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
2021-11-10 09:43:28	ga_ls9c_ard_3-2-1_094087_2021-11-10_final.stac-item
2021-11-25 09:48:27	ga_ls9c_ard_3-2-1_095081_2021-11-25_final.stac-item
2022-01-08 11:36:07	ga_ls9c_ard_3-2-1_112083_2022-01-08_final.stac-item
2022-01-15 11:42:16	ga_ls9c_ard_3-2-1_113083_2022-01-15_final.stac-item
2022-01-29 10:15:23	ga_ls9c_ard_3-2-1_099082_2022-01-29_final.stac-item
2022-02-01 09:07:48	ga_ls9c_ard_3-2-1_088083_2022-01-31_final.stac-item
2022-02-03 10:31:08	ga_ls9c_ard_3-2-1_102075_2022-02-03_final.stac-item
2022-02-04 09:37:06	ga_ls9c_ard_3-2-1_093079_2022-02-04_final.stac-item
2022-02-27 09:45:04	ga_ls9c_ard_3-2-1_094084_2022-02-27_final.stac-item
2022-03-22 09:49:59	ga_ls9c_ard_3-2-1_095081_2022-03-22_final.stac-item
2022-03-27 10:08:05	ga_ls9c_ard_3-2-1_098080_2022-03-27_final.stac-item
2022-04-05 11:37:35	ga_ls9c_ard_3-2-1_113072_2022-04-05_final.stac-item
2022-04-10 10:18:24	ga_ls9c_ard_3-2-1_100075_2022-04-10_final.stac-item
2022-04-21 09:58:55	ga_ls9c_ard_3-2-1_097073_2022-04-21_final.stac-item
2022-04-25 11:12:41	ga_ls9c_ard_3-2-1_109072_2022-04-25_final.stac-item
2022-04-25 11:17:04	ga_ls9c_ard_3-2-1_109083_2022-04-25_final.stac-item
2022-05-07 09:58:27	ga_ls9c_ard_3-2-1_097072_2022-05-07_final.stac-item
2022-05-15 09:15:42	ga_ls9c_ard_3-2-1_089089_2022-05-14_final.stac-item
2022-05-23 10:00:40	ga_ls9c_ard_3-2-1_097078_2022-05-23_final.stac-item
2022-05-24 09:06:15	ga_ls9c_ard_3-2-1_088081_2022-05-23_final.stac-item
2022-05-25 09:50:18	ga_ls9c_ard_3-2-1_095083_2022-05-25_final.stac-item
2022-05-27 11:16:49	ga_ls9c_ard_3-2-1_109083_2022-05-27_final.stac-item
2022-06-10 11:24:50	ga_ls9c_ard_3-2-1_111072_2022-06-10_final.stac-item
2022-06-12 09:34:25	ga_ls9c_ard_3-2-1_093074_2022-06-12_final.stac-item
2022-06-12 11:14:30	ga_ls9c_ard_3-2-1_109077_2022-06-12_final.stac-item
2022-07-09 09:20:32	ga_ls9c_ard_3-2-1_090085_2022-07-08_final.stac-item
2022-07-16 09:25:29	ga_ls9c_ard_3-2-1_091082_2022-07-15_final.stac-item
2022-07-20 10:38:08	ga_ls9c_ard_3-2-1_103078_2022-07-20_final.stac-item
2022-07-29 10:31:41	ga_ls9c_ard_3-2-1_102077_2022-07-29_final.stac-item
2022-08-02 10:05:01	ga_ls9c_ard_3-2-1_098072_2022-08-02_final.stac-item
2022-08-10 09:21:39	ga_ls9c_ard_3-2-1_090087_2022-08-09_final.stac-item
2022-08-17 11:02:22	ga_ls9c_ard_3-2-1_107076_2022-08-17_final.stac-item
2022-08-26 10:57:49	ga_ls9c_ard_3-2-1_106080_2022-08-26_final.stac-item
