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
2022-01-03 09:35:55	ga_ls9c_ard_3-2-1_093076_2022-01-03_final.stac-item
2022-01-24 09:52:51	ga_ls9c_ard_3-2-1_096072_2022-01-24_final.stac-item
2022-01-28 09:32:08	ga_ls9c_ard_3-2-1_092082_2022-01-28_final.stac-item
2022-01-31 11:41:31	ga_ls9c_ard_3-2-1_113081_2022-01-31_final.stac-item
2022-02-01 10:41:30	ga_ls9c_ard_3-2-1_104070_2022-02-01_final.stac-item
2022-04-04 10:53:08	ga_ls9c_ard_3-2-1_106069_2022-04-04_final.stac-item
2022-04-24 10:27:49	ga_ls9c_ard_3-2-1_102068_2022-04-24_final.stac-item
2022-05-06 09:18:48	ga_ls9c_ard_3-2-1_090081_2022-05-05_final.stac-item
2022-05-07 09:59:39	ga_ls9c_ard_3-2-1_097075_2022-05-07_final.stac-item
2022-05-24 10:44:44	ga_ls9c_ard_3-2-1_104080_2022-05-24_final.stac-item
2022-06-19 09:44:42	ga_ls9c_ard_3-2-1_094084_2022-06-19_final.stac-item
2022-07-23 11:07:05	ga_ls9c_ard_3-2-1_108073_2022-07-23_final.stac-item
2022-07-25 10:54:45	ga_ls9c_ard_3-2-1_106073_2022-07-25_final.stac-item
2022-08-07 10:25:37	ga_ls9c_ard_3-2-1_101077_2022-08-07_final.stac-item
2022-08-27 11:41:52	ga_ls9c_ard_3-2-1_113082_2022-08-27_final.stac-item
2022-09-05 09:52:49	ga_ls9c_ard_3-2-1_096072_2022-09-05_final.stac-item
2022-10-08 10:39:24	ga_ls9c_ard_3-2-1_103080_2022-10-08_final.stac-item
2022-10-13 10:58:24	ga_ls9c_ard_3-2-1_106081_2022-10-13_final.stac-item
2022-10-14 09:59:35	ga_ls9c_ard_3-2-1_097073_2022-10-14_final.stac-item
2022-10-17 10:30:07	ga_ls9c_ard_3-2-1_102072_2022-10-17_final.stac-item
2022-10-17 10:34:06	ga_ls9c_ard_3-2-1_102082_2022-10-17_final.stac-item
2022-10-21 10:06:12	ga_ls9c_ard_3-2-1_098074_2022-10-21_final.stac-item
2022-10-23 11:31:55	ga_ls9c_ard_3-2-1_112072_2022-10-23_final.stac-item
2022-11-01 11:25:43	ga_ls9c_ard_3-2-1_111072_2022-11-01_final.stac-item
2022-11-03 09:40:26	ga_ls9c_ard_3-2-1_093087_2022-11-03_final.stac-item
2022-11-03 11:12:08	ga_ls9c_ard_3-2-1_109069_2022-11-03_final.stac-item
2022-11-12 09:34:19	ga_ls9c_ard_3-2-1_092087_2022-11-12_final.stac-item
2022-11-22 10:09:48	ga_ls9c_ard_3-2-1_098083_2022-11-22_final.stac-item
2022-11-23 10:47:52	ga_ls9c_ard_3-2-1_105070_2022-11-23_final.stac-item
2022-11-24 09:55:50	ga_ls9c_ard_3-2-1_096079_2022-11-24_final.stac-item
2022-11-29 11:51:38	ga_ls9c_ard_3-2-1_115075_2022-11-29_final.stac-item
2022-12-01 09:59:10	ga_ls9c_ard_3-2-1_097072_2022-12-01_final.stac-item
2022-12-13 10:24:20	ga_ls9c_ard_3-2-1_101073_2022-12-13_final.stac-item
