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
2021-12-09 11:23:51	ga_ls9c_ard_3-2-1_110083_2021-12-09_final.stac-item
2021-12-15 10:41:55	ga_ls9c_ard_3-2-1_104071_2021-12-15_final.stac-item
2022-01-08 09:54:02	ga_ls9c_ard_3-2-1_096075_2022-01-08_final.stac-item
2022-01-26 09:43:17	ga_ls9c_ard_3-2-1_094079_2022-01-26_final.stac-item
2022-03-22 09:49:35	ga_ls9c_ard_3-2-1_095080_2022-03-22_final.stac-item
2022-03-23 10:32:26	ga_ls9c_ard_3-2-1_102079_2022-03-23_final.stac-item
2022-04-03 10:14:39	ga_ls9c_ard_3-2-1_099081_2022-04-03_final.stac-item
2022-04-06 10:45:09	ga_ls9c_ard_3-2-1_104080_2022-04-06_final.stac-item
2022-04-14 09:53:38	ga_ls9c_ard_3-2-1_096075_2022-04-14_final.stac-item
2022-04-15 10:38:05	ga_ls9c_ard_3-2-1_103078_2022-04-15_final.stac-item
2022-04-16 09:44:27	ga_ls9c_ard_3-2-1_094083_2022-04-16_final.stac-item
2022-04-30 09:53:55	ga_ls9c_ard_3-2-1_096076_2022-04-30_final.stac-item
2022-05-02 09:41:09	ga_ls9c_ard_3-2-1_094075_2022-05-02_final.stac-item
2022-05-08 10:41:42	ga_ls9c_ard_3-2-1_104072_2022-05-08_final.stac-item
2022-05-08 10:44:54	ga_ls9c_ard_3-2-1_104080_2022-05-08_final.stac-item
2022-06-09 10:44:45	ga_ls9c_ard_3-2-1_104080_2022-06-09_final.stac-item
2022-06-14 11:02:34	ga_ls9c_ard_3-2-1_107078_2022-06-14_final.stac-item
2022-07-11 10:43:27	ga_ls9c_ard_3-2-1_104076_2022-07-11_final.stac-item
2022-07-12 09:49:25	ga_ls9c_ard_3-2-1_095080_2022-07-12_final.stac-item
2022-07-12 09:49:49	ga_ls9c_ard_3-2-1_095081_2022-07-12_final.stac-item
2022-08-04 09:53:53	ga_ls9c_ard_3-2-1_096075_2022-08-04_final.stac-item
2022-08-10 10:57:20	ga_ls9c_ard_3-2-1_106079_2022-08-10_final.stac-item
2022-08-21 10:39:16	ga_ls9c_ard_3-2-1_103080_2022-08-21_final.stac-item
2022-09-12 10:03:25	ga_ls9c_ard_3-2-1_097083_2022-09-12_final.stac-item
2022-09-18 11:03:16	ga_ls9c_ard_3-2-1_107078_2022-09-18_final.stac-item
2022-09-22 10:38:35	ga_ls9c_ard_3-2-1_103078_2022-09-22_final.stac-item
2022-09-23 09:41:46	ga_ls9c_ard_3-2-1_094075_2022-09-23_final.stac-item
2022-10-01 10:31:13	ga_ls9c_ard_3-2-1_102075_2022-10-01_final.stac-item
2022-10-06 09:10:28	ga_ls9c_ard_3-2-1_089074_2022-10-05_final.stac-item
2022-10-07 11:35:00	ga_ls9c_ard_3-2-1_112080_2022-10-07_final.stac-item
2022-10-14 11:40:28	ga_ls9c_ard_3-2-1_113078_2022-10-14_final.stac-item
2022-11-01 11:28:06	ga_ls9c_ard_3-2-1_111078_2022-11-01_final.stac-item
2022-11-06 10:06:10	ga_ls9c_ard_3-2-1_098074_2022-11-06_final.stac-item
