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
2021-11-02 10:54:03	ga_ls9c_ard_3-2-1_106076_2021-11-02_final.stac-item
2021-11-05 09:37:01	ga_ls9c_ard_3-2-1_093077_2021-11-05_final.stac-item
2021-11-05 11:13:41	ga_ls9c_ard_3-2-1_109072_2021-11-05_final.stac-item
2021-11-12 10:55:49	ga_ls9c_ard_3-2-1_106068_2021-11-12_final.stac-item
2021-11-18 09:59:35	ga_ls9c_ard_3-2-1_097068_2021-11-18_final.stac-item
2021-11-18 10:04:45	ga_ls9c_ard_3-2-1_097081_2021-11-18_final.stac-item
2021-12-04 11:00:59	ga_ls9c_ard_3-2-1_107072_2021-12-04_final.stac-item
2021-12-06 09:13:18	ga_ls9c_ard_3-2-1_089081_2021-12-05_final.stac-item
2021-12-08 10:38:13	ga_ls9c_ard_3-2-1_103077_2021-12-08_final.stac-item
2021-12-19 10:19:58	ga_ls9c_ard_3-2-1_100078_2021-12-19_final.stac-item
2021-12-19 10:21:34	ga_ls9c_ard_3-2-1_100082_2021-12-19_final.stac-item
2021-12-22 10:51:17	ga_ls9c_ard_3-2-1_105079_2021-12-22_final.stac-item
2021-12-24 10:38:08	ga_ls9c_ard_3-2-1_103077_2021-12-24_final.stac-item
2021-12-25 09:43:18	ga_ls9c_ard_3-2-1_094079_2021-12-25_final.stac-item
2021-12-31 10:41:31	ga_ls9c_ard_3-2-1_104070_2021-12-31_final.stac-item
2022-01-01 09:47:05	ga_ls9c_ard_3-2-1_095073_2022-01-01_final.stac-item
2022-01-04 10:19:58	ga_ls9c_ard_3-2-1_100078_2022-01-04_final.stac-item
2022-01-06 10:07:36	ga_ls9c_ard_3-2-1_098078_2022-01-06_final.stac-item
2022-01-08 09:54:02	ga_ls9c_ard_3-2-1_096075_2022-01-08_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 09:35:17	ga_ls9c_ard_3-2-1_092090_2022-01-12_final.stac-item
2022-01-18 10:30:19	ga_ls9c_ard_3-2-1_102073_2022-01-18_final.stac-item
2022-01-19 11:15:35	ga_ls9c_ard_3-2-1_109078_2022-01-19_final.stac-item
2022-01-22 10:07:36	ga_ls9c_ard_3-2-1_098078_2022-01-22_final.stac-item
2022-01-28 09:30:08	ga_ls9c_ard_3-2-1_092077_2022-01-28_final.stac-item
2022-01-31 09:58:38	ga_ls9c_ard_3-2-1_097071_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
2022-02-04 11:14:23	ga_ls9c_ard_3-2-1_109075_2022-02-04_final.stac-item
2022-02-08 09:13:34	ga_ls9c_ard_3-2-1_089082_2022-02-07_final.stac-item
2022-02-09 09:54:02	ga_ls9c_ard_3-2-1_096075_2022-02-09_final.stac-item
2022-02-09 09:56:49	ga_ls9c_ard_3-2-1_096082_2022-02-09_final.stac-item
2022-02-11 09:40:51	ga_ls9c_ard_3-2-1_094073_2022-02-11_final.stac-item
2022-02-11 09:43:15	ga_ls9c_ard_3-2-1_094079_2022-02-11_final.stac-item
2022-02-17 10:41:24	ga_ls9c_ard_3-2-1_104070_2022-02-17_final.stac-item
2022-02-19 10:30:13	ga_ls9c_ard_3-2-1_102073_2022-02-19_final.stac-item
2022-02-19 10:32:37	ga_ls9c_ard_3-2-1_102079_2022-02-19_final.stac-item
2022-02-20 09:34:59	ga_ls9c_ard_3-2-1_093074_2022-02-20_final.stac-item
2022-02-23 10:09:03	ga_ls9c_ard_3-2-1_098082_2022-02-23_final.stac-item
2022-02-24 09:10:37	ga_ls9c_ard_3-2-1_089075_2022-02-23_final.stac-item
2022-02-24 10:51:06	ga_ls9c_ard_3-2-1_105079_2022-02-24_final.stac-item
2022-02-27 09:43:04	ga_ls9c_ard_3-2-1_094079_2022-02-27_final.stac-item
2022-02-28 10:27:07	ga_ls9c_ard_3-2-1_101081_2022-02-28_final.stac-item
2022-03-02 10:12:44	ga_ls9c_ard_3-2-1_099076_2022-03-02_final.stac-item
2022-03-05 10:41:15	ga_ls9c_ard_3-2-1_104070_2022-03-05_final.stac-item
2022-03-07 10:30:06	ga_ls9c_ard_3-2-1_102073_2022-03-07_final.stac-item
2022-03-09 10:17:20	ga_ls9c_ard_3-2-1_100072_2022-03-09_final.stac-item
2022-03-10 09:27:18	ga_ls9c_ard_3-2-1_091086_2022-03-09_final.stac-item
2022-03-12 09:13:20	ga_ls9c_ard_3-2-1_089082_2022-03-11_final.stac-item
2022-03-23 10:30:02	ga_ls9c_ard_3-2-1_102073_2022-03-23_final.stac-item
2022-03-31 09:40:34	ga_ls9c_ard_3-2-1_094073_2022-03-31_final.stac-item
2022-04-05 10:01:06	ga_ls9c_ard_3-2-1_097078_2022-04-05_final.stac-item
