Time in Yangon Burma

Yangon Burma Time

Exteriors of Port Autonomy, a restaurant and bar in Yangon, Myanmar, which represents the city's hipster culture. From Yangon, Myanmar to Paramus, NJ? Wink and you'll miss it! The Swissw Time Square in Yangon reflects the growing appreciation of Swiss luxury watches in Myanmar. Burma was under the Kingdom of Kirat in ancient times, as was eastern Nepal.

Sunset and sunrise for Yangon, Myanmar

Jangon (Dagon, Gian'nkon, Gorad Jangon, Jangon, Jangon, Jangon and Jangon Kiot, Jangona, Jangono, Jangun, Jangún, Ngiong-kong, Ngióng-kông, RGN, Rangon, Rangoon, Rangoun, Rangum, Rangun, Rangunas, Rangún, Rang?nas, Yangôn, yyanguna, yang-gon, yanghwn, yangung, yang-gon, yangon, yang-gon, yangun, yanguna, jangwn, Ýankon, ????????, ??????, ????? ?????? ??????, ??????, ??????, ?????? ??????, ?????, ?????, ??????, ?????, ?????? ??????,

Asia/Rangoon is the time zone. Yangon's forecast sunrises and sunsets are all predicated on perfect meteorological condition on flat surface at ocean-height. The real time may vary depending on the location. More information on how to calculate time, the meaning of things like "dawn", "dusk" and "dusk", and why the length of the equinox is probably not what you are expecting, can be found in the frequently asked questions.

Classified buildings in Yangon City, Myanmar with stereo GeoEye pictures, Landsat pictures and skylights information.

Yangon, the former capitol of Myanmar, is with more than five million inhabitants the largest town in the state and at the same time the economy region of the state. The areas are highly developed with three categories of housing, business and industry structures. The research suggested a method for classifying three class building typologies in Yangon, Myanmar, using remote sensing information.

This study used stereo GeoEye imagery, multispectral Landsat imagery and NTL imagery from the Visual Infrared Imaging Radiometer Suite (VIIRS) to retrieve building typologies. Stereo GeoEye pictures were used to preserve the height of the building, the Landsat picture was classed to give us ground coverage areas, and the NTL picture was used for seperate NTL work.

Using the hierarchical classifications with (1) height of edifices, (2) surface areas and (3) NTL consumption, the edifices were divided into three categories with (1) living, (2) business and (3) industry-fabricated. As part of the experiment, the estimate of the types of edifice maps was cross-referenced with a terrestrial survey and the measurement of edifice information according to our suggested methodology.

Comparison results showed that our method classifies the building type with an exactness of 76% and a kappa factor of 0,58.

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