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
2021-11-22 09:25:16	ga_ls9c_ard_3-2-1_091076_2021-11-21_final.stac-item
2021-12-04 11:02:10	ga_ls9c_ard_3-2-1_107075_2021-12-04_final.stac-item
2021-12-12 10:14:14	ga_ls9c_ard_3-2-1_099079_2021-12-12_final.stac-item
2021-12-17 10:29:08	ga_ls9c_ard_3-2-1_102070_2021-12-17_final.stac-item
2021-12-28 10:14:12	ga_ls9c_ard_3-2-1_099079_2021-12-28_final.stac-item
2022-01-02 10:29:09	ga_ls9c_ard_3-2-1_102070_2022-01-02_final.stac-item
2022-01-03 09:39:31	ga_ls9c_ard_3-2-1_093085_2022-01-03_final.stac-item
2022-01-10 11:20:09	ga_ls9c_ard_3-2-1_110074_2022-01-10_final.stac-item
2022-01-12 09:33:17	ga_ls9c_ard_3-2-1_092085_2022-01-12_final.stac-item
2022-01-20 10:18:46	ga_ls9c_ard_3-2-1_100075_2022-01-20_final.stac-item
2022-02-01 10:41:54	ga_ls9c_ard_3-2-1_104071_2022-02-01_final.stac-item
2022-02-06 11:05:13	ga_ls9c_ard_3-2-1_107083_2022-02-06_final.stac-item
2022-02-14 10:14:32	ga_ls9c_ard_3-2-1_099080_2022-02-14_final.stac-item
2022-02-17 09:06:55	ga_ls9c_ard_3-2-1_088081_2022-02-16_final.stac-item
2022-02-20 09:40:11	ga_ls9c_ard_3-2-1_093087_2022-02-20_final.stac-item
2022-02-22 11:00:17	ga_ls9c_ard_3-2-1_107071_2022-02-22_final.stac-item
2022-02-23 10:09:27	ga_ls9c_ard_3-2-1_098083_2022-02-23_final.stac-item
2022-03-06 11:24:55	ga_ls9c_ard_3-2-1_111071_2022-03-06_final.stac-item
2022-03-11 10:09:22	ga_ls9c_ard_3-2-1_098083_2022-03-11_final.stac-item
2022-03-31 09:40:34	ga_ls9c_ard_3-2-1_094073_2022-03-31_final.stac-item
2022-04-13 09:11:59	ga_ls9c_ard_3-2-1_089079_2022-04-12_final.stac-item
2022-04-27 09:27:01	ga_ls9c_ard_3-2-1_091086_2022-04-26_final.stac-item
2022-05-03 10:25:36	ga_ls9c_ard_3-2-1_101078_2022-05-03_final.stac-item
2022-05-05 11:52:55	ga_ls9c_ard_3-2-1_115080_2022-05-05_final.stac-item
2022-05-19 10:27:00	ga_ls9c_ard_3-2-1_101082_2022-05-19_final.stac-item
2022-05-21 10:09:02	ga_ls9c_ard_3-2-1_099068_2022-05-21_final.stac-item
2022-05-25 09:45:55	ga_ls9c_ard_3-2-1_095072_2022-05-25_final.stac-item
2022-06-08 11:39:11	ga_ls9c_ard_3-2-1_113077_2022-06-08_final.stac-item
2022-06-24 11:41:06	ga_ls9c_ard_3-2-1_113081_2022-06-24_final.stac-item
2022-07-05 09:45:40	ga_ls9c_ard_3-2-1_094086_2022-07-05_final.stac-item
2022-07-09 10:57:25	ga_ls9c_ard_3-2-1_106080_2022-07-09_final.stac-item
2022-07-17 10:07:10	ga_ls9c_ard_3-2-1_098078_2022-07-17_final.stac-item
2022-07-18 09:13:10	ga_ls9c_ard_3-2-1_089082_2022-07-17_final.stac-item
