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
2021-12-06 10:52:35	ga_ls9c_ard_3-2-1_105082_2021-12-06_final.stac-item
2021-12-13 09:21:24	ga_ls9c_ard_3-2-1_090086_2021-12-12_final.stac-item
2021-12-13 10:56:41	ga_ls9c_ard_3-2-1_106077_2021-12-13_final.stac-item
2021-12-14 10:03:27	ga_ls9c_ard_3-2-1_097083_2021-12-14_final.stac-item
2021-12-30 10:03:26	ga_ls9c_ard_3-2-1_097083_2021-12-30_final.stac-item
2022-01-28 11:11:49	ga_ls9c_ard_3-2-1_108084_2022-01-28_final.stac-item
2022-01-30 10:58:15	ga_ls9c_ard_3-2-1_106081_2022-01-30_final.stac-item
2022-02-17 10:41:24	ga_ls9c_ard_3-2-1_104070_2022-02-17_final.stac-item
2022-02-17 10:44:36	ga_ls9c_ard_3-2-1_104078_2022-02-17_final.stac-item
2022-02-23 10:09:03	ga_ls9c_ard_3-2-1_098082_2022-02-23_final.stac-item
2022-07-11 10:44:14	ga_ls9c_ard_3-2-1_104078_2022-07-11_final.stac-item
2022-07-16 11:01:11	ga_ls9c_ard_3-2-1_107074_2022-07-16_final.stac-item
2022-07-20 10:38:08	ga_ls9c_ard_3-2-1_103078_2022-07-20_final.stac-item
2022-07-25 10:57:09	ga_ls9c_ard_3-2-1_106079_2022-07-25_final.stac-item
2022-08-17 11:01:34	ga_ls9c_ard_3-2-1_107074_2022-08-17_final.stac-item
2022-08-21 10:38:28	ga_ls9c_ard_3-2-1_103078_2022-08-21_final.stac-item
2022-08-24 11:07:22	ga_ls9c_ard_3-2-1_108073_2022-08-24_final.stac-item
2022-10-11 09:34:15	ga_ls9c_ard_3-2-1_092087_2022-10-11_final.stac-item
2022-10-25 09:42:16	ga_ls9c_ard_3-2-1_094076_2022-10-25_final.stac-item
2022-10-26 10:28:20	ga_ls9c_ard_3-2-1_101083_2022-10-26_final.stac-item
2022-10-28 11:51:15	ga_ls9c_ard_3-2-1_115074_2022-10-28_final.stac-item
2022-11-08 09:56:13	ga_ls9c_ard_3-2-1_096080_2022-11-08_final.stac-item
2022-11-25 10:35:30	ga_ls9c_ard_3-2-1_103070_2022-11-25_final.stac-item
2022-11-26 09:43:04	ga_ls9c_ard_3-2-1_094078_2022-11-26_final.stac-item
2022-12-18 10:43:39	ga_ls9c_ard_3-2-1_104075_2022-12-18_final.stac-item
2022-12-28 09:43:03	ga_ls9c_ard_3-2-1_094078_2022-12-28_final.stac-item
2022-12-30 09:30:18	ga_ls9c_ard_3-2-1_092077_2022-12-30_final.stac-item
2023-01-06 09:39:17	ga_ls9c_ard_3-2-1_093084_2023-01-06_final.stac-item
2023-01-08 11:04:12	ga_ls9c_ard_3-2-1_107080_2023-01-08_final.stac-item
2023-01-15 11:10:19	ga_ls9c_ard_3-2-1_108080_2023-01-15_final.stac-item
2023-01-26 10:50:59	ga_ls9c_ard_3-2-1_105078_2023-01-26_final.stac-item
2023-01-31 11:11:35	ga_ls9c_ard_3-2-1_108083_2023-01-31_final.stac-item
2023-02-05 11:28:35	ga_ls9c_ard_3-2-1_111079_2023-02-05_final.stac-item
2023-02-10 10:09:27	ga_ls9c_ard_3-2-1_098082_2023-02-10_final.stac-item
2023-02-12 09:58:40	ga_ls9c_ard_3-2-1_096086_2023-02-12_final.stac-item
2023-02-13 10:34:44	ga_ls9c_ard_3-2-1_103068_2023-02-13_final.stac-item
2023-04-23 10:57:49	ga_ls9c_ard_3-2-1_106081_2023-04-23_final.stac-item
2023-04-24 09:59:47	ga_ls9c_ard_3-2-1_097075_2023-04-24_final.stac-item
2023-04-24 10:00:59	ga_ls9c_ard_3-2-1_097078_2023-04-24_final.stac-item
2023-04-24 10:02:11	ga_ls9c_ard_3-2-1_097081_2023-04-24_final.stac-item
2023-04-24 11:40:40	ga_ls9c_ard_3-2-1_113080_2023-04-24_final.stac-item
2023-04-25 10:41:03	ga_ls9c_ard_3-2-1_104070_2023-04-25_final.stac-item
2023-04-25 10:44:14	ga_ls9c_ard_3-2-1_104078_2023-04-25_final.stac-item
2023-04-26 09:48:12	ga_ls9c_ard_3-2-1_095077_2023-04-26_final.stac-item
2023-04-26 09:51:00	ga_ls9c_ard_3-2-1_095084_2023-04-26_final.stac-item
2023-04-28 09:38:12	ga_ls9c_ard_3-2-1_093083_2023-04-28_final.stac-item
2023-04-28 11:14:18	ga_ls9c_ard_3-2-1_109076_2023-04-28_final.stac-item
2023-04-29 10:21:51	ga_ls9c_ard_3-2-1_100084_2023-04-29_final.stac-item
2023-04-30 11:00:42	ga_ls9c_ard_3-2-1_107073_2023-04-30_final.stac-item
