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
2021-11-16 10:23:54	ga_ls9c_ard_3-2-1_100082_2021-11-16_final.stac-item
2021-11-23 10:02:50	ga_ls9c_ard_3-2-1_098070_2021-11-23_final.stac-item
2021-12-06 10:48:36	ga_ls9c_ard_3-2-1_105072_2021-12-06_final.stac-item
2021-12-10 10:24:14	ga_ls9c_ard_3-2-1_101073_2021-12-10_final.stac-item
2021-12-18 11:12:24	ga_ls9c_ard_3-2-1_109070_2021-12-18_final.stac-item
2021-12-27 09:30:57	ga_ls9c_ard_3-2-1_092079_2021-12-27_final.stac-item
2022-01-06 11:46:53	ga_ls9c_ard_3-2-1_114079_2022-01-06_final.stac-item
2022-01-08 09:52:27	ga_ls9c_ard_3-2-1_096071_2022-01-08_final.stac-item
2022-01-28 11:11:49	ga_ls9c_ard_3-2-1_108084_2022-01-28_final.stac-item
2022-02-03 10:31:56	ga_ls9c_ard_3-2-1_102077_2022-02-03_final.stac-item
2022-02-14 10:12:56	ga_ls9c_ard_3-2-1_099076_2022-02-14_final.stac-item
2022-02-16 10:01:45	ga_ls9c_ard_3-2-1_097079_2022-02-16_final.stac-item
2022-02-27 09:43:28	ga_ls9c_ard_3-2-1_094080_2022-02-27_final.stac-item
2022-03-01 11:10:22	ga_ls9c_ard_3-2-1_108081_2022-03-01_final.stac-item
2022-03-04 10:01:35	ga_ls9c_ard_3-2-1_097079_2022-03-04_final.stac-item
2022-03-04 10:02:47	ga_ls9c_ard_3-2-1_097082_2022-03-04_final.stac-item
2022-03-22 11:28:52	ga_ls9c_ard_3-2-1_111081_2022-03-22_final.stac-item
2022-03-25 10:20:27	ga_ls9c_ard_3-2-1_100080_2022-03-25_final.stac-item
2022-04-02 09:30:36	ga_ls9c_ard_3-2-1_092079_2022-04-02_final.stac-item
2022-04-09 09:36:45	ga_ls9c_ard_3-2-1_093079_2022-04-09_final.stac-item
2022-04-10 10:20:48	ga_ls9c_ard_3-2-1_100081_2022-04-10_final.stac-item
2022-04-18 11:06:09	ga_ls9c_ard_3-2-1_108071_2022-04-18_final.stac-item
2022-05-01 10:37:11	ga_ls9c_ard_3-2-1_103076_2022-05-01_final.stac-item
2022-05-02 11:23:14	ga_ls9c_ard_3-2-1_110083_2022-05-02_final.stac-item
2022-05-05 11:52:55	ga_ls9c_ard_3-2-1_115080_2022-05-05_final.stac-item
2022-05-09 11:26:09	ga_ls9c_ard_3-2-1_111075_2022-05-09_final.stac-item
2022-05-23 09:58:40	ga_ls9c_ard_3-2-1_097073_2022-05-23_final.stac-item
2022-06-04 10:24:37	ga_ls9c_ard_3-2-1_101076_2022-06-04_final.stac-item
2022-06-08 10:03:05	ga_ls9c_ard_3-2-1_097084_2022-06-08_final.stac-item
2022-06-14 11:03:22	ga_ls9c_ard_3-2-1_107080_2022-06-14_final.stac-item
2022-06-19 11:18:24	ga_ls9c_ard_3-2-1_110071_2022-06-19_final.stac-item
2022-06-21 11:11:18	ga_ls9c_ard_3-2-1_108084_2022-06-21_final.stac-item
2022-06-24 09:58:38	ga_ls9c_ard_3-2-1_097072_2022-06-24_final.stac-item
