Search ga_ls9c_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider. For Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

95 results

Time (local)	Label
2021-11-10 09:37:06	ga_ls9c_ard_3-2-1_094071_2021-11-10_final
2021-11-12 10:56:37	ga_ls9c_ard_3-2-1_106070_2021-11-12_final
2021-11-22 09:23:40	ga_ls9c_ard_3-2-1_091072_2021-11-21_final
2021-12-12 10:10:39	ga_ls9c_ard_3-2-1_099070_2021-12-12_final
2021-12-17 10:33:31	ga_ls9c_ard_3-2-1_102081_2021-12-17_final
2021-12-18 11:14:48	ga_ls9c_ard_3-2-1_109076_2021-12-18_final
2022-01-02 10:33:32	ga_ls9c_ard_3-2-1_102081_2022-01-02_final
2022-01-04 10:17:11	ga_ls9c_ard_3-2-1_100071_2022-01-04_final
2022-01-26 11:18:59	ga_ls9c_ard_3-2-1_110071_2022-01-26_final
2022-02-08 10:46:52	ga_ls9c_ard_3-2-1_105068_2022-02-08_final
2022-02-15 10:52:59	ga_ls9c_ard_3-2-1_106068_2022-02-15_final
2022-03-02 10:13:32	ga_ls9c_ard_3-2-1_099078_2022-03-02_final
2022-03-03 10:52:48	ga_ls9c_ard_3-2-1_106068_2022-03-03_final
2022-03-24 09:34:25	ga_ls9c_ard_3-2-1_093073_2022-03-24_final
2022-03-27 10:07:17	ga_ls9c_ard_3-2-1_098078_2022-03-27_final
2022-04-27 11:03:55	ga_ls9c_ard_3-2-1_107081_2022-04-27_final
2022-04-28 10:09:29	ga_ls9c_ard_3-2-1_098084_2022-04-28_final
2022-05-03 10:25:12	ga_ls9c_ard_3-2-1_101077_2022-05-03_final
2022-05-09 11:25:45	ga_ls9c_ard_3-2-1_111074_2022-05-09_final
2022-05-21 10:08:38	ga_ls9c_ard_3-2-1_099067_2022-05-21_final
2022-05-23 11:37:09	ga_ls9c_ard_3-2-1_113072_2022-05-23_final
2022-06-03 09:45:44	ga_ls9c_ard_3-2-1_094087_2022-06-03_final
2022-06-12 09:33:13	ga_ls9c_ard_3-2-1_093071_2022-06-12_final
2022-06-17 11:31:07	ga_ls9c_ard_3-2-1_112072_2022-06-17_final
2022-06-28 09:39:31	ga_ls9c_ard_3-2-1_093086_2022-06-28_final
2022-06-28 11:14:24	ga_ls9c_ard_3-2-1_109076_2022-06-28_final
2022-07-07 09:33:42	ga_ls9c_ard_3-2-1_092087_2022-07-07_final
2022-07-16 09:22:18	ga_ls9c_ard_3-2-1_091074_2022-07-15_final
2022-07-22 10:25:24	ga_ls9c_ard_3-2-1_101077_2022-07-22_final
2022-07-23 09:32:36	ga_ls9c_ard_3-2-1_092084_2022-07-23_final
2022-07-28 09:52:00	ga_ls9c_ard_3-2-1_095086_2022-07-28_final
2022-08-01 09:28:08	ga_ls9c_ard_3-2-1_091088_2022-07-31_final
2022-08-09 10:10:05	ga_ls9c_ard_3-2-1_099069_2022-08-09_final
2022-08-12 09:06:54	ga_ls9c_ard_3-2-1_088081_2022-08-11_final
2022-08-19 10:49:13	ga_ls9c_ard_3-2-1_105074_2022-08-19_final
2022-08-23 10:27:42	ga_ls9c_ard_3-2-1_101082_2022-08-23_final
2022-08-25 10:10:33	ga_ls9c_ard_3-2-1_099070_2022-08-25_final
2022-08-26 09:21:43	ga_ls9c_ard_3-2-1_090087_2022-08-25_final
2022-09-19 10:04:28	ga_ls9c_ard_3-2-1_098070_2022-09-19_final
2022-10-02 11:14:29	ga_ls9c_ard_3-2-1_109075_2022-10-02_final
2022-10-17 10:28:31	ga_ls9c_ard_3-2-1_102068_2022-10-17_final
2022-10-28 11:53:15	ga_ls9c_ard_3-2-1_115079_2022-10-28_final
2022-11-08 09:57:49	ga_ls9c_ard_3-2-1_096084_2022-11-08_final
2022-11-13 10:09:36	ga_ls9c_ard_3-2-1_099067_2022-11-13_final
2022-11-16 09:07:36	ga_ls9c_ard_3-2-1_088082_2022-11-15_final
2022-11-22 10:03:25	ga_ls9c_ard_3-2-1_098067_2022-11-22_final
2022-12-31 10:16:21	ga_ls9c_ard_3-2-1_099084_2022-12-31_final
2023-01-09 10:08:59	ga_ls9c_ard_3-2-1_098081_2023-01-09_final
2023-01-26 09:16:30	ga_ls9c_ard_3-2-1_089089_2023-01-25_final
2023-01-27 11:32:16	ga_ls9c_ard_3-2-1_112073_2023-01-27_final
