Jagannath Aryal

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Effective assessment of biodiversity in cities requires detailed vegetation maps. To date, most remote sensing of urban vegetation has focused on thematically coarse land cover products. Detailed habitat maps are created by manual interpretation of aerial photographs, but this is time consuming and costly at large scale. To address this issue, we tested the(More)
— The rapid access of sensor technology provides both challenges and opportunities to authenticated spatiotemporal data. Authentication can be assured by developing related ontologies. Ontology explicitly specifies shared conceptualization and formal vocabularies. In this paper, we proposed an environmental spatio-temporal ontology (ESTO) using unified(More)
Increasing Australian bush-fire frequencies over the last decade has indicated a major climatic change in coming future. Understanding such climatic change for Australian bush-fire is limited and there is an urgent need of scientific research, which is capable enough to contribute to Australian society. Frequency of bush-fire carries information on spatial,(More)
The Modifiable Areal Unit Problem (MAUP) is a well-known issue related to the influence of the spatial support on statistical observations. It occurs when different spatial units making different spatial partitions are used and when the resulting measures vary according to those partitions. In this paper, we first draw a state of the art. Considering the(More)
In this industrial application paper a novel application of salad leaf disease detection has been developed using a combination of big data analytics and on field multi-dimensional sensing. We propose a cloud computing based intelligent big data analysis and interactive visual analytics platform to predict farm hot spots with high probability of potential(More)