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
2021-11-03 09:54:34	ga_ls9c_ard_3-2-1_096074_2021-11-03_final.stac-item
2021-11-20 09:43:13	ga_ls9c_ard_3-2-1_094074_2021-11-20_final.stac-item
2021-12-09 09:45:46	ga_ls9c_ard_3-2-1_094085_2021-12-09_final.stac-item
2021-12-24 10:35:44	ga_ls9c_ard_3-2-1_103071_2021-12-24_final.stac-item
2021-12-27 09:34:32	ga_ls9c_ard_3-2-1_092088_2021-12-27_final.stac-item
2021-12-29 09:18:35	ga_ls9c_ard_3-2-1_090079_2021-12-28_final.stac-item
2022-01-10 09:42:04	ga_ls9c_ard_3-2-1_094076_2022-01-10_final.stac-item
2022-01-30 10:56:39	ga_ls9c_ard_3-2-1_106077_2022-01-30_final.stac-item
2022-02-11 09:45:39	ga_ls9c_ard_3-2-1_094085_2022-02-11_final.stac-item
2022-02-15 10:55:23	ga_ls9c_ard_3-2-1_106074_2022-02-15_final.stac-item
2022-02-17 10:42:36	ga_ls9c_ard_3-2-1_104073_2022-02-17_final.stac-item
2022-02-24 09:15:00	ga_ls9c_ard_3-2-1_089086_2022-02-23_final.stac-item
2022-03-03 09:19:55	ga_ls9c_ard_3-2-1_090083_2022-03-02_final.stac-item
2022-04-16 09:40:27	ga_ls9c_ard_3-2-1_094073_2022-04-16_final.stac-item
2022-05-21 10:12:14	ga_ls9c_ard_3-2-1_099076_2022-05-21_final.stac-item
2022-05-29 09:25:35	ga_ls9c_ard_3-2-1_091083_2022-05-28_final.stac-item
2022-06-03 09:40:09	ga_ls9c_ard_3-2-1_094073_2022-06-03_final.stac-item
2022-07-02 10:52:28	ga_ls9c_ard_3-2-1_105083_2022-07-02_final.stac-item
2022-07-10 09:59:23	ga_ls9c_ard_3-2-1_097074_2022-07-10_final.stac-item
2022-07-16 11:01:59	ga_ls9c_ard_3-2-1_107076_2022-07-16_final.stac-item
2022-08-03 10:50:17	ga_ls9c_ard_3-2-1_105077_2022-08-03_final.stac-item
2022-08-06 11:20:49	ga_ls9c_ard_3-2-1_110076_2022-08-06_final.stac-item
2022-08-10 10:54:09	ga_ls9c_ard_3-2-1_106071_2022-08-10_final.stac-item
2022-09-03 10:08:22	ga_ls9c_ard_3-2-1_098080_2022-09-03_final.stac-item
2022-09-19 10:07:16	ga_ls9c_ard_3-2-1_098077_2022-09-19_final.stac-item
2022-09-28 10:01:55	ga_ls9c_ard_3-2-1_097079_2022-09-28_final.stac-item
2022-10-01 10:32:01	ga_ls9c_ard_3-2-1_102077_2022-10-01_final.stac-item
2022-10-02 09:34:00	ga_ls9c_ard_3-2-1_093071_2022-10-02_final.stac-item
2022-10-03 10:19:15	ga_ls9c_ard_3-2-1_100076_2022-10-03_final.stac-item
2022-10-05 11:46:10	ga_ls9c_ard_3-2-1_114077_2022-10-05_final.stac-item
2022-10-06 10:52:56	ga_ls9c_ard_3-2-1_105083_2022-10-06_final.stac-item
2022-10-09 11:23:28	ga_ls9c_ard_3-2-1_110082_2022-10-09_final.stac-item
2022-10-22 09:14:10	ga_ls9c_ard_3-2-1_089083_2022-10-21_final.stac-item
