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
2021-11-09 10:37:00	ga_ls9c_ard_3-2-1_103074_2021-11-09_final.stac-item
2021-12-04 09:28:29	ga_ls9c_ard_3-2-1_091088_2021-12-03_final.stac-item
2021-12-09 11:20:16	ga_ls9c_ard_3-2-1_110074_2021-12-09_final.stac-item
2021-12-16 09:52:40	ga_ls9c_ard_3-2-1_095087_2021-12-16_final.stac-item
2021-12-21 10:10:25	ga_ls9c_ard_3-2-1_098085_2021-12-21_final.stac-item
2021-12-23 09:57:40	ga_ls9c_ard_3-2-1_096084_2021-12-23_final.stac-item
2021-12-29 10:54:40	ga_ls9c_ard_3-2-1_106072_2021-12-29_final.stac-item
2022-01-03 09:35:55	ga_ls9c_ard_3-2-1_093076_2022-01-03_final.stac-item
2022-01-06 11:44:54	ga_ls9c_ard_3-2-1_114074_2022-01-06_final.stac-item
2022-01-18 10:29:07	ga_ls9c_ard_3-2-1_102070_2022-01-18_final.stac-item
2022-01-26 11:23:22	ga_ls9c_ard_3-2-1_110082_2022-01-26_final.stac-item
2022-03-01 09:29:29	ga_ls9c_ard_3-2-1_092076_2022-02-28_final.stac-item
2022-03-07 10:30:06	ga_ls9c_ard_3-2-1_102073_2022-03-07_final.stac-item
2022-04-05 11:41:10	ga_ls9c_ard_3-2-1_113081_2022-04-05_final.stac-item
2022-04-13 09:13:59	ga_ls9c_ard_3-2-1_089084_2022-04-12_final.stac-item
2022-04-18 11:05:45	ga_ls9c_ard_3-2-1_108070_2022-04-18_final.stac-item
2022-04-19 10:14:06	ga_ls9c_ard_3-2-1_099080_2022-04-19_final.stac-item
2022-04-19 10:16:06	ga_ls9c_ard_3-2-1_099085_2022-04-19_final.stac-item
2022-04-21 10:01:19	ga_ls9c_ard_3-2-1_097079_2022-04-21_final.stac-item
2022-05-29 09:21:36	ga_ls9c_ard_3-2-1_091073_2022-05-28_final.stac-item
2022-05-30 10:07:39	ga_ls9c_ard_3-2-1_098080_2022-05-30_final.stac-item
2022-06-02 10:39:22	ga_ls9c_ard_3-2-1_103082_2022-06-02_final.stac-item
2022-06-16 10:46:14	ga_ls9c_ard_3-2-1_105068_2022-06-16_final.stac-item
2022-07-08 10:10:58	ga_ls9c_ard_3-2-1_099072_2022-07-08_final.stac-item
2022-07-16 10:59:59	ga_ls9c_ard_3-2-1_107071_2022-07-16_final.stac-item
2022-07-17 10:03:59	ga_ls9c_ard_3-2-1_098070_2022-07-17_final.stac-item
2022-07-27 09:06:44	ga_ls9c_ard_3-2-1_088081_2022-07-26_final.stac-item
2022-08-13 09:52:34	ga_ls9c_ard_3-2-1_095087_2022-08-13_final.stac-item
2022-08-24 09:32:53	ga_ls9c_ard_3-2-1_092084_2022-08-24_final.stac-item
2022-08-29 11:25:31	ga_ls9c_ard_3-2-1_111072_2022-08-29_final.stac-item
2022-08-31 09:39:52	ga_ls9c_ard_3-2-1_093086_2022-08-31_final.stac-item
2022-09-09 11:10:33	ga_ls9c_ard_3-2-1_108081_2022-09-09_final.stac-item
2022-09-26 11:51:58	ga_ls9c_ard_3-2-1_115076_2022-09-26_final.stac-item
