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

First 100 results (query limit)

Time (local)	Label
2021-11-18 11:43:25	ga_ls9c_ard_3-2-1_113081_2021-11-18_final.stac-item
2021-12-04 09:25:17	ga_ls9c_ard_3-2-1_091080_2021-12-03_final.stac-item
2021-12-07 11:36:38	ga_ls9c_ard_3-2-1_112084_2021-12-07_final.stac-item
2021-12-19 10:19:11	ga_ls9c_ard_3-2-1_100076_2021-12-19_final.stac-item
2021-12-21 10:04:02	ga_ls9c_ard_3-2-1_098069_2021-12-21_final.stac-item
2021-12-23 11:32:09	ga_ls9c_ard_3-2-1_112073_2021-12-23_final.stac-item
2021-12-29 09:19:47	ga_ls9c_ard_3-2-1_090082_2021-12-28_final.stac-item
2022-01-03 09:40:18	ga_ls9c_ard_3-2-1_093087_2022-01-03_final.stac-item
2022-01-24 11:36:08	ga_ls9c_ard_3-2-1_112083_2022-01-24_final.stac-item
2022-01-29 10:13:48	ga_ls9c_ard_3-2-1_099078_2022-01-29_final.stac-item
2022-02-06 09:22:44	ga_ls9c_ard_3-2-1_091074_2022-02-05_final.stac-item
2022-02-15 10:53:23	ga_ls9c_ard_3-2-1_106069_2022-02-15_final.stac-item
2022-02-17 09:06:31	ga_ls9c_ard_3-2-1_088080_2022-02-16_final.stac-item
2022-02-22 09:25:00	ga_ls9c_ard_3-2-1_091080_2022-02-21_final.stac-item
2022-03-03 10:52:48	ga_ls9c_ard_3-2-1_106068_2022-03-03_final.stac-item
2022-04-13 09:11:35	ga_ls9c_ard_3-2-1_089078_2022-04-12_final.stac-item
2022-04-26 10:16:40	ga_ls9c_ard_3-2-1_100071_2022-04-26_final.stac-item
2022-05-07 10:03:39	ga_ls9c_ard_3-2-1_097085_2022-05-07_final.stac-item
2022-05-07 11:41:20	ga_ls9c_ard_3-2-1_113082_2022-05-07_final.stac-item
2022-05-11 11:13:22	ga_ls9c_ard_3-2-1_109074_2022-05-11_final.stac-item
2022-05-20 09:32:57	ga_ls9c_ard_3-2-1_092086_2022-05-20_final.stac-item
2022-06-03 11:23:26	ga_ls9c_ard_3-2-1_110084_2022-06-03_final.stac-item
2022-06-08 09:57:54	ga_ls9c_ard_3-2-1_097071_2022-06-08_final.stac-item
2022-06-12 09:38:48	ga_ls9c_ard_3-2-1_093085_2022-06-12_final.stac-item
2022-06-29 10:21:10	ga_ls9c_ard_3-2-1_100082_2022-06-29_final.stac-item
2022-07-12 11:24:42	ga_ls9c_ard_3-2-1_111071_2022-07-12_final.stac-item
2022-07-16 09:26:17	ga_ls9c_ard_3-2-1_091084_2022-07-15_final.stac-item
2022-07-28 09:46:49	ga_ls9c_ard_3-2-1_095073_2022-07-28_final.stac-item
2022-07-30 11:16:09	ga_ls9c_ard_3-2-1_109080_2022-07-30_final.stac-item
2022-08-01 09:26:08	ga_ls9c_ard_3-2-1_091083_2022-07-31_final.stac-item
2022-08-03 09:11:48	ga_ls9c_ard_3-2-1_089078_2022-08-02_final.stac-item
2022-08-18 10:04:21	ga_ls9c_ard_3-2-1_098070_2022-08-18_final.stac-item
2022-09-10 10:10:34	ga_ls9c_ard_3-2-1_099070_2022-09-10_final.stac-item
