This thesis used weather information from two sources. アメダス(by the Japan Metereological Agency) and Weather Underground (www.wunderground.com) by an American agency. Problem with アメダス is that it doesn’t have enough locations with data, even within the 23 wards of Tokyo it has about 21 stations. Weather Underground on the other hand seems to have a lot more locations currently, maybe because of the increase of stations bought after this particular thesis was done
Weather Underground and Tokyo Hot spots
For tomorrow, take all the weather spots in the 23区area and put them in an excel sheet. Collect the following information:
- Location of the station
- ID of the station
Too huge, but the analytical space is limited to only 300m around the weather station
Cant really deal with heights and form of the city block. As shown before, in (res1) almost all countermeasures refer to change in surface material. But these measures are fairly impractical. We need a countermeasure that can be implemented through FORM.
Too specific to location, deals purely with changing or improving material
Such studies become too location specific, but try and employ countermeasures that are at the scale of remote sensing?? Why?
Need 東京温度分布, will make one based on netatmo data. And pick the top 20 locations