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
2021-11-05 09:36:37	ga_ls9c_ard_3-2-1_093076_2021-11-05_final.stac-item
2021-11-13 10:03:05	ga_ls9c_ard_3-2-1_097083_2021-11-13_final.stac-item
2021-12-29 10:58:16	ga_ls9c_ard_3-2-1_106081_2021-12-29_final.stac-item
2022-01-14 10:58:12	ga_ls9c_ard_3-2-1_106081_2022-01-14_final.stac-item
2022-01-30 09:22:34	ga_ls9c_ard_3-2-1_090089_2022-01-29_final.stac-item
2022-02-13 11:11:45	ga_ls9c_ard_3-2-1_108084_2022-02-13_final.stac-item
2022-03-06 09:47:38	ga_ls9c_ard_3-2-1_095075_2022-03-06_final.stac-item
2022-05-18 09:43:21	ga_ls9c_ard_3-2-1_094081_2022-05-18_final.stac-item
2022-06-21 09:30:49	ga_ls9c_ard_3-2-1_092080_2022-06-21_final.stac-item
2022-06-21 11:10:06	ga_ls9c_ard_3-2-1_108081_2022-06-21_final.stac-item
2022-07-26 09:57:57	ga_ls9c_ard_3-2-1_097070_2022-07-26_final.stac-item
2022-08-13 09:47:47	ga_ls9c_ard_3-2-1_095075_2022-08-13_final.stac-item
2022-09-17 10:22:00	ga_ls9c_ard_3-2-1_100083_2022-09-17_final.stac-item
2022-10-05 11:46:10	ga_ls9c_ard_3-2-1_114077_2022-10-05_final.stac-item
2022-10-19 11:59:02	ga_ls9c_ard_3-2-1_116078_2022-10-19_final.stac-item
2022-10-31 10:44:03	ga_ls9c_ard_3-2-1_104076_2022-10-31_final.stac-item
2022-11-06 11:47:27	ga_ls9c_ard_3-2-1_114080_2022-11-06_final.stac-item
2022-11-15 09:58:26	ga_ls9c_ard_3-2-1_097070_2022-11-15_final.stac-item
2022-12-12 11:23:57	ga_ls9c_ard_3-2-1_110083_2022-12-12_final.stac-item
2022-12-15 11:52:27	ga_ls9c_ard_3-2-1_115077_2022-12-15_final.stac-item
2022-12-23 09:28:52	ga_ls9c_ard_3-2-1_091089_2022-12-22_final.stac-item
2022-12-27 10:38:39	ga_ls9c_ard_3-2-1_103078_2022-12-27_final.stac-item
2022-12-30 09:31:06	ga_ls9c_ard_3-2-1_092079_2022-12-30_final.stac-item
2023-01-04 11:29:44	ga_ls9c_ard_3-2-1_111082_2023-01-04_final.stac-item
2023-01-07 10:18:33	ga_ls9c_ard_3-2-1_100074_2023-01-07_final.stac-item
2023-01-10 09:14:33	ga_ls9c_ard_3-2-1_089084_2023-01-09_final.stac-item
2023-01-17 10:57:32	ga_ls9c_ard_3-2-1_106079_2023-01-17_final.stac-item
2023-01-27 09:56:59	ga_ls9c_ard_3-2-1_096082_2023-01-27_final.stac-item
2023-02-03 10:04:02	ga_ls9c_ard_3-2-1_097084_2023-02-03_final.stac-item
2023-02-08 10:18:13	ga_ls9c_ard_3-2-1_100073_2023-02-08_final.stac-item
2023-04-22 10:14:10	ga_ls9c_ard_3-2-1_099080_2023-04-22_final.stac-item
2023-04-23 09:19:44	ga_ls9c_ard_3-2-1_090083_2023-04-22_final.stac-item
2023-04-23 10:54:13	ga_ls9c_ard_3-2-1_106072_2023-04-23_final.stac-item