2022-09-16 09:40:20	ga_ls9c_ard_3-2-1_093087_2022-09-16_final.stac-item
2022-09-20 09:16:50	ga_ls9c_ard_3-2-1_089090_2022-09-19_final.stac-item
2022-09-27 09:18:39	ga_ls9c_ard_3-2-1_090079_2022-09-26_final.stac-item
2022-10-01 10:28:26	ga_ls9c_ard_3-2-1_102068_2022-10-01_final.stac-item
2022-10-23 09:52:15	ga_ls9c_ard_3-2-1_096070_2022-10-23_final.stac-item
2022-10-26 10:26:20	ga_ls9c_ard_3-2-1_101078_2022-10-26_final.stac-item
2022-11-01 09:48:25	ga_ls9c_ard_3-2-1_095076_2022-11-01_final.stac-item
2022-11-01 11:25:19	ga_ls9c_ard_3-2-1_111071_2022-11-01_final.stac-item
2022-11-05 11:05:22	ga_ls9c_ard_3-2-1_107083_2022-11-05_final.stac-item
2022-11-11 10:23:33	ga_ls9c_ard_3-2-1_101071_2022-11-11_final.stac-item
2022-11-19 09:36:07	ga_ls9c_ard_3-2-1_093076_2022-11-19_final.stac-item
2022-11-22 10:04:13	ga_ls9c_ard_3-2-1_098069_2022-11-22_final.stac-item
2022-12-09 09:14:33	ga_ls9c_ard_3-2-1_089084_2022-12-08_final.stac-item
2022-12-14 09:33:54	ga_ls9c_ard_3-2-1_092086_2022-12-14_final.stac-item
2022-12-18 10:42:04	ga_ls9c_ard_3-2-1_104071_2022-12-18_final.stac-item
2022-12-22 11:58:11	ga_ls9c_ard_3-2-1_116076_2022-12-22_final.stac-item
2022-12-29 10:24:19	ga_ls9c_ard_3-2-1_101073_2022-12-29_final.stac-item
2023-01-10 09:13:45	ga_ls9c_ard_3-2-1_089082_2023-01-09_final.stac-item
2023-01-13 11:18:43	ga_ls9c_ard_3-2-1_110070_2023-01-13_final.stac-item
2023-01-13 11:24:42	ga_ls9c_ard_3-2-1_110085_2023-01-13_final.stac-item
2023-01-16 10:13:05	ga_ls9c_ard_3-2-1_099076_2023-01-16_final.stac-item
2023-01-25 10:04:55	ga_ls9c_ard_3-2-1_098071_2023-01-25_final.stac-item
2023-02-14 11:19:11	ga_ls9c_ard_3-2-1_110071_2023-02-14_final.stac-item
2023-02-18 09:21:54	ga_ls9c_ard_3-2-1_090087_2023-02-17_final.stac-item
2023-02-27 09:14:47	ga_ls9c_ard_3-2-1_089085_2023-02-26_final.stac-item
2023-02-27 09:15:11	ga_ls9c_ard_3-2-1_089086_2023-02-26_final.stac-item
2023-03-10 10:29:00	ga_ls9c_ard_3-2-1_102070_2023-03-10_final.stac-item
2023-03-15 09:12:16	ga_ls9c_ard_3-2-1_089079_2023-03-14_final.stac-item
2023-03-30 10:08:05	ga_ls9c_ard_3-2-1_098080_2023-03-30_final.stac-item
2023-04-18 10:34:06	ga_ls9c_ard_3-2-1_103068_2023-04-18_final.stac-item
2023-04-22 11:53:03	ga_ls9c_ard_3-2-1_115080_2023-04-22_final.stac-item
2023-05-06 10:27:31	ga_ls9c_ard_3-2-1_101083_2023-05-06_final.stac-item
2023-05-07 09:34:18	ga_ls9c_ard_3-2-1_092089_2023-05-07_final.stac-item
2023-05-23 11:07:03	ga_ls9c_ard_3-2-1_108074_2023-05-23_final.stac-item
