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
2021-11-07 09:21:04	ga_ls9c_ard_3-2-1_090084_2021-11-06_final.stac-item
2021-11-13 10:02:42	ga_ls9c_ard_3-2-1_097082_2021-11-13_final.stac-item
2021-11-18 10:01:34	ga_ls9c_ard_3-2-1_097073_2021-11-18_final.stac-item
2021-12-04 11:00:11	ga_ls9c_ard_3-2-1_107070_2021-12-04_final.stac-item
2021-12-27 11:08:14	ga_ls9c_ard_3-2-1_108075_2021-12-27_final.stac-item
2021-12-29 09:21:23	ga_ls9c_ard_3-2-1_090086_2021-12-28_final.stac-item
2022-01-12 09:34:05	ga_ls9c_ard_3-2-1_092087_2022-01-12_final.stac-item
2022-01-12 11:08:35	ga_ls9c_ard_3-2-1_108076_2022-01-12_final.stac-item
2022-01-12 11:11:46	ga_ls9c_ard_3-2-1_108084_2022-01-12_final.stac-item
2022-01-23 09:11:59	ga_ls9c_ard_3-2-1_089078_2022-01-22_final.stac-item
2022-01-28 11:11:49	ga_ls9c_ard_3-2-1_108084_2022-01-28_final.stac-item
2022-02-11 09:41:15	ga_ls9c_ard_3-2-1_094074_2022-02-11_final.stac-item
2022-03-07 10:28:30	ga_ls9c_ard_3-2-1_102069_2022-03-07_final.stac-item
2022-03-22 09:50:46	ga_ls9c_ard_3-2-1_095083_2022-03-22_final.stac-item
2022-04-04 09:22:38	ga_ls9c_ard_3-2-1_090090_2022-04-03_final.stac-item
2022-04-08 10:30:47	ga_ls9c_ard_3-2-1_102075_2022-04-08_final.stac-item
2022-04-14 11:36:07	ga_ls9c_ard_3-2-1_112084_2022-04-14_final.stac-item
2022-04-20 10:54:34	ga_ls9c_ard_3-2-1_106073_2022-04-20_final.stac-item
2022-04-25 11:16:40	ga_ls9c_ard_3-2-1_109082_2022-04-25_final.stac-item
2022-05-02 09:43:57	ga_ls9c_ard_3-2-1_094082_2022-05-02_final.stac-item
2022-05-07 11:41:20	ga_ls9c_ard_3-2-1_113082_2022-05-07_final.stac-item
2022-05-09 09:52:04	ga_ls9c_ard_3-2-1_095087_2022-05-09_final.stac-item
2022-05-14 10:02:57	ga_ls9c_ard_3-2-1_098068_2022-05-14_final.stac-item
2022-06-05 11:06:41	ga_ls9c_ard_3-2-1_108073_2022-06-05_final.stac-item
2022-06-13 10:21:41	ga_ls9c_ard_3-2-1_100084_2022-06-13_final.stac-item
2022-06-14 09:25:41	ga_ls9c_ard_3-2-1_091083_2022-06-13_final.stac-item
2022-07-05 09:44:04	ga_ls9c_ard_3-2-1_094082_2022-07-05_final.stac-item
2022-07-10 09:58:36	ga_ls9c_ard_3-2-1_097072_2022-07-10_final.stac-item
2022-07-16 09:23:06	ga_ls9c_ard_3-2-1_091076_2022-07-15_final.stac-item
2022-07-20 10:37:44	ga_ls9c_ard_3-2-1_103077_2022-07-20_final.stac-item
2022-08-03 09:16:36	ga_ls9c_ard_3-2-1_089090_2022-08-02_final.stac-item
2022-08-08 09:33:11	ga_ls9c_ard_3-2-1_092085_2022-08-08_final.stac-item
2022-08-28 10:43:27	ga_ls9c_ard_3-2-1_104075_2022-08-28_final.stac-item