2022-11-07 10:51:02	ga_ls9c_ard_3-2-1_105078_2022-11-07_final.stac-item
2022-11-17 09:49:16	ga_ls9c_ard_3-2-1_095078_2022-11-17_final.stac-item
2022-11-17 09:50:04	ga_ls9c_ard_3-2-1_095080_2022-11-17_final.stac-item
2022-11-17 11:28:33	ga_ls9c_ard_3-2-1_111079_2022-11-17_final.stac-item
2022-11-19 09:36:07	ga_ls9c_ard_3-2-1_093076_2022-11-19_final.stac-item
2022-12-01 10:00:22	ga_ls9c_ard_3-2-1_097075_2022-12-01_final.stac-item
2022-12-02 10:42:26	ga_ls9c_ard_3-2-1_104072_2022-12-02_final.stac-item
2022-12-06 10:21:20	ga_ls9c_ard_3-2-1_100081_2022-12-06_final.stac-item
2022-12-18 10:42:28	ga_ls9c_ard_3-2-1_104072_2022-12-18_final.stac-item
2023-01-18 10:03:05	ga_ls9c_ard_3-2-1_097082_2023-01-18_final.stac-item
2023-01-20 09:49:29	ga_ls9c_ard_3-2-1_095079_2023-01-20_final.stac-item
2023-01-20 09:49:53	ga_ls9c_ard_3-2-1_095080_2023-01-20_final.stac-item
2023-01-23 10:20:50	ga_ls9c_ard_3-2-1_100080_2023-01-23_final.stac-item
2023-01-29 09:43:03	ga_ls9c_ard_3-2-1_094078_2023-01-29_final.stac-item
2023-02-03 11:40:56	ga_ls9c_ard_3-2-1_113079_2023-02-03_final.stac-item
2023-02-04 10:42:31	ga_ls9c_ard_3-2-1_104072_2023-02-04_final.stac-item
2023-02-04 10:45:19	ga_ls9c_ard_3-2-1_104079_2023-02-04_final.stac-item
2023-02-04 10:46:07	ga_ls9c_ard_3-2-1_104081_2023-02-04_final.stac-item
2023-03-02 09:41:40	ga_ls9c_ard_3-2-1_094075_2023-03-02_final.stac-item
2023-04-03 09:42:58	ga_ls9c_ard_3-2-1_094079_2023-04-03_final.stac-item
2023-04-24 10:00:11	ga_ls9c_ard_3-2-1_097076_2023-04-24_final.stac-item
2023-04-24 10:02:59	ga_ls9c_ard_3-2-1_097083_2023-04-24_final.stac-item
2023-04-27 10:31:51	ga_ls9c_ard_3-2-1_102078_2023-04-27_final.stac-item
2023-04-28 11:15:30	ga_ls9c_ard_3-2-1_109079_2023-04-28_final.stac-item
2023-05-03 09:56:15	ga_ls9c_ard_3-2-1_096082_2023-05-03_final.stac-item
2023-05-05 11:21:57	ga_ls9c_ard_3-2-1_110080_2023-05-05_final.stac-item
2023-05-09 10:56:26	ga_ls9c_ard_3-2-1_106078_2023-05-09_final.stac-item
2023-05-09 10:58:26	ga_ls9c_ard_3-2-1_106083_2023-05-09_final.stac-item
2023-05-11 10:41:40	ga_ls9c_ard_3-2-1_104072_2023-05-11_final.stac-item
2023-05-11 10:44:04	ga_ls9c_ard_3-2-1_104078_2023-05-11_final.stac-item
2023-05-12 09:49:38	ga_ls9c_ard_3-2-1_095081_2023-05-12_final.stac-item
2023-05-12 11:28:07	ga_ls9c_ard_3-2-1_111080_2023-05-12_final.stac-item
2023-06-20 09:52:19	ga_ls9c_ard_3-2-1_096073_2023-06-20_final.stac-item
