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
2021-12-11 11:07:05	ga_ls9c_ard_3-2-1_108072_2021-12-11_final.stac-item
2021-12-11 11:09:52	ga_ls9c_ard_3-2-1_108079_2021-12-11_final.stac-item
2021-12-30 11:39:56	ga_ls9c_ard_3-2-1_113077_2021-12-30_final.stac-item
2022-01-06 11:45:41	ga_ls9c_ard_3-2-1_114076_2022-01-06_final.stac-item
2022-01-10 09:46:04	ga_ls9c_ard_3-2-1_094086_2022-01-10_final.stac-item
2022-01-15 11:41:53	ga_ls9c_ard_3-2-1_113082_2022-01-15_final.stac-item
2022-02-07 10:10:23	ga_ls9c_ard_3-2-1_098085_2022-02-07_final.stac-item
2022-02-09 11:32:07	ga_ls9c_ard_3-2-1_112073_2022-02-09_final.stac-item
2022-02-09 11:35:42	ga_ls9c_ard_3-2-1_112082_2022-02-09_final.stac-item
2022-02-15 10:56:59	ga_ls9c_ard_3-2-1_106078_2022-02-15_final.stac-item
2022-02-16 11:41:26	ga_ls9c_ard_3-2-1_113081_2022-02-16_final.stac-item
2022-03-03 09:19:07	ga_ls9c_ard_3-2-1_090081_2022-03-02_final.stac-item
2022-03-06 11:30:06	ga_ls9c_ard_3-2-1_111084_2022-03-06_final.stac-item
2022-03-08 11:15:21	ga_ls9c_ard_3-2-1_109078_2022-03-08_final.stac-item
2022-03-19 10:56:47	ga_ls9c_ard_3-2-1_106078_2022-03-19_final.stac-item
2022-03-20 11:37:39	ga_ls9c_ard_3-2-1_113072_2022-03-20_final.stac-item
2022-03-31 09:44:10	ga_ls9c_ard_3-2-1_094082_2022-03-31_final.stac-item
2022-04-05 09:57:30	ga_ls9c_ard_3-2-1_097069_2022-04-05_final.stac-item
2022-04-09 11:12:50	ga_ls9c_ard_3-2-1_109072_2022-04-09_final.stac-item
2022-04-16 09:45:39	ga_ls9c_ard_3-2-1_094086_2022-04-16_final.stac-item
2022-05-02 09:43:09	ga_ls9c_ard_3-2-1_094080_2022-05-02_final.stac-item
2022-05-09 11:28:57	ga_ls9c_ard_3-2-1_111082_2022-05-09_final.stac-item
2022-05-10 10:30:31	ga_ls9c_ard_3-2-1_102075_2022-05-10_final.stac-item
2022-05-17 10:36:36	ga_ls9c_ard_3-2-1_103075_2022-05-17_final.stac-item
2022-05-25 11:24:48	ga_ls9c_ard_3-2-1_111072_2022-05-25_final.stac-item
2022-06-02 10:34:11	ga_ls9c_ard_3-2-1_103069_2022-06-02_final.stac-item
2022-06-26 11:29:58	ga_ls9c_ard_3-2-1_111084_2022-06-26_final.stac-item
2022-07-26 11:41:14	ga_ls9c_ard_3-2-1_113081_2022-07-26_final.stac-item
2022-07-27 10:42:49	ga_ls9c_ard_3-2-1_104074_2022-07-27_final.stac-item
2022-07-29 10:29:18	ga_ls9c_ard_3-2-1_102071_2022-07-29_final.stac-item
2022-07-30 09:35:41	ga_ls9c_ard_3-2-1_093076_2022-07-30_final.stac-item
2022-07-30 09:37:40	ga_ls9c_ard_3-2-1_093081_2022-07-30_final.stac-item
2022-07-31 11:57:50	ga_ls9c_ard_3-2-1_116076_2022-07-31_final.stac-item
