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
2021-12-04 09:28:05	ga_ls9c_ard_3-2-1_091087_2021-12-03_final.stac-item
2021-12-13 10:53:30	ga_ls9c_ard_3-2-1_106069_2021-12-13_final.stac-item
2021-12-22 09:14:00	ga_ls9c_ard_3-2-1_089083_2021-12-21_final.stac-item
2021-12-23 11:32:33	ga_ls9c_ard_3-2-1_112074_2021-12-23_final.stac-item
2021-12-29 09:18:11	ga_ls9c_ard_3-2-1_090078_2021-12-28_final.stac-item
2022-01-03 11:18:00	ga_ls9c_ard_3-2-1_109084_2022-01-03_final.stac-item
2022-01-05 09:22:21	ga_ls9c_ard_3-2-1_091073_2022-01-04_final.stac-item
2022-01-23 09:13:11	ga_ls9c_ard_3-2-1_089081_2022-01-22_final.stac-item
2022-01-23 09:13:35	ga_ls9c_ard_3-2-1_089082_2022-01-22_final.stac-item
2022-02-01 09:06:37	ga_ls9c_ard_3-2-1_088080_2022-01-31_final.stac-item
2022-02-01 09:07:24	ga_ls9c_ard_3-2-1_088082_2022-01-31_final.stac-item
2022-02-15 09:20:53	ga_ls9c_ard_3-2-1_090085_2022-02-14_final.stac-item
2022-04-03 11:51:57	ga_ls9c_ard_3-2-1_115077_2022-04-03_final.stac-item
2022-04-18 09:28:28	ga_ls9c_ard_3-2-1_092074_2022-04-17_final.stac-item
2022-04-26 10:21:27	ga_ls9c_ard_3-2-1_100083_2022-04-26_final.stac-item
2022-05-15 10:49:00	ga_ls9c_ard_3-2-1_105075_2022-05-15_final.stac-item
2022-05-29 09:22:24	ga_ls9c_ard_3-2-1_091075_2022-05-28_final.stac-item
2022-06-05 11:06:41	ga_ls9c_ard_3-2-1_108073_2022-06-05_final.stac-item
2022-06-06 11:50:44	ga_ls9c_ard_3-2-1_115075_2022-06-06_final.stac-item
2022-06-16 10:48:38	ga_ls9c_ard_3-2-1_105074_2022-06-16_final.stac-item
2022-07-15 10:16:42	ga_ls9c_ard_3-2-1_100071_2022-07-15_final.stac-item
2022-08-10 09:22:51	ga_ls9c_ard_3-2-1_090090_2022-08-09_final.stac-item
2022-08-12 09:06:54	ga_ls9c_ard_3-2-1_088081_2022-08-11_final.stac-item
2022-08-15 09:33:50	ga_ls9c_ard_3-2-1_093071_2022-08-15_final.stac-item
2022-08-17 09:23:05	ga_ls9c_ard_3-2-1_091075_2022-08-16_final.stac-item
2022-08-17 09:28:40	ga_ls9c_ard_3-2-1_091089_2022-08-16_final.stac-item
2022-09-02 09:23:07	ga_ls9c_ard_3-2-1_091075_2022-09-01_final.stac-item
2022-10-06 10:49:21	ga_ls9c_ard_3-2-1_105074_2022-10-06_final.stac-item
2022-10-11 09:29:28	ga_ls9c_ard_3-2-1_092075_2022-10-10_final.stac-item
2022-10-30 09:58:00	ga_ls9c_ard_3-2-1_097069_2022-10-30_final.stac-item
2022-10-30 11:38:05	ga_ls9c_ard_3-2-1_113072_2022-10-30_final.stac-item
2022-11-01 11:26:06	ga_ls9c_ard_3-2-1_111073_2022-11-01_final.stac-item
2022-11-12 09:29:31	ga_ls9c_ard_3-2-1_092075_2022-11-11_final.stac-item
