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
2021-11-10 11:16:10	ga_ls9c_ard_3-2-1_110072_2021-11-10_final.stac-item
2021-12-05 11:45:26	ga_ls9c_ard_3-2-1_114075_2021-12-05_final.stac-item
2021-12-05 11:47:25	ga_ls9c_ard_3-2-1_114080_2021-12-05_final.stac-item
2021-12-09 11:21:28	ga_ls9c_ard_3-2-1_110077_2021-12-09_final.stac-item
2021-12-14 11:38:45	ga_ls9c_ard_3-2-1_113074_2021-12-14_final.stac-item
2021-12-15 10:44:42	ga_ls9c_ard_3-2-1_104078_2021-12-15_final.stac-item
2021-12-24 10:34:56	ga_ls9c_ard_3-2-1_103069_2021-12-24_final.stac-item
2021-12-28 11:51:54	ga_ls9c_ard_3-2-1_115076_2021-12-28_final.stac-item
2021-12-29 09:17:47	ga_ls9c_ard_3-2-1_090077_2021-12-28_final.stac-item
2022-01-01 11:25:34	ga_ls9c_ard_3-2-1_111072_2022-01-01_final.stac-item
2022-01-12 11:07:47	ga_ls9c_ard_3-2-1_108074_2022-01-12_final.stac-item
2022-01-19 11:13:59	ga_ls9c_ard_3-2-1_109074_2022-01-19_final.stac-item
2022-01-29 11:51:53	ga_ls9c_ard_3-2-1_115076_2022-01-29_final.stac-item
2022-01-30 10:59:03	ga_ls9c_ard_3-2-1_106083_2022-01-30_final.stac-item
2022-02-03 10:29:08	ga_ls9c_ard_3-2-1_102070_2022-02-03_final.stac-item
2022-02-08 09:14:46	ga_ls9c_ard_3-2-1_089085_2022-02-07_final.stac-item
2022-02-08 10:50:03	ga_ls9c_ard_3-2-1_105076_2022-02-08_final.stac-item
2022-02-10 10:36:05	ga_ls9c_ard_3-2-1_103072_2022-02-10_final.stac-item
2022-02-16 10:01:21	ga_ls9c_ard_3-2-1_097078_2022-02-16_final.stac-item
2022-02-19 10:29:02	ga_ls9c_ard_3-2-1_102070_2022-02-19_final.stac-item
2022-02-25 11:35:56	ga_ls9c_ard_3-2-1_112083_2022-02-25_final.stac-item
2022-03-10 09:28:54	ga_ls9c_ard_3-2-1_091090_2022-03-09_final.stac-item
2022-04-01 10:27:49	ga_ls9c_ard_3-2-1_101083_2022-04-01_final.stac-item
2022-04-04 09:22:14	ga_ls9c_ard_3-2-1_090089_2022-04-03_final.stac-item
2022-04-10 11:58:29	ga_ls9c_ard_3-2-1_116078_2022-04-10_final.stac-item
2022-04-12 10:03:14	ga_ls9c_ard_3-2-1_098068_2022-04-12_final.stac-item
2022-05-20 11:10:39	ga_ls9c_ard_3-2-1_108083_2022-05-20_final.stac-item
2022-05-24 10:45:31	ga_ls9c_ard_3-2-1_104082_2022-05-24_final.stac-item
2022-05-27 09:39:56	ga_ls9c_ard_3-2-1_093088_2022-05-27_final.stac-item
2022-05-31 09:12:50	ga_ls9c_ard_3-2-1_089082_2022-05-30_final.stac-item
2022-06-10 11:24:26	ga_ls9c_ard_3-2-1_111071_2022-06-10_final.stac-item
2022-07-02 09:14:47	ga_ls9c_ard_3-2-1_089086_2022-07-01_final.stac-item
2022-07-15 10:21:29	ga_ls9c_ard_3-2-1_100083_2022-07-15_final.stac-item