2022-08-03 09:16:12	ga_ls9c_ard_3-2-1_089089_2022-08-02_final.stac-item
2022-08-08 11:09:41	ga_ls9c_ard_3-2-1_108079_2022-08-08_final.stac-item
2022-08-11 11:40:37	ga_ls9c_ard_3-2-1_113079_2022-08-11_final.stac-item
2022-08-18 10:03:57	ga_ls9c_ard_3-2-1_098069_2022-08-18_final.stac-item
2022-08-26 10:54:37	ga_ls9c_ard_3-2-1_106072_2022-08-26_final.stac-item
2022-08-27 10:01:00	ga_ls9c_ard_3-2-1_097077_2022-08-27_final.stac-item
2022-08-28 10:43:04	ga_ls9c_ard_3-2-1_104074_2022-08-28_final.stac-item
2022-09-01 10:21:32	ga_ls9c_ard_3-2-1_100082_2022-09-01_final.stac-item
2022-09-03 10:06:22	ga_ls9c_ard_3-2-1_098075_2022-09-03_final.stac-item
2022-09-12 11:39:54	ga_ls9c_ard_3-2-1_113077_2022-09-12_final.stac-item
2022-09-18 11:00:53	ga_ls9c_ard_3-2-1_107072_2022-09-18_final.stac-item
2022-10-16 11:27:19	ga_ls9c_ard_3-2-1_111076_2022-10-16_final.stac-item
2022-10-21 11:47:05	ga_ls9c_ard_3-2-1_114079_2022-10-21_final.stac-item
2022-10-22 10:48:40	ga_ls9c_ard_3-2-1_105072_2022-10-22_final.stac-item
2022-10-22 10:50:39	ga_ls9c_ard_3-2-1_105077_2022-10-22_final.stac-item
2022-10-25 11:18:46	ga_ls9c_ard_3-2-1_110070_2022-10-25_final.stac-item
2022-10-31 10:41:39	ga_ls9c_ard_3-2-1_104070_2022-10-31_final.stac-item
2022-11-15 11:42:31	ga_ls9c_ard_3-2-1_113083_2022-11-15_final.stac-item
2022-11-17 09:51:40	ga_ls9c_ard_3-2-1_095084_2022-11-17_final.stac-item
2022-11-28 11:09:58	ga_ls9c_ard_3-2-1_108079_2022-11-28_final.stac-item
2022-11-30 10:59:11	ga_ls9c_ard_3-2-1_106083_2022-11-30_final.stac-item
2022-12-02 10:44:25	ga_ls9c_ard_3-2-1_104077_2022-12-02_final.stac-item
2022-12-16 09:20:44	ga_ls9c_ard_3-2-1_090084_2022-12-15_final.stac-item
2022-12-28 11:24:43	ga_ls9c_ard_3-2-1_110085_2022-12-28_final.stac-item
2022-12-29 10:26:43	ga_ls9c_ard_3-2-1_101079_2022-12-29_final.stac-item
2023-01-02 11:40:54	ga_ls9c_ard_3-2-1_113079_2023-01-02_final.stac-item
2023-01-03 10:44:28	ga_ls9c_ard_3-2-1_104077_2023-01-03_final.stac-item
2023-01-08 11:03:01	ga_ls9c_ard_3-2-1_107077_2023-01-08_final.stac-item
2023-01-22 09:35:09	ga_ls9c_ard_3-2-1_093074_2023-01-22_final.stac-item
2023-01-27 09:54:59	ga_ls9c_ard_3-2-1_096077_2023-01-27_final.stac-item
2023-01-28 10:38:15	ga_ls9c_ard_3-2-1_103077_2023-01-28_final.stac-item
2023-01-31 09:32:18	ga_ls9c_ard_3-2-1_092082_2023-01-31_final.stac-item
2023-02-06 10:30:58	ga_ls9c_ard_3-2-1_102074_2023-02-06_final.stac-item
2023-02-25 09:28:20	ga_ls9c_ard_3-2-1_091088_2023-02-24_final.stac-item