2022-12-01 09:58:22	ga_ls9c_ard_3-2-1_097070_2022-12-01_final.stac-item
2022-12-02 10:46:25	ga_ls9c_ard_3-2-1_104082_2022-12-02_final.stac-item
2022-12-07 09:27:19	ga_ls9c_ard_3-2-1_091085_2022-12-06_final.stac-item
2022-12-19 11:26:07	ga_ls9c_ard_3-2-1_111073_2022-12-19_final.stac-item
2022-12-23 11:00:58	ga_ls9c_ard_3-2-1_107072_2022-12-23_final.stac-item
2023-01-05 10:28:55	ga_ls9c_ard_3-2-1_102069_2023-01-05_final.stac-item
2023-01-08 09:23:44	ga_ls9c_ard_3-2-1_091076_2023-01-07_final.stac-item
2023-01-24 11:00:31	ga_ls9c_ard_3-2-1_107071_2023-01-24_final.stac-item
2023-01-26 09:10:54	ga_ls9c_ard_3-2-1_089075_2023-01-25_final.stac-item
2023-02-05 11:26:11	ga_ls9c_ard_3-2-1_111073_2023-02-05_final.stac-item
2023-02-14 09:41:30	ga_ls9c_ard_3-2-1_094074_2023-02-14_final.stac-item
2023-02-25 11:05:13	ga_ls9c_ard_3-2-1_107083_2023-02-25_final.stac-item
2023-03-07 10:03:44	ga_ls9c_ard_3-2-1_097084_2023-03-07_final.stac-item
2023-03-11 11:13:52	ga_ls9c_ard_3-2-1_109074_2023-03-11_final.stac-item
2023-03-15 09:13:28	ga_ls9c_ard_3-2-1_089082_2023-03-14_final.stac-item
2023-03-19 10:23:13	ga_ls9c_ard_3-2-1_101071_2023-03-19_final.stac-item
2023-03-23 09:58:27	ga_ls9c_ard_3-2-1_097071_2023-03-23_final.stac-item
2023-04-10 09:51:54	ga_ls9c_ard_3-2-1_095086_2023-04-10_final.stac-item
2023-04-28 11:11:30	ga_ls9c_ard_3-2-1_109069_2023-04-28_final.stac-item
2023-05-08 10:09:35	ga_ls9c_ard_3-2-1_099069_2023-05-08_final.stac-item
2023-05-09 10:55:14	ga_ls9c_ard_3-2-1_106075_2023-05-09_final.stac-item
2023-05-15 10:16:31	ga_ls9c_ard_3-2-1_100071_2023-05-15_final.stac-item
2023-05-24 10:08:13	ga_ls9c_ard_3-2-1_099066_2023-05-24_final.stac-item
2023-05-24 10:10:12	ga_ls9c_ard_3-2-1_099071_2023-05-24_final.stac-item
2023-05-26 11:37:07	ga_ls9c_ard_3-2-1_113072_2023-05-26_final.stac-item
2023-05-26 11:37:55	ga_ls9c_ard_3-2-1_113074_2023-05-26_final.stac-item
2023-06-11 09:56:33	ga_ls9c_ard_3-2-1_097068_2023-06-11_final.stac-item
2023-06-17 09:26:35	ga_ls9c_ard_3-2-1_091086_2023-06-16_final.stac-item
2023-06-26 10:54:07	ga_ls9c_ard_3-2-1_106073_2023-06-26_final.stac-item
2023-07-05 10:51:19	ga_ls9c_ard_3-2-1_105081_2023-07-05_final.stac-item
2023-07-11 10:08:43	ga_ls9c_ard_3-2-1_099067_2023-07-11_final.stac-item
2023-07-11 11:50:47	ga_ls9c_ard_3-2-1_115075_2023-07-11_final.stac-item
2023-07-26 11:06:45	ga_ls9c_ard_3-2-1_108073_2023-07-26_final.stac-item
2023-08-04 09:21:49	ga_ls9c_ard_3-2-1_091073_2023-08-03_final.stac-item