2022-07-30 11:13:22	ga_ls9c_ard_3-2-1_109073_2022-07-30_final.stac-item
2022-08-02 10:04:37	ga_ls9c_ard_3-2-1_098071_2022-08-02_final.stac-item
2022-08-19 10:46:26	ga_ls9c_ard_3-2-1_105067_2022-08-19_final.stac-item
2022-09-01 10:21:56	ga_ls9c_ard_3-2-1_100083_2022-09-01_final.stac-item
2022-09-11 10:53:50	ga_ls9c_ard_3-2-1_106070_2022-09-11_final.stac-item
2022-09-18 11:00:05	ga_ls9c_ard_3-2-1_107070_2022-09-18_final.stac-item
2022-09-26 10:10:41	ga_ls9c_ard_3-2-1_099070_2022-09-26_final.stac-item
2022-10-09 09:44:35	ga_ls9c_ard_3-2-1_094082_2022-10-09_final.stac-item
2022-10-13 10:56:24	ga_ls9c_ard_3-2-1_106076_2022-10-13_final.stac-item
2022-10-29 10:55:14	ga_ls9c_ard_3-2-1_106073_2022-10-29_final.stac-item
2022-11-03 09:34:03	ga_ls9c_ard_3-2-1_093071_2022-11-03_final.stac-item
2022-11-13 10:10:48	ga_ls9c_ard_3-2-1_099070_2022-11-13_final.stac-item
2022-11-13 11:53:40	ga_ls9c_ard_3-2-1_115080_2022-11-13_final.stac-item
2022-11-14 09:21:34	ga_ls9c_ard_3-2-1_090086_2022-11-13_final.stac-item
2022-11-14 10:55:39	ga_ls9c_ard_3-2-1_106074_2022-11-14_final.stac-item
2022-11-18 10:28:33	ga_ls9c_ard_3-2-1_102068_2022-11-18_final.stac-item
2022-11-19 09:35:43	ga_ls9c_ard_3-2-1_093075_2022-11-19_final.stac-item
2022-11-24 09:57:50	ga_ls9c_ard_3-2-1_096084_2022-11-24_final.stac-item
2022-11-26 09:46:39	ga_ls9c_ard_3-2-1_094087_2022-11-26_final.stac-item
2022-11-28 11:05:59	ga_ls9c_ard_3-2-1_108069_2022-11-28_final.stac-item
2022-11-28 11:08:46	ga_ls9c_ard_3-2-1_108076_2022-11-28_final.stac-item
2022-12-05 09:35:40	ga_ls9c_ard_3-2-1_093075_2022-12-05_final.stac-item
2022-12-05 11:12:09	ga_ls9c_ard_3-2-1_109069_2022-12-05_final.stac-item
2022-12-14 09:29:31	ga_ls9c_ard_3-2-1_092075_2022-12-13_final.stac-item
2022-12-17 09:58:00	ga_ls9c_ard_3-2-1_097069_2022-12-17_final.stac-item
2022-12-20 10:34:05	ga_ls9c_ard_3-2-1_102082_2022-12-20_final.stac-item
2022-12-21 09:35:15	ga_ls9c_ard_3-2-1_093074_2022-12-21_final.stac-item
2022-12-22 10:21:18	ga_ls9c_ard_3-2-1_100081_2022-12-22_final.stac-item
2022-12-25 09:12:07	ga_ls9c_ard_3-2-1_089078_2022-12-24_final.stac-item
2022-12-26 09:52:36	ga_ls9c_ard_3-2-1_096071_2022-12-26_final.stac-item
2023-01-07 11:58:14	ga_ls9c_ard_3-2-1_116076_2023-01-07_final.stac-item
2023-01-08 11:00:13	ga_ls9c_ard_3-2-1_107070_2023-01-08_final.stac-item
2023-01-23 11:58:31	ga_ls9c_ard_3-2-1_116077_2023-01-23_final.stac-item
2023-01-23 11:58:55	ga_ls9c_ard_3-2-1_116078_2023-01-23_final.stac-item
