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
2021-11-03 09:56:57	ga_ls9c_ard_3-2-1_096080_2021-11-03_final.stac-item
2021-11-08 09:59:26	ga_ls9c_ard_3-2-1_097080_2021-11-08_final.stac-item
2021-12-05 11:47:49	ga_ls9c_ard_3-2-1_114081_2021-12-05_final.stac-item
2021-12-16 11:29:09	ga_ls9c_ard_3-2-1_111081_2021-12-16_final.stac-item
2021-12-17 10:33:31	ga_ls9c_ard_3-2-1_102081_2021-12-17_final.stac-item
2021-12-21 11:47:42	ga_ls9c_ard_3-2-1_114081_2021-12-21_final.stac-item
2022-01-02 10:33:32	ga_ls9c_ard_3-2-1_102081_2022-01-02_final.stac-item
2022-01-06 11:47:41	ga_ls9c_ard_3-2-1_114081_2022-01-06_final.stac-item
2022-01-18 10:33:30	ga_ls9c_ard_3-2-1_102081_2022-01-18_final.stac-item
2022-01-22 11:47:41	ga_ls9c_ard_3-2-1_114081_2022-01-22_final.stac-item
2022-02-03 10:33:32	ga_ls9c_ard_3-2-1_102081_2022-02-03_final.stac-item
2022-02-07 11:47:41	ga_ls9c_ard_3-2-1_114081_2022-02-07_final.stac-item
2022-02-19 10:33:25	ga_ls9c_ard_3-2-1_102081_2022-02-19_final.stac-item
2022-02-23 11:47:32	ga_ls9c_ard_3-2-1_114081_2022-02-23_final.stac-item
2022-03-07 10:33:17	ga_ls9c_ard_3-2-1_102081_2022-03-07_final.stac-item
2022-03-11 11:47:27	ga_ls9c_ard_3-2-1_114081_2022-03-11_final.stac-item
2022-03-23 10:33:14	ga_ls9c_ard_3-2-1_102081_2022-03-23_final.stac-item
2022-03-27 11:47:22	ga_ls9c_ard_3-2-1_114081_2022-03-27_final.stac-item
2022-04-08 10:33:10	ga_ls9c_ard_3-2-1_102081_2022-04-08_final.stac-item
2022-04-12 11:47:18	ga_ls9c_ard_3-2-1_114081_2022-04-12_final.stac-item
2022-04-24 10:33:01	ga_ls9c_ard_3-2-1_102081_2022-04-24_final.stac-item
2022-04-28 11:47:10	ga_ls9c_ard_3-2-1_114081_2022-04-28_final.stac-item
2022-05-10 10:32:55	ga_ls9c_ard_3-2-1_102081_2022-05-10_final.stac-item
2022-05-14 11:47:02	ga_ls9c_ard_3-2-1_114081_2022-05-14_final.stac-item
2022-05-27 11:15:37	ga_ls9c_ard_3-2-1_109080_2022-05-27_final.stac-item
2022-05-30 11:46:56	ga_ls9c_ard_3-2-1_114081_2022-05-30_final.stac-item
2022-06-01 09:55:18	ga_ls9c_ard_3-2-1_096080_2022-06-01_final.stac-item
2022-06-08 10:01:30	ga_ls9c_ard_3-2-1_097080_2022-06-08_final.stac-item
2022-06-11 10:32:49	ga_ls9c_ard_3-2-1_102081_2022-06-11_final.stac-item
2022-06-15 11:47:02	ga_ls9c_ard_3-2-1_114081_2022-06-15_final.stac-item
2022-06-17 09:55:25	ga_ls9c_ard_3-2-1_096080_2022-06-17_final.stac-item
2022-06-26 11:28:46	ga_ls9c_ard_3-2-1_111081_2022-06-26_final.stac-item
2022-07-01 11:47:18	ga_ls9c_ard_3-2-1_114081_2022-07-01_final.stac-item
2022-07-12 09:49:25	ga_ls9c_ard_3-2-1_095080_2022-07-12_final.stac-item
2022-07-12 11:28:42	ga_ls9c_ard_3-2-1_111081_2022-07-12_final.stac-item
2022-07-14 11:15:55	ga_ls9c_ard_3-2-1_109080_2022-07-14_final.stac-item
