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

67 results

Time (local)	Label
2021-11-05 11:18:04	ga_ls9c_ard_3-2-1_109083_2021-11-05_final.stac-item
2021-12-09 11:19:52	ga_ls9c_ard_3-2-1_110073_2021-12-09_final.stac-item
2021-12-12 11:53:07	ga_ls9c_ard_3-2-1_115079_2021-12-12_final.stac-item
2021-12-17 10:28:20	ga_ls9c_ard_3-2-1_102068_2021-12-17_final.stac-item
2022-01-03 09:40:18	ga_ls9c_ard_3-2-1_093087_2022-01-03_final.stac-item
2022-01-03 11:14:00	ga_ls9c_ard_3-2-1_109074_2022-01-03_final.stac-item
2022-01-24 11:31:44	ga_ls9c_ard_3-2-1_112072_2022-01-24_final.stac-item
2022-02-01 10:42:18	ga_ls9c_ard_3-2-1_104072_2022-02-01_final.stac-item
2022-02-02 09:52:40	ga_ls9c_ard_3-2-1_095087_2022-02-02_final.stac-item
2022-02-09 09:52:26	ga_ls9c_ard_3-2-1_096071_2022-02-09_final.stac-item
2022-03-08 11:12:33	ga_ls9c_ard_3-2-1_109071_2022-03-08_final.stac-item
2022-03-09 10:19:20	ga_ls9c_ard_3-2-1_100077_2022-03-09_final.stac-item
2022-04-10 11:57:41	ga_ls9c_ard_3-2-1_116076_2022-04-10_final.stac-item
2022-04-12 11:47:18	ga_ls9c_ard_3-2-1_114081_2022-04-12_final.stac-item
2022-04-29 10:48:45	ga_ls9c_ard_3-2-1_105074_2022-04-29_final.stac-item
2022-05-18 09:40:10	ga_ls9c_ard_3-2-1_094073_2022-05-18_final.stac-item
2022-06-07 09:20:38	ga_ls9c_ard_3-2-1_090086_2022-06-06_final.stac-item
2022-06-18 10:35:30	ga_ls9c_ard_3-2-1_103072_2022-06-18_final.stac-item
2022-06-21 09:27:38	ga_ls9c_ard_3-2-1_092072_2022-06-20_final.stac-item
2022-06-23 10:55:49	ga_ls9c_ard_3-2-1_106076_2022-06-23_final.stac-item
2022-07-21 09:46:07	ga_ls9c_ard_3-2-1_094087_2022-07-21_final.stac-item
2022-07-30 11:13:22	ga_ls9c_ard_3-2-1_109073_2022-07-30_final.stac-item
2022-08-11 11:38:37	ga_ls9c_ard_3-2-1_113074_2022-08-11_final.stac-item
2022-09-02 11:00:00	ga_ls9c_ard_3-2-1_107070_2022-09-02_final.stac-item
2022-09-07 09:40:51	ga_ls9c_ard_3-2-1_094073_2022-09-07_final.stac-item
2022-09-27 10:56:20	ga_ls9c_ard_3-2-1_106076_2022-09-27_final.stac-item
2022-10-10 10:28:16	ga_ls9c_ard_3-2-1_101083_2022-10-10_final.stac-item
2022-10-20 11:01:49	ga_ls9c_ard_3-2-1_107074_2022-10-20_final.stac-item
2022-10-22 09:13:46	ga_ls9c_ard_3-2-1_089082_2022-10-21_final.stac-item
2022-10-27 09:32:18	ga_ls9c_ard_3-2-1_092082_2022-10-27_final.stac-item
2022-10-29 09:21:08	ga_ls9c_ard_3-2-1_090085_2022-10-28_final.stac-item
2022-11-30 10:55:12	ga_ls9c_ard_3-2-1_106073_2022-11-30_final.stac-item
2022-12-11 10:36:18	ga_ls9c_ard_3-2-1_103072_2022-12-11_final.stac-item