2022-09-05 11:33:18	ga_ls9c_ard_3-2-1_112076_2022-09-05_final.stac-item
2022-09-25 11:06:42	ga_ls9c_ard_3-2-1_108071_2022-09-25_final.stac-item
2022-09-28 10:01:31	ga_ls9c_ard_3-2-1_097078_2022-09-28_final.stac-item
2022-10-05 10:09:17	ga_ls9c_ard_3-2-1_098082_2022-10-05_final.stac-item
2022-10-09 09:44:11	ga_ls9c_ard_3-2-1_094081_2022-10-09_final.stac-item
2022-10-12 10:13:08	ga_ls9c_ard_3-2-1_099076_2022-10-12_final.stac-item
2022-10-15 10:41:40	ga_ls9c_ard_3-2-1_104070_2022-10-15_final.stac-item
2022-10-17 10:30:54	ga_ls9c_ard_3-2-1_102074_2022-10-17_final.stac-item
2022-11-02 10:28:53	ga_ls9c_ard_3-2-1_102069_2022-11-02_final.stac-item
2022-11-03 11:12:08	ga_ls9c_ard_3-2-1_109069_2022-11-03_final.stac-item
2022-11-10 11:23:57	ga_ls9c_ard_3-2-1_110083_2022-11-10_final.stac-item
2022-11-11 10:24:21	ga_ls9c_ard_3-2-1_101073_2022-11-11_final.stac-item
2022-11-30 09:19:55	ga_ls9c_ard_3-2-1_090082_2022-11-29_final.stac-item
2022-12-06 10:22:32	ga_ls9c_ard_3-2-1_100084_2022-12-06_final.stac-item
2022-12-17 11:39:17	ga_ls9c_ard_3-2-1_113075_2022-12-17_final.stac-item
2022-12-17 11:42:29	ga_ls9c_ard_3-2-1_113083_2022-12-17_final.stac-item
2022-12-20 10:30:05	ga_ls9c_ard_3-2-1_102072_2022-12-20_final.stac-item
2023-01-02 11:42:29	ga_ls9c_ard_3-2-1_113083_2023-01-02_final.stac-item
2023-01-25 11:45:00	ga_ls9c_ard_3-2-1_114074_2023-01-25_final.stac-item
2023-02-07 09:38:33	ga_ls9c_ard_3-2-1_093082_2023-02-07_final.stac-item
2023-02-07 11:13:50	ga_ls9c_ard_3-2-1_109073_2023-02-07_final.stac-item
2023-02-07 11:17:02	ga_ls9c_ard_3-2-1_109081_2023-02-07_final.stac-item
2023-02-08 10:21:48	ga_ls9c_ard_3-2-1_100082_2023-02-08_final.stac-item
2023-02-11 09:14:13	ga_ls9c_ard_3-2-1_089083_2023-02-10_final.stac-item
2023-03-04 11:10:58	ga_ls9c_ard_3-2-1_108082_2023-03-04_final.stac-item
2023-03-06 09:20:30	ga_ls9c_ard_3-2-1_090084_2023-03-05_final.stac-item
2023-03-07 11:41:26	ga_ls9c_ard_3-2-1_113081_2023-03-07_final.stac-item
2023-03-09 11:27:01	ga_ls9c_ard_3-2-1_111076_2023-03-09_final.stac-item
2023-03-17 10:36:47	ga_ls9c_ard_3-2-1_103074_2023-03-17_final.stac-item
2023-03-25 09:46:04	ga_ls9c_ard_3-2-1_095071_2023-03-25_final.stac-item
2023-03-25 09:51:15	ga_ls9c_ard_3-2-1_095084_2023-03-25_final.stac-item
2023-04-03 11:22:39	ga_ls9c_ard_3-2-1_110081_2023-04-03_final.stac-item
2023-04-25 10:40:39	ga_ls9c_ard_3-2-1_104069_2023-04-25_final.stac-item
2023-04-29 10:21:03	ga_ls9c_ard_3-2-1_100082_2023-04-29_final.stac-item
