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

81 results

Time (local)	Label
2021-11-10 09:38:18	ga_ls9c_ard_3-2-1_094074_2021-11-10_final.stac-item
2021-11-23 10:01:38	ga_ls9c_ard_3-2-1_098067_2021-11-23_final.stac-item
2021-12-04 09:22:53	ga_ls9c_ard_3-2-1_091074_2021-12-03_final.stac-item
2021-12-06 09:14:54	ga_ls9c_ard_3-2-1_089085_2021-12-05_final.stac-item
2022-01-19 11:11:59	ga_ls9c_ard_3-2-1_109069_2022-01-19_final.stac-item
2022-01-21 11:00:02	ga_ls9c_ard_3-2-1_107070_2022-01-21_final.stac-item
2022-01-26 09:41:18	ga_ls9c_ard_3-2-1_094074_2022-01-26_final.stac-item
2022-02-21 10:19:26	ga_ls9c_ard_3-2-1_100077_2022-02-21_final.stac-item
2022-03-06 11:24:07	ga_ls9c_ard_3-2-1_111069_2022-03-06_final.stac-item
2022-03-24 09:33:37	ga_ls9c_ard_3-2-1_093071_2022-03-24_final.stac-item
2022-04-09 11:11:38	ga_ls9c_ard_3-2-1_109069_2022-04-09_final.stac-item
2022-04-10 10:16:48	ga_ls9c_ard_3-2-1_100071_2022-04-10_final.stac-item
2022-04-21 09:56:32	ga_ls9c_ard_3-2-1_097067_2022-04-21_final.stac-item
2022-05-09 11:24:34	ga_ls9c_ard_3-2-1_111071_2022-05-09_final.stac-item
2022-05-21 10:10:14	ga_ls9c_ard_3-2-1_099071_2022-05-21_final.stac-item
2022-06-10 09:51:56	ga_ls9c_ard_3-2-1_095087_2022-06-10_final.stac-item
2022-06-12 11:17:18	ga_ls9c_ard_3-2-1_109084_2022-06-12_final.stac-item
2022-07-02 10:48:52	ga_ls9c_ard_3-2-1_105074_2022-07-02_final.stac-item
2022-08-07 10:27:36	ga_ls9c_ard_3-2-1_101082_2022-08-07_final.stac-item
2022-08-18 10:09:57	ga_ls9c_ard_3-2-1_098084_2022-08-18_final.stac-item
2022-08-24 11:08:10	ga_ls9c_ard_3-2-1_108075_2022-08-24_final.stac-item
2022-09-09 09:34:04	ga_ls9c_ard_3-2-1_092087_2022-09-09_final.stac-item
2022-09-10 10:09:22	ga_ls9c_ard_3-2-1_099067_2022-09-10_final.stac-item
2022-10-06 10:49:21	ga_ls9c_ard_3-2-1_105074_2022-10-06_final.stac-item
2022-10-07 09:58:31	ga_ls9c_ard_3-2-1_096086_2022-10-07_final.stac-item
2022-10-18 09:34:53	ga_ls9c_ard_3-2-1_093073_2022-10-18_final.stac-item
2022-10-23 11:32:43	ga_ls9c_ard_3-2-1_112074_2022-10-23_final.stac-item
2022-10-29 09:21:56	ga_ls9c_ard_3-2-1_090087_2022-10-28_final.stac-item
2022-11-08 11:36:42	ga_ls9c_ard_3-2-1_112084_2022-11-08_final.stac-item
2022-11-21 09:22:33	ga_ls9c_ard_3-2-1_091073_2022-11-20_final.stac-item
2022-12-15 10:14:22	ga_ls9c_ard_3-2-1_099079_2022-12-15_final.stac-item
2022-12-16 10:53:14	ga_ls9c_ard_3-2-1_106068_2022-12-16_final.stac-item
2023-01-24 09:22:02	ga_ls9c_ard_3-2-1_091072_2023-01-23_final.stac-item
2023-01-31 09:28:19	ga_ls9c_ard_3-2-1_092072_2023-01-30_final.stac-item
2023-01-31 11:08:00	ga_ls9c_ard_3-2-1_108074_2023-01-31_final.stac-item
2023-02-07 09:34:57	ga_ls9c_ard_3-2-1_093073_2023-02-07_final.stac-item
2023-02-16 11:07:59	ga_ls9c_ard_3-2-1_108074_2023-02-16_final.stac-item
2023-03-17 10:39:35	ga_ls9c_ard_3-2-1_103081_2023-03-17_final.stac-item
2023-03-27 11:14:08	ga_ls9c_ard_3-2-1_109075_2023-03-27_final.stac-item
2023-04-28 09:39:00	ga_ls9c_ard_3-2-1_093085_2023-04-28_final.stac-item