2022-07-18 09:13:10	ga_ls9c_ard_3-2-1_089082_2022-07-17_final.stac-item
2022-07-25 09:21:04	ga_ls9c_ard_3-2-1_090086_2022-07-24_final.stac-item
2022-08-06 11:19:38	ga_ls9c_ard_3-2-1_110073_2022-08-06_final.stac-item
2022-08-08 09:35:11	ga_ls9c_ard_3-2-1_092090_2022-08-08_final.stac-item
2022-08-10 10:53:21	ga_ls9c_ard_3-2-1_106069_2022-08-10_final.stac-item
2022-08-19 10:46:26	ga_ls9c_ard_3-2-1_105067_2022-08-19_final.stac-item
2022-08-24 09:32:05	ga_ls9c_ard_3-2-1_092082_2022-08-24_final.stac-item
2022-08-30 10:28:18	ga_ls9c_ard_3-2-1_102068_2022-08-30_final.stac-item
2022-08-30 10:28:42	ga_ls9c_ard_3-2-1_102069_2022-08-30_final.stac-item
2022-09-05 11:36:05	ga_ls9c_ard_3-2-1_112083_2022-09-05_final.stac-item
2022-09-09 11:06:10	ga_ls9c_ard_3-2-1_108070_2022-09-09_final.stac-item
2022-09-10 10:15:21	ga_ls9c_ard_3-2-1_099082_2022-09-10_final.stac-item
2022-09-18 11:05:16	ga_ls9c_ard_3-2-1_107083_2022-09-18_final.stac-item
2022-09-27 09:23:03	ga_ls9c_ard_3-2-1_090090_2022-09-26_final.stac-item
2022-10-05 10:05:42	ga_ls9c_ard_3-2-1_098073_2022-10-05_final.stac-item
2022-10-06 10:46:33	ga_ls9c_ard_3-2-1_105067_2022-10-06_final.stac-item
2022-10-09 11:19:29	ga_ls9c_ard_3-2-1_110072_2022-10-09_final.stac-item
2022-10-13 10:54:00	ga_ls9c_ard_3-2-1_106070_2022-10-13_final.stac-item
2022-10-14 11:38:52	ga_ls9c_ard_3-2-1_113074_2022-10-14_final.stac-item
2022-10-19 10:19:21	ga_ls9c_ard_3-2-1_100076_2022-10-19_final.stac-item
2022-10-26 10:28:20	ga_ls9c_ard_3-2-1_101083_2022-10-26_final.stac-item
2022-10-28 10:11:34	ga_ls9c_ard_3-2-1_099072_2022-10-28_final.stac-item
2022-11-01 09:52:49	ga_ls9c_ard_3-2-1_095087_2022-11-01_final.stac-item
2022-11-20 10:19:22	ga_ls9c_ard_3-2-1_100076_2022-11-20_final.stac-item
2022-12-07 11:02:12	ga_ls9c_ard_3-2-1_107075_2022-12-07_final.stac-item
2022-12-10 09:58:37	ga_ls9c_ard_3-2-1_096086_2022-12-10_final.stac-item
2022-12-11 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-12-11_final.stac-item
2022-12-19 11:25:19	ga_ls9c_ard_3-2-1_111071_2022-12-19_final.stac-item
2023-01-06 09:40:29	ga_ls9c_ard_3-2-1_093087_2023-01-06_final.stac-item
2023-01-08 09:27:19	ga_ls9c_ard_3-2-1_091085_2023-01-07_final.stac-item
2023-01-13 11:20:43	ga_ls9c_ard_3-2-1_110075_2023-01-13_final.stac-item
2023-01-16 11:51:58	ga_ls9c_ard_3-2-1_115076_2023-01-16_final.stac-item
2023-01-19 10:42:44	ga_ls9c_ard_3-2-1_104073_2023-01-19_final.stac-item
2023-02-10 10:09:51	ga_ls9c_ard_3-2-1_098083_2023-02-10_final.stac-item