2022-08-31 09:40:16	ga_ls9c_ard_3-2-1_093087_2022-08-31_final.stac-item
2022-09-06 10:34:52	ga_ls9c_ard_3-2-1_103069_2022-09-06_final.stac-item
2022-09-11 10:55:26	ga_ls9c_ard_3-2-1_106074_2022-09-11_final.stac-item
2022-09-19 10:05:16	ga_ls9c_ard_3-2-1_098072_2022-09-19_final.stac-item
2022-10-09 09:45:23	ga_ls9c_ard_3-2-1_094084_2022-10-09_final.stac-item
2022-10-11 11:06:45	ga_ls9c_ard_3-2-1_108071_2022-10-11_final.stac-item
2022-10-17 10:28:55	ga_ls9c_ard_3-2-1_102069_2022-10-17_final.stac-item
2022-10-20 09:29:19	ga_ls9c_ard_3-2-1_091090_2022-10-19_final.stac-item
2022-10-21 11:47:53	ga_ls9c_ard_3-2-1_114081_2022-10-21_final.stac-item
2022-11-10 11:18:46	ga_ls9c_ard_3-2-1_110070_2022-11-10_final.stac-item
2022-11-12 09:31:07	ga_ls9c_ard_3-2-1_092079_2022-11-12_final.stac-item
2022-11-15 09:58:50	ga_ls9c_ard_3-2-1_097071_2022-11-15_final.stac-item
2022-11-18 10:29:20	ga_ls9c_ard_3-2-1_102070_2022-11-18_final.stac-item
2022-11-28 09:29:53	ga_ls9c_ard_3-2-1_092076_2022-11-27_final.stac-item
2022-12-02 10:42:50	ga_ls9c_ard_3-2-1_104073_2022-12-02_final.stac-item
2022-12-03 09:51:12	ga_ls9c_ard_3-2-1_095083_2022-12-03_final.stac-item
2022-12-04 10:28:53	ga_ls9c_ard_3-2-1_102069_2022-12-04_final.stac-item
2022-12-04 10:30:05	ga_ls9c_ard_3-2-1_102072_2022-12-04_final.stac-item
2022-12-07 11:02:36	ga_ls9c_ard_3-2-1_107076_2022-12-07_final.stac-item
2022-12-10 09:58:13	ga_ls9c_ard_3-2-1_096085_2022-12-10_final.stac-item
2022-12-12 09:45:28	ga_ls9c_ard_3-2-1_094084_2022-12-12_final.stac-item
2022-12-17 09:58:00	ga_ls9c_ard_3-2-1_097069_2022-12-17_final.stac-item
2022-12-17 11:42:29	ga_ls9c_ard_3-2-1_113083_2022-12-17_final.stac-item
2023-01-06 09:35:42	ga_ls9c_ard_3-2-1_093075_2023-01-06_final.stac-item
2023-01-09 10:06:11	ga_ls9c_ard_3-2-1_098074_2023-01-09_final.stac-item
2023-01-13 11:20:43	ga_ls9c_ard_3-2-1_110075_2023-01-13_final.stac-item
2023-01-17 09:20:15	ga_ls9c_ard_3-2-1_090083_2023-01-16_final.stac-item
2023-01-18 09:57:06	ga_ls9c_ard_3-2-1_097067_2023-01-18_final.stac-item
2023-01-20 09:46:17	ga_ls9c_ard_3-2-1_095071_2023-01-20_final.stac-item
2023-01-24 09:27:13	ga_ls9c_ard_3-2-1_091085_2023-01-23_final.stac-item
2023-01-24 09:28:01	ga_ls9c_ard_3-2-1_091087_2023-01-23_final.stac-item
2023-01-31 09:32:18	ga_ls9c_ard_3-2-1_092082_2023-01-31_final.stac-item
2023-02-25 09:27:08	ga_ls9c_ard_3-2-1_091085_2023-02-24_final.stac-item