2023-01-24 09:27:13	ga_ls9c_ard_3-2-1_091085_2023-01-23_final.stac-item
2023-01-24 09:28:01	ga_ls9c_ard_3-2-1_091087_2023-01-23_final.stac-item
2023-01-24 11:05:42	ga_ls9c_ard_3-2-1_107084_2023-01-24_final.stac-item
2023-01-31 09:33:30	ga_ls9c_ard_3-2-1_092085_2023-01-31_final.stac-item
2023-02-01 11:53:40	ga_ls9c_ard_3-2-1_115080_2023-02-01_final.stac-item
2023-02-26 11:44:54	ga_ls9c_ard_3-2-1_114074_2023-02-26_final.stac-item
2023-03-26 10:28:06	ga_ls9c_ard_3-2-1_102068_2023-03-26_final.stac-item
2023-03-26 10:28:54	ga_ls9c_ard_3-2-1_102070_2023-03-26_final.stac-item
2023-03-28 10:22:05	ga_ls9c_ard_3-2-1_100084_2023-03-28_final.stac-item
2023-03-31 09:13:16	ga_ls9c_ard_3-2-1_089082_2023-03-30_final.stac-item
2023-04-03 11:23:27	ga_ls9c_ard_3-2-1_110083_2023-04-03_final.stac-item
2023-04-07 10:55:07	ga_ls9c_ard_3-2-1_106074_2023-04-07_final.stac-item
2023-04-12 11:12:49	ga_ls9c_ard_3-2-1_109072_2023-04-12_final.stac-item
2023-04-23 10:55:49	ga_ls9c_ard_3-2-1_106076_2023-04-23_final.stac-item
2023-05-01 10:07:03	ga_ls9c_ard_3-2-1_098078_2023-05-01_final.stac-item
2023-05-03 09:51:52	ga_ls9c_ard_3-2-1_096071_2023-05-03_final.stac-item
2023-05-14 09:39:39	ga_ls9c_ard_3-2-1_093087_2023-05-14_final.stac-item
2023-05-17 10:03:20	ga_ls9c_ard_3-2-1_098069_2023-05-17_final.stac-item
2023-05-30 11:15:36	ga_ls9c_ard_3-2-1_109080_2023-05-30_final.stac-item
2023-06-26 09:16:01	ga_ls9c_ard_3-2-1_090075_2023-06-25_final.stac-item
2023-07-19 09:28:04	ga_ls9c_ard_3-2-1_091089_2023-07-18_final.stac-item
2023-07-27 10:13:08	ga_ls9c_ard_3-2-1_099078_2023-07-27_final.stac-item
2023-07-29 11:40:54	ga_ls9c_ard_3-2-1_113081_2023-07-29_final.stac-item
2023-07-31 11:24:58	ga_ls9c_ard_3-2-1_111072_2023-07-31_final.stac-item
2023-08-03 10:17:02	ga_ls9c_ard_3-2-1_100072_2023-08-03_final.stac-item
2023-08-11 11:08:07	ga_ls9c_ard_3-2-1_108076_2023-08-11_final.stac-item
2023-08-16 11:24:39	ga_ls9c_ard_3-2-1_111071_2023-08-16_final.stac-item
2023-10-23 09:28:43	ga_ls9c_ard_3-2-1_091089_2023-10-22_final.stac-item
2023-10-23 11:00:25	ga_ls9c_ard_3-2-1_107071_2023-10-23_final.stac-item
2023-10-25 10:48:50	ga_ls9c_ard_3-2-1_105073_2023-10-25_final.stac-item
2023-11-17 09:22:29	ga_ls9c_ard_3-2-1_090089_2023-11-16_final.stac-item
2023-11-17 10:53:47	ga_ls9c_ard_3-2-1_106070_2023-11-17_final.stac-item
2023-11-20 09:47:03	ga_ls9c_ard_3-2-1_095073_2023-11-20_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