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 09:17:23	ga_ls9c_ard_3-2-1_090081_2021-11-01_final.stac-item
2021-11-02 10:54:51	ga_ls9c_ard_3-2-1_106078_2021-11-02_final.stac-item
2021-11-17 09:24:52	ga_ls9c_ard_3-2-1_091081_2021-11-16_final.stac-item
2021-12-06 10:52:59	ga_ls9c_ard_3-2-1_105083_2021-12-06_final.stac-item
2021-12-07 09:52:34	ga_ls9c_ard_3-2-1_096071_2021-12-07_final.stac-item
2021-12-12 11:51:32	ga_ls9c_ard_3-2-1_115075_2021-12-12_final.stac-item
2021-12-21 10:04:02	ga_ls9c_ard_3-2-1_098069_2021-12-21_final.stac-item
2021-12-27 11:06:38	ga_ls9c_ard_3-2-1_108071_2021-12-27_final.stac-item
2022-01-03 11:13:36	ga_ls9c_ard_3-2-1_109073_2022-01-03_final.stac-item
2022-01-03 11:14:00	ga_ls9c_ard_3-2-1_109074_2022-01-03_final.stac-item
2022-01-05 11:00:26	ga_ls9c_ard_3-2-1_107071_2022-01-05_final.stac-item
2022-01-21 09:27:56	ga_ls9c_ard_3-2-1_091087_2022-01-20_final.stac-item
2022-01-29 11:51:29	ga_ls9c_ard_3-2-1_115075_2022-01-29_final.stac-item
2022-01-31 11:38:43	ga_ls9c_ard_3-2-1_113074_2022-01-31_final.stac-item
2022-02-02 09:50:40	ga_ls9c_ard_3-2-1_095082_2022-02-02_final.stac-item
2022-02-03 10:29:32	ga_ls9c_ard_3-2-1_102071_2022-02-03_final.stac-item
2022-02-12 10:28:06	ga_ls9c_ard_3-2-1_101083_2022-02-12_final.stac-item
2022-02-13 11:06:58	ga_ls9c_ard_3-2-1_108072_2022-02-13_final.stac-item
2022-02-14 10:14:08	ga_ls9c_ard_3-2-1_099079_2022-02-14_final.stac-item
2022-04-21 10:03:43	ga_ls9c_ard_3-2-1_097085_2022-04-21_final.stac-item
2022-04-23 09:51:45	ga_ls9c_ard_3-2-1_095086_2022-04-23_final.stac-item
2022-05-21 11:52:43	ga_ls9c_ard_3-2-1_115080_2022-05-21_final.stac-item
2022-05-28 11:58:06	ga_ls9c_ard_3-2-1_116078_2022-05-28_final.stac-item
2022-05-31 10:46:32	ga_ls9c_ard_3-2-1_105069_2022-05-31_final.stac-item
2022-06-07 10:57:55	ga_ls9c_ard_3-2-1_106082_2022-06-07_final.stac-item
2022-06-08 09:58:42	ga_ls9c_ard_3-2-1_097073_2022-06-08_final.stac-item
2022-06-08 11:40:23	ga_ls9c_ard_3-2-1_113080_2022-06-08_final.stac-item
2022-06-10 11:25:38	ga_ls9c_ard_3-2-1_111074_2022-06-10_final.stac-item
2022-06-20 10:25:13	ga_ls9c_ard_3-2-1_101077_2022-06-20_final.stac-item
2022-06-24 09:59:26	ga_ls9c_ard_3-2-1_097074_2022-06-24_final.stac-item
2022-07-06 10:25:20	ga_ls9c_ard_3-2-1_101077_2022-07-06_final.stac-item
2022-07-28 11:26:06	ga_ls9c_ard_3-2-1_111074_2022-07-28_final.stac-item
2022-08-26 09:21:19	ga_ls9c_ard_3-2-1_090086_2022-08-25_final.stac-item
