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
2021-11-09 10:37:00	ga_ls9c_ard_3-2-1_103074_2021-11-09_final.stac-item
2021-11-17 09:26:04	ga_ls9c_ard_3-2-1_091084_2021-11-16_final.stac-item
2021-11-23 11:45:04	ga_ls9c_ard_3-2-1_114079_2021-11-23_final.stac-item
2021-12-11 09:32:11	ga_ls9c_ard_3-2-1_092082_2021-12-11_final.stac-item
2021-12-12 11:53:31	ga_ls9c_ard_3-2-1_115080_2021-12-12_final.stac-item
2021-12-13 09:22:36	ga_ls9c_ard_3-2-1_090089_2021-12-12_final.stac-item
2021-12-29 09:21:47	ga_ls9c_ard_3-2-1_090087_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
2022-01-21 09:25:08	ga_ls9c_ard_3-2-1_091080_2022-01-20_final.stac-item
2022-02-13 11:08:34	ga_ls9c_ard_3-2-1_108076_2022-02-13_final.stac-item
2022-02-25 11:31:57	ga_ls9c_ard_3-2-1_112073_2022-02-25_final.stac-item
2022-03-10 09:27:42	ga_ls9c_ard_3-2-1_091087_2022-03-09_final.stac-item
2022-03-21 09:06:43	ga_ls9c_ard_3-2-1_088081_2022-03-20_final.stac-item
2022-03-26 09:28:25	ga_ls9c_ard_3-2-1_091089_2022-03-25_final.stac-item
2022-04-11 09:24:46	ga_ls9c_ard_3-2-1_091080_2022-04-10_final.stac-item
2022-04-29 09:16:15	ga_ls9c_ard_3-2-1_089090_2022-04-28_final.stac-item
2022-05-04 11:05:16	ga_ls9c_ard_3-2-1_108069_2022-05-04_final.stac-item
2022-05-23 09:57:52	ga_ls9c_ard_3-2-1_097071_2022-05-23_final.stac-item
2022-05-29 09:24:23	ga_ls9c_ard_3-2-1_091080_2022-05-28_final.stac-item
2022-06-07 10:54:19	ga_ls9c_ard_3-2-1_106073_2022-06-07_final.stac-item
2022-06-29 10:21:34	ga_ls9c_ard_3-2-1_100083_2022-06-29_final.stac-item
2022-07-15 10:17:54	ga_ls9c_ard_3-2-1_100074_2022-07-15_final.stac-item
2022-07-15 10:21:29	ga_ls9c_ard_3-2-1_100083_2022-07-15_final.stac-item
2022-07-16 09:27:29	ga_ls9c_ard_3-2-1_091087_2022-07-15_final.stac-item
2022-08-08 11:06:29	ga_ls9c_ard_3-2-1_108071_2022-08-08_final.stac-item
2022-08-24 11:05:47	ga_ls9c_ard_3-2-1_108069_2022-08-24_final.stac-item
2022-08-26 10:53:49	ga_ls9c_ard_3-2-1_106070_2022-08-26_final.stac-item
2022-09-16 09:35:56	ga_ls9c_ard_3-2-1_093076_2022-09-16_final.stac-item
2022-09-23 11:23:03	ga_ls9c_ard_3-2-1_110081_2022-09-23_final.stac-item
2022-09-28 09:59:55	ga_ls9c_ard_3-2-1_097074_2022-09-28_final.stac-item
2022-10-13 10:53:37	ga_ls9c_ard_3-2-1_106069_2022-10-13_final.stac-item
2022-10-15 10:42:28	ga_ls9c_ard_3-2-1_104072_2022-10-15_final.stac-item
2022-10-18 09:36:05	ga_ls9c_ard_3-2-1_093076_2022-10-18_final.stac-item
