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
2021-11-09 10:39:23	ga_ls9c_ard_3-2-1_103080_2021-11-09_final.stac-item
2021-11-14 10:41:51	ga_ls9c_ard_3-2-1_103080_2021-11-14_final.stac-item
2021-11-20 09:42:49	ga_ls9c_ard_3-2-1_094073_2021-11-20_final.stac-item
2021-12-07 09:58:33	ga_ls9c_ard_3-2-1_096086_2021-12-07_final.stac-item
2021-12-29 09:21:23	ga_ls9c_ard_3-2-1_090086_2021-12-28_final.stac-item
2022-01-01 09:46:17	ga_ls9c_ard_3-2-1_095071_2022-01-01_final.stac-item
2022-02-12 10:28:06	ga_ls9c_ard_3-2-1_101083_2022-02-12_final.stac-item
2022-04-20 09:21:40	ga_ls9c_ard_3-2-1_090088_2022-04-19_final.stac-item
2022-05-15 10:50:59	ga_ls9c_ard_3-2-1_105080_2022-05-15_final.stac-item
2022-05-22 09:22:12	ga_ls9c_ard_3-2-1_090090_2022-05-21_final.stac-item
2022-06-02 10:34:11	ga_ls9c_ard_3-2-1_103069_2022-06-02_final.stac-item
2022-06-05 11:07:29	ga_ls9c_ard_3-2-1_108075_2022-06-05_final.stac-item
2022-06-16 10:50:14	ga_ls9c_ard_3-2-1_105078_2022-06-16_final.stac-item
2022-06-17 09:54:37	ga_ls9c_ard_3-2-1_096078_2022-06-17_final.stac-item
2022-06-22 10:09:20	ga_ls9c_ard_3-2-1_099068_2022-06-22_final.stac-item
2022-07-03 09:54:51	ga_ls9c_ard_3-2-1_096078_2022-07-03_final.stac-item
2022-07-18 10:51:15	ga_ls9c_ard_3-2-1_105080_2022-07-18_final.stac-item
2022-08-01 09:22:09	ga_ls9c_ard_3-2-1_091073_2022-07-31_final.stac-item
2022-08-06 09:41:08	ga_ls9c_ard_3-2-1_094074_2022-08-06_final.stac-item
2022-08-22 11:22:55	ga_ls9c_ard_3-2-1_110081_2022-08-22_final.stac-item
2022-08-29 11:26:19	ga_ls9c_ard_3-2-1_111074_2022-08-29_final.stac-item
2022-09-07 09:43:14	ga_ls9c_ard_3-2-1_094079_2022-09-07_final.stac-item
2022-09-11 10:57:49	ga_ls9c_ard_3-2-1_106080_2022-09-11_final.stac-item
2022-09-12 11:41:30	ga_ls9c_ard_3-2-1_113081_2022-09-12_final.stac-item
2022-09-13 10:41:30	ga_ls9c_ard_3-2-1_104070_2022-09-13_final.stac-item
2022-09-27 10:58:44	ga_ls9c_ard_3-2-1_106082_2022-09-27_final.stac-item
2022-10-05 10:09:41	ga_ls9c_ard_3-2-1_098083_2022-10-05_final.stac-item
2022-10-09 11:24:40	ga_ls9c_ard_3-2-1_110085_2022-10-09_final.stac-item
2022-10-21 10:09:23	ga_ls9c_ard_3-2-1_098082_2022-10-21_final.stac-item
2022-10-29 10:58:25	ga_ls9c_ard_3-2-1_106081_2022-10-29_final.stac-item
2022-11-06 10:10:09	ga_ls9c_ard_3-2-1_098084_2022-11-06_final.stac-item
2022-11-10 09:44:16	ga_ls9c_ard_3-2-1_094081_2022-11-10_final.stac-item
2022-11-14 09:21:34	ga_ls9c_ard_3-2-1_090086_2022-11-13_final.stac-item