2022-07-19 09:52:03	ga_ls9c_ard_3-2-1_096071_2022-07-19_final.stac-item
2022-07-19 09:52:51	ga_ls9c_ard_3-2-1_096073_2022-07-19_final.stac-item
2022-07-19 11:35:20	ga_ls9c_ard_3-2-1_112082_2022-07-19_final.stac-item
2022-07-21 11:21:25	ga_ls9c_ard_3-2-1_110078_2022-07-21_final.stac-item
2022-07-30 09:34:53	ga_ls9c_ard_3-2-1_093074_2022-07-30_final.stac-item
2022-08-04 09:57:52	ga_ls9c_ard_3-2-1_096085_2022-08-04_final.stac-item
2022-08-05 10:36:21	ga_ls9c_ard_3-2-1_103073_2022-08-05_final.stac-item
2022-08-11 11:41:00	ga_ls9c_ard_3-2-1_113080_2022-08-11_final.stac-item
2022-08-31 09:33:53	ga_ls9c_ard_3-2-1_093071_2022-08-31_final.stac-item
2022-09-18 09:22:00	ga_ls9c_ard_3-2-1_091072_2022-09-17_final.stac-item
2022-09-20 09:14:50	ga_ls9c_ard_3-2-1_089085_2022-09-19_final.stac-item
2022-09-24 10:24:14	ga_ls9c_ard_3-2-1_101073_2022-09-24_final.stac-item
2022-09-27 09:19:27	ga_ls9c_ard_3-2-1_090081_2022-09-26_final.stac-item
2022-10-14 11:41:40	ga_ls9c_ard_3-2-1_113081_2022-10-14_final.stac-item
2022-10-18 09:40:05	ga_ls9c_ard_3-2-1_093086_2022-10-18_final.stac-item
2022-10-25 11:21:33	ga_ls9c_ard_3-2-1_110077_2022-10-25_final.stac-item
2022-10-28 10:13:10	ga_ls9c_ard_3-2-1_099076_2022-10-28_final.stac-item
2022-10-30 11:42:04	ga_ls9c_ard_3-2-1_113082_2022-10-30_final.stac-item
2022-11-23 10:48:40	ga_ls9c_ard_3-2-1_105072_2022-11-23_final.stac-item
2023-01-09 11:46:16	ga_ls9c_ard_3-2-1_114077_2023-01-09_final.stac-item
2023-02-02 09:19:58	ga_ls9c_ard_3-2-1_090082_2023-02-01_final.stac-item
2023-02-03 11:42:07	ga_ls9c_ard_3-2-1_113082_2023-02-03_final.stac-item
2023-02-10 11:45:32	ga_ls9c_ard_3-2-1_114075_2023-02-10_final.stac-item
2023-02-12 09:56:40	ga_ls9c_ard_3-2-1_096081_2023-02-12_final.stac-item
2023-02-18 10:54:48	ga_ls9c_ard_3-2-1_106072_2023-02-18_final.stac-item
2023-02-19 11:42:01	ga_ls9c_ard_3-2-1_113082_2023-02-19_final.stac-item
2023-02-22 10:30:46	ga_ls9c_ard_3-2-1_102074_2023-02-22_final.stac-item
2023-03-20 09:30:47	ga_ls9c_ard_3-2-1_092079_2023-03-20_final.stac-item
2023-03-21 11:53:19	ga_ls9c_ard_3-2-1_115080_2023-03-21_final.stac-item
2023-04-07 10:57:31	ga_ls9c_ard_3-2-1_106080_2023-04-07_final.stac-item
2023-04-25 10:43:02	ga_ls9c_ard_3-2-1_104075_2023-04-25_final.stac-item
2023-05-03 11:35:32	ga_ls9c_ard_3-2-1_112083_2023-05-03_final.stac-item
2023-05-21 09:43:21	ga_ls9c_ard_3-2-1_094081_2023-05-21_final.stac-item
2023-05-30 09:34:19	ga_ls9c_ard_3-2-1_093074_2023-05-30_final.stac-item