2022-10-28 11:52:27	ga_ls9c_ard_3-2-1_115077_2022-10-28_final.stac-item
2022-11-03 09:35:39	ga_ls9c_ard_3-2-1_093075_2022-11-03_final.stac-item
2022-11-05 11:02:11	ga_ls9c_ard_3-2-1_107075_2022-11-05_final.stac-item
2022-11-06 11:45:51	ga_ls9c_ard_3-2-1_114076_2022-11-06_final.stac-item
2022-11-06 11:46:39	ga_ls9c_ard_3-2-1_114078_2022-11-06_final.stac-item
2022-11-10 11:23:09	ga_ls9c_ard_3-2-1_110081_2022-11-10_final.stac-item
2022-11-15 09:58:26	ga_ls9c_ard_3-2-1_097070_2022-11-15_final.stac-item
2022-12-03 11:30:05	ga_ls9c_ard_3-2-1_111083_2022-12-03_final.stac-item
2022-12-12 11:23:33	ga_ls9c_ard_3-2-1_110082_2022-12-12_final.stac-item
2022-12-15 10:11:58	ga_ls9c_ard_3-2-1_099073_2022-12-15_final.stac-item
2022-12-16 10:55:14	ga_ls9c_ard_3-2-1_106073_2022-12-16_final.stac-item
2022-12-18 10:44:03	ga_ls9c_ard_3-2-1_104076_2022-12-18_final.stac-item
2022-12-27 10:37:52	ga_ls9c_ard_3-2-1_103076_2022-12-27_final.stac-item
2022-12-28 11:19:56	ga_ls9c_ard_3-2-1_110073_2022-12-28_final.stac-item
2022-12-29 10:25:55	ga_ls9c_ard_3-2-1_101077_2022-12-29_final.stac-item
2023-01-05 10:28:55	ga_ls9c_ard_3-2-1_102069_2023-01-05_final.stac-item
2023-01-09 11:45:52	ga_ls9c_ard_3-2-1_114076_2023-01-09_final.stac-item
2023-01-16 11:51:11	ga_ls9c_ard_3-2-1_115074_2023-01-16_final.stac-item
2023-01-17 10:54:20	ga_ls9c_ard_3-2-1_106071_2023-01-17_final.stac-item
2023-01-18 11:42:22	ga_ls9c_ard_3-2-1_113083_2023-01-18_final.stac-item
2023-01-24 09:24:50	ga_ls9c_ard_3-2-1_091079_2023-01-23_final.stac-item
2023-02-01 10:10:24	ga_ls9c_ard_3-2-1_099069_2023-02-01_final.stac-item
2023-02-05 11:25:47	ga_ls9c_ard_3-2-1_111072_2023-02-05_final.stac-item
2023-02-11 09:15:01	ga_ls9c_ard_3-2-1_089085_2023-02-10_final.stac-item
2023-03-03 10:22:56	ga_ls9c_ard_3-2-1_101070_2023-03-03_final.stac-item
2023-03-06 09:21:42	ga_ls9c_ard_3-2-1_090087_2023-03-05_final.stac-item
2023-03-08 09:07:18	ga_ls9c_ard_3-2-1_088082_2023-03-07_final.stac-item
2023-03-11 09:36:11	ga_ls9c_ard_3-2-1_093077_2023-03-11_final.stac-item
2023-03-11 11:12:40	ga_ls9c_ard_3-2-1_109071_2023-03-11_final.stac-item
2023-03-29 09:28:02	ga_ls9c_ard_3-2-1_091088_2023-03-28_final.stac-item
2023-04-22 11:51:27	ga_ls9c_ard_3-2-1_115076_2023-04-22_final.stac-item
2023-04-23 09:17:44	ga_ls9c_ard_3-2-1_090078_2023-04-22_final.stac-item
2023-04-25 09:06:33	ga_ls9c_ard_3-2-1_088081_2023-04-24_final.stac-item
2023-05-07 11:05:36	ga_ls9c_ard_3-2-1_108070_2023-05-07_final.stac-item