2023-04-23 10:57:01	ga_ls9c_ard_3-2-1_106079_2023-04-23_final.stac-item
2023-04-25 10:40:39	ga_ls9c_ard_3-2-1_104069_2023-04-25_final.stac-item
2023-04-25 10:45:26	ga_ls9c_ard_3-2-1_104081_2023-04-25_final.stac-item
2023-04-26 09:47:00	ga_ls9c_ard_3-2-1_095074_2023-04-26_final.stac-item
2023-04-28 09:37:01	ga_ls9c_ard_3-2-1_093080_2023-04-28_final.stac-item
2023-04-28 11:12:42	ga_ls9c_ard_3-2-1_109072_2023-04-28_final.stac-item
2023-04-28 11:17:05	ga_ls9c_ard_3-2-1_109083_2023-04-28_final.stac-item
2023-04-30 10:59:54	ga_ls9c_ard_3-2-1_107071_2023-04-30_final.stac-item
2023-04-30 11:04:18	ga_ls9c_ard_3-2-1_107082_2023-04-30_final.stac-item
2023-07-05 10:45:44	ga_ls9c_ard_3-2-1_105067_2023-07-05_final.stac-item
2023-07-24 11:22:41	ga_ls9c_ard_3-2-1_110082_2023-07-24_final.stac-item
2023-07-24 11:23:52	ga_ls9c_ard_3-2-1_110085_2023-07-24_final.stac-item
2023-07-27 10:09:09	ga_ls9c_ard_3-2-1_099068_2023-07-27_final.stac-item
2023-07-27 10:09:57	ga_ls9c_ard_3-2-1_099070_2023-07-27_final.stac-item
2023-07-28 10:53:13	ga_ls9c_ard_3-2-1_106070_2023-07-28_final.stac-item
2023-08-02 09:34:57	ga_ls9c_ard_3-2-1_093075_2023-08-02_final.stac-item
2023-08-02 09:38:33	ga_ls9c_ard_3-2-1_093084_2023-08-02_final.stac-item
2023-08-04 09:26:36	ga_ls9c_ard_3-2-1_091085_2023-08-03_final.stac-item
2023-08-04 11:01:06	ga_ls9c_ard_3-2-1_107074_2023-08-04_final.stac-item
2023-08-04 11:02:18	ga_ls9c_ard_3-2-1_107077_2023-08-04_final.stac-item
2023-08-05 11:44:22	ga_ls9c_ard_3-2-1_114074_2023-08-05_final.stac-item
2023-10-13 10:23:18	ga_ls9c_ard_3-2-1_101071_2023-10-13_final.stac-item
2023-10-14 09:31:40	ga_ls9c_ard_3-2-1_092081_2023-10-14_final.stac-item
2023-10-15 10:09:45	ga_ls9c_ard_3-2-1_099068_2023-10-15_final.stac-item
2023-10-16 09:20:08	ga_ls9c_ard_3-2-1_090083_2023-10-15_final.stac-item
2023-10-16 10:57:25	ga_ls9c_ard_3-2-1_106079_2023-10-16_final.stac-item
2023-10-17 10:01:24	ga_ls9c_ard_3-2-1_097078_2023-10-17_final.stac-item
2023-10-17 10:01:48	ga_ls9c_ard_3-2-1_097079_2023-10-17_final.stac-item
2023-10-17 11:41:05	ga_ls9c_ard_3-2-1_113080_2023-10-17_final.stac-item
2023-10-17 11:41:53	ga_ls9c_ard_3-2-1_113082_2023-10-17_final.stac-item
2023-10-20 10:30:43	ga_ls9c_ard_3-2-1_102074_2023-10-20_final.stac-item
2023-10-20 10:31:07	ga_ls9c_ard_3-2-1_102075_2023-10-20_final.stac-item
2023-10-20 10:33:06	ga_ls9c_ard_3-2-1_102080_2023-10-20_final.stac-item
2023-10-21 11:12:23	ga_ls9c_ard_3-2-1_109070_2023-10-21_final.stac-item
