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

96 results

Time (local)	Label
2021-11-02 10:55:39	ga_ls9c_ard_3-2-1_106080_2021-11-02_final.stac-item
2021-12-11 11:06:17	ga_ls9c_ard_3-2-1_108070_2021-12-11_final.stac-item
2021-12-12 10:10:39	ga_ls9c_ard_3-2-1_099070_2021-12-12_final.stac-item
2021-12-15 10:43:31	ga_ls9c_ard_3-2-1_104075_2021-12-15_final.stac-item
2021-12-16 09:46:41	ga_ls9c_ard_3-2-1_095072_2021-12-16_final.stac-item
2021-12-19 10:19:35	ga_ls9c_ard_3-2-1_100077_2021-12-19_final.stac-item
2021-12-27 11:05:50	ga_ls9c_ard_3-2-1_108069_2021-12-27_final.stac-item
2022-01-03 09:39:31	ga_ls9c_ard_3-2-1_093085_2022-01-03_final.stac-item
2022-01-10 11:20:57	ga_ls9c_ard_3-2-1_110076_2022-01-10_final.stac-item
2022-01-12 09:33:41	ga_ls9c_ard_3-2-1_092086_2022-01-12_final.stac-item
2022-01-16 10:41:52	ga_ls9c_ard_3-2-1_104071_2022-01-16_final.stac-item
2022-01-25 10:37:43	ga_ls9c_ard_3-2-1_103076_2022-01-25_final.stac-item
2022-02-07 11:44:53	ga_ls9c_ard_3-2-1_114074_2022-02-07_final.stac-item
2022-02-11 11:19:20	ga_ls9c_ard_3-2-1_110072_2022-02-11_final.stac-item
2022-03-08 11:13:21	ga_ls9c_ard_3-2-1_109073_2022-03-08_final.stac-item
2022-03-22 11:25:16	ga_ls9c_ard_3-2-1_111072_2022-03-22_final.stac-item
2022-04-03 11:51:57	ga_ls9c_ard_3-2-1_115077_2022-04-03_final.stac-item
2022-04-14 09:52:27	ga_ls9c_ard_3-2-1_096072_2022-04-14_final.stac-item
2022-04-18 09:32:27	ga_ls9c_ard_3-2-1_092084_2022-04-18_final.stac-item
2022-04-20 10:53:46	ga_ls9c_ard_3-2-1_106071_2022-04-20_final.stac-item
2022-04-20 10:54:10	ga_ls9c_ard_3-2-1_106072_2022-04-20_final.stac-item
2022-04-29 09:13:52	ga_ls9c_ard_3-2-1_089084_2022-04-28_final.stac-item
2022-05-29 09:22:48	ga_ls9c_ard_3-2-1_091076_2022-05-28_final.stac-item
2022-05-30 10:02:52	ga_ls9c_ard_3-2-1_098068_2022-05-30_final.stac-item
2022-07-01 10:08:01	ga_ls9c_ard_3-2-1_098080_2022-07-01_final.stac-item
2022-07-03 11:31:20	ga_ls9c_ard_3-2-1_112072_2022-07-03_final.stac-item
2022-07-09 10:53:02	ga_ls9c_ard_3-2-1_106069_2022-07-09_final.stac-item
2022-07-18 09:14:22	ga_ls9c_ard_3-2-1_089085_2022-07-17_final.stac-item
2022-07-29 10:30:05	ga_ls9c_ard_3-2-1_102073_2022-07-29_final.stac-item
2022-09-10 11:52:14	ga_ls9c_ard_3-2-1_115077_2022-09-10_final.stac-item
2022-09-30 11:30:02	ga_ls9c_ard_3-2-1_111083_2022-09-30_final.stac-item
2022-10-08 10:40:12	ga_ls9c_ard_3-2-1_103082_2022-10-08_final.stac-item
2022-10-13 10:58:00	ga_ls9c_ard_3-2-1_106080_2022-10-13_final.stac-item
2022-10-16 11:26:08	ga_ls9c_ard_3-2-1_111073_2022-10-16_final.stac-item
2022-10-27 11:11:59	ga_ls9c_ard_3-2-1_108084_2022-10-27_final.stac-item
2022-11-01 09:47:13	ga_ls9c_ard_3-2-1_095073_2022-11-01_final.stac-item
2022-11-06 10:04:10	ga_ls9c_ard_3-2-1_098069_2022-11-06_final.stac-item
2022-11-08 11:34:42	ga_ls9c_ard_3-2-1_112079_2022-11-08_final.stac-item
2022-11-14 10:55:15	ga_ls9c_ard_3-2-1_106073_2022-11-14_final.stac-item
2022-12-01 10:04:22	ga_ls9c_ard_3-2-1_097085_2022-12-01_final.stac-item
2022-12-12 11:19:34	ga_ls9c_ard_3-2-1_110072_2022-12-12_final.stac-item
2022-12-16 09:20:20	ga_ls9c_ard_3-2-1_090083_2022-12-15_final.stac-item
2023-01-01 10:56:50	ga_ls9c_ard_3-2-1_106077_2023-01-01_final.stac-item
2023-01-09 11:47:28	ga_ls9c_ard_3-2-1_114080_2023-01-09_final.stac-item
2023-01-23 11:58:55	ga_ls9c_ard_3-2-1_116078_2023-01-23_final.stac-item
2023-01-24 11:05:18	ga_ls9c_ard_3-2-1_107083_2023-01-24_final.stac-item
2023-02-21 11:26:49	ga_ls9c_ard_3-2-1_111075_2023-02-21_final.stac-item
2023-03-15 10:52:21	ga_ls9c_ard_3-2-1_105082_2023-03-15_final.stac-item
