![]() Var totalBangalore = total.clip(bangalore) Clip the image to the city boundary and display Since CHIRPS data has only 1 band named precipitation, the dictionary will have only a single key named precipitation_sum. The result of a reduceRegion() operation is a dictionary which has the stats for each band of the image. CHIRPS spatial resolution is 0.05° – which is approximately 6km. In the code below, we specify 5000m as the scale. For this example, we will compute the total average rainfall within the city of Bengaluru, India. Now that we have computed an Image with the total rainfall for each pixel, we can compute average total rainfall in any given geometry using reduceRegion() function. The region could be anything – a river basin, an administrative area (city/district) or a polygon. Most hydrological applications will require computing the Areal Mean Rainfall (AMR) – which is the average total rainfall in a region. Map.addLayer(total, visParams, 'Total Precipitation') ![]() Unless you specifically need daily data, you should use the pentad dataset. Note that CHIRPS is also provided in a daily time-step which is computed by disaggregating the pentad data. Pentads reset at the beginning of each month. There are 6 pentads in a calendar month: Five 5-day pentads and One pentad with the remaining 3 to 6 days of the month. Pentad represents the grouping of 5 days. The primary computing time step for the CHIRP is the pentad.
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