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
2021-11-11 10:17:27	ga_ls9c_ard_3-2-1_100072_2021-11-11_final.stac-item
2021-11-23 11:43:05	ga_ls9c_ard_3-2-1_114074_2021-11-23_final.stac-item
2021-12-05 11:45:02	ga_ls9c_ard_3-2-1_114074_2021-12-05_final.stac-item
2021-12-07 09:58:33	ga_ls9c_ard_3-2-1_096086_2021-12-07_final.stac-item
2021-12-11 09:32:59	ga_ls9c_ard_3-2-1_092084_2021-12-11_final.stac-item
2021-12-12 11:52:20	ga_ls9c_ard_3-2-1_115077_2021-12-12_final.stac-item
2021-12-12 11:53:31	ga_ls9c_ard_3-2-1_115080_2021-12-12_final.stac-item
2021-12-18 09:40:18	ga_ls9c_ard_3-2-1_093087_2021-12-18_final.stac-item
2021-12-21 11:44:55	ga_ls9c_ard_3-2-1_114074_2021-12-21_final.stac-item
2021-12-27 09:30:09	ga_ls9c_ard_3-2-1_092077_2021-12-27_final.stac-item
2021-12-28 11:52:18	ga_ls9c_ard_3-2-1_115077_2021-12-28_final.stac-item
2021-12-28 11:53:29	ga_ls9c_ard_3-2-1_115080_2021-12-28_final.stac-item
2022-01-06 11:44:54	ga_ls9c_ard_3-2-1_114074_2022-01-06_final.stac-item
2022-01-07 09:11:11	ga_ls9c_ard_3-2-1_089076_2022-01-06_final.stac-item
2022-01-08 09:56:50	ga_ls9c_ard_3-2-1_096082_2022-01-08_final.stac-item
2022-01-13 11:52:14	ga_ls9c_ard_3-2-1_115077_2022-01-13_final.stac-item
2022-01-13 11:53:02	ga_ls9c_ard_3-2-1_115079_2022-01-13_final.stac-item
2022-01-13 11:53:26	ga_ls9c_ard_3-2-1_115080_2022-01-13_final.stac-item
2022-01-15 09:57:24	ga_ls9c_ard_3-2-1_097068_2022-01-15_final.stac-item
2022-01-23 09:13:11	ga_ls9c_ard_3-2-1_089081_2022-01-22_final.stac-item
2022-01-26 09:41:18	ga_ls9c_ard_3-2-1_094074_2022-01-26_final.stac-item
2022-01-29 10:13:00	ga_ls9c_ard_3-2-1_099076_2022-01-29_final.stac-item
2022-01-29 11:52:17	ga_ls9c_ard_3-2-1_115077_2022-01-29_final.stac-item
2022-01-29 11:53:05	ga_ls9c_ard_3-2-1_115079_2022-01-29_final.stac-item
2022-01-29 11:53:29	ga_ls9c_ard_3-2-1_115080_2022-01-29_final.stac-item
2022-01-31 11:40:43	ga_ls9c_ard_3-2-1_113079_2022-01-31_final.stac-item
2022-02-06 09:23:32	ga_ls9c_ard_3-2-1_091076_2022-02-05_final.stac-item
2022-02-07 11:44:53	ga_ls9c_ard_3-2-1_114074_2022-02-07_final.stac-item
2022-02-08 09:13:10	ga_ls9c_ard_3-2-1_089081_2022-02-07_final.stac-item
2022-02-11 09:41:15	ga_ls9c_ard_3-2-1_094074_2022-02-11_final.stac-item
2022-02-14 11:52:13	ga_ls9c_ard_3-2-1_115077_2022-02-14_final.stac-item
2022-02-14 11:53:01	ga_ls9c_ard_3-2-1_115079_2022-02-14_final.stac-item
2022-02-14 11:53:25	ga_ls9c_ard_3-2-1_115080_2022-02-14_final.stac-item
