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
2021-11-13 10:03:05	ga_ls9c_ard_3-2-1_097083_2021-11-13_final.stac-item
2021-11-13 11:41:21	ga_ls9c_ard_3-2-1_113082_2021-11-13_final.stac-item
2021-11-16 10:23:06	ga_ls9c_ard_3-2-1_100080_2021-11-16_final.stac-item
2021-11-17 09:23:16	ga_ls9c_ard_3-2-1_091077_2021-11-16_final.stac-item
2021-11-18 10:03:10	ga_ls9c_ard_3-2-1_097077_2021-11-18_final.stac-item
2021-12-11 11:06:41	ga_ls9c_ard_3-2-1_108071_2021-12-11_final.stac-item
2021-12-18 11:13:36	ga_ls9c_ard_3-2-1_109073_2021-12-18_final.stac-item
2021-12-23 09:52:28	ga_ls9c_ard_3-2-1_096071_2021-12-23_final.stac-item
2021-12-30 09:58:39	ga_ls9c_ard_3-2-1_097071_2021-12-30_final.stac-item
2021-12-30 09:59:51	ga_ls9c_ard_3-2-1_097074_2021-12-30_final.stac-item
2022-01-02 10:31:56	ga_ls9c_ard_3-2-1_102077_2022-01-02_final.stac-item
2022-01-10 11:18:10	ga_ls9c_ard_3-2-1_110069_2022-01-10_final.stac-item
2022-01-17 09:47:27	ga_ls9c_ard_3-2-1_095074_2022-01-17_final.stac-item
2022-01-18 10:28:43	ga_ls9c_ard_3-2-1_102069_2022-01-18_final.stac-item
2022-01-29 11:52:41	ga_ls9c_ard_3-2-1_115078_2022-01-29_final.stac-item
2022-02-07 11:46:05	ga_ls9c_ard_3-2-1_114077_2022-02-07_final.stac-item
2022-02-11 11:22:56	ga_ls9c_ard_3-2-1_110081_2022-02-11_final.stac-item
2022-03-10 09:26:30	ga_ls9c_ard_3-2-1_091084_2022-03-09_final.stac-item
2022-03-30 10:34:36	ga_ls9c_ard_3-2-1_103069_2022-03-30_final.stac-item
2022-03-31 09:40:58	ga_ls9c_ard_3-2-1_094074_2022-03-31_final.stac-item
2022-04-18 11:10:56	ga_ls9c_ard_3-2-1_108083_2022-04-18_final.stac-item
2022-04-22 10:44:58	ga_ls9c_ard_3-2-1_104080_2022-04-22_final.stac-item
2022-04-27 11:01:55	ga_ls9c_ard_3-2-1_107076_2022-04-27_final.stac-item
2022-05-02 09:42:21	ga_ls9c_ard_3-2-1_094078_2022-05-02_final.stac-item
2022-05-02 11:20:50	ga_ls9c_ard_3-2-1_110077_2022-05-02_final.stac-item
2022-05-21 10:15:25	ga_ls9c_ard_3-2-1_099084_2022-05-21_final.stac-item
2022-06-09 09:05:52	ga_ls9c_ard_3-2-1_088080_2022-06-08_final.stac-item
2022-06-21 11:06:55	ga_ls9c_ard_3-2-1_108073_2022-06-21_final.stac-item
2022-06-23 10:53:25	ga_ls9c_ard_3-2-1_106070_2022-06-23_final.stac-item
2022-06-27 10:30:45	ga_ls9c_ard_3-2-1_102075_2022-06-27_final.stac-item
2022-07-03 11:34:56	ga_ls9c_ard_3-2-1_112081_2022-07-03_final.stac-item
2022-07-10 11:37:29	ga_ls9c_ard_3-2-1_113072_2022-07-10_final.stac-item
2022-07-24 11:51:58	ga_ls9c_ard_3-2-1_115077_2022-07-24_final.stac-item