2022-11-20 10:22:10	ga_ls9c_ard_3-2-1_100083_2022-11-20_final.stac-item
2022-11-24 09:54:38	ga_ls9c_ard_3-2-1_096076_2022-11-24_final.stac-item
2022-12-02 10:46:01	ga_ls9c_ard_3-2-1_104081_2022-12-02_final.stac-item
2022-12-03 09:47:13	ga_ls9c_ard_3-2-1_095073_2022-12-03_final.stac-item
2022-12-03 09:50:48	ga_ls9c_ard_3-2-1_095082_2022-12-03_final.stac-item
2022-12-04 10:31:17	ga_ls9c_ard_3-2-1_102075_2022-12-04_final.stac-item
2022-12-12 11:22:21	ga_ls9c_ard_3-2-1_110079_2022-12-12_final.stac-item
2022-12-19 09:50:49	ga_ls9c_ard_3-2-1_095082_2022-12-19_final.stac-item
2022-12-21 09:40:51	ga_ls9c_ard_3-2-1_093088_2022-12-21_final.stac-item
2022-12-28 11:20:20	ga_ls9c_ard_3-2-1_110074_2022-12-28_final.stac-item
2022-12-30 09:31:54	ga_ls9c_ard_3-2-1_092081_2022-12-30_final.stac-item
2022-12-30 09:32:42	ga_ls9c_ard_3-2-1_092083_2022-12-30_final.stac-item
2022-12-31 10:15:10	ga_ls9c_ard_3-2-1_099081_2022-12-31_final.stac-item
2023-01-04 09:49:39	ga_ls9c_ard_3-2-1_095079_2023-01-04_final.stac-item
2023-01-08 11:01:25	ga_ls9c_ard_3-2-1_107073_2023-01-08_final.stac-item
2023-01-15 09:31:26	ga_ls9c_ard_3-2-1_092080_2023-01-15_final.stac-item
2023-01-15 09:34:14	ga_ls9c_ard_3-2-1_092087_2023-01-15_final.stac-item
2023-01-16 10:13:53	ga_ls9c_ard_3-2-1_099078_2023-01-16_final.stac-item
2023-02-01 10:12:47	ga_ls9c_ard_3-2-1_099075_2023-02-01_final.stac-item
2023-02-02 10:55:40	ga_ls9c_ard_3-2-1_106074_2023-02-02_final.stac-item
2023-02-02 10:56:27	ga_ls9c_ard_3-2-1_106076_2023-02-02_final.stac-item
2023-02-04 10:46:07	ga_ls9c_ard_3-2-1_104081_2023-02-04_final.stac-item
2023-02-07 09:35:45	ga_ls9c_ard_3-2-1_093075_2023-02-07_final.stac-item
2023-02-07 09:38:09	ga_ls9c_ard_3-2-1_093081_2023-02-07_final.stac-item
2023-02-08 10:18:13	ga_ls9c_ard_3-2-1_100073_2023-02-08_final.stac-item
2023-02-14 09:44:17	ga_ls9c_ard_3-2-1_094081_2023-02-14_final.stac-item
2023-03-01 10:39:18	ga_ls9c_ard_3-2-1_103080_2023-03-01_final.stac-item
2023-03-02 11:19:22	ga_ls9c_ard_3-2-1_110072_2023-03-02_final.stac-item
2023-03-02 11:20:57	ga_ls9c_ard_3-2-1_110076_2023-03-02_final.stac-item
2023-03-13 09:27:49	ga_ls9c_ard_3-2-1_091087_2023-03-12_final.stac-item
2023-03-30 11:44:34	ga_ls9c_ard_3-2-1_114074_2023-03-30_final.stac-item
2023-04-03 09:46:10	ga_ls9c_ard_3-2-1_094087_2023-04-03_final.stac-item
2023-04-06 10:10:16	ga_ls9c_ard_3-2-1_099070_2023-04-06_final.stac-item