2023-02-12 11:36:45	ga_ls9c_ard_3-2-1_112084_2023-02-12_final.stac-item
2023-02-21 09:52:20	ga_ls9c_ard_3-2-1_095086_2023-02-21_final.stac-item
2023-02-21 11:25:37	ga_ls9c_ard_3-2-1_111072_2023-02-21_final.stac-item
2023-02-24 10:19:10	ga_ls9c_ard_3-2-1_100076_2023-02-24_final.stac-item
2023-02-25 11:02:02	ga_ls9c_ard_3-2-1_107075_2023-02-25_final.stac-item
2023-02-27 10:49:16	ga_ls9c_ard_3-2-1_105074_2023-02-27_final.stac-item
2023-03-02 11:20:33	ga_ls9c_ard_3-2-1_110075_2023-03-02_final.stac-item
2023-03-05 11:53:25	ga_ls9c_ard_3-2-1_115080_2023-03-05_final.stac-item
2023-03-07 09:57:45	ga_ls9c_ard_3-2-1_097069_2023-03-07_final.stac-item
2023-03-07 10:00:57	ga_ls9c_ard_3-2-1_097077_2023-03-07_final.stac-item
2023-03-11 11:12:40	ga_ls9c_ard_3-2-1_109071_2023-03-11_final.stac-item
2023-03-14 10:10:17	ga_ls9c_ard_3-2-1_098085_2023-03-14_final.stac-item
2023-04-07 10:55:55	ga_ls9c_ard_3-2-1_106076_2023-04-07_final.stac-item
2023-04-12 09:39:31	ga_ls9c_ard_3-2-1_093086_2023-04-12_final.stac-item
2023-04-19 09:40:52	ga_ls9c_ard_3-2-1_094074_2023-04-19_final.stac-item
2023-05-01 10:03:04	ga_ls9c_ard_3-2-1_098068_2023-05-01_final.stac-item
2023-05-13 10:28:06	ga_ls9c_ard_3-2-1_102069_2023-05-13_final.stac-item
2023-05-18 09:15:41	ga_ls9c_ard_3-2-1_089089_2023-05-17_final.stac-item
2023-05-23 09:32:57	ga_ls9c_ard_3-2-1_092086_2023-05-23_final.stac-item
2023-05-26 11:41:31	ga_ls9c_ard_3-2-1_113083_2023-05-26_final.stac-item
2023-06-25 10:09:38	ga_ls9c_ard_3-2-1_099070_2023-06-25_final.stac-item
2023-06-29 09:45:49	ga_ls9c_ard_3-2-1_095072_2023-06-29_final.stac-item
2023-06-30 10:27:55	ga_ls9c_ard_3-2-1_102069_2023-06-30_final.stac-item
2023-07-03 09:26:22	ga_ls9c_ard_3-2-1_091085_2023-07-02_final.stac-item
2023-07-05 09:12:02	ga_ls9c_ard_3-2-1_089080_2023-07-04_final.stac-item
2023-07-08 11:19:28	ga_ls9c_ard_3-2-1_110074_2023-07-08_final.stac-item
2023-07-16 10:27:40	ga_ls9c_ard_3-2-1_102068_2023-07-16_final.stac-item
2023-08-12 10:09:18	ga_ls9c_ard_3-2-1_099068_2023-08-12_final.stac-item
2023-08-13 09:20:28	ga_ls9c_ard_3-2-1_090085_2023-08-12_final.stac-item
2023-10-18 10:46:16	ga_ls9c_ard_3-2-1_104082_2023-10-18_final.stac-item
2023-11-02 09:58:06	ga_ls9c_ard_3-2-1_097070_2023-11-02_final.stac-item
2023-11-16 10:10:54	ga_ls9c_ard_3-2-1_099071_2023-11-16_final.stac-item
2023-11-17 09:21:17	ga_ls9c_ard_3-2-1_090086_2023-11-16_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