2022-07-27 10:40:26	ga_ls9c_ard_3-2-1_104068_2022-07-27_final.stac-item
2022-08-21 10:35:16	ga_ls9c_ard_3-2-1_103070_2022-08-21_final.stac-item
2022-08-22 09:45:14	ga_ls9c_ard_3-2-1_094084_2022-08-22_final.stac-item
2022-09-03 10:04:23	ga_ls9c_ard_3-2-1_098070_2022-09-03_final.stac-item
2022-09-05 09:57:12	ga_ls9c_ard_3-2-1_096083_2022-09-05_final.stac-item
2022-09-18 09:23:59	ga_ls9c_ard_3-2-1_091077_2022-09-17_final.stac-item
2022-09-21 11:34:36	ga_ls9c_ard_3-2-1_112079_2022-09-21_final.stac-item
2022-09-28 11:42:24	ga_ls9c_ard_3-2-1_113083_2022-09-28_final.stac-item
2022-10-04 09:25:38	ga_ls9c_ard_3-2-1_091081_2022-10-03_final.stac-item
2022-10-09 09:43:24	ga_ls9c_ard_3-2-1_094079_2022-10-09_final.stac-item
2022-10-11 09:35:03	ga_ls9c_ard_3-2-1_092089_2022-10-11_final.stac-item
2022-10-15 09:06:46	ga_ls9c_ard_3-2-1_088080_2022-10-14_final.stac-item
2022-10-19 10:18:57	ga_ls9c_ard_3-2-1_100075_2022-10-19_final.stac-item
2022-10-23 11:34:19	ga_ls9c_ard_3-2-1_112078_2022-10-23_final.stac-item
2022-10-29 09:19:56	ga_ls9c_ard_3-2-1_090082_2022-10-28_final.stac-item
2022-10-29 10:54:50	ga_ls9c_ard_3-2-1_106072_2022-10-29_final.stac-item
2022-11-01 09:48:25	ga_ls9c_ard_3-2-1_095076_2022-11-01_final.stac-item
2022-12-10 09:55:50	ga_ls9c_ard_3-2-1_096079_2022-12-10_final.stac-item
2022-12-14 11:09:59	ga_ls9c_ard_3-2-1_108079_2022-12-14_final.stac-item
2022-12-28 09:46:14	ga_ls9c_ard_3-2-1_094086_2022-12-28_final.stac-item
2023-01-01 09:20:20	ga_ls9c_ard_3-2-1_090083_2022-12-31_final.stac-item
2023-01-10 09:13:45	ga_ls9c_ard_3-2-1_089082_2023-01-09_final.stac-item
2023-01-12 10:35:28	ga_ls9c_ard_3-2-1_103070_2023-01-12_final.stac-item
2023-01-13 09:46:13	ga_ls9c_ard_3-2-1_094086_2023-01-13_final.stac-item
2023-01-13 11:19:07	ga_ls9c_ard_3-2-1_110071_2023-01-13_final.stac-item
2023-01-25 11:45:24	ga_ls9c_ard_3-2-1_114075_2023-01-25_final.stac-item
2023-02-19 10:02:44	ga_ls9c_ard_3-2-1_097081_2023-02-19_final.stac-item
2023-02-23 09:40:19	ga_ls9c_ard_3-2-1_093087_2023-02-23_final.stac-item
2023-02-24 10:19:58	ga_ls9c_ard_3-2-1_100078_2023-02-24_final.stac-item
2023-03-10 10:29:24	ga_ls9c_ard_3-2-1_102071_2023-03-10_final.stac-item
2023-04-02 10:39:00	ga_ls9c_ard_3-2-1_103080_2023-04-02_final.stac-item
2023-04-05 11:05:30	ga_ls9c_ard_3-2-1_108069_2023-04-05_final.stac-item
2023-04-10 09:49:54	ga_ls9c_ard_3-2-1_095081_2023-04-10_final.stac-item
2023-04-15 10:04:47	ga_ls9c_ard_3-2-1_098072_2023-04-15_final.stac-item
