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
2021-12-12 10:14:38	ga_ls9c_ard_3-2-1_099080_2021-12-12_final.stac-item
2021-12-12 11:51:08	ga_ls9c_ard_3-2-1_115074_2021-12-12_final.stac-item
2021-12-16 11:26:45	ga_ls9c_ard_3-2-1_111075_2021-12-16_final.stac-item
2022-01-01 09:46:17	ga_ls9c_ard_3-2-1_095071_2022-01-01_final.stac-item
2022-01-03 09:39:55	ga_ls9c_ard_3-2-1_093086_2022-01-03_final.stac-item
2022-01-06 11:46:53	ga_ls9c_ard_3-2-1_114079_2022-01-06_final.stac-item
2022-01-14 09:21:43	ga_ls9c_ard_3-2-1_090087_2022-01-13_final.stac-item
2022-01-21 09:25:08	ga_ls9c_ard_3-2-1_091080_2022-01-20_final.stac-item
2022-01-21 09:28:44	ga_ls9c_ard_3-2-1_091089_2022-01-20_final.stac-item
2022-01-30 10:57:51	ga_ls9c_ard_3-2-1_106080_2022-01-30_final.stac-item
2022-02-04 11:17:35	ga_ls9c_ard_3-2-1_109083_2022-02-04_final.stac-item
2022-02-06 09:23:32	ga_ls9c_ard_3-2-1_091076_2022-02-05_final.stac-item
2022-02-13 09:32:04	ga_ls9c_ard_3-2-1_092082_2022-02-13_final.stac-item
2022-02-17 09:07:43	ga_ls9c_ard_3-2-1_088083_2022-02-16_final.stac-item
2022-03-20 11:39:14	ga_ls9c_ard_3-2-1_113076_2022-03-20_final.stac-item
2022-03-24 11:14:53	ga_ls9c_ard_3-2-1_109077_2022-03-24_final.stac-item
2022-03-27 10:08:28	ga_ls9c_ard_3-2-1_098081_2022-03-27_final.stac-item
2022-03-30 10:35:00	ga_ls9c_ard_3-2-1_103070_2022-03-30_final.stac-item
2022-03-31 09:42:10	ga_ls9c_ard_3-2-1_094077_2022-03-31_final.stac-item
2022-04-02 11:05:30	ga_ls9c_ard_3-2-1_108069_2022-04-02_final.stac-item
2022-04-17 10:23:42	ga_ls9c_ard_3-2-1_101073_2022-04-17_final.stac-item
2022-04-29 09:12:40	ga_ls9c_ard_3-2-1_089081_2022-04-28_final.stac-item
2022-05-02 11:22:26	ga_ls9c_ard_3-2-1_110081_2022-05-02_final.stac-item
2022-05-06 09:19:12	ga_ls9c_ard_3-2-1_090082_2022-05-05_final.stac-item
2022-05-08 10:40:31	ga_ls9c_ard_3-2-1_104069_2022-05-08_final.stac-item
2022-05-12 10:20:08	ga_ls9c_ard_3-2-1_100080_2022-05-12_final.stac-item
2022-05-16 09:54:57	ga_ls9c_ard_3-2-1_096079_2022-05-16_final.stac-item
2022-05-17 10:35:48	ga_ls9c_ard_3-2-1_103073_2022-05-17_final.stac-item
2022-05-18 09:42:34	ga_ls9c_ard_3-2-1_094079_2022-05-18_final.stac-item
2022-05-23 09:57:52	ga_ls9c_ard_3-2-1_097071_2022-05-23_final.stac-item
2022-05-24 10:40:44	ga_ls9c_ard_3-2-1_104070_2022-05-24_final.stac-item
2022-05-29 11:00:29	ga_ls9c_ard_3-2-1_107073_2022-05-29_final.stac-item
2022-06-07 10:53:31	ga_ls9c_ard_3-2-1_106071_2022-06-07_final.stac-item
