Browsing by Author "Hettiarachchi, N"

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Open Access
Application of Sentinel-2 Satellite Data to Map Forest Cover in Southeast Sri Lanka through the Random Forest Classifier
(SLIIT, Faculty of Engineering, 2022-09) Gunawansa, T; Perera, K; Apan, A; Hettiarachchi, N
Sentinel-2 satellite data has been used for forest cover monitoring for almost five years. Mapping with Sentinel data will be a cost-effective solution for Sri Lanka, where the lack of updated land cover maps with high spatial resolution is a significant challenge in the land resource management of the country. A study area of about 5,000 km2 located in southeast Sri Lanka was selected for this study. Agricultural lands, forests including Yala national park, and villages with perennial crops make up the region. A Level-2A Sentinel-2 image with less than 10 percent cloud cover was used in the European Space Agency's (ESA) SNAP software version 8.0.0 for image processing and the forest cover of the study area was mapped through the Random Forest classifier (RFC). Normalized Difference Vegetation Index (NDVI) is also calculated as a Sentinel product to support RFC output. For RFC, ground truth data were collected through the reference of Google Earth high-resolution data. The classification accuracy was assessed using the Google Earth image as the reference dataset. Furthermore, RFC results were compared with NVDI greenness values. The classification accuracy was calculated using a confusion matrix (error matrix) through randomly selected 100 sample points. The overall accuracy of the land cover map was 85 percent, with a 96 percent accuracy for forest cover identification. The study found RFC as an effective method to isolate forest cover in Sri Lanka.
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Fueling the future: unveiling what drives gig worker motivation and engagement in Sri Lanka’s corporate landscape
(Emerald Publishing, 2025-03-25) Perera, L; Jayasena, C; Hettiarachchi, N; Siriwardana, D; Wisenthige, K; Wickramaarachchi, C
Purpose: The gig economy has rapidly grown due to economic trends supporting flexible work and digital platforms, leading to increased demand for corporate gig workers. Although numerous studies have explored various aspects of the gig economy, research on the motivational and engagement factors of gig workers remains relatively rare. This study aims to investigate the factors that influence corporate gig workers’ motivation and engagement in the geographical context of Sri Lanka. Specifically, job autonomy, remuneration, social connection and technology and investigated here. Design/methodology/approach: A quantitative study, employing a deductive research approach, was conducted with data gathered through a survey designed using a five-point Likert scale questionnaire. Respondents were conveniently selected from Sri Lankan corporate gig workers. A total of 397 responses were obtained through a snowball sampling technique. The collected data were analyzed using partial least squares structural equation modeling, providing a robust framework for evaluating the hypothesized relationships. Findings: The findings revealed that job autonomy, remuneration, social connection and technology significantly influence corporate gig worker motivation, whereas motivation significantly influences the engagement of corporate gig workers in Sri Lanka. Research limitations/implications: This study faced common limitations. Due to challenges in identifying the framework for the population, a snowball sampling technique was employed. One key limitation is the study’s narrow focus on motivation factors within the Sri Lankan context, which may affect the generalizability of the findings. Additionally, the geographic focus and uneven sample distribution could limit the broader applicability of the conclusions. Future research should adopt a cross-cultural approach to explore the influence of social commerce adoption, enhancing the generalizability of the results. Practical implications: A comprehensive understanding of the factors that influence the corporate gig worker motivation and engagement is provided, facilitating, the decision-makers to gain insight to enhance worker motivation and engagement by adapting strategies. This can lead to higher productivity and job satisfaction among gig workers. Originality/value: Examination of the motivational and engagement factors specific to corporate gig workers in Sri Lanka, a context that has received limited attention in previous research. Also, it contributes to the existing literature by providing a deeper understanding of the gig economy and gig work, particularly in a non-Western setting.
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Geo-enabled FOSS tool supports for immediate flood disaster response planning
(IEEE, 2014-12-22) Ramanayake, K; Vithanage, D; Hettiarachchi, N; Rathnayake, G; Rajapaksha, S, K; Fernando, N
—Flood is a major natural hazard occur recurrently in Sri Lanka. Allocating victims to camps and provide medical facilities are two main activities at the immediate response phase of a flood and use of manual methods delayed this process. This project developed a geoenabled application to support immediate response planning, mainly focusing on allocation victims to IDP camps, provide medical facilities, and supporting access avoiding already blocked roads based on administrative divisions of the affected area. Capacities and facilities in camps and hospitals are matched against the needs of the victims. It identifies the blocked roads, alternative routes to reach resource centers, camps and hospitals and provide navigation guidance. The tool can be used after a flood disaster, assuming basic demographic data and the current flood affected area data are available. The tool is developed as a plug-in for QGIS, a free and open source desktop Geographic Information System software. The tool is verified with sample data related to “Kaluthara” area. It is intended to integrate with InaSAFE disaster response support tool at a later stage.