2023-08-10 10:25:39	ga_ls9c_ard_3-2-1_101078_2023-08-10_final.stac-item
2023-08-22 10:49:14	ga_ls9c_ard_3-2-1_105075_2023-08-22_final.stac-item
2023-08-23 09:57:13	ga_ls9c_ard_3-2-1_096084_2023-08-23_final.stac-item
2023-09-09 10:35:53	ga_ls9c_ard_3-2-1_103072_2023-09-09_final.stac-item
2023-09-17 11:26:10	ga_ls9c_ard_3-2-1_111074_2023-09-17_final.stac-item
2023-09-30 09:21:07	ga_ls9c_ard_3-2-1_090086_2023-09-29_final.stac-item
2023-10-05 09:34:33	ga_ls9c_ard_3-2-1_093073_2023-10-05_final.stac-item
2023-10-11 10:36:01	ga_ls9c_ard_3-2-1_103072_2023-10-11_final.stac-item
2023-10-15 10:10:57	ga_ls9c_ard_3-2-1_099071_2023-10-15_final.stac-item
2023-11-09 10:03:08	ga_ls9c_ard_3-2-1_098067_2023-11-09_final.stac-item
2023-11-16 10:14:29	ga_ls9c_ard_3-2-1_099080_2023-11-16_final.stac-item
2023-11-28 10:36:09	ga_ls9c_ard_3-2-1_103072_2023-11-28_final.stac-item
2023-12-01 11:07:51	ga_ls9c_ard_3-2-1_108074_2023-12-01_final.stac-item
2023-12-08 11:14:45	ga_ls9c_ard_3-2-1_109076_2023-12-08_final.stac-item
2023-12-10 11:01:37	ga_ls9c_ard_3-2-1_107074_2023-12-10_final.stac-item
2023-12-22 11:26:26	ga_ls9c_ard_3-2-1_111074_2023-12-22_final.stac-item
2023-12-25 10:22:02	ga_ls9c_ard_3-2-1_100083_2023-12-25_final.stac-item
2024-01-02 09:28:08	ga_ls9c_ard_3-2-1_092072_2024-01-01_final.stac-item
2024-01-03 10:11:23	ga_ls9c_ard_3-2-1_099072_2024-01-03_final.stac-item
2024-01-11 09:23:09	ga_ls9c_ard_3-2-1_091075_2024-01-10_final.stac-item
2024-01-23 09:47:01	ga_ls9c_ard_3-2-1_095073_2024-01-23_final.stac-item
2024-01-29 09:16:23	ga_ls9c_ard_3-2-1_089089_2024-01-28_final.stac-item
2024-02-04 10:11:50	ga_ls9c_ard_3-2-1_099073_2024-02-04_final.stac-item
2024-02-05 10:54:42	ga_ls9c_ard_3-2-1_106072_2024-02-05_final.stac-item
2024-02-08 11:26:00	ga_ls9c_ard_3-2-1_111073_2024-02-08_final.stac-item
2024-02-12 09:22:46	ga_ls9c_ard_3-2-1_091074_2024-02-11_final.stac-item
2024-02-12 09:23:34	ga_ls9c_ard_3-2-1_091076_2024-02-11_final.stac-item
2024-02-28 09:23:01	ga_ls9c_ard_3-2-1_091075_2024-02-27_final.stac-item
2024-03-06 09:29:15	ga_ls9c_ard_3-2-1_092075_2024-03-05_final.stac-item
2024-03-10 10:41:24	ga_ls9c_ard_3-2-1_104070_2024-03-10_final.stac-item
2024-03-15 10:59:56	ga_ls9c_ard_3-2-1_107070_2024-03-15_final.stac-item
2024-03-20 09:40:46	ga_ls9c_ard_3-2-1_094073_2024-03-20_final.stac-item
2024-04-21 11:20:26	ga_ls9c_ard_3-2-1_110076_2024-04-21_nrt.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