Surface Area Time Series

Download as ASCII

# Import package
from dahitiapi.DAHITI import DAHITI

# Initialize DAHITI Class
dahiti = DAHITI()

# Select DAHITI target by DAHITI id
dahiti_id = 10146

# Download Surface Area Time Series in ASCII format
response = dahiti.download_surface_area_ascii(dahiti_id)

# Download Surface Area Time Series in ASCII format and write response to file
response = dahiti.download_surface_area_ascii_to_file(dahiti_id,'/tmp/10146_wse.txt')

Output of ASCII response:

1984-04-09 16:29:22 8.910 7.970
1986-03-14 16:28:17 13.160 8.140
...
2025-08-16 17:14:10 116.990 3.830
2025-08-21 17:10:27 116.460 3.930

Download as JSON

# Import package
from dahitiapi.DAHITI import DAHITI

# Initialize DAHITI Class
dahiti = DAHITI()

# Select DAHITI target by DAHITI id
dahiti_id = 10146

# Download Surface Area Time Series in JSON format
response = dahiti.download_surface_area_json(dahiti_id)

# Download Surface Area Time Series in JSON format and write response to file
response = dahiti.download_surface_area_json_to_file(dahiti_id,'/tmp/10146_wse.json')

Output of JSON response:

[
     {'datetime': '1984-04-09 16:29:22', 'wsa': 8.91, 'wsa_u': 7.97},
     {'datetime': '1986-03-14 16:28:17', 'wsa': 13.16, 'wsa_u': 8.14},
     ...
     {'datetime': '2025-08-16 17:14:10', 'wsa': 116.99, 'wsa_u': 3.83},
     {'datetime': '2025-08-21 17:10:27', 'wsa': 116.46, 'wsa_u': 3.93}],
]

Download as CSV

# Import package
from dahitiapi.DAHITI import DAHITI

# Initialize DAHITI Class
dahiti = DAHITI()

# Select DAHITI target by DAHITI id
dahiti_id = 10146

# Download Surface Area Time Series in CSV format
response = dahiti.download_surface_area_csv(dahiti_id)

# Download Surface Area Time Series in CSV format and write response to file
response = dahiti.download_surface_area_csv_to_file(dahiti_id,'/tmp/10146_wse.csv')

Output of CSV response:

datetime;wsa;wsa_u
1984-04-09 16:29:22;8.910;7.970
1986-03-14 16:28:17;13.160;8.140
...
2025-08-16 17:14:10;116.990;3.830
2025-08-21 17:10:27;116.460;3.930

Download as NetCDF

# Import package
from dahitiapi.DAHITI import DAHITI

# Initialize DAHITI Class
dahiti = DAHITI()

# Select DAHITI target by DAHITI id
dahiti_id = 10146

# Download Surface Area Time Series in CSV format and write response to file
response = dahiti.download_surface_area_netcdf_to_file(dahiti_id,'/tmp/10146_wse.nc')

Content of NetCDF file:

netcdf \10146_wsa {
   dimensions:
      time = 555 ;
   variables:
      string date(time) ;
         date:standard_name = "UTC Date (YYYY-MM-DD HH:MM:SS)" ;
         date:valid_min = "1984-04-09 16:29:22" ;
         date:valid_max = "2025-08-21 17:10:27" ;
      float wsa(time) ;
         wsa:standard_name = "Surface area derived from optical imagery" ;
         wsa:unit = "km2" ;
         wsa:valid_min = 0.29 ;
         wsa:valid_max = 119.11 ;
      float wsa_u(time) ;
         wsa_u:standard_name = "Surface area uncertainty" ;
         wsa_u:unit = "km2" ;
         wsa_u:valid_min = 1.51 ;
         wsa_u:valid_max = 9.64 ;

   // global attributes:
      :dahiti_id = "10146" ;
      :dataset = "surface-area" ;
      :target_name = "Ray Roberts, Reservoir" ;
      :location = "None" ;
      :country = "United States of America" ;
      :continent = "North America" ;
      :longitude = -97.0557 ;
      :latitude = 33.3615 ;
      :software = "3.0" ;
      :institution = "DGFI-TUM" ;
      :source = "DAHITI" ;
      :url = "https://dahiti.dgfi.tum.de/10146/" ;
      :creation_date = "2025-10-23 10:38:55" ;

   data:

   date = "1984-04-09 16:29:22", "1986-03-14 16:28:17", "1986-08-05 16:24:12",
      "1987-01-12 16:21:50", "1987-06-05 16:26:33", "1987-07-23 16:27:33",
      ...
      "2025-08-09 05:17:18", "2025-08-16 17:14:10", "2025-08-21 17:10:27" ;

   wsa = 8.91, 13.16, 5.56, 0.29, 12.25, 6.89, 26.26, 26.93, 28.41, 29.49,
      29.49, 29.1, 29.25, 29.24, 29.09, 28.61, 28.21, 28.37, 102.19, 104.49,
      ...
      116.65, 117.66, 116.95, 116.99, 116.46 ;

   wsa_u = 7.97, 8.14, 2.73, 9.41, 5.25, 3.45, 3.69, 3.13, 2.6, 3.33, 3.39,
      3.13, 3.19, 3.26, 3.65, 2.65, 2.62, 2.7, 9.62, 8.57, 7.68, 7.66, 9.44,
      ...
      3.67, 9.64, 2.88, 8.08, 3.32, 3.68, 3.36, 3.83, 3.93 ;
}