2023-02-26 11:47:41	ga_ls9c_ard_3-2-1_114081_2023-02-26_final.stac-item
2023-03-03 10:22:56	ga_ls9c_ard_3-2-1_101070_2023-03-03_final.stac-item
2023-04-10 09:47:07	ga_ls9c_ard_3-2-1_095074_2023-04-10_final.stac-item
2023-04-26 09:52:12	ga_ls9c_ard_3-2-1_095087_2023-04-26_final.stac-item
2023-04-29 10:16:40	ga_ls9c_ard_3-2-1_100071_2023-04-29_final.stac-item
2023-05-02 09:16:12	ga_ls9c_ard_3-2-1_089090_2023-05-01_final.stac-item
2023-05-08 10:12:46	ga_ls9c_ard_3-2-1_099077_2023-05-08_final.stac-item
2023-05-08 11:52:27	ga_ls9c_ard_3-2-1_115079_2023-05-08_final.stac-item
2023-05-12 09:46:26	ga_ls9c_ard_3-2-1_095073_2023-05-12_final.stac-item
2023-05-14 11:11:21	ga_ls9c_ard_3-2-1_109069_2023-05-14_final.stac-item
2023-05-16 09:21:41	ga_ls9c_ard_3-2-1_091073_2023-05-15_final.stac-item
2023-05-16 09:23:17	ga_ls9c_ard_3-2-1_091077_2023-05-15_final.stac-item
2023-05-19 11:35:25	ga_ls9c_ard_3-2-1_112083_2023-05-19_final.stac-item
2023-05-20 10:38:59	ga_ls9c_ard_3-2-1_103081_2023-05-20_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 10:16:23	ga_ls9c_ard_3-2-1_100071_2023-05-31_final.stac-item
2023-06-20 11:34:47	ga_ls9c_ard_3-2-1_112082_2023-06-20_final.stac-item
2023-06-21 10:38:46	ga_ls9c_ard_3-2-1_103081_2023-06-21_final.stac-item
2023-07-03 09:27:10	ga_ls9c_ard_3-2-1_091087_2023-07-02_final.stac-item
2023-07-03 09:28:22	ga_ls9c_ard_3-2-1_091090_2023-07-02_final.stac-item
2023-07-05 10:48:32	ga_ls9c_ard_3-2-1_105074_2023-07-05_final.stac-item
2023-07-19 11:00:58	ga_ls9c_ard_3-2-1_107074_2023-07-19_final.stac-item
2023-07-21 09:16:06	ga_ls9c_ard_3-2-1_089090_2023-07-20_final.stac-item
2023-08-09 09:40:23	ga_ls9c_ard_3-2-1_094073_2023-08-09_final.stac-item
2023-10-16 10:54:37	ga_ls9c_ard_3-2-1_106072_2023-10-16_final.stac-item
2023-10-17 11:42:17	ga_ls9c_ard_3-2-1_113083_2023-10-17_final.stac-item
2023-10-19 09:51:03	ga_ls9c_ard_3-2-1_095083_2023-10-19_final.stac-item
2023-10-19 11:29:56	ga_ls9c_ard_3-2-1_111083_2023-10-19_final.stac-item
2023-10-23 09:26:19	ga_ls9c_ard_3-2-1_091083_2023-10-22_final.stac-item
2023-10-23 11:01:36	ga_ls9c_ard_3-2-1_107074_2023-10-23_final.stac-item
2023-10-26 11:35:41	ga_ls9c_ard_3-2-1_112082_2023-10-26_final.stac-item
2023-11-15 11:10:54	ga_ls9c_ard_3-2-1_108082_2023-11-15_final.stac-item
2023-11-17 10:56:10	ga_ls9c_ard_3-2-1_106076_2023-11-17_final.stac-item
2023-11-20 09:47:27	ga_ls9c_ard_3-2-1_095074_2023-11-20_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