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

100 results

Time (local)	Label
2021-11-13 10:03:05	ga_ls9c_ard_3-2-1_097083_2021-11-13_final.stac-item
2021-12-11 09:30:36	ga_ls9c_ard_3-2-1_092078_2021-12-11_final.stac-item
2021-12-13 10:58:41	ga_ls9c_ard_3-2-1_106082_2021-12-13_final.stac-item
2021-12-15 10:46:18	ga_ls9c_ard_3-2-1_104082_2021-12-15_final.stac-item
2021-12-28 10:16:12	ga_ls9c_ard_3-2-1_099084_2021-12-28_final.stac-item
2022-01-02 10:28:21	ga_ls9c_ard_3-2-1_102068_2022-01-02_final.stac-item
2022-01-03 09:33:55	ga_ls9c_ard_3-2-1_093071_2022-01-03_final.stac-item
2022-01-12 09:32:29	ga_ls9c_ard_3-2-1_092083_2022-01-12_final.stac-item
2022-01-14 09:19:43	ga_ls9c_ard_3-2-1_090082_2022-01-13_final.stac-item
2022-01-31 10:04:14	ga_ls9c_ard_3-2-1_097085_2022-01-31_final.stac-item
2022-02-03 10:33:32	ga_ls9c_ard_3-2-1_102081_2022-02-03_final.stac-item
2022-03-22 09:51:34	ga_ls9c_ard_3-2-1_095085_2022-03-22_final.stac-item
2022-03-23 10:28:03	ga_ls9c_ard_3-2-1_102068_2022-03-23_final.stac-item
2022-04-09 11:14:02	ga_ls9c_ard_3-2-1_109075_2022-04-09_final.stac-item
2022-05-04 11:10:27	ga_ls9c_ard_3-2-1_108082_2022-05-04_final.stac-item
2022-05-09 09:48:04	ga_ls9c_ard_3-2-1_095077_2022-05-09_final.stac-item
2022-05-18 11:21:03	ga_ls9c_ard_3-2-1_110078_2022-05-18_final.stac-item
2022-05-25 09:48:42	ga_ls9c_ard_3-2-1_095079_2022-05-25_final.stac-item
2022-05-29 11:02:28	ga_ls9c_ard_3-2-1_107078_2022-05-29_final.stac-item
2022-06-10 09:51:08	ga_ls9c_ard_3-2-1_095085_2022-06-10_final.stac-item
2022-06-11 10:27:38	ga_ls9c_ard_3-2-1_102068_2022-06-11_final.stac-item
2022-06-30 11:05:14	ga_ls9c_ard_3-2-1_107084_2022-06-30_final.stac-item
2022-07-31 08:42:28	ga_ls9c_ard_3-2-1_084082_2022-07-30_final.stac-item
2022-08-30 10:28:18	ga_ls9c_ard_3-2-1_102068_2022-08-30_final.stac-item
2022-09-20 10:50:08	ga_ls9c_ard_3-2-1_105076_2022-09-20_final.stac-item
2022-09-28 10:00:43	ga_ls9c_ard_3-2-1_097076_2022-09-28_final.stac-item
2022-10-01 10:33:37	ga_ls9c_ard_3-2-1_102081_2022-10-01_final.stac-item
2022-10-13 09:18:43	ga_ls9c_ard_3-2-1_090079_2022-10-12_final.stac-item
2022-10-13 10:56:24	ga_ls9c_ard_3-2-1_106076_2022-10-13_final.stac-item
2022-10-22 10:50:39	ga_ls9c_ard_3-2-1_105077_2022-10-22_final.stac-item
2022-10-24 10:39:30	ga_ls9c_ard_3-2-1_103080_2022-10-24_final.stac-item
2022-10-30 10:02:47	ga_ls9c_ard_3-2-1_097081_2022-10-30_final.stac-item
2022-11-07 10:50:14	ga_ls9c_ard_3-2-1_105076_2022-11-07_final.stac-item