2023-04-06 10:09:05	ga_ls9c_ard_3-2-1_099067_2023-04-06_final
2023-04-14 10:59:37	ga_ls9c_ard_3-2-1_107070_2023-04-14_final
2023-04-20 10:27:20	ga_ls9c_ard_3-2-1_101082_2023-04-20_final
2023-04-21 09:33:42	ga_ls9c_ard_3-2-1_092087_2023-04-21_final
2023-04-22 11:53:03	ga_ls9c_ard_3-2-1_115080_2023-04-22_final
2023-04-24 09:57:00	ga_ls9c_ard_3-2-1_097068_2023-04-24_final
2023-04-28 09:39:00	ga_ls9c_ard_3-2-1_093085_2023-04-28_final
2023-05-07 09:34:18	ga_ls9c_ard_3-2-1_092089_2023-05-07_final
2023-05-09 10:55:14	ga_ls9c_ard_3-2-1_106075_2023-05-09_final
2023-06-01 09:28:20	ga_ls9c_ard_3-2-1_091090_2023-05-31_final
2023-06-15 11:13:50	ga_ls9c_ard_3-2-1_109076_2023-06-15_final
2023-06-25 10:13:14	ga_ls9c_ard_3-2-1_099079_2023-06-25_final
2023-07-21 09:11:43	ga_ls9c_ard_3-2-1_089079_2023-07-20_final
2023-07-27 10:08:21	ga_ls9c_ard_3-2-1_099066_2023-07-27_final
2023-08-18 09:33:48	ga_ls9c_ard_3-2-1_093072_2023-08-18_final
2023-08-28 10:09:03	ga_ls9c_ard_3-2-1_099067_2023-08-28_final
2023-10-24 10:10:22	ga_ls9c_ard_3-2-1_098085_2023-10-24_final
2023-11-08 11:01:32	ga_ls9c_ard_3-2-1_107074_2023-11-08_final
2023-11-16 10:10:06	ga_ls9c_ard_3-2-1_099069_2023-11-16_final
2023-11-20 11:25:08	ga_ls9c_ard_3-2-1_111071_2023-11-20_final
2023-11-27 09:52:54	ga_ls9c_ard_3-2-1_096072_2023-11-27_final
2023-11-29 11:24:12	ga_ls9c_ard_3-2-1_110084_2023-11-29_final
2023-12-04 09:57:26	ga_ls9c_ard_3-2-1_097068_2023-12-04_final
2023-12-08 11:11:57	ga_ls9c_ard_3-2-1_109069_2023-12-08_final
2023-12-11 10:07:36	ga_ls9c_ard_3-2-1_098078_2023-12-11_final
2023-12-26 09:23:37	ga_ls9c_ard_3-2-1_091076_2023-12-25_final
2023-12-31 11:20:12	ga_ls9c_ard_3-2-1_110074_2023-12-31_final
2024-01-02 09:29:44	ga_ls9c_ard_3-2-1_092076_2024-01-01_final
2024-01-16 11:19:23	ga_ls9c_ard_3-2-1_110072_2024-01-16_final
2024-01-17 10:27:45	ga_ls9c_ard_3-2-1_101082_2024-01-17_final
2024-01-21 11:38:41	ga_ls9c_ard_3-2-1_113074_2024-01-21_final
2024-01-22 09:06:58	ga_ls9c_ard_3-2-1_088081_2024-01-21_final
2024-01-27 11:00:49	ga_ls9c_ard_3-2-1_107072_2024-01-27_final
2024-02-13 10:05:13	ga_ls9c_ard_3-2-1_098072_2024-02-13_final
2024-02-17 09:41:14	ga_ls9c_ard_3-2-1_094074_2024-02-17_final
2024-02-26 11:14:14	ga_ls9c_ard_3-2-1_109075_2024-02-26_final
2024-02-29 10:03:06	ga_ls9c_ard_3-2-1_098067_2024-02-29_final
2024-03-01 09:15:04	ga_ls9c_ard_3-2-1_089086_2024-02-29_final
2024-03-23 10:09:39	ga_ls9c_ard_3-2-1_099068_2024-03-23_final
2024-03-25 09:56:52	ga_ls9c_ard_3-2-1_097067_2024-03-25_final
2024-04-01 10:07:45	ga_ls9c_ard_3-2-1_098079_2024-04-01_final
2024-04-23 11:07:35	ga_ls9c_ard_3-2-1_108075_2024-04-23_final
2024-04-26 10:01:11	ga_ls9c_ard_3-2-1_097079_2024-04-26_final
2024-05-13 09:06:42	ga_ls9c_ard_3-2-1_088082_2024-05-12_final
2024-05-18 09:26:44	ga_ls9c_ard_3-2-1_091086_2024-05-17_final

Return to ga_ls9c_ard_3 whole collection overview

ga_ls9c_ard_3: Geoscience Australia Landsat 9 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

GA Collection 3

USGS Products

Collection 2 NBAR

Collection 2 NBAR Tiled

Pixel Quality

Collection 2 Level1

Tidal

Water Observations

Fractional Cover

Sentinel 2

Ingested Pixel Quality

Geomedians

TMAD

Telemetry data

Summary

Other Products

All years