2023-05-09 09:17:57	ga_ls9c_ard_3-2-1_090079_2023-05-08_final.stac-item
2023-05-10 11:40:29	ga_ls9c_ard_3-2-1_113080_2023-05-10_final.stac-item
2023-05-17 10:04:56	ga_ls9c_ard_3-2-1_098073_2023-05-17_final.stac-item
2023-05-17 11:45:01	ga_ls9c_ard_3-2-1_114076_2023-05-17_final.stac-item
2023-05-28 11:28:21	ga_ls9c_ard_3-2-1_111081_2023-05-28_final.stac-item
2023-06-01 09:24:21	ga_ls9c_ard_3-2-1_091080_2023-05-31_final.stac-item
2023-06-04 09:51:15	ga_ls9c_ard_3-2-1_096070_2023-06-04_final.stac-item
2023-06-22 11:18:50	ga_ls9c_ard_3-2-1_110073_2023-06-22_final.stac-item
2023-06-24 11:05:40	ga_ls9c_ard_3-2-1_108071_2023-06-24_final.stac-item
2023-06-24 11:06:52	ga_ls9c_ard_3-2-1_108074_2023-06-24_final.stac-item
2023-06-27 09:57:43	ga_ls9c_ard_3-2-1_097071_2023-06-27_final.stac-item
2023-06-27 11:41:00	ga_ls9c_ard_3-2-1_113082_2023-06-27_final.stac-item
2023-07-01 09:36:18	ga_ls9c_ard_3-2-1_093079_2023-07-01_final.stac-item
2023-07-03 09:21:11	ga_ls9c_ard_3-2-1_091072_2023-07-02_final.stac-item
2023-07-05 10:46:32	ga_ls9c_ard_3-2-1_105069_2023-07-05_final.stac-item
2023-07-15 11:24:53	ga_ls9c_ard_3-2-1_111072_2023-07-15_final.stac-item
2023-07-20 10:02:57	ga_ls9c_ard_3-2-1_098068_2023-07-20_final.stac-item
2023-07-20 11:46:37	ga_ls9c_ard_3-2-1_114080_2023-07-20_final.stac-item
2023-07-21 09:12:31	ga_ls9c_ard_3-2-1_089081_2023-07-20_final.stac-item
2023-07-27 11:52:01	ga_ls9c_ard_3-2-1_115078_2023-07-27_final.stac-item
2023-08-02 11:13:02	ga_ls9c_ard_3-2-1_109073_2023-08-02_final.stac-item
2023-08-05 11:46:22	ga_ls9c_ard_3-2-1_114079_2023-08-05_final.stac-item
2023-08-14 11:41:25	ga_ls9c_ard_3-2-1_113082_2023-08-14_final.stac-item
2023-10-14 11:05:46	ga_ls9c_ard_3-2-1_108069_2023-10-14_final.stac-item
2023-10-15 10:10:33	ga_ls9c_ard_3-2-1_099070_2023-10-15_final.stac-item
2023-10-15 10:11:45	ga_ls9c_ard_3-2-1_099073_2023-10-15_final.stac-item
2023-10-23 09:23:55	ga_ls9c_ard_3-2-1_091077_2023-10-22_final.stac-item
2023-10-28 11:21:42	ga_ls9c_ard_3-2-1_110078_2023-10-28_final.stac-item
2023-10-31 10:12:53	ga_ls9c_ard_3-2-1_099076_2023-10-31_final.stac-item
2023-11-16 10:11:42	ga_ls9c_ard_3-2-1_099073_2023-11-16_final.stac-item
2023-11-16 10:12:53	ga_ls9c_ard_3-2-1_099076_2023-11-16_final.stac-item
2023-11-18 09:57:46	ga_ls9c_ard_3-2-1_097069_2023-11-18_final.stac-item
2023-11-23 10:19:11	ga_ls9c_ard_3-2-1_100076_2023-11-23_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