How to download SMAP data in GeoTiff and HDF formats from the NSIDC (

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  • Опубликовано: 12 сен 2024
  • National Soil and Ice Data Center (nsidc.org/data)

Комментарии • 21

  • @akashsenthilkumaran9610
    @akashsenthilkumaran9610 2 года назад +1

    Thank you so much. It was very helpful. Expecting more videos from you.

  • @senpaiyajuu2914
    @senpaiyajuu2914 8 месяцев назад +1

    looks like all smap soil Moisture h5 file are globe size. is there any way we can select a single area to download? globe is too big

  • @samestate11
    @samestate11 4 месяца назад

    Thank you! You’re a lifesaver

  • @jhoreenejulian8767
    @jhoreenejulian8767 2 года назад +1

    Thank you for the very helpful tutorial! But may I know how to download and extract large data for a month-long period.

    • @geospatialcamp5618
      @geospatialcamp5618  2 года назад

      You should select the period of interest and it downloads all data at once. There will be one raster file for each 3-hourly soil moisture data that I then summarized by averaging through Python codes.

  • @heatherlovesyou11
    @heatherlovesyou11 Год назад

    thank you, this was very helpful

  • @Home-bh6rf
    @Home-bh6rf 2 года назад +2

    Great tutorial. After downloading, as these are 3 hourly data, could you please share some way to format them daily and then monthly? Thank you

    • @geospatialcamp5618
      @geospatialcamp5618  2 года назад +1

      I wrote a python script to summarize data into daily and monthly raster files. IF you leave an email, I can send the script to you.

    • @geospatialcamp5618
      @geospatialcamp5618  Год назад +1

      Check this: import arcpy
      import os from shutil
      import copy2
      arcpy.CheckOutExtension("Spatial")
      from collections import defaultdict
      def main():
      raster_dir = r"D:\NASA\Data\USA\SMAP_L4\Processed-Daily"
      arcpy.env.workspace = raster_dir
      raster_days = defaultdict(list)
      for r in arcpy.ListRasters():
      #To calculate Daily Average
      #raster_days[r[15:23]].append(r)
      # To calculate Monthly Average
      raster_days[r[0:6]].append(r)
      if not os.path.exists(raster_dir+"\Processed-Monthly"):
      os.makedirs(raster_dir+"\Processed-Monthly")
      for date, rasters in raster_days.items():
      print(date)
      outCellStatistics = arcpy.sa.CellStatistics(rasters, "MEAN")
      outCellStatistics.save(raster_dir+"\Processed-Monthly\{}.tif".format(date))
      if __name__ == '__main__':
      main()

    • @Home-bh6rf
      @Home-bh6rf Год назад +1

      @@geospatialcamp5618 thank you so much

  • @max477
    @max477 Год назад +1

    after downloading 3 hourly data for 1 day How to convert that data into 1 day data what method or logic you use.
    Thank you for sharing.

    • @geospatialcamp5618
      @geospatialcamp5618  Год назад

      I wrote a script in python (arcpy package) and averaged 3-hourly data into daily data (specified the date based on the file names)

    • @geospatialcamp5618
      @geospatialcamp5618  Год назад

      Python Script:
      import arcpy
      import os from shutil
      import copy2
      arcpy.CheckOutExtension("Spatial")
      from collections import defaultdict
      def main():
      raster_dir = r"D:\NASA\Data\USA\SMAP_L4\Processed-Daily"
      arcpy.env.workspace = raster_dir
      raster_days = defaultdict(list)
      for r in arcpy.ListRasters():
      #To calculate Daily Average
      #raster_days[r[15:23]].append(r)
      # To calculate Monthly Average
      raster_days[r[0:6]].append(r)
      if not os.path.exists(raster_dir+"\Processed-Monthly"):
      os.makedirs(raster_dir+"\Processed-Monthly")
      for date, rasters in raster_days.items():
      print(date)
      outCellStatistics = arcpy.sa.CellStatistics(rasters, "MEAN")
      outCellStatistics.save(raster_dir+"\Processed-Monthly\{}.tif".format(date))
      if _name_ == '__main__':
      main()

    • @max477
      @max477 Год назад +1

      @@geospatialcamp5618 Thanks you so much...!
      what kind of jobs profile available for these skills..? can you suggest any well-paying remote jobs related to these skills.?
      Need video related to this.
      Thanks in advance

  • @habtamumulugeta2298
    @habtamumulugeta2298 2 года назад +1

    thank you for your excellent explanation, but still I could not get the exact measurements of the soil moisture, which means how can I read it in Arc map gis? thank you so much

    • @geospatialcamp5618
      @geospatialcamp5618  2 года назад

      Did you download the GeoTiff format? You can add the GeoTiff file directly into ArcMAP (same as a raster file). Clicking on each pixel (grid cell) using ArcMAP "Identify" tool, you can know the exact values of soil moisture. If you have downloaded large data (for a long period) let me know and I can show you how to extract data for your study area.

    • @raymondariho2613
      @raymondariho2613 9 месяцев назад

      @@geospatialcamp5618 I downloaded numerous Geotiff files for three days. How do I get exact soil moisture data using python

  • @majilybalo5100
    @majilybalo5100 Год назад +1

    Hello, ma'am. Do you have a video tutorial on extracting monthly averaged soil moisture data with a resolution of 30m or less?

    • @amenehtavakol8587
      @amenehtavakol8587 Год назад

      It should be the same! At the beginning choose the monthly data and the rest is the same!

  • @abrahamalvarez2730
    @abrahamalvarez2730 Год назад

    hello the website was way more simpler, no it is not like this video and it is so difficult to extract the data.