A computer-implemented method for generating navigation data of a geographical location, the method comprising: identifying at least one landmark located along a source road in the geographical location from a source image captured by an imaging device; segmenting the source image using a deep learning model by segmenting image pixels of the source image into multiple classes to identify a segmentation mask; generating a template image based on the segmentation mask and a street image of the at least one landmark, wherein the street image comprises a 2D footprint of the at least one landmark falling within a field-of-view of the imaging device and the template image is generated by: determining areas of the street image corresponding to one or more footprint polygons of the at least one landmark; identifying portions of the one or more footprint polygons falling within the field-of-view of the imaging device; projecting the identified portions onto the source image; generating one or more faces of the at least one landmark based on the segmentation mask and the projected portions in the source image; and wherein the template image comprises the one or more faces of the at least one landmark; matching the template image successively with a sequence of images of the at least one landmark to determine a confidence score for each image in the sequence of images; identifying a first image from the sequence of images whose confidence score is below a predetermined threshold; selecting a second image from the sequence of images, that is immediately preceding the first image in the sequence of images, wherein the confidence score of the second image is above the predetermined threshold; calculating a visibility distance of the at least one landmark based on the source image and the second image; and generating the navigation data based on the calculated visibility distance, the navigation data for providing navigation instruction, to a user, for reaching a destination. identifying at least one landmark located along a source road in the geographical location from a source image captured by an imaging device; segmenting the source image using a deep learning model by segmenting image pixels of the source image into multiple classes to identify a segmentation mask; generating a template image based on the segmentation mask and a street image of the at least one landmark, wherein the street image comprises a 2D footprint of the at least one landmark falling within a field-of-view of the imaging device and the template image is generated by: determining areas of the street image corresponding to one or more footprint polygons of the at least one landmark; identifying portions of the one or more footprint polygons falling within the field-of-view of the imaging device; projecting the identified portions onto the source image; generating one or more faces of the at least one landmark based on the segmentation mask and the projected portions in the source image; and wherein the template image comprises the one or more faces of the at least one landmark; determining areas of the street image corresponding to one or more footprint polygons of the at least one landmark; identifying portions of the one or more footprint polygons falling within the field-of-view of the imaging device; projecting the identified portions onto the source image; generating one or more faces of the at least one landmark based on the segmentation mask and the projected portions in the source image; and wherein the template image comprises the one or more faces of the at least one landmark; matching the template image successively with a sequence of images of the at least one landmark to determine a confidence score for each image in the sequence of images; identifying a first image from the sequence of images whose confidence score is below a predetermined threshold; selecting a second image from the sequence of images, that is immediately preceding the first image in the sequence of images, wherein the confidence score of the second image is above the predetermined threshold; calculating a visibility distance of the at least one landmark based on the source image and the second image; and generating the navigation data based on the calculated visibility distance, the navigation data for providing navigation instruction, to a user, for reaching a destination.