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
2021-11-05 09:40:36	ga_ls9c_ard_3-2-1_093086_2021-11-05_final.stac-item
2021-12-05 11:47:01	ga_ls9c_ard_3-2-1_114079_2021-12-05_final.stac-item
2021-12-18 09:35:55	ga_ls9c_ard_3-2-1_093076_2021-12-18_final.stac-item
2021-12-31 10:41:31	ga_ls9c_ard_3-2-1_104070_2021-12-31_final.stac-item
2022-01-12 09:29:42	ga_ls9c_ard_3-2-1_092076_2022-01-11_final.stac-item
2022-02-16 11:40:14	ga_ls9c_ard_3-2-1_113078_2022-02-16_final.stac-item
2022-02-17 10:42:36	ga_ls9c_ard_3-2-1_104073_2022-02-17_final.stac-item
2022-03-28 10:47:21	ga_ls9c_ard_3-2-1_105070_2022-03-28_final.stac-item
2022-04-11 09:25:58	ga_ls9c_ard_3-2-1_091083_2022-04-10_final.stac-item
2022-06-04 10:25:25	ga_ls9c_ard_3-2-1_101078_2022-06-04_final.stac-item
2022-06-10 09:47:09	ga_ls9c_ard_3-2-1_095075_2022-06-10_final.stac-item
2022-06-15 10:07:45	ga_ls9c_ard_3-2-1_098080_2022-06-15_final.stac-item
2022-07-14 11:11:56	ga_ls9c_ard_3-2-1_109070_2022-07-14_final.stac-item
2022-07-18 10:46:04	ga_ls9c_ard_3-2-1_105067_2022-07-18_final.stac-item
2022-08-16 10:18:18	ga_ls9c_ard_3-2-1_100074_2022-08-16_final.stac-item
2022-08-27 11:41:28	ga_ls9c_ard_3-2-1_113081_2022-08-27_final.stac-item
2022-09-18 11:01:41	ga_ls9c_ard_3-2-1_107074_2022-09-18_final.stac-item
2022-09-28 11:42:24	ga_ls9c_ard_3-2-1_113083_2022-09-28_final.stac-item
2022-10-02 09:34:00	ga_ls9c_ard_3-2-1_093071_2022-10-02_final.stac-item
2022-10-05 11:44:59	ga_ls9c_ard_3-2-1_114074_2022-10-05_final.stac-item
2022-10-07 11:36:36	ga_ls9c_ard_3-2-1_112084_2022-10-07_final.stac-item
2022-11-03 09:37:14	ga_ls9c_ard_3-2-1_093079_2022-11-03_final.stac-item
2022-11-03 11:14:08	ga_ls9c_ard_3-2-1_109074_2022-11-03_final.stac-item
2022-11-06 11:45:51	ga_ls9c_ard_3-2-1_114076_2022-11-06_final.stac-item
2022-11-07 09:14:33	ga_ls9c_ard_3-2-1_089084_2022-11-06_final.stac-item
2022-11-09 10:36:42	ga_ls9c_ard_3-2-1_103073_2022-11-09_final.stac-item
2022-11-14 10:57:39	ga_ls9c_ard_3-2-1_106079_2022-11-14_final.stac-item
2022-11-21 11:03:50	ga_ls9c_ard_3-2-1_107079_2022-11-21_final.stac-item
2022-11-29 10:13:09	ga_ls9c_ard_3-2-1_099076_2022-11-29_final.stac-item
2022-11-30 10:57:36	ga_ls9c_ard_3-2-1_106079_2022-11-30_final.stac-item
2022-12-01 09:59:58	ga_ls9c_ard_3-2-1_097074_2022-12-01_final.stac-item
2022-12-02 10:42:50	ga_ls9c_ard_3-2-1_104073_2022-12-02_final.stac-item
2022-12-04 10:30:29	ga_ls9c_ard_3-2-1_102073_2022-12-04_final.stac-item
