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
2021-10-31 11:11:36	ga_ls9c_ard_3-2-1_109073_2021-10-31_final.stac-item
2021-11-16 10:19:55	ga_ls9c_ard_3-2-1_100072_2021-11-16_final.stac-item
2021-11-22 09:25:16	ga_ls9c_ard_3-2-1_091076_2021-11-21_final.stac-item
2021-11-24 10:44:46	ga_ls9c_ard_3-2-1_104075_2021-11-24_final.stac-item
2021-12-04 09:28:29	ga_ls9c_ard_3-2-1_091088_2021-12-03_final.stac-item
2021-12-13 09:21:48	ga_ls9c_ard_3-2-1_090087_2021-12-12_final.stac-item
2021-12-24 10:40:07	ga_ls9c_ard_3-2-1_103082_2021-12-24_final.stac-item
2021-12-29 09:18:35	ga_ls9c_ard_3-2-1_090079_2021-12-28_final.stac-item
2021-12-29 09:21:23	ga_ls9c_ard_3-2-1_090086_2021-12-28_final.stac-item
2022-01-01 09:47:29	ga_ls9c_ard_3-2-1_095074_2022-01-01_final.stac-item
2022-01-20 11:58:51	ga_ls9c_ard_3-2-1_116078_2022-01-20_final.stac-item
2022-01-22 11:44:54	ga_ls9c_ard_3-2-1_114074_2022-01-22_final.stac-item
2022-01-22 11:45:41	ga_ls9c_ard_3-2-1_114076_2022-01-22_final.stac-item
2022-01-23 10:49:40	ga_ls9c_ard_3-2-1_105075_2022-01-23_final.stac-item
2022-01-29 11:51:53	ga_ls9c_ard_3-2-1_115076_2022-01-29_final.stac-item
2022-01-30 09:19:46	ga_ls9c_ard_3-2-1_090082_2022-01-29_final.stac-item
2022-01-31 11:39:07	ga_ls9c_ard_3-2-1_113075_2022-01-31_final.stac-item
2022-02-04 09:39:30	ga_ls9c_ard_3-2-1_093085_2022-02-04_final.stac-item
2022-02-08 10:47:39	ga_ls9c_ard_3-2-1_105070_2022-02-08_final.stac-item
2022-03-03 09:22:42	ga_ls9c_ard_3-2-1_090090_2022-03-02_final.stac-item
2022-03-10 09:24:06	ga_ls9c_ard_3-2-1_091078_2022-03-09_final.stac-item
2022-03-19 10:53:11	ga_ls9c_ard_3-2-1_106069_2022-03-19_final.stac-item
2022-03-25 10:22:03	ga_ls9c_ard_3-2-1_100084_2022-03-25_final.stac-item
2022-04-19 10:14:06	ga_ls9c_ard_3-2-1_099080_2022-04-19_final.stac-item
2022-05-21 11:52:43	ga_ls9c_ard_3-2-1_115080_2022-05-21_final.stac-item
2022-06-09 09:05:52	ga_ls9c_ard_3-2-1_088080_2022-06-08_final.stac-item
2022-06-19 11:18:48	ga_ls9c_ard_3-2-1_110072_2022-06-19_final.stac-item
2022-06-24 11:41:54	ga_ls9c_ard_3-2-1_113083_2022-06-24_final.stac-item
2022-07-08 10:10:58	ga_ls9c_ard_3-2-1_099072_2022-07-08_final.stac-item
2022-07-10 09:57:48	ga_ls9c_ard_3-2-1_097070_2022-07-10_final.stac-item
2022-07-18 09:11:34	ga_ls9c_ard_3-2-1_089078_2022-07-17_final.stac-item
2022-08-08 11:11:41	ga_ls9c_ard_3-2-1_108084_2022-08-08_final.stac-item
2022-08-16 10:21:54	ga_ls9c_ard_3-2-1_100083_2022-08-16_final.stac-item