2022-12-16 09:19:32	ga_ls9c_ard_3-2-1_090081_2022-12-15_final.stac-item
2022-12-17 09:59:36	ga_ls9c_ard_3-2-1_097073_2022-12-17_final.stac-item
2022-12-17 10:00:00	ga_ls9c_ard_3-2-1_097074_2022-12-17_final.stac-item
2022-12-17 11:38:53	ga_ls9c_ard_3-2-1_113074_2022-12-17_final.stac-item
2022-12-21 11:17:20	ga_ls9c_ard_3-2-1_109082_2022-12-21_final.stac-item
2022-12-24 10:10:31	ga_ls9c_ard_3-2-1_098085_2022-12-24_final.stac-item
2022-12-31 10:15:34	ga_ls9c_ard_3-2-1_099082_2022-12-31_final.stac-item
2023-01-03 10:44:52	ga_ls9c_ard_3-2-1_104078_2023-01-03_final.stac-item
2023-01-04 11:30:08	ga_ls9c_ard_3-2-1_111083_2023-01-04_final.stac-item
2023-01-06 11:16:58	ga_ls9c_ard_3-2-1_109081_2023-01-06_final.stac-item
2023-01-13 09:46:37	ga_ls9c_ard_3-2-1_094087_2023-01-13_final.stac-item
2023-01-17 10:54:20	ga_ls9c_ard_3-2-1_106071_2023-01-17_final.stac-item
2023-01-17 10:55:08	ga_ls9c_ard_3-2-1_106073_2023-01-17_final.stac-item
2023-01-18 09:59:54	ga_ls9c_ard_3-2-1_097074_2023-01-18_final.stac-item
2023-01-19 09:06:39	ga_ls9c_ard_3-2-1_088080_2023-01-18_final.stac-item
2023-01-29 09:41:51	ga_ls9c_ard_3-2-1_094075_2023-01-29_final.stac-item
2023-02-02 10:58:27	ga_ls9c_ard_3-2-1_106081_2023-02-02_final.stac-item
2023-03-04 11:07:47	ga_ls9c_ard_3-2-1_108074_2023-03-04_final.stac-item
2023-04-21 09:33:18	ga_ls9c_ard_3-2-1_092086_2023-04-21_final.stac-item
2023-04-23 10:54:13	ga_ls9c_ard_3-2-1_106072_2023-04-23_final.stac-item
2023-04-23 10:58:13	ga_ls9c_ard_3-2-1_106082_2023-04-23_final.stac-item
2023-04-26 11:29:29	ga_ls9c_ard_3-2-1_111083_2023-04-26_final.stac-item
2023-04-28 09:37:01	ga_ls9c_ard_3-2-1_093080_2023-04-28_final.stac-item
2023-05-01 10:05:28	ga_ls9c_ard_3-2-1_098074_2023-05-01_final.stac-item
2023-05-03 09:56:15	ga_ls9c_ard_3-2-1_096082_2023-05-03_final.stac-item
2023-05-09 10:57:38	ga_ls9c_ard_3-2-1_106081_2023-05-09_final.stac-item
2023-05-11 10:41:40	ga_ls9c_ard_3-2-1_104072_2023-05-11_final.stac-item
2023-05-12 09:47:14	ga_ls9c_ard_3-2-1_095075_2023-05-12_final.stac-item
2023-05-12 11:25:20	ga_ls9c_ard_3-2-1_111073_2023-05-12_final.stac-item
2023-05-13 10:28:30	ga_ls9c_ard_3-2-1_102070_2023-05-13_final.stac-item
2023-05-16 09:25:41	ga_ls9c_ard_3-2-1_091083_2023-05-15_final.stac-item
2023-05-17 10:07:20	ga_ls9c_ard_3-2-1_098079_2023-05-17_final.stac-item
2023-05-18 09:14:29	ga_ls9c_ard_3-2-1_089086_2023-05-17_final.stac-item
2023-06-01 09:25:57	ga_ls9c_ard_3-2-1_091084_2023-05-31_final.stac-item