2022-11-14 10:56:03	ga_ls9c_ard_3-2-1_106075_2022-11-14_final.stac-item
2022-11-30 10:56:24	ga_ls9c_ard_3-2-1_106076_2022-11-30_final.stac-item
2022-12-09 10:51:51	ga_ls9c_ard_3-2-1_105080_2022-12-09_final.stac-item
2022-12-11 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-12-11_final.stac-item
2022-12-11 10:39:29	ga_ls9c_ard_3-2-1_103080_2022-12-11_final.stac-item
2022-12-12 09:45:52	ga_ls9c_ard_3-2-1_094085_2022-12-12_final.stac-item
2022-12-23 11:00:10	ga_ls9c_ard_3-2-1_107070_2022-12-23_final.stac-item
2022-12-23 11:04:57	ga_ls9c_ard_3-2-1_107082_2022-12-23_final.stac-item
2022-12-25 10:51:48	ga_ls9c_ard_3-2-1_105080_2022-12-25_final.stac-item
2023-01-03 10:46:04	ga_ls9c_ard_3-2-1_104081_2023-01-03_final.stac-item
2023-01-06 09:35:42	ga_ls9c_ard_3-2-1_093075_2023-01-06_final.stac-item
2023-01-17 10:56:20	ga_ls9c_ard_3-2-1_106076_2023-01-17_final.stac-item
2023-01-20 09:46:41	ga_ls9c_ard_3-2-1_095072_2023-01-20_final.stac-item
2023-02-02 10:58:51	ga_ls9c_ard_3-2-1_106082_2023-02-02_final.stac-item
2023-02-05 09:52:53	ga_ls9c_ard_3-2-1_095087_2023-02-05_final.stac-item
2023-02-07 11:14:38	ga_ls9c_ard_3-2-1_109075_2023-02-07_final.stac-item
2023-02-20 10:45:59	ga_ls9c_ard_3-2-1_104081_2023-02-20_final.stac-item
2023-02-22 10:28:47	ga_ls9c_ard_3-2-1_102069_2023-02-22_final.stac-item
2023-02-23 11:16:00	ga_ls9c_ard_3-2-1_109079_2023-02-23_final.stac-item
2023-03-08 10:45:47	ga_ls9c_ard_3-2-1_104081_2023-03-08_final.stac-item
2023-03-09 08:10:51	ga_ls9c_ard_3-2-1_079080_2023-03-08_final.stac-item
2023-03-31 09:10:28	ga_ls9c_ard_3-2-1_089075_2023-03-30_final.stac-item
2023-05-14 11:13:45	ga_ls9c_ard_3-2-1_109075_2023-05-14_final.stac-item
2023-05-15 10:19:19	ga_ls9c_ard_3-2-1_100078_2023-05-15_final.stac-item
2023-05-22 10:22:12	ga_ls9c_ard_3-2-1_101070_2023-05-22_final.stac-item
2023-06-01 11:02:02	ga_ls9c_ard_3-2-1_107077_2023-06-01_final.stac-item
2023-07-03 11:02:04	ga_ls9c_ard_3-2-1_107077_2023-07-03_final.stac-item
2023-07-03 11:02:28	ga_ls9c_ard_3-2-1_107078_2023-07-03_final.stac-item
2023-07-14 10:44:49	ga_ls9c_ard_3-2-1_104080_2023-07-14_final.stac-item
2023-07-18 11:57:47	ga_ls9c_ard_3-2-1_116077_2023-07-18_final.stac-item
2023-07-31 09:51:40	ga_ls9c_ard_3-2-1_095086_2023-07-31_final.stac-item
2023-08-04 11:05:05	ga_ls9c_ard_3-2-1_107084_2023-08-04_final.stac-item
2023-08-15 10:45:23	ga_ls9c_ard_3-2-1_104081_2023-08-15_final.stac-item
2023-09-07 09:15:43	ga_ls9c_ard_3-2-1_089088_2023-09-06_final.stac-item
