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
2021-11-11 10:19:03	ga_ls9c_ard_3-2-1_100076_2021-11-11_final.stac-item
2021-11-12 11:00:36	ga_ls9c_ard_3-2-1_106080_2021-11-12_final.stac-item
2021-12-05 11:47:25	ga_ls9c_ard_3-2-1_114080_2021-12-05_final.stac-item
2021-12-13 10:54:42	ga_ls9c_ard_3-2-1_106072_2021-12-13_final.stac-item
2021-12-14 10:04:15	ga_ls9c_ard_3-2-1_097085_2021-12-14_final.stac-item
2021-12-25 11:20:12	ga_ls9c_ard_3-2-1_110074_2021-12-25_final.stac-item
2021-12-29 10:54:17	ga_ls9c_ard_3-2-1_106071_2021-12-29_final.stac-item
2022-01-21 11:05:37	ga_ls9c_ard_3-2-1_107084_2022-01-21_final.stac-item
2022-01-23 10:50:04	ga_ls9c_ard_3-2-1_105076_2022-01-23_final.stac-item
2022-02-17 10:40:37	ga_ls9c_ard_3-2-1_104068_2022-02-17_final.stac-item
2022-02-20 11:13:52	ga_ls9c_ard_3-2-1_109074_2022-02-20_final.stac-item
2022-03-27 11:44:58	ga_ls9c_ard_3-2-1_114075_2022-03-27_final.stac-item
2022-04-06 10:42:21	ga_ls9c_ard_3-2-1_104073_2022-04-06_final.stac-item
2022-04-19 10:10:55	ga_ls9c_ard_3-2-1_099072_2022-04-19_final.stac-item
2022-04-20 09:22:04	ga_ls9c_ard_3-2-1_090089_2022-04-19_final.stac-item
2022-04-25 09:33:24	ga_ls9c_ard_3-2-1_093071_2022-04-25_final.stac-item
2022-04-25 11:16:40	ga_ls9c_ard_3-2-1_109082_2022-04-25_final.stac-item
2022-04-28 10:03:06	ga_ls9c_ard_3-2-1_098068_2022-04-28_final.stac-item
2022-04-28 10:04:42	ga_ls9c_ard_3-2-1_098072_2022-04-28_final.stac-item
2022-05-23 10:03:04	ga_ls9c_ard_3-2-1_097084_2022-05-23_final.stac-item
2022-05-25 09:45:55	ga_ls9c_ard_3-2-1_095072_2022-05-25_final.stac-item
2022-06-16 09:16:08	ga_ls9c_ard_3-2-1_089090_2022-06-15_final.stac-item
2022-07-28 11:25:42	ga_ls9c_ard_3-2-1_111073_2022-07-28_final.stac-item
2022-08-01 09:28:32	ga_ls9c_ard_3-2-1_091089_2022-07-31_final.stac-item
2022-08-03 09:12:36	ga_ls9c_ard_3-2-1_089080_2022-08-02_final.stac-item
2022-08-04 11:36:21	ga_ls9c_ard_3-2-1_112084_2022-08-04_final.stac-item
2022-08-06 11:19:38	ga_ls9c_ard_3-2-1_110073_2022-08-06_final.stac-item
2022-08-06 11:20:25	ga_ls9c_ard_3-2-1_110075_2022-08-06_final.stac-item
2022-08-16 10:19:06	ga_ls9c_ard_3-2-1_100076_2022-08-16_final.stac-item
2022-08-18 10:03:34	ga_ls9c_ard_3-2-1_098068_2022-08-18_final.stac-item
2022-08-19 09:11:56	ga_ls9c_ard_3-2-1_089078_2022-08-18_final.stac-item
2022-08-19 09:12:20	ga_ls9c_ard_3-2-1_089079_2022-08-18_final.stac-item
2022-08-22 11:19:20	ga_ls9c_ard_3-2-1_110072_2022-08-22_final.stac-item