2023-05-05 11:20:21	ga_ls9c_ard_3-2-1_110076_2023-05-05_final.stac-item
2023-05-07 11:08:24	ga_ls9c_ard_3-2-1_108077_2023-05-07_final.stac-item
2023-05-12 09:48:26	ga_ls9c_ard_3-2-1_095078_2023-05-12_final.stac-item
2023-05-14 09:34:28	ga_ls9c_ard_3-2-1_093074_2023-05-14_final.stac-item
2023-05-31 11:58:03	ga_ls9c_ard_3-2-1_116078_2023-05-31_final.stac-item
2023-06-24 11:07:40	ga_ls9c_ard_3-2-1_108076_2023-06-24_final.stac-item
2023-06-25 10:15:14	ga_ls9c_ard_3-2-1_099084_2023-06-25_final.stac-item
2023-07-15 11:26:05	ga_ls9c_ard_3-2-1_111075_2023-07-15_final.stac-item
2023-07-17 09:36:03	ga_ls9c_ard_3-2-1_093078_2023-07-17_final.stac-item
2023-07-21 10:49:48	ga_ls9c_ard_3-2-1_105077_2023-07-21_final.stac-item
2023-07-28 10:57:13	ga_ls9c_ard_3-2-1_106080_2023-07-28_final.stac-item
2023-07-28 10:58:25	ga_ls9c_ard_3-2-1_106083_2023-07-28_final.stac-item
2023-07-31 09:48:29	ga_ls9c_ard_3-2-1_095078_2023-07-31_final.stac-item
2023-08-02 11:15:02	ga_ls9c_ard_3-2-1_109078_2023-08-02_final.stac-item
2023-08-08 10:34:25	ga_ls9c_ard_3-2-1_103069_2023-08-08_final.stac-item
2023-08-13 10:52:58	ga_ls9c_ard_3-2-1_106069_2023-08-13_final.stac-item
2023-10-14 09:31:16	ga_ls9c_ard_3-2-1_092080_2023-10-14_final.stac-item
2023-10-14 09:31:40	ga_ls9c_ard_3-2-1_092081_2023-10-14_final.stac-item
2023-10-14 11:08:10	ga_ls9c_ard_3-2-1_108075_2023-10-14_final.stac-item
2023-10-18 10:43:04	ga_ls9c_ard_3-2-1_104074_2023-10-18_final.stac-item
2023-10-19 11:24:20	ga_ls9c_ard_3-2-1_111069_2023-10-19_final.stac-item
2023-10-23 11:00:01	ga_ls9c_ard_3-2-1_107070_2023-10-23_final.stac-item
2023-10-25 10:51:38	ga_ls9c_ard_3-2-1_105080_2023-10-25_final.stac-item
2023-10-28 11:20:54	ga_ls9c_ard_3-2-1_110076_2023-10-28_final.stac-item
2023-10-29 10:24:52	ga_ls9c_ard_3-2-1_101075_2023-10-29_final.stac-item
2023-10-30 09:31:14	ga_ls9c_ard_3-2-1_092080_2023-10-30_final.stac-item
2023-11-03 10:40:32	ga_ls9c_ard_3-2-1_104068_2023-11-03_final.stac-item
2023-11-03 10:45:44	ga_ls9c_ard_3-2-1_104081_2023-11-03_final.stac-item
2023-11-15 09:32:25	ga_ls9c_ard_3-2-1_092083_2023-11-15_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 10:56:10	ga_ls9c_ard_3-2-1_106076_2023-11-17_final.stac-item
2023-11-24 11:03:15	ga_ls9c_ard_3-2-1_107078_2023-11-24_final.stac-item
2023-11-24 11:05:39	ga_ls9c_ard_3-2-1_107084_2023-11-24_final.stac-item
2023-11-25 10:05:15	ga_ls9c_ard_3-2-1_098072_2023-11-25_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