2023-06-22 11:21:14	ga_ls9c_ard_3-2-1_110079_2023-06-22_final.stac-item
2023-06-24 09:29:11	ga_ls9c_ard_3-2-1_092077_2023-06-23_final.stac-item
2023-06-28 10:41:25	ga_ls9c_ard_3-2-1_104072_2023-06-28_final.stac-item
2023-06-30 10:29:07	ga_ls9c_ard_3-2-1_102072_2023-06-30_final.stac-item
2023-07-01 09:37:30	ga_ls9c_ard_3-2-1_093082_2023-07-01_final.stac-item
2023-07-02 11:58:04	ga_ls9c_ard_3-2-1_116078_2023-07-02_final.stac-item
2023-07-06 11:32:12	ga_ls9c_ard_3-2-1_112075_2023-07-06_final.stac-item
2023-07-15 11:26:53	ga_ls9c_ard_3-2-1_111077_2023-07-15_final.stac-item
2023-07-16 10:32:04	ga_ls9c_ard_3-2-1_102079_2023-07-16_final.stac-item
2023-07-18 11:57:47	ga_ls9c_ard_3-2-1_116077_2023-07-18_final.stac-item
2023-07-19 11:02:34	ga_ls9c_ard_3-2-1_107078_2023-07-19_final.stac-item
2023-07-19 11:04:10	ga_ls9c_ard_3-2-1_107082_2023-07-19_final.stac-item
2023-07-21 10:47:00	ga_ls9c_ard_3-2-1_105070_2023-07-21_final.stac-item
2023-07-22 09:53:22	ga_ls9c_ard_3-2-1_096075_2023-07-22_final.stac-item
2023-07-22 09:56:10	ga_ls9c_ard_3-2-1_096082_2023-07-22_final.stac-item
2023-07-26 09:29:27	ga_ls9c_ard_3-2-1_092077_2023-07-25_final.stac-item
2023-07-29 10:02:48	ga_ls9c_ard_3-2-1_097083_2023-07-29_final.stac-item
2023-07-30 10:44:53	ga_ls9c_ard_3-2-1_104080_2023-07-30_final.stac-item
2023-08-04 11:04:17	ga_ls9c_ard_3-2-1_107082_2023-08-04_final.stac-item
2023-08-05 10:08:17	ga_ls9c_ard_3-2-1_098081_2023-08-05_final.stac-item
2023-10-17 11:40:17	ga_ls9c_ard_3-2-1_113078_2023-10-17_final.stac-item
2023-10-18 10:45:52	ga_ls9c_ard_3-2-1_104081_2023-10-18_final.stac-item
2023-10-26 09:56:00	ga_ls9c_ard_3-2-1_096080_2023-10-26_final.stac-item
2023-10-26 09:56:48	ga_ls9c_ard_3-2-1_096082_2023-10-26_final.stac-item
2023-10-27 10:40:03	ga_ls9c_ard_3-2-1_103082_2023-10-27_final.stac-item
2023-10-29 10:27:16	ga_ls9c_ard_3-2-1_101081_2023-10-29_final.stac-item
2023-11-03 10:41:44	ga_ls9c_ard_3-2-1_104071_2023-11-03_final.stac-item
2023-11-03 10:45:44	ga_ls9c_ard_3-2-1_104081_2023-11-03_final.stac-item
2023-11-04 11:27:25	ga_ls9c_ard_3-2-1_111077_2023-11-04_final.stac-item
2023-11-04 11:29:24	ga_ls9c_ard_3-2-1_111082_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
2023-11-18 10:02:34	ga_ls9c_ard_3-2-1_097081_2023-11-18_final.stac-item
2023-11-18 11:40:39	ga_ls9c_ard_3-2-1_113079_2023-11-18_final.stac-item
2023-11-19 10:45:50	ga_ls9c_ard_3-2-1_104081_2023-11-19_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