2022-10-05 10:04:06	ga_ls9c_ard_3-2-1_098069_2022-10-05_final.stac-item
2022-10-18 09:40:29	ga_ls9c_ard_3-2-1_093087_2022-10-18_final.stac-item
2022-10-25 11:19:10	ga_ls9c_ard_3-2-1_110071_2022-10-25_final.stac-item
2022-10-30 11:38:53	ga_ls9c_ard_3-2-1_113074_2022-10-30_final.stac-item
2022-10-31 10:44:03	ga_ls9c_ard_3-2-1_104076_2022-10-31_final.stac-item
2022-11-07 09:14:09	ga_ls9c_ard_3-2-1_089083_2022-11-06_final.stac-item
2022-11-17 09:46:53	ga_ls9c_ard_3-2-1_095072_2022-11-17_final.stac-item
2022-11-21 09:27:44	ga_ls9c_ard_3-2-1_091086_2022-11-20_final.stac-item
2022-11-23 10:52:39	ga_ls9c_ard_3-2-1_105082_2022-11-23_final.stac-item
2022-11-29 11:51:38	ga_ls9c_ard_3-2-1_115075_2022-11-29_final.stac-item
2022-12-02 10:44:49	ga_ls9c_ard_3-2-1_104078_2022-12-02_final.stac-item
2022-12-03 09:52:48	ga_ls9c_ard_3-2-1_095087_2022-12-03_final.stac-item
2022-12-04 10:34:05	ga_ls9c_ard_3-2-1_102082_2022-12-04_final.stac-item
2022-12-07 11:00:36	ga_ls9c_ard_3-2-1_107071_2022-12-07_final.stac-item
2022-12-07 11:01:48	ga_ls9c_ard_3-2-1_107074_2022-12-07_final.stac-item
2022-12-23 09:26:28	ga_ls9c_ard_3-2-1_091083_2022-12-22_final.stac-item
2022-12-23 11:05:21	ga_ls9c_ard_3-2-1_107083_2022-12-23_final.stac-item
2022-12-30 09:31:30	ga_ls9c_ard_3-2-1_092080_2022-12-30_final.stac-item
2022-12-30 09:33:05	ga_ls9c_ard_3-2-1_092084_2022-12-30_final.stac-item
2022-12-31 10:11:58	ga_ls9c_ard_3-2-1_099073_2022-12-31_final.stac-item
2023-01-08 11:02:37	ga_ls9c_ard_3-2-1_107076_2023-01-08_final.stac-item
2023-01-24 09:27:37	ga_ls9c_ard_3-2-1_091086_2023-01-23_final.stac-item
2023-01-24 11:01:43	ga_ls9c_ard_3-2-1_107074_2023-01-24_final.stac-item
2023-02-01 11:53:40	ga_ls9c_ard_3-2-1_115080_2023-02-01_final.stac-item
2023-02-04 10:42:55	ga_ls9c_ard_3-2-1_104073_2023-02-04_final.stac-item
2023-02-08 10:22:36	ga_ls9c_ard_3-2-1_100084_2023-02-08_final.stac-item
2023-02-10 10:07:51	ga_ls9c_ard_3-2-1_098078_2023-02-10_final.stac-item
2023-02-27 10:47:41	ga_ls9c_ard_3-2-1_105070_2023-02-27_final.stac-item
2023-03-02 09:40:53	ga_ls9c_ard_3-2-1_094073_2023-03-02_final.stac-item
2023-03-09 09:50:56	ga_ls9c_ard_3-2-1_095083_2023-03-09_final.stac-item
2023-03-12 11:57:56	ga_ls9c_ard_3-2-1_116076_2023-03-12_final.stac-item
2023-03-13 09:25:01	ga_ls9c_ard_3-2-1_091080_2023-03-12_final.stac-item
2023-03-15 09:13:04	ga_ls9c_ard_3-2-1_089081_2023-03-14_final.stac-item
2023-03-28 10:17:17	ga_ls9c_ard_3-2-1_100072_2023-03-28_final.stac-item
