(Department of Earth Resources Engineering, University of Moratuwa, 2021-12) Ariyarathne, RCDK; Samaraweera, SACV; Maduwantha, LSE; Insaf, MJM; Hemalal, PVA; Illankoon, IMTN; Dharmaratne, PGR; Chaminda, SP; Lasantha, MML; Dissanayake, DMDOK; Jayawardena, CL
In Sri Lanka, Geological Survey and Mines Bureau (GSMB) imposed royalty levy for aggregate production volume using an equation (indirect method) which utilises the quantity of explosives for the calculation. Since the equation resulted in higher deviations and the previous studies emphasise the advantages of photogrammetric 3-dimensional (3D) modelling (direct method) when determining production volume of bench blast, the present study focus on investigating its applicability to irregular faced dynamic quarry with uneven overburden. Pre and post 3D Digital Surface Models (DSMs) of the quarry were generated using the structure from motion (SFM) algorithm with Real-Time Kinematic (RTK) positioning system and Pix4D mapper software. Golden Software Surfer 16 was used to determine depleted rock volume as the difference between pre and post 3D DSMs. Results indicate a 5.50% deviation of the proposed method from true depleted rock volume determined by truck measurements due to uncleaned quarry face during the pre-Drone survey and unaccounted soil overburden removal. Presence of overburden while generating DSMs can be overcome by pile volume estimation of overburden and decreasing it from depleted rock volume when calculating production volume. GSMB equation calculated production deviate -32% from true production due to the unaccounted explosive amounts which contributed to the production and confirm the suitability of the proposed direct method (5.5% deviation) for determining the depleted rock volume in open-cast mines.
item: Conference-Full-text
Determining the characteristics of the calcite intrusions in the southern part of eppawala deposit and its applicability for the industries
(Department of Earth Resources Engineering, University of Moratuwa, Sri Lanka, 2022-12-23) Peter, GKMR; Sivaruban, S; Jayathilaka, GMANGNMB; Lasantha, MML; Rathnayake, NP; Hemalal, PVA; Batapola, BDNM; Jayawardena, CL
Eppawala is the only phosphate deposit that is currently being mined in Sri Lanka and is composed of mainly two parts northern and southern. The ongoing phosphate mining process in the southern part has resulted in the exposure of fresh carbonatite embedded with large apatite crystals and those intrusions need to be removed before continuing further phosphate mining in that area. Therefore, we need to address a suitable method to use those calcite intrusions properly. In this paper, we are discussing the characteristics of calcite matrix such as critical anions (fluoride, chloride), P2O5 content, heavy metals, oxides, and the suitability of applying those removing calcite boulders for further industries including the fertilizer industry. Ion selectivity, titration, colorimetry, and induced coupled plasma spectrophotometry were used for analyzing the characteristics respectively for fifteen samples from three different boulders in the southern part. Results from critical anions and heavy metal percentages proved the absence of toxicity in calcite matrix and oxides percentages showed that it can be applied directly in its natural form only for the fertilizer industry by a quantitative comparison whereas upgrading processes need to be implemented to meet the specifications in other industries.
item: Conference-Abstract
Determining the Invasive Plant Dynamics in Bolgoda Lake Using Open-source Data
(Department of Earth Resources Engineering, University of Moratuwa, Sri Lanka, 2022-12-23) Kannangara, KATT; Shoukie, MB; Nayomi, MPA; Dassanayake, SM; Dassanyake, ABN; Jayawardena, CL; Jayawardena, CL
Identifying invasive plants (IP) and monitoring their dynamics is essential to minimize potential adverse effects on natural resources. Remote sensing (RS) could effectively cater to such requirements by acquiring data in many critical domains. Limitations of spatial resolution, spectral information, and large imagery files usually hinder retrieving, managing, and analyzing remotely sensed data. The cloud-based computational capabilities of Google Earth Engine (GEE) provide the amenities for geospatial data analysis, retrieval, and processing with access to a majority of freely available, public, multi-temporal RS data. Integrating machine learning algorithms into GEE generates a promising path toward operationalizing automated RS-based IP monitoring by overcoming traditional challenges. Use of Classification and Regression Trees (CART) classifier to generate water-vegetation classification over six years (2016-2021) with Landsat 8 and Sentinel 2 images enabled mapping the invasive plants and their dominant component of Water Hyacinth (Pontederia crassipes) across a heterogeneous landscape in Bolgoda Lake, Sri Lanka. Also, the study could develop a relatively accurate classification of the water-vegetation dynamics over the time of interest. The classified time series data indicates the annual variation of the water, vegetation, and non-vegetation classes with rapidly fluctuating seasonal cycles for the vegetation cover. These results could benefit regulatory authorities and institutions to optimize environmental resource management and prioritize eco-preservation attempts. Moreover, the findings reflect the capabilities of deep learning models to identify invasive plant behaviors even with modest spatial and spectral resolution imagery.
item: Article-Full-text
Developing a reliable monitoring framework to detect environmental changes near mining areas : a remote sensing approach
(2011) Thiruchittampalam, S; Jayawardena, CL
Agriculture and mining are two key industries that govern the growth of the socio-economic systems of a country. Detrimental effects on the socio-environment during mining activities are unavoidable. Hence, a proper balance between social, environmental, and economic aspects needs to be promoted in mining industries. Developing robust real-time monitoring systems will prevent overexploitation of resources, negative impact on the socio-environmental system, illegal mining activities, and abandoned mines without proper reclamation. This study aims to recommend utilising no-cost satellite data to assess effects on the environment due to mining. Further, the machine learning approach in this study is expected to lead to an autonomous realtime monitoring mechanism. Based on accessibility and stakeholder interest, a cluster of abandoned and operating quarry sites in the Anuradhapura District, Sri Lanka, was selected as the study area. Freely available high spatial resolution satellite images were obtained from Google Earth and Copernicus Open Access Hub (Sentinel 2 satellite data). Imageries acquired were subjected to object-based land cover classification. Machine learning algorithms, namely, Decision Tree, Random Forest, and Support Vector Machine, were used in the classification process. The best performing algorithm in land cover classification was chosen for multitemporal analysis of the area of interest. In addition, false colour composites and spectral indices were generated using Sentinel 2 images to differentiate human-induced negative impacts and natural changes. The results show that Support Vector Machine outperformed other algorithms in classifying land cover near mining areas. Further, multitemporal analysis of land cover changes using this algorithm implies autonomous monitoring using satellite data was viable. Additionally, auxiliary information such as false colour composites and spectral indices confirmed that the increased proportion of water bodies in the area was due to leaving the abandoned mines without proper rehabilitation. This study provides evidence that the fusion of machine learning based classification with spectral indices helps develop robust monitoring systems.