2022-12-14 11:10:23	ga_ls9c_ard_3-2-1_108080_2022-12-14_final.stac-item
2023-01-09 11:47:52	ga_ls9c_ard_3-2-1_114081_2023-01-09_final.stac-item
2023-01-14 10:24:17	ga_ls9c_ard_3-2-1_101073_2023-01-14_final.stac-item
2023-02-08 10:19:01	ga_ls9c_ard_3-2-1_100075_2023-02-08_final.stac-item
2023-02-10 11:47:56	ga_ls9c_ard_3-2-1_114081_2023-02-10_final.stac-item
2023-03-07 09:58:09	ga_ls9c_ard_3-2-1_097070_2023-03-07_final.stac-item
2023-03-27 11:17:19	ga_ls9c_ard_3-2-1_109083_2023-03-27_final.stac-item
2023-04-06 10:15:28	ga_ls9c_ard_3-2-1_099083_2023-04-06_final.stac-item
2023-04-19 11:19:22	ga_ls9c_ard_3-2-1_110073_2023-04-19_final.stac-item
2023-05-08 10:15:10	ga_ls9c_ard_3-2-1_099083_2023-05-08_final.stac-item
2023-05-13 10:27:42	ga_ls9c_ard_3-2-1_102068_2023-05-13_final.stac-item
2023-05-20 10:37:23	ga_ls9c_ard_3-2-1_103077_2023-05-20_final.stac-item
2023-06-01 09:21:57	ga_ls9c_ard_3-2-1_091074_2023-05-31_final.stac-item
2023-06-08 09:31:40	ga_ls9c_ard_3-2-1_092083_2023-06-08_final.stac-item
2023-06-15 09:33:46	ga_ls9c_ard_3-2-1_093073_2023-06-15_final.stac-item
2023-06-17 09:21:48	ga_ls9c_ard_3-2-1_091074_2023-06-16_final.stac-item
2023-06-17 09:27:47	ga_ls9c_ard_3-2-1_091089_2023-06-16_final.stac-item
2023-07-03 10:59:16	ga_ls9c_ard_3-2-1_107070_2023-07-03_final.stac-item
2023-08-06 09:14:40	ga_ls9c_ard_3-2-1_089086_2023-08-05_final.stac-item
2023-08-11 09:32:49	ga_ls9c_ard_3-2-1_092085_2023-08-11_final.stac-item
2023-08-16 09:52:09	ga_ls9c_ard_3-2-1_095087_2023-08-16_final.stac-item
2023-09-05 09:21:40	ga_ls9c_ard_3-2-1_091072_2023-09-04_final.stac-item
2023-09-17 09:50:52	ga_ls9c_ard_3-2-1_095083_2023-09-17_final.stac-item
2023-10-23 09:21:56	ga_ls9c_ard_3-2-1_091072_2023-10-22_final.stac-item
2023-11-18 10:01:46	ga_ls9c_ard_3-2-1_097079_2023-11-18_final.stac-item
2023-11-24 09:27:58	ga_ls9c_ard_3-2-1_091087_2023-11-23_final.stac-item
2023-11-24 11:01:39	ga_ls9c_ard_3-2-1_107074_2023-11-24_final.stac-item
2023-12-30 10:36:09	ga_ls9c_ard_3-2-1_103072_2023-12-30_final.stac-item
2024-02-03 09:28:10	ga_ls9c_ard_3-2-1_092072_2024-02-02_final.stac-item
2024-02-12 09:22:46	ga_ls9c_ard_3-2-1_091074_2024-02-11_final.stac-item
2024-03-13 09:40:35	ga_ls9c_ard_3-2-1_093088_2024-03-13_final.stac-item
2024-03-25 09:58:03	ga_ls9c_ard_3-2-1_097070_2024-03-25_final.stac-item
2024-04-05 09:41:25	ga_ls9c_ard_3-2-1_094075_2024-04-05_final.stac-item
2024-04-16 11:02:02	ga_ls9c_ard_3-2-1_107076_2024-04-16_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