2022-10-22 10:46:40	ga_ls9c_ard_3-2-1_105067_2022-10-22_final.stac-item
2022-10-29 09:19:32	ga_ls9c_ard_3-2-1_090081_2022-10-28_final.stac-item
2022-11-09 10:38:17	ga_ls9c_ard_3-2-1_103077_2022-11-09_final.stac-item
2022-11-10 11:18:46	ga_ls9c_ard_3-2-1_110070_2022-11-10_final.stac-item
2022-11-13 10:13:11	ga_ls9c_ard_3-2-1_099076_2022-11-13_final.stac-item
2022-11-19 09:38:06	ga_ls9c_ard_3-2-1_093081_2022-11-19_final.stac-item
2022-11-23 09:14:10	ga_ls9c_ard_3-2-1_089083_2022-11-22_final.stac-item
2022-11-26 09:45:03	ga_ls9c_ard_3-2-1_094083_2022-11-26_final.stac-item
2022-12-03 09:52:24	ga_ls9c_ard_3-2-1_095086_2022-12-03_final.stac-item
2022-12-04 10:32:05	ga_ls9c_ard_3-2-1_102077_2022-12-04_final.stac-item
2022-12-08 11:45:52	ga_ls9c_ard_3-2-1_114076_2022-12-08_final.stac-item
2022-12-09 10:47:51	ga_ls9c_ard_3-2-1_105070_2022-12-09_final.stac-item
2022-12-10 11:32:19	ga_ls9c_ard_3-2-1_112073_2022-12-10_final.stac-item
2022-12-10 11:33:07	ga_ls9c_ard_3-2-1_112075_2022-12-10_final.stac-item
2022-12-13 10:26:20	ga_ls9c_ard_3-2-1_101078_2022-12-13_final.stac-item
2022-12-31 10:12:22	ga_ls9c_ard_3-2-1_099074_2022-12-31_final.stac-item
2023-01-08 09:28:55	ga_ls9c_ard_3-2-1_091089_2023-01-07_final.stac-item
2023-01-08 11:02:13	ga_ls9c_ard_3-2-1_107075_2023-01-08_final.stac-item
2023-01-09 11:45:52	ga_ls9c_ard_3-2-1_114076_2023-01-09_final.stac-item
2023-01-10 09:15:21	ga_ls9c_ard_3-2-1_089086_2023-01-09_final.stac-item
2023-01-16 11:52:22	ga_ls9c_ard_3-2-1_115077_2023-01-16_final.stac-item
2023-01-23 11:58:07	ga_ls9c_ard_3-2-1_116076_2023-01-23_final.stac-item
2023-02-03 10:03:14	ga_ls9c_ard_3-2-1_097082_2023-02-03_final.stac-item
2023-02-03 11:41:20	ga_ls9c_ard_3-2-1_113080_2023-02-03_final.stac-item
2023-03-13 09:25:01	ga_ls9c_ard_3-2-1_091080_2023-03-12_final.stac-item
2023-03-13 09:25:25	ga_ls9c_ard_3-2-1_091081_2023-03-12_final.stac-item
2023-04-03 11:20:40	ga_ls9c_ard_3-2-1_110076_2023-04-03_final.stac-item
2023-04-21 09:33:18	ga_ls9c_ard_3-2-1_092086_2023-04-21_final.stac-item
2023-04-26 11:29:29	ga_ls9c_ard_3-2-1_111083_2023-04-26_final.stac-item
2023-04-28 11:16:17	ga_ls9c_ard_3-2-1_109081_2023-04-28_final.stac-item
2023-05-01 10:05:04	ga_ls9c_ard_3-2-1_098073_2023-05-01_final.stac-item
2023-05-03 09:51:52	ga_ls9c_ard_3-2-1_096071_2023-05-03_final.stac-item
2023-05-06 10:22:44	ga_ls9c_ard_3-2-1_101071_2023-05-06_final.stac-item