2022-02-16 11:40:38	ga_ls9c_ard_3-2-1_113079_2022-02-16_final.stac-item
2022-02-21 11:58:43	ga_ls9c_ard_3-2-1_116078_2022-02-21_final.stac-item
2022-02-22 09:23:24	ga_ls9c_ard_3-2-1_091076_2022-02-21_final.stac-item
2022-02-23 11:44:44	ga_ls9c_ard_3-2-1_114074_2022-02-23_final.stac-item
2022-03-02 11:52:49	ga_ls9c_ard_3-2-1_115079_2022-03-02_final.stac-item
2022-03-02 11:53:13	ga_ls9c_ard_3-2-1_115080_2022-03-02_final.stac-item
2022-03-04 10:01:11	ga_ls9c_ard_3-2-1_097078_2022-03-04_final.stac-item
2022-03-06 09:46:50	ga_ls9c_ard_3-2-1_095073_2022-03-06_final.stac-item
2022-03-09 11:58:37	ga_ls9c_ard_3-2-1_116078_2022-03-09_final.stac-item
2022-03-11 11:44:39	ga_ls9c_ard_3-2-1_114074_2022-03-11_final.stac-item
2022-03-29 09:52:32	ga_ls9c_ard_3-2-1_096072_2022-03-29_final.stac-item
2022-04-02 09:35:00	ga_ls9c_ard_3-2-1_092090_2022-04-02_final.stac-item
2022-04-03 11:52:45	ga_ls9c_ard_3-2-1_115079_2022-04-03_final.stac-item
2022-04-05 11:40:23	ga_ls9c_ard_3-2-1_113079_2022-04-05_final.stac-item
2022-04-06 09:07:04	ga_ls9c_ard_3-2-1_088082_2022-04-05_final.stac-item
2022-04-12 10:03:14	ga_ls9c_ard_3-2-1_098068_2022-04-12_final.stac-item
2022-04-12 10:08:49	ga_ls9c_ard_3-2-1_098082_2022-04-12_final.stac-item
2022-04-13 10:52:28	ga_ls9c_ard_3-2-1_105083_2022-04-13_final.stac-item
2022-04-20 09:16:52	ga_ls9c_ard_3-2-1_090076_2022-04-19_final.stac-item
2022-04-23 09:48:57	ga_ls9c_ard_3-2-1_095079_2022-04-23_final.stac-item
2022-04-26 11:58:20	ga_ls9c_ard_3-2-1_116078_2022-04-26_final.stac-item
2022-04-27 09:27:01	ga_ls9c_ard_3-2-1_091086_2022-04-26_final.stac-item
2022-05-05 10:12:26	ga_ls9c_ard_3-2-1_099076_2022-05-05_final.stac-item
2022-05-07 11:40:08	ga_ls9c_ard_3-2-1_113079_2022-05-07_final.stac-item
2022-05-22 09:18:36	ga_ls9c_ard_3-2-1_090081_2022-05-21_final.stac-item
2022-05-23 11:39:57	ga_ls9c_ard_3-2-1_113079_2022-05-23_final.stac-item
2022-05-25 09:47:54	ga_ls9c_ard_3-2-1_095077_2022-05-25_final.stac-item
2022-05-27 09:36:44	ga_ls9c_ard_3-2-1_093080_2022-05-27_final.stac-item
2022-06-08 10:00:42	ga_ls9c_ard_3-2-1_097078_2022-06-08_final.stac-item
2022-06-08 11:39:59	ga_ls9c_ard_3-2-1_113079_2022-06-08_final.stac-item
2022-06-15 11:44:15	ga_ls9c_ard_3-2-1_114074_2022-06-15_final.stac-item
2022-06-19 09:42:42	ga_ls9c_ard_3-2-1_094079_2022-06-19_final.stac-item
2022-06-21 09:28:01	ga_ls9c_ard_3-2-1_092073_2022-06-20_final.stac-item
2022-06-26 09:51:05	ga_ls9c_ard_3-2-1_095084_2022-06-26_final.stac-item