2022-08-24 09:29:17	ga_ls9c_ard_3-2-1_092075_2022-08-23_final.stac-item
2022-09-07 11:23:19	ga_ls9c_ard_3-2-1_110082_2022-09-07_final.stac-item
2022-09-11 10:53:50	ga_ls9c_ard_3-2-1_106070_2022-09-11_final.stac-item
2022-09-13 09:07:00	ga_ls9c_ard_3-2-1_088081_2022-09-12_final.stac-item
2022-10-10 10:23:29	ga_ls9c_ard_3-2-1_101071_2022-10-10_final.stac-item
2022-10-11 11:06:45	ga_ls9c_ard_3-2-1_108071_2022-10-11_final.stac-item
2022-10-11 11:07:57	ga_ls9c_ard_3-2-1_108074_2022-10-11_final.stac-item
2022-10-15 09:07:10	ga_ls9c_ard_3-2-1_088081_2022-10-14_final.stac-item
2022-10-17 10:30:31	ga_ls9c_ard_3-2-1_102073_2022-10-17_final.stac-item
2022-10-20 09:28:07	ga_ls9c_ard_3-2-1_091087_2022-10-19_final.stac-item
2022-10-21 10:04:12	ga_ls9c_ard_3-2-1_098069_2022-10-21_final.stac-item
2022-10-28 10:14:22	ga_ls9c_ard_3-2-1_099079_2022-10-28_final.stac-item
2022-11-12 09:35:07	ga_ls9c_ard_3-2-1_092089_2022-11-12_final.stac-item
2022-11-20 10:22:10	ga_ls9c_ard_3-2-1_100083_2022-11-20_final.stac-item
2022-11-26 09:45:51	ga_ls9c_ard_3-2-1_094085_2022-11-26_final.stac-item
2022-11-30 09:22:42	ga_ls9c_ard_3-2-1_090089_2022-11-29_final.stac-item
2022-12-04 10:30:05	ga_ls9c_ard_3-2-1_102072_2022-12-04_final.stac-item
2022-12-06 11:58:37	ga_ls9c_ard_3-2-1_116077_2022-12-06_final.stac-item
2022-12-10 09:52:14	ga_ls9c_ard_3-2-1_096070_2022-12-10_final.stac-item
2022-12-10 11:35:54	ga_ls9c_ard_3-2-1_112082_2022-12-10_final.stac-item
2023-01-08 09:27:19	ga_ls9c_ard_3-2-1_091085_2023-01-07_final.stac-item
2023-01-08 11:05:24	ga_ls9c_ard_3-2-1_107083_2023-01-08_final.stac-item
2023-01-17 09:20:39	ga_ls9c_ard_3-2-1_090084_2023-01-16_final.stac-item
2023-01-17 09:22:14	ga_ls9c_ard_3-2-1_090088_2023-01-16_final.stac-item
2023-01-20 09:46:17	ga_ls9c_ard_3-2-1_095071_2023-01-20_final.stac-item
2023-01-23 10:22:02	ga_ls9c_ard_3-2-1_100083_2023-01-23_final.stac-item
2023-01-30 10:24:20	ga_ls9c_ard_3-2-1_101073_2023-01-30_final.stac-item
2023-02-23 11:16:48	ga_ls9c_ard_3-2-1_109081_2023-02-23_final.stac-item
2023-03-07 10:00:57	ga_ls9c_ard_3-2-1_097077_2023-03-07_final.stac-item
2023-03-26 10:30:06	ga_ls9c_ard_3-2-1_102073_2023-03-26_final.stac-item
2023-04-05 09:34:36	ga_ls9c_ard_3-2-1_092089_2023-04-05_final.stac-item
2023-04-15 10:02:47	ga_ls9c_ard_3-2-1_098067_2023-04-15_final.stac-item
2023-04-22 11:51:51	ga_ls9c_ard_3-2-1_115077_2023-04-22_final.stac-item
2023-04-23 09:22:07	ga_ls9c_ard_3-2-1_090089_2023-04-22_final.stac-item