2023-05-28 09:47:52	ga_ls9c_ard_3-2-1_095077_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
2023-05-28 11:24:46	ga_ls9c_ard_3-2-1_111072_2023-05-28_final.stac-item
2023-05-28 11:26:22	ga_ls9c_ard_3-2-1_111076_2023-05-28_final.stac-item
2023-05-30 09:37:31	ga_ls9c_ard_3-2-1_093082_2023-05-30_final.stac-item
2023-07-05 10:50:32	ga_ls9c_ard_3-2-1_105079_2023-07-05_final.stac-item
2023-07-16 10:33:16	ga_ls9c_ard_3-2-1_102082_2023-07-16_final.stac-item
2023-07-17 11:16:07	ga_ls9c_ard_3-2-1_109081_2023-07-17_final.stac-item
2023-07-24 09:42:12	ga_ls9c_ard_3-2-1_094078_2023-07-24_final.stac-item
2023-07-24 09:42:36	ga_ls9c_ard_3-2-1_094079_2023-07-24_final.stac-item
2023-07-26 09:31:51	ga_ls9c_ard_3-2-1_092083_2023-07-26_final.stac-item
2023-07-28 10:54:25	ga_ls9c_ard_3-2-1_106073_2023-07-28_final.stac-item
2023-07-28 10:55:37	ga_ls9c_ard_3-2-1_106076_2023-07-28_final.stac-item
2023-07-28 10:56:25	ga_ls9c_ard_3-2-1_106078_2023-07-28_final.stac-item
2023-07-28 10:58:01	ga_ls9c_ard_3-2-1_106082_2023-07-28_final.stac-item
2023-08-02 09:39:21	ga_ls9c_ard_3-2-1_093086_2023-08-02_final.stac-item
2023-08-04 09:26:12	ga_ls9c_ard_3-2-1_091084_2023-08-03_final.stac-item
2023-08-04 11:00:42	ga_ls9c_ard_3-2-1_107073_2023-08-04_final.stac-item
2023-08-05 10:08:41	ga_ls9c_ard_3-2-1_098082_2023-08-05_final.stac-item
2023-08-06 09:13:52	ga_ls9c_ard_3-2-1_089084_2023-08-05_final.stac-item
2023-10-13 10:26:53	ga_ls9c_ard_3-2-1_101080_2023-10-13_final.stac-item
2023-10-14 09:29:41	ga_ls9c_ard_3-2-1_092076_2023-10-13_final.stac-item
2023-10-17 10:01:24	ga_ls9c_ard_3-2-1_097078_2023-10-17_final.stac-item
2023-10-17 10:02:12	ga_ls9c_ard_3-2-1_097080_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 09:49:51	ga_ls9c_ard_3-2-1_095080_2023-10-19_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 11:26:20	ga_ls9c_ard_3-2-1_111074_2023-10-19_final.stac-item
2023-10-20 10:29:07	ga_ls9c_ard_3-2-1_102070_2023-10-20_final.stac-item
2023-10-21 09:34:18	ga_ls9c_ard_3-2-1_093072_2023-10-21_final.stac-item
2023-10-21 11:15:58	ga_ls9c_ard_3-2-1_109079_2023-10-21_final.stac-item
2023-10-21 11:16:22	ga_ls9c_ard_3-2-1_109080_2023-10-21_final.stac-item
2023-10-22 10:21:09	ga_ls9c_ard_3-2-1_100081_2023-10-22_final.stac-item
2023-10-22 10:22:20	ga_ls9c_ard_3-2-1_100084_2023-10-22_final.stac-item
2023-10-28 11:20:54	ga_ls9c_ard_3-2-1_110076_2023-10-28_final.stac-item
2023-10-30 09:30:50	ga_ls9c_ard_3-2-1_092079_2023-10-30_final.stac-item
2023-10-30 11:10:07	ga_ls9c_ard_3-2-1_108080_2023-10-30_final.stac-item
2023-11-04 09:51:19	ga_ls9c_ard_3-2-1_095084_2023-11-04_final.stac-item
2023-11-05 10:33:00	ga_ls9c_ard_3-2-1_102080_2023-11-05_final.stac-item
2023-11-14 10:24:27	ga_ls9c_ard_3-2-1_101074_2023-11-14_final.stac-item
2023-11-15 11:09:18	ga_ls9c_ard_3-2-1_108078_2023-11-15_final.stac-item
2023-11-16 11:50:59	ga_ls9c_ard_3-2-1_115074_2023-11-16_final.stac-item
2023-11-20 09:51:26	ga_ls9c_ard_3-2-1_095084_2023-11-20_final.stac-item
2023-11-20 11:28:19	ga_ls9c_ard_3-2-1_111079_2023-11-20_final.stac-item
2023-11-21 10:33:55	ga_ls9c_ard_3-2-1_102082_2023-11-21_final.stac-item
2023-11-22 09:38:18	ga_ls9c_ard_3-2-1_093082_2023-11-22_final.stac-item
2023-11-22 09:39:06	ga_ls9c_ard_3-2-1_093084_2023-11-22_final.stac-item
2023-11-22 09:40:18	ga_ls9c_ard_3-2-1_093087_2023-11-22_final.stac-item
2023-11-22 11:15:12	ga_ls9c_ard_3-2-1_109077_2023-11-22_final.stac-item
2023-11-23 10:20:47	ga_ls9c_ard_3-2-1_100080_2023-11-23_final.stac-item
2023-11-24 09:24:46	ga_ls9c_ard_3-2-1_091079_2023-11-23_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