2022-08-24 09:32:05	ga_ls9c_ard_3-2-1_092082_2022-08-24_final.stac-item
2022-09-02 09:28:18	ga_ls9c_ard_3-2-1_091088_2022-09-01_final.stac-item
2022-09-11 09:21:44	ga_ls9c_ard_3-2-1_090087_2022-09-10_final.stac-item
2022-09-12 11:42:18	ga_ls9c_ard_3-2-1_113083_2022-09-12_final.stac-item
2022-09-24 10:23:26	ga_ls9c_ard_3-2-1_101071_2022-09-24_final.stac-item
2022-09-30 11:26:51	ga_ls9c_ard_3-2-1_111075_2022-09-30_final.stac-item
2022-10-04 11:01:43	ga_ls9c_ard_3-2-1_107074_2022-10-04_final.stac-item
2022-10-06 10:49:45	ga_ls9c_ard_3-2-1_105075_2022-10-06_final.stac-item
2022-10-13 10:53:37	ga_ls9c_ard_3-2-1_106069_2022-10-13_final.stac-item
2022-10-20 11:00:37	ga_ls9c_ard_3-2-1_107071_2022-10-20_final.stac-item
2022-10-27 11:11:59	ga_ls9c_ard_3-2-1_108084_2022-10-27_final.stac-item
2022-10-29 09:21:32	ga_ls9c_ard_3-2-1_090086_2022-10-28_final.stac-item
2022-11-06 10:03:46	ga_ls9c_ard_3-2-1_098068_2022-11-06_final.stac-item
2022-11-06 10:07:46	ga_ls9c_ard_3-2-1_098078_2022-11-06_final.stac-item
2022-11-13 10:13:11	ga_ls9c_ard_3-2-1_099076_2022-11-13_final.stac-item
2022-11-14 10:54:51	ga_ls9c_ard_3-2-1_106072_2022-11-14_final.stac-item
2022-11-15 09:59:14	ga_ls9c_ard_3-2-1_097072_2022-11-15_final.stac-item
2022-11-17 11:26:57	ga_ls9c_ard_3-2-1_111075_2022-11-17_final.stac-item
2022-11-22 11:45:29	ga_ls9c_ard_3-2-1_114075_2022-11-22_final.stac-item
2022-11-27 10:27:55	ga_ls9c_ard_3-2-1_101082_2022-11-27_final.stac-item
2022-12-04 10:29:41	ga_ls9c_ard_3-2-1_102071_2022-12-04_final.stac-item
2022-12-07 09:24:07	ga_ls9c_ard_3-2-1_091077_2022-12-06_final.stac-item
2022-12-07 09:28:54	ga_ls9c_ard_3-2-1_091089_2022-12-06_final.stac-item
2022-12-12 11:21:09	ga_ls9c_ard_3-2-1_110076_2022-12-12_final.stac-item
2022-12-14 11:06:00	ga_ls9c_ard_3-2-1_108069_2022-12-14_final.stac-item
2022-12-16 10:54:50	ga_ls9c_ard_3-2-1_106072_2022-12-16_final.stac-item
2022-12-23 09:24:04	ga_ls9c_ard_3-2-1_091077_2022-12-22_final.stac-item
2022-12-24 10:08:32	ga_ls9c_ard_3-2-1_098080_2022-12-24_final.stac-item
2022-12-25 09:14:55	ga_ls9c_ard_3-2-1_089085_2022-12-24_final.stac-item
2023-01-08 09:27:43	ga_ls9c_ard_3-2-1_091086_2023-01-07_final.stac-item
2023-01-11 11:33:06	ga_ls9c_ard_3-2-1_112075_2023-01-11_final.stac-item
2023-01-17 09:22:14	ga_ls9c_ard_3-2-1_090088_2023-01-16_final.stac-item
2023-01-24 09:25:14	ga_ls9c_ard_3-2-1_091080_2023-01-23_final.stac-item
2023-01-24 09:29:13	ga_ls9c_ard_3-2-1_091090_2023-01-23_final.stac-item