2023-09-19 11:14:12	ga_ls9c_ard_3-2-1_109075_2023-09-19_final.stac-item
2023-09-22 10:10:12	ga_ls9c_ard_3-2-1_098085_2023-09-22_final.stac-item
2023-09-29 10:08:45	ga_ls9c_ard_3-2-1_099066_2023-09-29_final.stac-item
2023-10-02 10:45:17	ga_ls9c_ard_3-2-1_104080_2023-10-02_final.stac-item
2023-10-12 11:24:05	ga_ls9c_ard_3-2-1_110084_2023-10-12_final.stac-item
2023-10-18 10:45:52	ga_ls9c_ard_3-2-1_104081_2023-10-18_final.stac-item
2023-10-21 11:14:22	ga_ls9c_ard_3-2-1_109075_2023-10-21_final.stac-item
2023-10-24 11:47:39	ga_ls9c_ard_3-2-1_114081_2023-10-24_final.stac-item
2023-10-25 09:11:33	ga_ls9c_ard_3-2-1_089077_2023-10-24_final.stac-item
2023-11-01 10:56:08	ga_ls9c_ard_3-2-1_106076_2023-11-01_final.stac-item
2023-11-17 10:56:10	ga_ls9c_ard_3-2-1_106076_2023-11-17_final.stac-item
2023-12-01 09:35:21	ga_ls9c_ard_3-2-1_092090_2023-12-01_final.stac-item
2023-12-01 11:08:15	ga_ls9c_ard_3-2-1_108075_2023-12-01_final.stac-item
2024-01-02 09:34:56	ga_ls9c_ard_3-2-1_092089_2024-01-02_final.stac-item
2024-01-09 09:39:29	ga_ls9c_ard_3-2-1_093085_2024-01-09_final.stac-item
2024-01-18 09:32:31	ga_ls9c_ard_3-2-1_092083_2024-01-18_final.stac-item
2024-01-27 11:04:48	ga_ls9c_ard_3-2-1_107082_2024-01-27_final.stac-item
2024-01-31 10:34:32	ga_ls9c_ard_3-2-1_103068_2024-01-31_final.stac-item
2024-02-09 10:28:23	ga_ls9c_ard_3-2-1_102068_2024-02-09_final.stac-item
2024-02-10 11:14:50	ga_ls9c_ard_3-2-1_109076_2024-02-10_final.stac-item
2024-02-13 10:05:37	ga_ls9c_ard_3-2-1_098073_2024-02-13_final.stac-item
2024-02-26 11:14:38	ga_ls9c_ard_3-2-1_109076_2024-02-26_final.stac-item
2024-02-29 10:09:53	ga_ls9c_ard_3-2-1_098084_2024-02-29_final.stac-item
2024-03-01 09:15:52	ga_ls9c_ard_3-2-1_089088_2024-02-29_final.stac-item
2024-03-02 09:57:56	ga_ls9c_ard_3-2-1_096085_2024-03-02_final.stac-item
2024-03-08 10:58:10	ga_ls9c_ard_3-2-1_106081_2024-03-08_final.stac-item
2024-03-24 09:22:00	ga_ls9c_ard_3-2-1_090088_2024-03-23_final.stac-item
2024-03-28 10:28:06	ga_ls9c_ard_3-2-1_102068_2024-03-28_final.stac-item
2024-03-28 10:33:17	ga_ls9c_ard_3-2-1_102081_2024-03-28_final.stac-item
2024-04-19 09:57:10	ga_ls9c_ard_3-2-1_096084_2024-04-19_final.stac-item
2024-05-09 09:28:40	ga_ls9c_ard_3-2-1_092075_2024-05-08_final.stac-item
2024-05-18 11:02:02	ga_ls9c_ard_3-2-1_107077_2024-05-18_nrt.stac-item
2024-05-19 11:46:53	ga_ls9c_ard_3-2-1_114081_2024-05-19_nrt.stac-item

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

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years