2023-04-26 11:25:53	ga_ls9c_ard_3-2-1_111074_2023-04-26_final.stac-item
2023-05-14 09:39:15	ga_ls9c_ard_3-2-1_093086_2023-05-14_final.stac-item
2023-05-14 09:39:39	ga_ls9c_ard_3-2-1_093087_2023-05-14_final.stac-item
2023-05-27 09:05:49	ga_ls9c_ard_3-2-1_088080_2023-05-26_final.stac-item
2023-06-03 09:13:34	ga_ls9c_ard_3-2-1_089084_2023-06-02_final.stac-item
2023-06-17 09:22:12	ga_ls9c_ard_3-2-1_091075_2023-06-16_final.stac-item
2023-06-17 09:26:11	ga_ls9c_ard_3-2-1_091085_2023-06-16_final.stac-item
2023-06-25 11:51:43	ga_ls9c_ard_3-2-1_115078_2023-06-25_final.stac-item
2023-07-09 10:22:15	ga_ls9c_ard_3-2-1_101070_2023-07-09_final.stac-item
2023-07-21 09:15:42	ga_ls9c_ard_3-2-1_089089_2023-07-20_final.stac-item
2023-07-22 09:57:46	ga_ls9c_ard_3-2-1_096086_2023-07-22_final.stac-item
2023-07-29 11:38:06	ga_ls9c_ard_3-2-1_113074_2023-07-29_final.stac-item
2023-08-05 10:03:29	ga_ls9c_ard_3-2-1_098069_2023-08-05_final.stac-item
2023-08-10 10:25:15	ga_ls9c_ard_3-2-1_101077_2023-08-10_final.stac-item
2023-08-20 09:26:40	ga_ls9c_ard_3-2-1_091085_2023-08-19_final.stac-item
2023-08-28 10:09:26	ga_ls9c_ard_3-2-1_099068_2023-08-28_final.stac-item
2023-09-21 11:01:26	ga_ls9c_ard_3-2-1_107074_2023-09-21_final.stac-item
2023-10-21 09:33:54	ga_ls9c_ard_3-2-1_093071_2023-10-21_final.stac-item
2023-10-22 10:17:33	ga_ls9c_ard_3-2-1_100072_2023-10-22_final.stac-item
2023-10-25 10:52:26	ga_ls9c_ard_3-2-1_105082_2023-10-25_final.stac-item
2023-11-04 11:26:13	ga_ls9c_ard_3-2-1_111074_2023-11-04_final.stac-item
2023-11-08 11:00:20	ga_ls9c_ard_3-2-1_107071_2023-11-08_final.stac-item
2023-11-16 10:10:54	ga_ls9c_ard_3-2-1_099071_2023-11-16_final.stac-item
2023-11-17 10:54:58	ga_ls9c_ard_3-2-1_106073_2023-11-17_final.stac-item
2023-11-24 11:01:39	ga_ls9c_ard_3-2-1_107074_2023-11-24_final.stac-item
2023-11-27 11:36:10	ga_ls9c_ard_3-2-1_112083_2023-11-27_final.stac-item
2023-11-29 11:19:49	ga_ls9c_ard_3-2-1_110073_2023-11-29_final.stac-item
2023-11-30 10:25:47	ga_ls9c_ard_3-2-1_101077_2023-11-30_final.stac-item
2023-12-06 11:25:08	ga_ls9c_ard_3-2-1_111071_2023-12-06_final.stac-item
2023-12-12 09:12:47	ga_ls9c_ard_3-2-1_089080_2023-12-11_final.stac-item
2023-12-18 10:11:27	ga_ls9c_ard_3-2-1_099072_2023-12-18_final.stac-item
2023-12-19 09:19:50	ga_ls9c_ard_3-2-1_090082_2023-12-18_final.stac-item
2023-12-24 09:40:46	ga_ls9c_ard_3-2-1_093088_2023-12-24_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