2023-05-14 09:34:28	ga_ls9c_ard_3-2-1_093074_2023-05-14_final.stac-item
2023-05-14 09:37:15	ga_ls9c_ard_3-2-1_093081_2023-05-14_final.stac-item
2023-05-16 11:01:46	ga_ls9c_ard_3-2-1_107076_2023-05-16_final.stac-item
2023-05-18 09:12:30	ga_ls9c_ard_3-2-1_089081_2023-05-17_final.stac-item
2023-05-30 11:12:00	ga_ls9c_ard_3-2-1_109071_2023-05-30_final.stac-item
2023-06-01 09:22:45	ga_ls9c_ard_3-2-1_091076_2023-05-31_final.stac-item
2023-06-22 09:40:21	ga_ls9c_ard_3-2-1_094074_2023-06-22_final.stac-item
2023-06-25 10:12:02	ga_ls9c_ard_3-2-1_099076_2023-06-25_final.stac-item
2023-07-17 11:12:56	ga_ls9c_ard_3-2-1_109073_2023-07-17_final.stac-item
2023-07-21 09:14:30	ga_ls9c_ard_3-2-1_089086_2023-07-20_final.stac-item
2023-07-24 09:43:48	ga_ls9c_ard_3-2-1_094082_2023-07-24_final.stac-item
2023-07-29 10:03:36	ga_ls9c_ard_3-2-1_097085_2023-07-29_final.stac-item
2023-07-30 10:40:06	ga_ls9c_ard_3-2-1_104068_2023-07-30_final.stac-item
2023-07-30 10:42:30	ga_ls9c_ard_3-2-1_104074_2023-07-30_final.stac-item
2023-08-02 09:34:57	ga_ls9c_ard_3-2-1_093075_2023-08-02_final.stac-item
2023-08-04 09:24:36	ga_ls9c_ard_3-2-1_091080_2023-08-03_final.stac-item
2023-08-04 11:01:54	ga_ls9c_ard_3-2-1_107076_2023-08-04_final.stac-item
2023-08-05 11:47:10	ga_ls9c_ard_3-2-1_114081_2023-08-05_final.stac-item
2023-08-06 09:12:40	ga_ls9c_ard_3-2-1_089081_2023-08-05_final.stac-item
2023-08-09 09:43:59	ga_ls9c_ard_3-2-1_094082_2023-08-09_final.stac-item
2023-08-11 09:32:49	ga_ls9c_ard_3-2-1_092085_2023-08-11_final.stac-item
2023-08-14 09:57:20	ga_ls9c_ard_3-2-1_097069_2023-08-14_final.stac-item
2023-10-16 10:58:37	ga_ls9c_ard_3-2-1_106082_2023-10-16_final.stac-item
2023-10-21 09:35:05	ga_ls9c_ard_3-2-1_093074_2023-10-21_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 09:12:45	ga_ls9c_ard_3-2-1_089080_2023-10-24_final.stac-item
2023-10-29 10:28:04	ga_ls9c_ard_3-2-1_101083_2023-10-29_final.stac-item
2023-11-01 10:58:55	ga_ls9c_ard_3-2-1_106083_2023-11-01_final.stac-item
2023-11-03 10:40:56	ga_ls9c_ard_3-2-1_104069_2023-11-03_final.stac-item
2023-11-04 11:27:01	ga_ls9c_ard_3-2-1_111076_2023-11-04_final.stac-item
2023-11-05 10:30:36	ga_ls9c_ard_3-2-1_102074_2023-11-05_final.stac-item
2023-11-18 10:01:22	ga_ls9c_ard_3-2-1_097078_2023-11-18_final.stac-item
2023-11-20 09:51:26	ga_ls9c_ard_3-2-1_095084_2023-11-20_final.stac-item
2023-11-22 11:13:12	ga_ls9c_ard_3-2-1_109072_2023-11-22_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