2023-03-16 09:53:08	ga_ls9c_ard_3-2-1_096073_2023-03-16_final.stac-item
2023-03-19 10:24:49	ga_ls9c_ard_3-2-1_101075_2023-03-19_final.stac-item
2023-03-24 10:44:30	ga_ls9c_ard_3-2-1_104078_2023-03-24_final.stac-item
2023-03-27 11:12:08	ga_ls9c_ard_3-2-1_109070_2023-03-27_final.stac-item
2023-03-30 10:06:05	ga_ls9c_ard_3-2-1_098075_2023-03-30_final.stac-item
2023-04-05 11:08:42	ga_ls9c_ard_3-2-1_108077_2023-04-05_final.stac-item
2023-04-20 10:23:44	ga_ls9c_ard_3-2-1_101073_2023-04-20_final.stac-item
2023-05-02 09:14:13	ga_ls9c_ard_3-2-1_089085_2023-05-01_final.stac-item
2023-05-06 10:23:32	ga_ls9c_ard_3-2-1_101073_2023-05-06_final.stac-item
2023-05-17 11:46:13	ga_ls9c_ard_3-2-1_114079_2023-05-17_final.stac-item
2023-05-18 10:47:47	ga_ls9c_ard_3-2-1_105072_2023-05-18_final.stac-item
2023-05-20 10:35:48	ga_ls9c_ard_3-2-1_103073_2023-05-20_final.stac-item
2023-06-24 11:05:40	ga_ls9c_ard_3-2-1_108071_2023-06-24_final.stac-item
2023-07-03 11:00:28	ga_ls9c_ard_3-2-1_107073_2023-07-03_final.stac-item
2023-08-27 11:11:26	ga_ls9c_ard_3-2-1_108084_2023-08-27_final.stac-item
2023-09-15 10:01:38	ga_ls9c_ard_3-2-1_097079_2023-09-15_final.stac-item
2023-09-20 11:58:39	ga_ls9c_ard_3-2-1_116078_2023-09-20_final.stac-item
2023-10-05 09:33:45	ga_ls9c_ard_3-2-1_093071_2023-10-05_final.stac-item
2023-10-05 11:16:38	ga_ls9c_ard_3-2-1_109081_2023-10-05_final.stac-item
2023-10-06 11:58:42	ga_ls9c_ard_3-2-1_116078_2023-10-06_final.stac-item
2023-10-15 10:12:09	ga_ls9c_ard_3-2-1_099074_2023-10-15_final.stac-item
2023-11-06 11:15:29	ga_ls9c_ard_3-2-1_109078_2023-11-06_final.stac-item
2023-11-14 10:25:15	ga_ls9c_ard_3-2-1_101076_2023-11-14_final.stac-item
2023-12-13 09:57:16	ga_ls9c_ard_3-2-1_096083_2023-12-13_final.stac-item
2023-12-15 11:21:25	ga_ls9c_ard_3-2-1_110077_2023-12-15_final.stac-item
2023-12-17 11:09:04	ga_ls9c_ard_3-2-1_108077_2023-12-17_final.stac-item
2023-12-22 09:48:21	ga_ls9c_ard_3-2-1_095076_2023-12-22_final.stac-item
2023-12-22 11:29:37	ga_ls9c_ard_3-2-1_111082_2023-12-22_final.stac-item
2023-12-29 11:35:47	ga_ls9c_ard_3-2-1_112082_2023-12-29_final.stac-item
2024-01-02 09:30:56	ga_ls9c_ard_3-2-1_092079_2024-01-02_final.stac-item
2024-01-05 11:41:52	ga_ls9c_ard_3-2-1_113082_2024-01-05_final.stac-item
2024-01-11 09:24:45	ga_ls9c_ard_3-2-1_091079_2024-01-10_final.stac-item
2024-01-11 11:01:14	ga_ls9c_ard_3-2-1_107073_2024-01-11_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