Abstract. Increasing land use land cover changes, especially urban growth has put a negative impact on biodiversity and ecological process. As a consequences, they are creating a major impact on the global climate change. There is a recent concern on the necessity of exploring the cause of urban growth with its prediction in future and consequences caused by this for sustainable development. This can be achieved by using multitemporal remote sensing imagery analysis, spatial metrics, and modeling. In this study, spatio-temporal urban change analysis and modeling were performed for Biratnagar City and its surrounding area in Nepal. Land use land cover map of 2004, 2010, and 2016 were prepared using Landsat TM imagery using supervised classification based on support vector machine classifier. Urban change dynamics, in term of quantity, and pattern was measured and analyzed using selected spatial metrics and using Shannon’s entropy index. The result showed that there is increasing trend of urban sprawl and showed infill characteristics of urban expansion. Projected land use land cover map of 2020 was modeled using cellular automata-based approach. The predictive power of the model was validated using kappa statistics. Spatial distribution of urban expansion in projected land use land cover map showed that there is increasing threat of urban expansion on agricultural land.
A study on “Issues associated with the shelter reconstruction after Gorkha Earthquake 2015 in Nepal” was conducted during the period of March to September 2017 on the basis of secondary literature received from different sources and field observation. Various articles, journal and government documents retrieved from online research database like ‘Google Scholars’ and topic related government online sites were reviewed. It has been realized that reconstruction after disasters is a long process. To manifest and implement the notion of build back better and successful completion of shelter reconstruction projects, there is a need for an in-depth knowledge of construction project management because 600,000 houses are to be constructed and about 250,000 to be repaired and retrofitted as well. The study reveals that the lack of funding, construction materials, labors and experienced human resources hinder the smooth progress of reconstruction. Similarly, reconstruction projects can take place only when the affected people are also involved in the design and planning process as well as in the implementation phase of the project, ensuring the best utilization of local knowledge and resources as much as possible. The strong coordination among various stakeholders can act as the key to an effective reconstruction in the context of Nepal.
There is a possibility in finding hidden patterns that might help find a relationship between the information provided by the Loan Applicants during the Loan Application process and the status of their loan repayment. This paper highlights on finding such patterns by building a Decision Tree with the help of the data provided during the loan application process. Eleven attribute information of Five Hundred sixty four loan applicants were collected from Garima Bikas Bank Ltd. A decision tree model with a depth of 6 has been built by calculating the entropy and information gain at each split and selecting the feature with the highest information gain.
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