2022-06-09 10:40:46	ga_ls9c_ard_3-2-1_104070_2022-06-09_final.stac-item
2022-06-10 11:24:50	ga_ls9c_ard_3-2-1_111072_2022-06-10_final.stac-item
2022-06-19 09:42:42	ga_ls9c_ard_3-2-1_094079_2022-06-19_final.stac-item
2022-06-19 11:21:12	ga_ls9c_ard_3-2-1_110078_2022-06-19_final.stac-item
2022-06-21 11:06:07	ga_ls9c_ard_3-2-1_108071_2022-06-21_final.stac-item
2022-07-01 11:45:42	ga_ls9c_ard_3-2-1_114077_2022-07-01_final.stac-item
2022-07-06 10:23:44	ga_ls9c_ard_3-2-1_101073_2022-07-06_final.stac-item
2022-07-13 10:31:28	ga_ls9c_ard_3-2-1_102077_2022-07-13_final.stac-item
2022-07-18 09:13:34	ga_ls9c_ard_3-2-1_089083_2022-07-17_final.stac-item
2022-07-21 11:18:37	ga_ls9c_ard_3-2-1_110071_2022-07-21_final.stac-item
2022-07-26 09:58:45	ga_ls9c_ard_3-2-1_097072_2022-07-26_final.stac-item
2022-07-30 09:37:40	ga_ls9c_ard_3-2-1_093081_2022-07-30_final.stac-item
2022-08-05 10:34:45	ga_ls9c_ard_3-2-1_103069_2022-08-05_final.stac-item
2022-08-10 09:19:15	ga_ls9c_ard_3-2-1_090081_2022-08-09_final.stac-item
2022-08-15 11:16:43	ga_ls9c_ard_3-2-1_109081_2022-08-15_final.stac-item
2022-08-20 09:53:36	ga_ls9c_ard_3-2-1_096074_2022-08-20_final.stac-item
2022-08-26 09:19:44	ga_ls9c_ard_3-2-1_090082_2022-08-25_final.stac-item
2022-08-31 11:12:22	ga_ls9c_ard_3-2-1_109070_2022-08-31_final.stac-item
2022-09-05 09:56:24	ga_ls9c_ard_3-2-1_096081_2022-09-05_final.stac-item
2022-09-11 09:18:32	ga_ls9c_ard_3-2-1_090079_2022-09-10_final.stac-item
2022-09-12 09:58:37	ga_ls9c_ard_3-2-1_097071_2022-09-12_final.stac-item
2022-09-20 09:14:26	ga_ls9c_ard_3-2-1_089084_2022-09-19_final.stac-item
2022-09-24 10:25:26	ga_ls9c_ard_3-2-1_101076_2022-09-24_final.stac-item
2022-09-29 10:44:47	ga_ls9c_ard_3-2-1_104078_2022-09-29_final.stac-item
2022-10-04 09:24:02	ga_ls9c_ard_3-2-1_091077_2022-10-03_final.stac-item
2022-10-11 09:35:27	ga_ls9c_ard_3-2-1_092090_2022-10-11_final.stac-item
2022-10-13 09:18:19	ga_ls9c_ard_3-2-1_090078_2022-10-12_final.stac-item
2022-10-17 10:33:42	ga_ls9c_ard_3-2-1_102081_2022-10-17_final.stac-item
2022-10-18 11:12:59	ga_ls9c_ard_3-2-1_109071_2022-10-18_final.stac-item
2022-11-01 11:29:18	ga_ls9c_ard_3-2-1_111081_2022-11-01_final.stac-item
2022-11-01 11:29:42	ga_ls9c_ard_3-2-1_111082_2022-11-01_final.stac-item
2022-11-03 09:38:26	ga_ls9c_ard_3-2-1_093082_2022-11-03_final.stac-item
2022-11-03 11:12:56	ga_ls9c_ard_3-2-1_109071_2022-11-03_final.stac-item
2022-12-09 10:46:40	ga_ls9c_ard_3-2-1_105067_2022-12-09_final.stac-item