2023-06-23 10:26:48	ga_ls9c_ard_3-2-1_101082_2023-06-23_final.stac-item
2023-06-26 10:53:19	ga_ls9c_ard_3-2-1_106071_2023-06-26_final.stac-item
2023-06-26 10:57:42	ga_ls9c_ard_3-2-1_106082_2023-06-26_final.stac-item
2023-06-27 09:58:07	ga_ls9c_ard_3-2-1_097072_2023-06-27_final.stac-item
2023-07-05 10:48:08	ga_ls9c_ard_3-2-1_105073_2023-07-05_final.stac-item
2023-07-06 09:51:43	ga_ls9c_ard_3-2-1_096071_2023-07-06_final.stac-item
2023-07-15 09:50:00	ga_ls9c_ard_3-2-1_095082_2023-07-15_final.stac-item
2023-07-18 10:17:43	ga_ls9c_ard_3-2-1_100074_2023-07-18_final.stac-item
2023-07-19 09:28:04	ga_ls9c_ard_3-2-1_091089_2023-07-18_final.stac-item
2023-07-19 11:04:10	ga_ls9c_ard_3-2-1_107082_2023-07-19_final.stac-item
2023-07-20 10:05:45	ga_ls9c_ard_3-2-1_098075_2023-07-20_final.stac-item
2023-07-22 09:52:11	ga_ls9c_ard_3-2-1_096072_2023-07-22_final.stac-item
2023-07-23 10:34:14	ga_ls9c_ard_3-2-1_103069_2023-07-23_final.stac-item
2023-07-29 09:58:01	ga_ls9c_ard_3-2-1_097071_2023-07-29_final.stac-item
2023-07-29 11:38:06	ga_ls9c_ard_3-2-1_113074_2023-07-29_final.stac-item
2023-08-02 09:39:21	ga_ls9c_ard_3-2-1_093086_2023-08-02_final.stac-item
2023-08-17 10:28:38	ga_ls9c_ard_3-2-1_102070_2023-08-17_final.stac-item
2023-10-14 11:06:34	ga_ls9c_ard_3-2-1_108071_2023-10-14_final.stac-item
2023-10-15 10:10:33	ga_ls9c_ard_3-2-1_099070_2023-10-15_final.stac-item
2023-10-16 10:59:01	ga_ls9c_ard_3-2-1_106083_2023-10-16_final.stac-item
2023-10-17 11:41:53	ga_ls9c_ard_3-2-1_113082_2023-10-17_final.stac-item
2023-10-18 10:41:52	ga_ls9c_ard_3-2-1_104071_2023-10-18_final.stac-item
2023-10-24 10:07:11	ga_ls9c_ard_3-2-1_098077_2023-10-24_final.stac-item
2023-10-27 10:36:04	ga_ls9c_ard_3-2-1_103072_2023-10-27_final.stac-item
2023-11-01 10:54:56	ga_ls9c_ard_3-2-1_106073_2023-11-01_final.stac-item
2023-11-15 09:32:01	ga_ls9c_ard_3-2-1_092082_2023-11-15_final.stac-item
2023-11-15 09:33:37	ga_ls9c_ard_3-2-1_092086_2023-11-15_final.stac-item
2023-11-17 09:20:53	ga_ls9c_ard_3-2-1_090085_2023-11-16_final.stac-item
2023-11-18 09:57:46	ga_ls9c_ard_3-2-1_097069_2023-11-18_final.stac-item
2023-11-18 09:58:34	ga_ls9c_ard_3-2-1_097071_2023-11-18_final.stac-item
2023-11-22 09:35:31	ga_ls9c_ard_3-2-1_093075_2023-11-22_final.stac-item
2023-11-24 09:29:10	ga_ls9c_ard_3-2-1_091090_2023-11-23_final.stac-item
2023-11-26 09:15:13	ga_ls9c_ard_3-2-1_089086_2023-11-25_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