2023-03-21 10:14:02	ga_ls9c_ard_3-2-1_099079_2023-03-21_final.stac-item
2023-04-10 09:50:18	ga_ls9c_ard_3-2-1_095082_2023-04-10_final.stac-item
2023-04-13 10:17:10	ga_ls9c_ard_3-2-1_100072_2023-04-13_final.stac-item
2023-04-14 09:27:55	ga_ls9c_ard_3-2-1_091088_2023-04-13_final.stac-item
2023-04-19 09:46:04	ga_ls9c_ard_3-2-1_094087_2023-04-19_final.stac-item
2023-04-27 10:28:15	ga_ls9c_ard_3-2-1_102069_2023-04-27_final.stac-item
2023-04-28 11:11:30	ga_ls9c_ard_3-2-1_109069_2023-04-28_final.stac-item
2023-04-28 11:16:17	ga_ls9c_ard_3-2-1_109081_2023-04-28_final.stac-item
2023-05-21 11:18:39	ga_ls9c_ard_3-2-1_110072_2023-05-21_final.stac-item
2023-06-11 09:58:33	ga_ls9c_ard_3-2-1_097073_2023-06-11_final.stac-item
2023-06-26 09:21:37	ga_ls9c_ard_3-2-1_090089_2023-06-25_final.stac-item
2023-07-08 09:45:46	ga_ls9c_ard_3-2-1_094087_2023-07-08_final.stac-item
2023-07-14 10:45:37	ga_ls9c_ard_3-2-1_104082_2023-07-14_final.stac-item
2023-07-27 11:52:01	ga_ls9c_ard_3-2-1_115078_2023-07-27_final.stac-item
2023-08-20 09:27:04	ga_ls9c_ard_3-2-1_091086_2023-08-19_final.stac-item
2023-08-31 09:07:04	ga_ls9c_ard_3-2-1_088082_2023-08-30_final.stac-item
2023-09-05 11:04:56	ga_ls9c_ard_3-2-1_107083_2023-09-05_final.stac-item
2023-09-15 09:58:27	ga_ls9c_ard_3-2-1_097071_2023-09-15_final.stac-item
2023-09-21 11:01:50	ga_ls9c_ard_3-2-1_107075_2023-09-21_final.stac-item
2023-09-26 11:19:07	ga_ls9c_ard_3-2-1_110072_2023-09-26_final.stac-item
2023-10-03 11:24:58	ga_ls9c_ard_3-2-1_111071_2023-10-03_final.stac-item
2023-10-11 10:34:26	ga_ls9c_ard_3-2-1_103068_2023-10-11_final.stac-item
2023-10-11 10:36:25	ga_ls9c_ard_3-2-1_103073_2023-10-11_final.stac-item
2023-10-11 10:38:01	ga_ls9c_ard_3-2-1_103077_2023-10-11_final.stac-item
2023-10-16 09:20:32	ga_ls9c_ard_3-2-1_090084_2023-10-15_final.stac-item
2023-10-23 11:05:12	ga_ls9c_ard_3-2-1_107083_2023-10-23_final.stac-item
2023-10-26 09:54:48	ga_ls9c_ard_3-2-1_096077_2023-10-26_final.stac-item
2023-11-01 09:22:50	ga_ls9c_ard_3-2-1_090090_2023-10-31_final.stac-item
2023-11-01 10:54:08	ga_ls9c_ard_3-2-1_106071_2023-11-01_final.stac-item
2023-11-03 09:06:27	ga_ls9c_ard_3-2-1_088080_2023-11-02_final.stac-item
2023-11-03 10:40:32	ga_ls9c_ard_3-2-1_104068_2023-11-03_final.stac-item
2023-11-24 09:24:46	ga_ls9c_ard_3-2-1_091079_2023-11-23_final.stac-item
2023-11-28 10:34:58	ga_ls9c_ard_3-2-1_103069_2023-11-28_final.stac-item
2023-12-03 10:55:04	ga_ls9c_ard_3-2-1_106073_2023-12-03_final.stac-item
2023-12-04 11:39:55	ga_ls9c_ard_3-2-1_113077_2023-12-04_final.stac-item
2023-12-04 11:41:07	ga_ls9c_ard_3-2-1_113080_2023-12-04_final.stac-item
2023-12-22 09:50:44	ga_ls9c_ard_3-2-1_095082_2023-12-22_final.stac-item
2023-12-27 11:46:33	ga_ls9c_ard_3-2-1_114078_2023-12-27_final.stac-item
2024-02-10 09:39:32	ga_ls9c_ard_3-2-1_093085_2024-02-10_final.stac-item
2024-02-10 09:39:56	ga_ls9c_ard_3-2-1_093086_2024-02-10_final.stac-item
2024-02-12 09:26:46	ga_ls9c_ard_3-2-1_091084_2024-02-11_final.stac-item
2024-02-19 09:30:49	ga_ls9c_ard_3-2-1_092079_2024-02-19_final.stac-item
2024-02-20 10:12:04	ga_ls9c_ard_3-2-1_099074_2024-02-20_final.stac-item
2024-04-03 11:36:16	ga_ls9c_ard_3-2-1_112084_2024-04-03_final.stac-item
2024-04-08 10:15:06	ga_ls9c_ard_3-2-1_099082_2024-04-08_final.stac-item
2024-04-12 11:26:25	ga_ls9c_ard_3-2-1_111075_2024-04-12_final.stac-item
2024-04-18 09:13:08	ga_ls9c_ard_3-2-1_089082_2024-04-17_final.stac-item
2024-05-08 10:25:29	ga_ls9c_ard_3-2-1_101078_2024-05-08_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