2023-03-28 10:18:05	ga_ls9c_ard_3-2-1_100074_2023-03-28_final.stac-item
2023-03-30 10:10:05	ga_ls9c_ard_3-2-1_098085_2023-03-30_final.stac-item
2023-04-05 09:33:00	ga_ls9c_ard_3-2-1_092085_2023-04-05_final.stac-item
2023-04-07 10:55:07	ga_ls9c_ard_3-2-1_106074_2023-04-07_final.stac-item
2023-04-14 11:04:48	ga_ls9c_ard_3-2-1_107083_2023-04-14_final.stac-item
2023-04-23 09:19:44	ga_ls9c_ard_3-2-1_090083_2023-04-22_final.stac-item
2023-05-01 11:44:21	ga_ls9c_ard_3-2-1_114074_2023-05-01_final.stac-item
2023-05-07 09:29:07	ga_ls9c_ard_3-2-1_092076_2023-05-06_final.stac-item
2023-05-07 09:32:42	ga_ls9c_ard_3-2-1_092085_2023-05-07_final.stac-item
2023-05-10 10:02:48	ga_ls9c_ard_3-2-1_097083_2023-05-10_final.stac-item
2023-05-16 11:01:22	ga_ls9c_ard_3-2-1_107075_2023-05-16_final.stac-item
2023-05-17 10:02:56	ga_ls9c_ard_3-2-1_098068_2023-05-17_final.stac-item
2023-05-21 11:19:50	ga_ls9c_ard_3-2-1_110075_2023-05-21_final.stac-item
2023-05-28 09:46:17	ga_ls9c_ard_3-2-1_095073_2023-05-28_final.stac-item
2023-05-28 09:50:16	ga_ls9c_ard_3-2-1_095083_2023-05-28_final.stac-item
2023-05-31 10:18:22	ga_ls9c_ard_3-2-1_100076_2023-05-31_final.stac-item
2023-06-02 10:07:36	ga_ls9c_ard_3-2-1_098080_2023-06-02_final.stac-item
2023-06-24 11:06:28	ga_ls9c_ard_3-2-1_108073_2023-06-24_final.stac-item
2023-06-25 11:51:19	ga_ls9c_ard_3-2-1_115077_2023-06-25_final.stac-item
2023-07-20 10:03:21	ga_ls9c_ard_3-2-1_098069_2023-07-20_final.stac-item
2023-07-20 10:09:44	ga_ls9c_ard_3-2-1_098085_2023-07-20_final.stac-item
2023-07-24 11:19:05	ga_ls9c_ard_3-2-1_110073_2023-07-24_final.stac-item
2023-07-27 10:09:57	ga_ls9c_ard_3-2-1_099070_2023-07-27_final.stac-item
2023-07-29 11:40:30	ga_ls9c_ard_3-2-1_113080_2023-07-29_final.stac-item
2023-08-06 10:51:33	ga_ls9c_ard_3-2-1_105081_2023-08-06_final.stac-item
2023-10-22 11:58:02	ga_ls9c_ard_3-2-1_116076_2023-10-22_final.stac-item
2023-10-28 11:18:55	ga_ls9c_ard_3-2-1_110071_2023-10-28_final.stac-item
2023-10-29 10:24:52	ga_ls9c_ard_3-2-1_101075_2023-10-29_final.stac-item
2023-10-30 11:06:32	ga_ls9c_ard_3-2-1_108071_2023-10-30_final.stac-item
2023-10-31 11:51:46	ga_ls9c_ard_3-2-1_115076_2023-10-31_final.stac-item
2023-11-01 10:54:56	ga_ls9c_ard_3-2-1_106073_2023-11-01_final.stac-item
2023-11-01 10:55:20	ga_ls9c_ard_3-2-1_106074_2023-11-01_final.stac-item
2023-11-16 10:15:41	ga_ls9c_ard_3-2-1_099083_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