New answers tagged

2

The issue is in the projection you are assigning the image for the export in Earth Engine. I could not get it to work with that projection either, but if I changed it to another they align as expect. You should export with a different projection, and then reproject layer if required. //// Export the data // Export table for plotting Export.table.toDrive({ ...


0

I guess it's because of the periodically different daily path of TERRA and AQUA as they orbit the earth from poles. So, their position is not the same as the day before. About the two other products you mentioned, they have been combined from both onboard sensors and therefore are constant spatially.


1

Normally when rendering an image, EE works at different scales for different zoom levels. The docs explain how this works. When you reproject, you force EE to work at the scale you specified, and depending on your zoom level, each map tile will contain more or less pixels. When zoomed out too far, each tile simply contain too many pixels for EE to handle . ...


0

If you are using anaconda, the installation should be carried out by running conda install -c auto pymodis in the Anaconda prompt. You can find it by typing "Anaconda" in the search bar on Windows. Make sure to run Anaconda as administrator: If you have never installed Python packages this way before, there is a general installation guide.


1

The link you provided had a not found error. But I used a different MODIS file and it works: https://corteva.github.io/rioxarray/stable/examples/reproject.html import rioxarray rds = rioxarray.open_rasterio( "MOD09GA.A2008061.h08v04.006.2015172051346.hdf", variable="SolarZenith_1" ) rds.SolarZenith_1.rio.reproject("EPSG:4326").rio.to_raster("...


2

im not familiar with MOD021 but you can try the code below. It will convert every band in the product. You need to loop across the hdf layers. If the subdataset is still a multiband then you need to loop in that particular dataset and use GetRasterBand. I have tried it and it works. This code will transform each band to TIFF. The names will be 'band1.tif', '...


0

You are on the right track with map(). Hopefully this code explains how you can do this: // Your area of interest var region = ee.Geometry.Point([12.492362, 41.890232]).buffer(500).bounds() // Some collection of images. You're using MODIS here var imageCollection = ee.ImageCollection('COPERNICUS/S2') .filterDate('2019-01-01', '2019-02-01') ....


Top 50 recent answers are included