2022-04-05 10:03:53	ga_ls9c_ard_3-2-1_097085_2022-04-05_final.stac-item
2022-04-06 10:45:09	ga_ls9c_ard_3-2-1_104080_2022-04-06_final.stac-item
2022-04-07 09:49:31	ga_ls9c_ard_3-2-1_095080_2022-04-07_final.stac-item
2022-04-08 10:29:59	ga_ls9c_ard_3-2-1_102073_2022-04-08_final.stac-item
2022-04-11 09:25:10	ga_ls9c_ard_3-2-1_091081_2022-04-10_final.stac-item
2022-05-02 09:40:45	ga_ls9c_ard_3-2-1_094074_2022-05-02_final.stac-item
2022-05-04 11:10:03	ga_ls9c_ard_3-2-1_108081_2022-05-04_final.stac-item
2022-05-09 09:50:52	ga_ls9c_ard_3-2-1_095084_2022-05-09_final.stac-item
2022-05-09 09:52:04	ga_ls9c_ard_3-2-1_095087_2022-05-09_final.stac-item
2022-05-18 09:40:34	ga_ls9c_ard_3-2-1_094074_2022-05-18_final.stac-item
2022-05-22 09:16:36	ga_ls9c_ard_3-2-1_090076_2022-05-21_final.stac-item
2022-05-31 09:10:03	ga_ls9c_ard_3-2-1_089075_2022-05-30_final.stac-item
2022-06-02 10:34:11	ga_ls9c_ard_3-2-1_103069_2022-06-02_final.stac-item
2022-06-03 09:40:33	ga_ls9c_ard_3-2-1_094074_2022-06-03_final.stac-item
2022-06-05 09:30:35	ga_ls9c_ard_3-2-1_092080_2022-06-05_final.stac-item
2022-06-05 11:09:52	ga_ls9c_ard_3-2-1_108081_2022-06-05_final.stac-item
2022-06-09 10:44:45	ga_ls9c_ard_3-2-1_104080_2022-06-09_final.stac-item
2022-06-10 09:51:56	ga_ls9c_ard_3-2-1_095087_2022-06-10_final.stac-item
2022-06-14 11:02:34	ga_ls9c_ard_3-2-1_107078_2022-06-14_final.stac-item
2022-06-15 10:04:34	ga_ls9c_ard_3-2-1_098072_2022-06-15_final.stac-item
2022-06-21 09:30:49	ga_ls9c_ard_3-2-1_092080_2022-06-21_final.stac-item
2022-06-23 10:55:25	ga_ls9c_ard_3-2-1_106075_2022-06-23_final.stac-item
2022-06-30 09:23:57	ga_ls9c_ard_3-2-1_091078_2022-06-29_final.stac-item
2022-07-01 10:03:13	ga_ls9c_ard_3-2-1_098068_2022-07-01_final.stac-item
2022-07-01 10:04:49	ga_ls9c_ard_3-2-1_098072_2022-07-01_final.stac-item
2022-07-02 10:48:29	ga_ls9c_ard_3-2-1_105073_2022-07-02_final.stac-item
2022-07-07 09:30:30	ga_ls9c_ard_3-2-1_092079_2022-07-07_final.stac-item
2022-07-18 10:48:28	ga_ls9c_ard_3-2-1_105073_2022-07-18_final.stac-item
2022-07-20 10:34:32	ga_ls9c_ard_3-2-1_103069_2022-07-20_final.stac-item
2022-07-25 09:19:04	ga_ls9c_ard_3-2-1_090081_2022-07-24_final.stac-item
2022-07-30 11:12:58	ga_ls9c_ard_3-2-1_109072_2022-07-30_final.stac-item
2022-08-03 10:48:42	ga_ls9c_ard_3-2-1_105073_2022-08-03_final.stac-item
2022-08-06 09:44:44	ga_ls9c_ard_3-2-1_094083_2022-08-06_final.stac-item
2022-08-06 11:22:49	ga_ls9c_ard_3-2-1_110081_2022-08-06_final.stac-item
2022-08-10 09:19:15	ga_ls9c_ard_3-2-1_090081_2022-08-09_final.stac-item
2022-08-12 09:07:18	ga_ls9c_ard_3-2-1_088082_2022-08-11_final.stac-item
2022-08-14 10:30:15	ga_ls9c_ard_3-2-1_102073_2022-08-14_final.stac-item
2022-08-15 09:38:38	ga_ls9c_ard_3-2-1_093083_2022-08-15_final.stac-item
2022-08-17 09:21:53	ga_ls9c_ard_3-2-1_091072_2022-08-16_final.stac-item
2022-08-17 11:03:10	ga_ls9c_ard_3-2-1_107078_2022-08-17_final.stac-item
2022-08-22 09:43:14	ga_ls9c_ard_3-2-1_094079_2022-08-22_final.stac-item
2022-08-22 11:22:55	ga_ls9c_ard_3-2-1_110081_2022-08-22_final.stac-item
2022-08-26 09:19:20	ga_ls9c_ard_3-2-1_090081_2022-08-25_final.stac-item
2022-08-26 10:56:13	ga_ls9c_ard_3-2-1_106076_2022-08-26_final.stac-item
2022-08-30 10:30:18	ga_ls9c_ard_3-2-1_102073_2022-08-30_final.stac-item
2022-08-31 09:40:16	ga_ls9c_ard_3-2-1_093087_2022-08-31_final.stac-item
2022-08-31 11:13:10	ga_ls9c_ard_3-2-1_109072_2022-08-31_final.stac-item
2022-09-25 09:34:12	ga_ls9c_ard_3-2-1_092087_2022-09-25_final.stac-item
2022-09-27 09:19:27	ga_ls9c_ard_3-2-1_090081_2022-09-26_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