2022-09-03 10:04:47	ga_ls9c_ard_3-2-1_098071_2022-09-03_final.stac-item
2022-09-17 10:19:12	ga_ls9c_ard_3-2-1_100076_2022-09-17_final.stac-item
2022-09-21 11:32:36	ga_ls9c_ard_3-2-1_112074_2022-09-21_final.stac-item
2022-10-13 09:18:19	ga_ls9c_ard_3-2-1_090078_2022-10-12_final.stac-item
2022-10-18 09:34:06	ga_ls9c_ard_3-2-1_093071_2022-10-18_final.stac-item
2022-11-01 09:47:13	ga_ls9c_ard_3-2-1_095073_2022-11-01_final.stac-item
2022-11-05 11:01:47	ga_ls9c_ard_3-2-1_107074_2022-11-05_final.stac-item
2022-11-14 09:18:22	ga_ls9c_ard_3-2-1_090078_2022-11-13_final.stac-item
2022-11-17 11:25:46	ga_ls9c_ard_3-2-1_111072_2022-11-17_final.stac-item
2022-11-23 10:49:04	ga_ls9c_ard_3-2-1_105073_2022-11-23_final.stac-item
2022-11-27 10:23:31	ga_ls9c_ard_3-2-1_101071_2022-11-27_final.stac-item
2022-12-12 11:19:34	ga_ls9c_ard_3-2-1_110072_2022-12-12_final.stac-item
2022-12-12 11:21:09	ga_ls9c_ard_3-2-1_110076_2022-12-12_final.stac-item
2022-12-14 09:33:54	ga_ls9c_ard_3-2-1_092086_2022-12-14_final.stac-item
2022-12-15 10:15:58	ga_ls9c_ard_3-2-1_099083_2022-12-15_final.stac-item
2022-12-16 10:54:26	ga_ls9c_ard_3-2-1_106071_2022-12-16_final.stac-item
2022-12-17 11:38:53	ga_ls9c_ard_3-2-1_113074_2022-12-17_final.stac-item
2022-12-18 10:42:04	ga_ls9c_ard_3-2-1_104071_2022-12-18_final.stac-item
2022-12-21 09:35:39	ga_ls9c_ard_3-2-1_093075_2022-12-21_final.stac-item
2022-12-29 10:25:07	ga_ls9c_ard_3-2-1_101075_2022-12-29_final.stac-item
2022-12-31 10:14:22	ga_ls9c_ard_3-2-1_099079_2022-12-31_final.stac-item
2023-01-01 09:20:44	ga_ls9c_ard_3-2-1_090084_2022-12-31_final.stac-item
2023-01-06 11:18:10	ga_ls9c_ard_3-2-1_109084_2023-01-06_final.stac-item
2023-01-08 09:24:08	ga_ls9c_ard_3-2-1_091077_2023-01-07_final.stac-item
2023-01-15 11:07:32	ga_ls9c_ard_3-2-1_108073_2023-01-15_final.stac-item
2023-01-17 10:54:44	ga_ls9c_ard_3-2-1_106072_2023-01-17_final.stac-item
2023-01-21 10:29:09	ga_ls9c_ard_3-2-1_102070_2023-01-21_final.stac-item
2023-01-27 11:35:52	ga_ls9c_ard_3-2-1_112082_2023-01-27_final.stac-item
2023-02-18 09:21:06	ga_ls9c_ard_3-2-1_090085_2023-02-17_final.stac-item
2023-03-04 11:07:47	ga_ls9c_ard_3-2-1_108074_2023-03-04_final.stac-item
2023-03-05 11:51:26	ga_ls9c_ard_3-2-1_115075_2023-03-05_final.stac-item
2023-03-14 10:10:17	ga_ls9c_ard_3-2-1_098085_2023-03-14_final.stac-item
2023-03-20 11:07:40	ga_ls9c_ard_3-2-1_108074_2023-03-20_final.stac-item
2023-03-22 10:53:41	ga_ls9c_ard_3-2-1_106070_2023-03-22_final.stac-item