2022-12-17 10:04:00	ga_ls9c_ard_3-2-1_097084_2022-12-17_final.stac-item
2023-01-07 10:21:45	ga_ls9c_ard_3-2-1_100082_2023-01-07_final.stac-item
2023-01-09 10:06:59	ga_ls9c_ard_3-2-1_098076_2023-01-09_final.stac-item
2023-01-09 11:46:16	ga_ls9c_ard_3-2-1_114077_2023-01-09_final.stac-item
2023-01-16 10:15:29	ga_ls9c_ard_3-2-1_099082_2023-01-16_final.stac-item
2023-01-16 11:52:22	ga_ls9c_ard_3-2-1_115077_2023-01-16_final.stac-item
2023-02-02 09:20:46	ga_ls9c_ard_3-2-1_090084_2023-02-01_final.stac-item
2023-02-10 10:06:39	ga_ls9c_ard_3-2-1_098075_2023-02-10_final.stac-item
2023-02-11 09:10:37	ga_ls9c_ard_3-2-1_089074_2023-02-10_final.stac-item
2023-02-14 09:42:18	ga_ls9c_ard_3-2-1_094076_2023-02-14_final.stac-item
2023-03-12 10:21:26	ga_ls9c_ard_3-2-1_100082_2023-03-12_final.stac-item
2023-03-15 09:15:04	ga_ls9c_ard_3-2-1_089086_2023-03-14_final.stac-item
2023-04-12 11:16:24	ga_ls9c_ard_3-2-1_109081_2023-04-12_final.stac-item
2023-04-14 09:21:56	ga_ls9c_ard_3-2-1_091073_2023-04-13_final.stac-item
2023-05-01 10:08:15	ga_ls9c_ard_3-2-1_098081_2023-05-01_final.stac-item
2023-05-04 10:34:42	ga_ls9c_ard_3-2-1_103070_2023-05-04_final.stac-item
2023-05-11 10:40:28	ga_ls9c_ard_3-2-1_104069_2023-05-11_final.stac-item
2023-05-21 11:21:02	ga_ls9c_ard_3-2-1_110078_2023-05-21_final.stac-item
2023-05-26 10:00:38	ga_ls9c_ard_3-2-1_097078_2023-05-26_final.stac-item
2023-05-26 11:41:07	ga_ls9c_ard_3-2-1_113082_2023-05-26_final.stac-item
2023-06-16 10:19:49	ga_ls9c_ard_3-2-1_100080_2023-06-16_final.stac-item
2023-06-26 09:17:13	ga_ls9c_ard_3-2-1_090078_2023-06-25_final.stac-item
2023-07-19 09:25:41	ga_ls9c_ard_3-2-1_091083_2023-07-18_final.stac-item
2023-08-08 10:38:24	ga_ls9c_ard_3-2-1_103079_2023-08-08_final.stac-item
2023-10-25 09:10:21	ga_ls9c_ard_3-2-1_089074_2023-10-24_final.stac-item
2023-10-29 10:25:16	ga_ls9c_ard_3-2-1_101076_2023-10-29_final.stac-item
2023-10-30 09:32:02	ga_ls9c_ard_3-2-1_092082_2023-10-30_final.stac-item
2023-11-04 09:49:43	ga_ls9c_ard_3-2-1_095080_2023-11-04_final.stac-item
2023-11-14 10:26:51	ga_ls9c_ard_3-2-1_101080_2023-11-14_final.stac-item
2023-11-19 09:07:45	ga_ls9c_ard_3-2-1_088083_2023-11-18_final.stac-item
2023-11-22 11:17:35	ga_ls9c_ard_3-2-1_109083_2023-11-22_final.stac-item
2023-11-25 11:45:20	ga_ls9c_ard_3-2-1_114075_2023-11-25_final.stac-item
2024-02-16 10:37:40	ga_ls9c_ard_3-2-1_103076_2024-02-16_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