2022-12-06 11:58:13	ga_ls9c_ard_3-2-1_116076_2022-12-06_final.stac-item
2022-12-07 09:25:19	ga_ls9c_ard_3-2-1_091080_2022-12-06_final.stac-item
2022-12-08 10:07:23	ga_ls9c_ard_3-2-1_098077_2022-12-08_final.stac-item
2022-12-09 10:52:39	ga_ls9c_ard_3-2-1_105082_2022-12-09_final.stac-item
2022-12-12 11:20:21	ga_ls9c_ard_3-2-1_110074_2022-12-12_final.stac-item
2022-12-16 09:19:32	ga_ls9c_ard_3-2-1_090081_2022-12-15_final.stac-item
2022-12-19 09:48:50	ga_ls9c_ard_3-2-1_095077_2022-12-19_final.stac-item
2022-12-21 11:14:08	ga_ls9c_ard_3-2-1_109074_2022-12-21_final.stac-item
2022-12-28 11:24:19	ga_ls9c_ard_3-2-1_110084_2022-12-28_final.stac-item
2023-01-06 09:36:30	ga_ls9c_ard_3-2-1_093077_2023-01-06_final.stac-item
2023-01-06 09:40:05	ga_ls9c_ard_3-2-1_093086_2023-01-06_final.stac-item
2023-01-12 10:38:16	ga_ls9c_ard_3-2-1_103077_2023-01-12_final.stac-item
2023-01-15 11:08:44	ga_ls9c_ard_3-2-1_108076_2023-01-15_final.stac-item
2023-01-19 10:44:20	ga_ls9c_ard_3-2-1_104077_2023-01-19_final.stac-item
2023-01-22 09:40:20	ga_ls9c_ard_3-2-1_093087_2023-01-22_final.stac-item
2023-01-26 10:50:11	ga_ls9c_ard_3-2-1_105076_2023-01-26_final.stac-item
2023-01-26 10:50:35	ga_ls9c_ard_3-2-1_105077_2023-01-26_final.stac-item
2023-01-29 11:24:44	ga_ls9c_ard_3-2-1_110085_2023-01-29_final.stac-item
2023-02-01 11:52:28	ga_ls9c_ard_3-2-1_115077_2023-02-01_final.stac-item
2023-02-05 11:29:47	ga_ls9c_ard_3-2-1_111082_2023-02-05_final.stac-item
2023-02-05 11:30:35	ga_ls9c_ard_3-2-1_111084_2023-02-05_final.stac-item
2023-02-08 10:19:25	ga_ls9c_ard_3-2-1_100076_2023-02-08_final.stac-item
2023-02-10 11:45:32	ga_ls9c_ard_3-2-1_114075_2023-02-10_final.stac-item
2023-02-13 10:39:08	ga_ls9c_ard_3-2-1_103079_2023-02-13_final.stac-item
2023-04-03 11:20:40	ga_ls9c_ard_3-2-1_110076_2023-04-03_final.stac-item
2023-04-23 09:18:56	ga_ls9c_ard_3-2-1_090081_2023-04-22_final.stac-item
2023-04-28 11:11:54	ga_ls9c_ard_3-2-1_109070_2023-04-28_final.stac-item
2023-05-01 10:05:04	ga_ls9c_ard_3-2-1_098073_2023-05-01_final.stac-item
2023-05-09 10:52:50	ga_ls9c_ard_3-2-1_106069_2023-05-09_final.stac-item
2023-05-13 10:30:30	ga_ls9c_ard_3-2-1_102075_2023-05-13_final.stac-item
2023-05-16 09:24:53	ga_ls9c_ard_3-2-1_091081_2023-05-15_final.stac-item
2023-06-01 09:25:09	ga_ls9c_ard_3-2-1_091082_2023-05-31_final.stac-item
2023-06-02 10:04:25	ga_ls9c_ard_3-2-1_098072_2023-06-02_final.stac-item