2023-03-23 11:42:08	ga_ls9c_ard_3-2-1_113083_2023-03-23_final.stac-item
2023-04-19 09:40:52	ga_ls9c_ard_3-2-1_094074_2023-04-19_final.stac-item
2023-04-21 11:07:23	ga_ls9c_ard_3-2-1_108074_2023-04-21_final.stac-item
2023-04-25 10:42:14	ga_ls9c_ard_3-2-1_104073_2023-04-25_final.stac-item
2023-04-28 09:39:48	ga_ls9c_ard_3-2-1_093087_2023-04-28_final.stac-item
2023-05-08 11:50:51	ga_ls9c_ard_3-2-1_115075_2023-05-08_final.stac-item
2023-05-09 09:21:32	ga_ls9c_ard_3-2-1_090088_2023-05-08_final.stac-item
2023-06-02 10:02:49	ga_ls9c_ard_3-2-1_098068_2023-06-02_final.stac-item
2023-06-02 10:06:24	ga_ls9c_ard_3-2-1_098077_2023-06-02_final.stac-item
2023-06-16 11:57:30	ga_ls9c_ard_3-2-1_116077_2023-06-16_final.stac-item
2023-06-19 09:11:02	ga_ls9c_ard_3-2-1_089078_2023-06-18_final.stac-item
2023-06-19 09:12:38	ga_ls9c_ard_3-2-1_089082_2023-06-18_final.stac-item
2023-06-25 10:15:14	ga_ls9c_ard_3-2-1_099084_2023-06-25_final.stac-item
2023-06-25 11:52:07	ga_ls9c_ard_3-2-1_115079_2023-06-25_final.stac-item
2023-06-26 09:16:01	ga_ls9c_ard_3-2-1_090075_2023-06-25_final.stac-item
2023-06-27 10:00:55	ga_ls9c_ard_3-2-1_097079_2023-06-27_final.stac-item
2023-07-08 09:44:58	ga_ls9c_ard_3-2-1_094085_2023-07-08_final.stac-item
2023-09-07 10:46:13	ga_ls9c_ard_3-2-1_105067_2023-09-07_final.stac-item
2023-09-10 09:45:03	ga_ls9c_ard_3-2-1_094084_2023-09-10_final.stac-item
2023-09-28 09:33:02	ga_ls9c_ard_3-2-1_092085_2023-09-28_final.stac-item
2023-09-30 10:53:37	ga_ls9c_ard_3-2-1_106070_2023-09-30_final.stac-item
2023-10-05 11:14:38	ga_ls9c_ard_3-2-1_109076_2023-10-05_final.stac-item
2023-10-15 10:09:21	ga_ls9c_ard_3-2-1_099067_2023-10-15_final.stac-item
2023-10-18 10:46:16	ga_ls9c_ard_3-2-1_104082_2023-10-18_final.stac-item
2023-10-21 09:35:29	ga_ls9c_ard_3-2-1_093075_2023-10-21_final.stac-item
2023-10-25 09:14:45	ga_ls9c_ard_3-2-1_089085_2023-10-24_final.stac-item
2023-10-25 10:48:50	ga_ls9c_ard_3-2-1_105073_2023-10-25_final.stac-item
2023-11-02 10:03:41	ga_ls9c_ard_3-2-1_097084_2023-11-02_final.stac-item
2023-11-02 11:38:34	ga_ls9c_ard_3-2-1_113074_2023-11-02_final.stac-item
2023-11-17 10:53:47	ga_ls9c_ard_3-2-1_106070_2023-11-17_final.stac-item
2023-11-21 10:28:20	ga_ls9c_ard_3-2-1_102068_2023-11-21_final.stac-item
2023-11-26 10:52:54	ga_ls9c_ard_3-2-1_105083_2023-11-26_final.stac-item
2023-12-01 09:32:09	ga_ls9c_ard_3-2-1_092082_2023-12-01_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