2023-10-21 11:15:10	ga_ls9c_ard_3-2-1_109077_2023-10-21_final.stac-item
2023-10-22 10:19:09	ga_ls9c_ard_3-2-1_100076_2023-10-22_final.stac-item
2023-10-22 10:21:33	ga_ls9c_ard_3-2-1_100082_2023-10-22_final.stac-item
2023-10-23 09:25:31	ga_ls9c_ard_3-2-1_091081_2023-10-22_final.stac-item
2023-10-24 10:03:59	ga_ls9c_ard_3-2-1_098069_2023-10-24_final.stac-item
2023-10-24 10:05:59	ga_ls9c_ard_3-2-1_098074_2023-10-24_final.stac-item
2023-10-24 11:46:52	ga_ls9c_ard_3-2-1_114079_2023-10-24_final.stac-item
2023-10-25 09:13:09	ga_ls9c_ard_3-2-1_089081_2023-10-24_final.stac-item
2023-10-26 09:52:25	ga_ls9c_ard_3-2-1_096071_2023-10-26_final.stac-item
2023-10-26 09:53:12	ga_ls9c_ard_3-2-1_096073_2023-10-26_final.stac-item
2023-10-27 10:39:15	ga_ls9c_ard_3-2-1_103080_2023-10-27_final.stac-item
2023-10-29 10:28:04	ga_ls9c_ard_3-2-1_101083_2023-10-29_final.stac-item
2023-10-30 09:31:14	ga_ls9c_ard_3-2-1_092080_2023-10-30_final.stac-item
2023-10-30 09:32:02	ga_ls9c_ard_3-2-1_092082_2023-10-30_final.stac-item
2023-10-30 11:11:19	ga_ls9c_ard_3-2-1_108083_2023-10-30_final.stac-item
2023-11-01 09:20:02	ga_ls9c_ard_3-2-1_090083_2023-10-31_final.stac-item
2023-11-01 09:20:26	ga_ls9c_ard_3-2-1_090084_2023-10-31_final.stac-item
2023-11-02 10:01:41	ga_ls9c_ard_3-2-1_097079_2023-11-02_final.stac-item
2023-11-02 10:02:53	ga_ls9c_ard_3-2-1_097082_2023-11-02_final.stac-item
2023-11-02 11:41:46	ga_ls9c_ard_3-2-1_113082_2023-11-02_final.stac-item
2023-11-04 09:47:44	ga_ls9c_ard_3-2-1_095075_2023-11-04_final.stac-item
2023-11-05 10:31:00	ga_ls9c_ard_3-2-1_102075_2023-11-05_final.stac-item
2023-11-05 10:31:48	ga_ls9c_ard_3-2-1_102077_2023-11-05_final.stac-item
2023-11-15 11:05:43	ga_ls9c_ard_3-2-1_108069_2023-11-15_final.stac-item
2023-11-15 11:10:30	ga_ls9c_ard_3-2-1_108081_2023-11-15_final.stac-item
2023-11-18 09:58:58	ga_ls9c_ard_3-2-1_097072_2023-11-18_final.stac-item
2023-11-18 11:41:03	ga_ls9c_ard_3-2-1_113080_2023-11-18_final.stac-item
2023-11-19 10:44:15	ga_ls9c_ard_3-2-1_104077_2023-11-19_final.stac-item
2023-11-22 09:37:30	ga_ls9c_ard_3-2-1_093080_2023-11-22_final.stac-item
2023-11-22 11:12:24	ga_ls9c_ard_3-2-1_109070_2023-11-22_final.stac-item
2023-11-23 10:17:59	ga_ls9c_ard_3-2-1_100073_2023-11-23_final.stac-item
2023-11-25 10:06:27	ga_ls9c_ard_3-2-1_098075_2023-11-25_final.stac-item
2023-11-26 09:14:01	ga_ls9c_ard_3-2-1_089083_2023-11-25_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