2023-06-22 11:19:14	ga_ls9c_ard_3-2-1_110074_2023-06-22_final.stac-item
2023-06-26 09:17:37	ga_ls9c_ard_3-2-1_090079_2023-06-25_final.stac-item
2023-06-28 10:40:37	ga_ls9c_ard_3-2-1_104070_2023-06-28_final.stac-item
2023-07-03 09:25:34	ga_ls9c_ard_3-2-1_091083_2023-07-02_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 11:25:41	ga_ls9c_ard_3-2-1_111074_2023-07-15_final.stac-item
2023-07-20 10:07:44	ga_ls9c_ard_3-2-1_098080_2023-07-20_final.stac-item
2023-07-22 09:51:47	ga_ls9c_ard_3-2-1_096071_2023-07-22_final.stac-item
2023-07-24 09:40:36	ga_ls9c_ard_3-2-1_094074_2023-07-24_final.stac-item
2023-07-31 09:50:53	ga_ls9c_ard_3-2-1_095084_2023-07-31_final.stac-item
2023-08-02 11:13:02	ga_ls9c_ard_3-2-1_109073_2023-08-02_final.stac-item
2023-08-04 09:24:36	ga_ls9c_ard_3-2-1_091080_2023-08-03_final.stac-item
2023-08-05 10:07:53	ga_ls9c_ard_3-2-1_098080_2023-08-05_final.stac-item
2023-08-14 11:41:25	ga_ls9c_ard_3-2-1_113082_2023-08-14_final.stac-item
2023-08-17 10:33:25	ga_ls9c_ard_3-2-1_102082_2023-08-17_final.stac-item
2023-10-16 09:18:08	ga_ls9c_ard_3-2-1_090078_2023-10-15_final.stac-item
2023-10-17 09:58:36	ga_ls9c_ard_3-2-1_097071_2023-10-17_final.stac-item
2023-10-17 09:59:00	ga_ls9c_ard_3-2-1_097072_2023-10-17_final.stac-item
2023-10-18 10:43:04	ga_ls9c_ard_3-2-1_104074_2023-10-18_final.stac-item
2023-10-19 09:47:27	ga_ls9c_ard_3-2-1_095074_2023-10-19_final.stac-item
2023-10-21 09:35:05	ga_ls9c_ard_3-2-1_093074_2023-10-21_final.stac-item
2023-10-23 09:28:43	ga_ls9c_ard_3-2-1_091089_2023-10-22_final.stac-item
2023-10-25 09:13:57	ga_ls9c_ard_3-2-1_089083_2023-10-24_final.stac-item
2023-10-29 10:24:52	ga_ls9c_ard_3-2-1_101075_2023-10-29_final.stac-item
2023-10-29 10:26:04	ga_ls9c_ard_3-2-1_101078_2023-10-29_final.stac-item
2023-11-02 09:58:29	ga_ls9c_ard_3-2-1_097071_2023-11-02_final.stac-item
2023-11-02 11:42:10	ga_ls9c_ard_3-2-1_113083_2023-11-02_final.stac-item
2023-11-03 10:43:44	ga_ls9c_ard_3-2-1_104076_2023-11-03_final.stac-item
2023-11-04 11:25:25	ga_ls9c_ard_3-2-1_111072_2023-11-04_final.stac-item
2023-11-04 11:28:13	ga_ls9c_ard_3-2-1_111079_2023-11-04_final.stac-item
2023-11-16 10:15:41	ga_ls9c_ard_3-2-1_099083_2023-11-16_final.stac-item
2023-11-16 11:53:22	ga_ls9c_ard_3-2-1_115080_2023-11-16_final.stac-item
2023-11-18 10:01:22	ga_ls9c_ard_3-2-1_097078_2023-11-18_final.stac-item
2023-11-20 09:47:50	ga_ls9c_ard_3-2-1_095075_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