2022-07-01 10:06:01	ga_ls9c_ard_3-2-1_098075_2022-07-01_final.stac-item
2022-07-01 11:46:30	ga_ls9c_ard_3-2-1_114079_2022-07-01_final.stac-item
2022-07-05 09:44:28	ga_ls9c_ard_3-2-1_094083_2022-07-05_final.stac-item
2022-07-09 09:16:56	ga_ls9c_ard_3-2-1_090076_2022-07-08_final.stac-item
2022-07-10 11:40:16	ga_ls9c_ard_3-2-1_113079_2022-07-10_final.stac-item
2022-07-11 09:06:57	ga_ls9c_ard_3-2-1_088082_2022-07-10_final.stac-item
2022-07-12 09:49:01	ga_ls9c_ard_3-2-1_095079_2022-07-12_final.stac-item
2022-07-15 10:19:30	ga_ls9c_ard_3-2-1_100078_2022-07-15_final.stac-item
2022-07-17 11:46:28	ga_ls9c_ard_3-2-1_114079_2022-07-17_final.stac-item
2022-07-19 09:52:03	ga_ls9c_ard_3-2-1_096071_2022-07-19_final.stac-item
2022-07-19 09:56:27	ga_ls9c_ard_3-2-1_096082_2022-07-19_final.stac-item
2022-08-02 11:46:42	ga_ls9c_ard_3-2-1_114079_2022-08-02_final.stac-item
2022-08-03 09:13:00	ga_ls9c_ard_3-2-1_089081_2022-08-02_final.stac-item
2022-08-19 09:11:08	ga_ls9c_ard_3-2-1_089076_2022-08-18_final.stac-item
2022-08-19 09:13:08	ga_ls9c_ard_3-2-1_089081_2022-08-18_final.stac-item
2022-08-27 11:40:41	ga_ls9c_ard_3-2-1_113079_2022-08-27_final.stac-item
2022-09-03 11:46:51	ga_ls9c_ard_3-2-1_114079_2022-09-03_final.stac-item
2022-09-19 11:44:57	ga_ls9c_ard_3-2-1_114074_2022-09-19_final.stac-item
2022-09-25 09:31:00	ga_ls9c_ard_3-2-1_092079_2022-09-25_final.stac-item
2023-06-05 10:33:42	ga_ls9c_ard_3-2-1_103068_2023-06-05_final.stac-item
2023-06-05 10:34:06	ga_ls9c_ard_3-2-1_103069_2023-06-05_final.stac-item
2023-06-05 10:34:30	ga_ls9c_ard_3-2-1_103070_2023-06-05_final.stac-item
2023-06-05 10:34:54	ga_ls9c_ard_3-2-1_103071_2023-06-05_final.stac-item
2023-06-05 10:35:18	ga_ls9c_ard_3-2-1_103072_2023-06-05_final.stac-item
2023-06-05 10:35:42	ga_ls9c_ard_3-2-1_103073_2023-06-05_final.stac-item
2023-06-05 10:36:06	ga_ls9c_ard_3-2-1_103074_2023-06-05_final.stac-item
2023-06-05 10:36:29	ga_ls9c_ard_3-2-1_103075_2023-06-05_final.stac-item
2023-06-05 10:36:53	ga_ls9c_ard_3-2-1_103076_2023-06-05_final.stac-item
2023-06-05 10:37:17	ga_ls9c_ard_3-2-1_103077_2023-06-05_final.stac-item
2023-06-05 10:37:41	ga_ls9c_ard_3-2-1_103078_2023-06-05_final.stac-item
2023-06-05 10:38:05	ga_ls9c_ard_3-2-1_103079_2023-06-05_final.stac-item
2023-06-05 10:38:29	ga_ls9c_ard_3-2-1_103080_2023-06-05_final.stac-item
2023-06-05 10:38:53	ga_ls9c_ard_3-2-1_103081_2023-06-05_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years