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Dengue Fever has become an increasing public health concern around the world due to its serious health consequences including death, lack of effective vaccine and specific treatment. Influence of area specific meteorological and physiographical characteristics on the spread of infectious diseases need to be studied to understand spatial-temporal aspects of infectious diseases in a particular area. Mathematical relationships between various explanatory variables (causative factors) and Dengue Fever incidences have been established to quantify and prioritize the influence of various factors. So that, effective health care services could be provided in these areas. The study successfully explains the occurrences of Dengue Fever in Delhi in term of geo-spatial phenomena/variables. Meteorological data of 13 stations in Delhi at hourly temporal scale for a period 2006-2015 have been used along with multi-spectral satellite data. Data on reported cases of Dengue Fever on daily basis and for a period of ten years from 2006 to 2015 have been obtained for Delhi. Python modules have been developed to extract values of geospatial parameters and to perform Poisson regression. To assess the accuracy of developed Poisson regression based equations, r-squared and error statistics have been calculated. Results indicate strong association of Dengue Fever incidences with temperature, humidity, wind speed, sunshine hours, built-up and vegetation density and distance from dairy locations, waterbodies and drainage network. Further, critical ranges of various parameters favouring high number of Dengue Fever incidences have been determined. These findings have significant public health implications for control and prevention of Dengue Fever incidences in Delhi city and surrounding region. Occurrences of Dengue Fever incidences are found to be highest in the month of September and October. These months represent transition period from rainy season to winter season. It is recommended that further study should focus on detailed analysis of causative factors in this period. (C) 2018 Elsevier B.V. All rights reserved.