2023-05-10 09:58:01	ga_ls9c_ard_3-2-1_097071_2023-05-10_final.stac-item
2023-05-12 09:46:50	ga_ls9c_ard_3-2-1_095074_2023-05-12_final.stac-item
2023-05-18 09:12:30	ga_ls9c_ard_3-2-1_089081_2023-05-17_final.stac-item
2023-05-24 10:14:36	ga_ls9c_ard_3-2-1_099082_2023-05-24_final.stac-item
2023-05-26 10:01:26	ga_ls9c_ard_3-2-1_097080_2023-05-26_final.stac-item
2023-06-01 11:02:02	ga_ls9c_ard_3-2-1_107077_2023-06-01_final.stac-item
2023-06-04 11:35:19	ga_ls9c_ard_3-2-1_112083_2023-06-04_final.stac-item
2023-06-05 10:34:30	ga_ls9c_ard_3-2-1_103070_2023-06-05_final.stac-item
2023-06-10 09:19:41	ga_ls9c_ard_3-2-1_090084_2023-06-09_final.stac-item
2023-06-13 09:46:33	ga_ls9c_ard_3-2-1_095074_2023-06-13_final.stac-item
2023-06-17 11:00:17	ga_ls9c_ard_3-2-1_107073_2023-06-17_final.stac-item
2023-06-24 09:28:23	ga_ls9c_ard_3-2-1_092075_2023-06-23_final.stac-item
2023-06-27 10:00:31	ga_ls9c_ard_3-2-1_097078_2023-06-27_final.stac-item
2023-07-04 10:09:39	ga_ls9c_ard_3-2-1_098085_2023-07-04_final.stac-item
2023-07-08 11:18:16	ga_ls9c_ard_3-2-1_110071_2023-07-08_final.stac-item
2023-07-10 09:29:02	ga_ls9c_ard_3-2-1_092076_2023-07-09_final.stac-item
2023-07-15 11:29:17	ga_ls9c_ard_3-2-1_111083_2023-07-15_final.stac-item
2023-07-19 09:23:17	ga_ls9c_ard_3-2-1_091077_2023-07-18_final.stac-item
2023-07-21 09:12:55	ga_ls9c_ard_3-2-1_089082_2023-07-20_final.stac-item
2023-08-10 10:24:51	ga_ls9c_ard_3-2-1_101076_2023-08-10_final.stac-item
2023-08-16 09:47:22	ga_ls9c_ard_3-2-1_095075_2023-08-16_final.stac-item
2023-08-16 09:49:22	ga_ls9c_ard_3-2-1_095080_2023-08-16_final.stac-item
2023-08-27 11:05:27	ga_ls9c_ard_3-2-1_108069_2023-08-27_final.stac-item
2023-08-31 10:40:22	ga_ls9c_ard_3-2-1_104068_2023-08-31_final.stac-item
2023-09-19 11:12:12	ga_ls9c_ard_3-2-1_109070_2023-09-19_final.stac-item
2023-09-21 11:05:01	ga_ls9c_ard_3-2-1_107083_2023-09-21_final.stac-item
2023-10-20 10:30:43	ga_ls9c_ard_3-2-1_102074_2023-10-20_final.stac-item
2023-10-23 11:03:12	ga_ls9c_ard_3-2-1_107078_2023-10-23_final.stac-item
2023-10-25 10:50:26	ga_ls9c_ard_3-2-1_105077_2023-10-25_final.stac-item
2023-11-10 10:50:23	ga_ls9c_ard_3-2-1_105077_2023-11-10_final.stac-item
2023-11-25 10:08:02	ga_ls9c_ard_3-2-1_098079_2023-11-25_final.stac-item
2024-01-05 11:41:04	ga_ls9c_ard_3-2-1_113080_2024-01-05_final.stac-item
2024-01-09 09:39:29	ga_ls9c_ard_3-2-1_093085_2024-01-09_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