2023-05-30 09:33:07	ga_ls9c_ard_3-2-1_093071_2023-05-30_final.stac-item
2023-06-07 10:24:55	ga_ls9c_ard_3-2-1_101077_2023-06-07_final.stac-item
2023-06-09 11:52:37	ga_ls9c_ard_3-2-1_115080_2023-06-09_final.stac-item
2023-06-16 10:18:37	ga_ls9c_ard_3-2-1_100077_2023-06-16_final.stac-item
2023-07-06 11:31:48	ga_ls9c_ard_3-2-1_112074_2023-07-06_final.stac-item
2023-07-08 09:39:23	ga_ls9c_ard_3-2-1_094071_2023-07-08_final.stac-item
2023-07-11 10:13:06	ga_ls9c_ard_3-2-1_099078_2023-07-11_final.stac-item
2023-07-16 10:29:40	ga_ls9c_ard_3-2-1_102073_2023-07-16_final.stac-item
2023-07-19 09:22:05	ga_ls9c_ard_3-2-1_091074_2023-07-18_final.stac-item
2023-07-24 11:19:53	ga_ls9c_ard_3-2-1_110075_2023-07-24_final.stac-item
2023-07-28 10:55:37	ga_ls9c_ard_3-2-1_106076_2023-07-28_final.stac-item
2023-08-13 09:16:52	ga_ls9c_ard_3-2-1_090076_2023-08-12_final.stac-item
2023-08-26 10:27:22	ga_ls9c_ard_3-2-1_101082_2023-08-26_final.stac-item
2023-08-27 11:07:51	ga_ls9c_ard_3-2-1_108075_2023-08-27_final.stac-item
2023-09-07 10:49:01	ga_ls9c_ard_3-2-1_105074_2023-09-07_final.stac-item
2023-09-17 11:24:34	ga_ls9c_ard_3-2-1_111070_2023-09-17_final.stac-item
2023-09-19 11:11:49	ga_ls9c_ard_3-2-1_109069_2023-09-19_final.stac-item
2023-10-05 09:34:09	ga_ls9c_ard_3-2-1_093072_2023-10-05_final.stac-item
2023-10-05 09:34:33	ga_ls9c_ard_3-2-1_093073_2023-10-05_final.stac-item
2023-10-19 11:30:20	ga_ls9c_ard_3-2-1_111084_2023-10-19_final.stac-item
2023-11-09 10:03:08	ga_ls9c_ard_3-2-1_098067_2023-11-09_final.stac-item
2023-12-05 09:07:47	ga_ls9c_ard_3-2-1_088083_2023-12-04_final.stac-item
2023-12-12 10:46:53	ga_ls9c_ard_3-2-1_105068_2023-12-12_final.stac-item
2023-12-26 09:23:37	ga_ls9c_ard_3-2-1_091076_2023-12-25_final.stac-item
2024-01-02 11:07:49	ga_ls9c_ard_3-2-1_108074_2024-01-02_final.stac-item
2024-01-03 11:53:28	ga_ls9c_ard_3-2-1_115080_2024-01-03_final.stac-item
2024-01-13 09:16:47	ga_ls9c_ard_3-2-1_089090_2024-01-12_final.stac-item
2024-01-15 10:35:20	ga_ls9c_ard_3-2-1_103070_2024-01-15_final.stac-item
2024-02-04 11:53:31	ga_ls9c_ard_3-2-1_115080_2024-02-04_final.stac-item
2024-02-10 09:34:45	ga_ls9c_ard_3-2-1_093073_2024-02-10_final.stac-item
2024-02-17 09:40:02	ga_ls9c_ard_3-2-1_094071_2024-02-17_final.stac-item
2024-03-02 09:58:20	ga_ls9c_ard_3-2-1_096086_2024-03-02_final.stac-item
2024-03-11 09:46:35	ga_ls9c_ard_3-2-1_095072_2024-03-11_final.stac-item
2024-03-21 10:24:01	ga_ls9c_ard_3-2-1_101073_2024-03-21_final.stac-item
2024-03-26 09:07:36	ga_ls9c_ard_3-2-1_088083_2024-03-25_final.stac-item
2024-04-01 10:04:09	ga_ls9c_ard_3-2-1_098070_2024-04-01_final.stac-item
2024-04-19 09:57:58	ga_ls9c_ard_3-2-1_096086_2024-04-19_final.stac-item
2024-04-24 10:12:44	ga_ls9c_ard_3-2-1_099077_2024-04-24_final.stac-item
2024-04-26 09:56:48	ga_ls9c_ard_3-2-1_097068_2024-04-26_final.stac-item
2024-04-26 10:01:11	ga_ls9c_ard_3-2-1_097079_2024-04-26_final.stac-item
2024-05-10 11:52:48	ga_ls9c_ard_3-2-1_115080_2024-05-10_nrt.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