2023-06-22 11:22:25	ga_ls9c_ard_3-2-1_110082_2023-06-22_final.stac-item
2023-06-27 11:40:36	ga_ls9c_ard_3-2-1_113081_2023-06-27_final.stac-item
2023-07-02 11:58:04	ga_ls9c_ard_3-2-1_116078_2023-07-02_final.stac-item
2023-07-21 09:12:07	ga_ls9c_ard_3-2-1_089080_2023-07-20_final.stac-item
2023-07-27 10:12:20	ga_ls9c_ard_3-2-1_099076_2023-07-27_final.stac-item
2023-08-10 10:24:27	ga_ls9c_ard_3-2-1_101075_2023-08-10_final.stac-item
2023-08-14 10:03:43	ga_ls9c_ard_3-2-1_097085_2023-08-14_final.stac-item
2023-08-16 09:52:09	ga_ls9c_ard_3-2-1_095087_2023-08-16_final.stac-item
2023-08-26 10:24:58	ga_ls9c_ard_3-2-1_101076_2023-08-26_final.stac-item
2023-08-28 11:50:43	ga_ls9c_ard_3-2-1_115074_2023-08-28_final.stac-item
2023-09-03 09:33:36	ga_ls9c_ard_3-2-1_093071_2023-09-03_final.stac-item
2023-09-03 09:38:23	ga_ls9c_ard_3-2-1_093083_2023-09-03_final.stac-item
2023-09-05 09:25:15	ga_ls9c_ard_3-2-1_091081_2023-09-04_final.stac-item
2023-09-07 10:52:12	ga_ls9c_ard_3-2-1_105082_2023-09-07_final.stac-item
2023-09-12 11:11:36	ga_ls9c_ard_3-2-1_108084_2023-09-12_final.stac-item
2023-09-24 09:52:38	ga_ls9c_ard_3-2-1_096072_2023-09-24_final.stac-item
2023-10-01 10:01:36	ga_ls9c_ard_3-2-1_097079_2023-10-01_final.stac-item
2023-10-05 11:13:02	ga_ls9c_ard_3-2-1_109072_2023-10-05_final.stac-item
2023-10-09 10:51:56	ga_ls9c_ard_3-2-1_105081_2023-10-09_final.stac-item
2023-10-13 10:24:53	ga_ls9c_ard_3-2-1_101075_2023-10-13_final.stac-item
2023-10-26 11:34:05	ga_ls9c_ard_3-2-1_112078_2023-10-26_final.stac-item
2023-11-22 09:33:55	ga_ls9c_ard_3-2-1_093071_2023-11-22_final.stac-item
2023-11-24 09:28:46	ga_ls9c_ard_3-2-1_091089_2023-11-23_final.stac-item
2023-11-27 11:34:58	ga_ls9c_ard_3-2-1_112080_2023-11-27_final.stac-item
2023-12-14 10:37:44	ga_ls9c_ard_3-2-1_103076_2023-12-14_final.stac-item
2023-12-16 10:23:48	ga_ls9c_ard_3-2-1_101072_2023-12-16_final.stac-item
2023-12-20 11:41:59	ga_ls9c_ard_3-2-1_113082_2023-12-20_final.stac-item
2023-12-26 09:25:37	ga_ls9c_ard_3-2-1_091081_2023-12-25_final.stac-item
2023-12-28 10:47:44	ga_ls9c_ard_3-2-1_105070_2023-12-28_final.stac-item
2024-01-06 10:41:51	ga_ls9c_ard_3-2-1_104071_2024-01-06_final.stac-item
2024-01-21 10:03:48	ga_ls9c_ard_3-2-1_097084_2024-01-21_final.stac-item
2024-01-23 09:47:25	ga_ls9c_ard_3-2-1_095074_2024-01-23_final.stac-item
2024-01-30 09:56:03	ga_ls9c_ard_3-2-1_096080_2024-01-30_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