2023-04-18 10:38:29	ga_ls9c_ard_3-2-1_103079_2023-04-18_final.stac-item
2023-04-24 09:59:23	ga_ls9c_ard_3-2-1_097074_2023-04-24_final.stac-item
2023-04-27 10:29:03	ga_ls9c_ard_3-2-1_102071_2023-04-27_final.stac-item
2023-04-28 09:37:01	ga_ls9c_ard_3-2-1_093080_2023-04-28_final.stac-item
2023-05-25 10:56:39	ga_ls9c_ard_3-2-1_106079_2023-05-25_final.stac-item
2023-06-07 10:24:31	ga_ls9c_ard_3-2-1_101076_2023-06-07_final.stac-item
2023-06-08 11:07:46	ga_ls9c_ard_3-2-1_108076_2023-06-08_final.stac-item
2023-06-17 11:00:17	ga_ls9c_ard_3-2-1_107073_2023-06-17_final.stac-item
2023-06-18 10:09:27	ga_ls9c_ard_3-2-1_098085_2023-06-18_final.stac-item
2023-06-24 09:33:58	ga_ls9c_ard_3-2-1_092089_2023-06-24_final.stac-item
2023-06-26 10:53:43	ga_ls9c_ard_3-2-1_106072_2023-06-26_final.stac-item
2023-07-02 11:58:04	ga_ls9c_ard_3-2-1_116078_2023-07-02_final.stac-item
2023-07-10 09:27:26	ga_ls9c_ard_3-2-1_092072_2023-07-09_final.stac-item
2023-07-10 11:05:08	ga_ls9c_ard_3-2-1_108069_2023-07-10_final.stac-item
2023-09-26 09:40:38	ga_ls9c_ard_3-2-1_094073_2023-09-26_final.stac-item
2023-09-26 11:23:07	ga_ls9c_ard_3-2-1_110082_2023-09-26_final.stac-item
2023-10-06 11:58:42	ga_ls9c_ard_3-2-1_116078_2023-10-06_final.stac-item
2023-10-07 09:21:48	ga_ls9c_ard_3-2-1_091072_2023-10-06_final.stac-item
2023-10-08 10:08:16	ga_ls9c_ard_3-2-1_098080_2023-10-08_final.stac-item
2023-10-17 11:41:05	ga_ls9c_ard_3-2-1_113080_2023-10-17_final.stac-item
2023-10-24 10:08:22	ga_ls9c_ard_3-2-1_098080_2023-10-24_final.stac-item
2023-10-31 10:09:18	ga_ls9c_ard_3-2-1_099067_2023-10-31_final.stac-item
2023-11-01 09:19:14	ga_ls9c_ard_3-2-1_090081_2023-10-31_final.stac-item
2023-11-09 11:46:24	ga_ls9c_ard_3-2-1_114078_2023-11-09_final.stac-item
2023-11-16 10:10:54	ga_ls9c_ard_3-2-1_099071_2023-11-16_final.stac-item
2023-11-18 11:41:03	ga_ls9c_ard_3-2-1_113080_2023-11-18_final.stac-item
2023-11-22 11:17:11	ga_ls9c_ard_3-2-1_109082_2023-11-22_final.stac-item
2023-12-03 10:57:52	ga_ls9c_ard_3-2-1_106080_2023-12-03_final.stac-item
2023-12-06 11:25:08	ga_ls9c_ard_3-2-1_111071_2023-12-06_final.stac-item
2023-12-10 09:28:43	ga_ls9c_ard_3-2-1_091089_2023-12-09_final.stac-item
2023-12-15 09:43:43	ga_ls9c_ard_3-2-1_094080_2023-12-15_final.stac-item
2023-12-16 10:27:24	ga_ls9c_ard_3-2-1_101081_2023-12-16_final.stac-item
2023-12-31 11:21:00	ga_ls9c_ard_3-2-1_110076_2023-12-31_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