2023-05-31 10:16:47	ga_ls9c_ard_3-2-1_100072_2023-05-31_final.stac-item
2023-05-31 11:57:16	ga_ls9c_ard_3-2-1_116076_2023-05-31_final.stac-item
2023-06-03 10:48:28	ga_ls9c_ard_3-2-1_105074_2023-06-03_final.stac-item
2023-06-03 10:48:52	ga_ls9c_ard_3-2-1_105075_2023-06-03_final.stac-item
2023-06-08 09:32:04	ga_ls9c_ard_3-2-1_092084_2023-06-08_final.stac-item
2023-06-09 10:09:20	ga_ls9c_ard_3-2-1_099069_2023-06-09_final.stac-item
2023-06-23 10:26:48	ga_ls9c_ard_3-2-1_101082_2023-06-23_final.stac-item
2023-06-29 09:49:01	ga_ls9c_ard_3-2-1_095080_2023-06-29_final.stac-item
2023-07-05 10:46:32	ga_ls9c_ard_3-2-1_105069_2023-07-05_final.stac-item
2023-07-06 09:57:43	ga_ls9c_ard_3-2-1_096086_2023-07-06_final.stac-item
2023-07-10 09:33:26	ga_ls9c_ard_3-2-1_092087_2023-07-10_final.stac-item
2023-07-31 11:25:22	ga_ls9c_ard_3-2-1_111073_2023-07-31_final.stac-item
2023-08-04 09:26:12	ga_ls9c_ard_3-2-1_091084_2023-08-03_final.stac-item
2023-08-14 09:57:20	ga_ls9c_ard_3-2-1_097069_2023-08-14_final.stac-item
2023-08-18 09:39:47	ga_ls9c_ard_3-2-1_093087_2023-08-18_final.stac-item
2023-08-18 11:13:53	ga_ls9c_ard_3-2-1_109075_2023-08-18_final.stac-item
2023-09-01 09:50:44	ga_ls9c_ard_3-2-1_095083_2023-09-01_final.stac-item
2023-09-01 11:26:26	ga_ls9c_ard_3-2-1_111075_2023-09-01_final.stac-item
2023-09-14 09:21:34	ga_ls9c_ard_3-2-1_090087_2023-09-13_final.stac-item
2023-10-09 09:12:39	ga_ls9c_ard_3-2-1_089080_2023-10-08_final.stac-item
2023-10-24 11:47:39	ga_ls9c_ard_3-2-1_114081_2023-10-24_final.stac-item
2023-10-31 10:13:17	ga_ls9c_ard_3-2-1_099077_2023-10-31_final.stac-item
2023-10-31 10:13:41	ga_ls9c_ard_3-2-1_099078_2023-10-31_final.stac-item
2023-11-10 09:11:30	ga_ls9c_ard_3-2-1_089077_2023-11-09_final.stac-item
2023-11-21 10:33:31	ga_ls9c_ard_3-2-1_102081_2023-11-21_final.stac-item
2023-11-23 10:21:59	ga_ls9c_ard_3-2-1_100083_2023-11-23_final.stac-item
2023-11-27 09:52:30	ga_ls9c_ard_3-2-1_096071_2023-11-27_final.stac-item
2023-12-01 09:32:09	ga_ls9c_ard_3-2-1_092082_2023-12-01_final.stac-item
2023-12-04 11:42:19	ga_ls9c_ard_3-2-1_113083_2023-12-04_final.stac-item
2023-12-06 11:26:44	ga_ls9c_ard_3-2-1_111075_2023-12-06_final.stac-item
2023-12-20 09:58:42	ga_ls9c_ard_3-2-1_097071_2023-12-20_final.stac-item
2024-02-01 11:18:36	ga_ls9c_ard_3-2-1_110070_2024-02-01_final.stac-item
2024-02-04 11:53:31	ga_ls9c_ard_3-2-1_115080_2024-02-04_final.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