2023-02-01 10:16:47	ga_ls9c_ard_3-2-1_099085_2023-02-01_final.stac-item
2023-02-09 09:26:11	ga_ls9c_ard_3-2-1_091082_2023-02-08_final.stac-item
2023-02-09 11:00:17	ga_ls9c_ard_3-2-1_107070_2023-02-09_final.stac-item
2023-02-23 11:12:25	ga_ls9c_ard_3-2-1_109070_2023-02-23_final.stac-item
2023-03-08 09:07:18	ga_ls9c_ard_3-2-1_088082_2023-03-07_final.stac-item
2023-03-17 10:34:24	ga_ls9c_ard_3-2-1_103068_2023-03-17_final.stac-item
2023-03-28 10:17:17	ga_ls9c_ard_3-2-1_100072_2023-03-28_final.stac-item
2023-03-30 10:08:05	ga_ls9c_ard_3-2-1_098080_2023-03-30_final.stac-item
2023-03-30 10:10:05	ga_ls9c_ard_3-2-1_098085_2023-03-30_final.stac-item
2023-04-09 09:07:27	ga_ls9c_ard_3-2-1_088083_2023-04-08_final.stac-item
2023-04-11 10:27:58	ga_ls9c_ard_3-2-1_102068_2023-04-11_final.stac-item
2023-05-07 11:06:48	ga_ls9c_ard_3-2-1_108073_2023-05-07_final.stac-item
2023-05-09 09:21:32	ga_ls9c_ard_3-2-1_090088_2023-05-08_final.stac-item
2023-05-10 10:01:12	ga_ls9c_ard_3-2-1_097079_2023-05-10_final.stac-item
2023-05-10 10:02:48	ga_ls9c_ard_3-2-1_097083_2023-05-10_final.stac-item
2023-05-14 11:15:45	ga_ls9c_ard_3-2-1_109080_2023-05-14_final.stac-item
2023-05-21 11:23:26	ga_ls9c_ard_3-2-1_110084_2023-05-21_final.stac-item
2023-06-01 09:25:57	ga_ls9c_ard_3-2-1_091084_2023-05-31_final.stac-item
2023-06-18 10:07:04	ga_ls9c_ard_3-2-1_098079_2023-06-18_final.stac-item
2023-06-18 10:09:03	ga_ls9c_ard_3-2-1_098084_2023-06-18_final.stac-item
2023-06-24 11:06:52	ga_ls9c_ard_3-2-1_108074_2023-06-24_final.stac-item
2023-06-24 11:10:27	ga_ls9c_ard_3-2-1_108083_2023-06-24_final.stac-item
2023-07-03 09:26:22	ga_ls9c_ard_3-2-1_091085_2023-07-02_final.stac-item
2023-08-03 10:17:02	ga_ls9c_ard_3-2-1_100072_2023-08-03_final.stac-item
2023-08-03 10:18:37	ga_ls9c_ard_3-2-1_100076_2023-08-03_final.stac-item
2023-08-14 09:57:44	ga_ls9c_ard_3-2-1_097070_2023-08-14_final.stac-item
2023-08-16 11:25:03	ga_ls9c_ard_3-2-1_111072_2023-08-16_final.stac-item
2023-10-16 10:56:13	ga_ls9c_ard_3-2-1_106076_2023-10-16_final.stac-item
2023-10-23 09:27:31	ga_ls9c_ard_3-2-1_091086_2023-10-22_final.stac-item
2023-10-23 11:00:25	ga_ls9c_ard_3-2-1_107071_2023-10-23_final.stac-item
2023-11-01 09:22:26	ga_ls9c_ard_3-2-1_090089_2023-10-31_final.stac-item
2023-11-15 09:33:37	ga_ls9c_ard_3-2-1_092086_2023-11-15_final.stac-item
2023-11-16 11:51:47	ga_ls9c_ard_3-2-1_115076_2023-11-16_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