2022-07-17 11:47:15	ga_ls9c_ard_3-2-1_114081_2022-07-17_final.stac-item
2022-07-28 11:28:54	ga_ls9c_ard_3-2-1_111081_2022-07-28_final.stac-item
2022-08-02 11:47:30	ga_ls9c_ard_3-2-1_114081_2022-08-02_final.stac-item
2022-08-13 11:29:04	ga_ls9c_ard_3-2-1_111081_2022-08-13_final.stac-item
2022-08-14 10:33:27	ga_ls9c_ard_3-2-1_102081_2022-08-14_final.stac-item
2022-08-18 11:47:38	ga_ls9c_ard_3-2-1_114081_2022-08-18_final.stac-item
2022-08-29 11:29:07	ga_ls9c_ard_3-2-1_111081_2022-08-29_final.stac-item
2022-08-31 11:16:21	ga_ls9c_ard_3-2-1_109080_2022-08-31_final.stac-item
2022-09-03 11:47:39	ga_ls9c_ard_3-2-1_114081_2022-09-03_final.stac-item
2022-09-14 09:49:52	ga_ls9c_ard_3-2-1_095080_2022-09-14_final.stac-item
2022-09-14 11:29:10	ga_ls9c_ard_3-2-1_111081_2022-09-14_final.stac-item
2022-09-15 10:33:33	ga_ls9c_ard_3-2-1_102081_2022-09-15_final.stac-item
2022-09-19 11:47:44	ga_ls9c_ard_3-2-1_114081_2022-09-19_final.stac-item
2022-09-30 11:29:14	ga_ls9c_ard_3-2-1_111081_2022-09-30_final.stac-item
2022-10-05 11:47:46	ga_ls9c_ard_3-2-1_114081_2022-10-05_final.stac-item
2022-10-16 11:29:19	ga_ls9c_ard_3-2-1_111081_2022-10-16_final.stac-item
2022-10-21 11:47:53	ga_ls9c_ard_3-2-1_114081_2022-10-21_final.stac-item
2022-11-01 11:29:18	ga_ls9c_ard_3-2-1_111081_2022-11-01_final.stac-item
2022-11-02 10:33:40	ga_ls9c_ard_3-2-1_102081_2022-11-02_final.stac-item
2022-11-06 11:47:51	ga_ls9c_ard_3-2-1_114081_2022-11-06_final.stac-item
2022-11-17 11:29:21	ga_ls9c_ard_3-2-1_111081_2022-11-17_final.stac-item
2022-11-22 11:47:53	ga_ls9c_ard_3-2-1_114081_2022-11-22_final.stac-item
2022-12-03 11:29:18	ga_ls9c_ard_3-2-1_111081_2022-12-03_final.stac-item
2022-12-04 10:33:41	ga_ls9c_ard_3-2-1_102081_2022-12-04_final.stac-item
2022-12-08 11:47:52	ga_ls9c_ard_3-2-1_114081_2022-12-08_final.stac-item
2022-12-19 11:29:18	ga_ls9c_ard_3-2-1_111081_2022-12-19_final.stac-item
2022-12-20 10:33:41	ga_ls9c_ard_3-2-1_102081_2022-12-20_final.stac-item
2022-12-24 11:47:49	ga_ls9c_ard_3-2-1_114081_2022-12-24_final.stac-item
2023-01-04 11:29:20	ga_ls9c_ard_3-2-1_111081_2023-01-04_final.stac-item
2023-01-05 10:33:43	ga_ls9c_ard_3-2-1_102081_2023-01-05_final.stac-item
2023-01-09 11:47:52	ga_ls9c_ard_3-2-1_114081_2023-01-09_final.stac-item
2023-01-20 11:29:10	ga_ls9c_ard_3-2-1_111081_2023-01-20_final.stac-item
2023-01-21 10:33:33	ga_ls9c_ard_3-2-1_102081_2023-01-21_final.stac-item
2023-01-25 11:47:47	ga_ls9c_ard_3-2-1_114081_2023-01-25_final.stac-item
2023-02-05 11:29:23	ga_ls9c_ard_3-2-1_111081_2023-02-05_final.stac-item
2023-02-10 11:47:56	ga_ls9c_ard_3-2-1_114081_2023-02-10_final.stac-item
2023-02-26 11:47:41	ga_ls9c_ard_3-2-1_114081_2023-02-26_final.stac-item
2023-03-14 11:47:34	ga_ls9c_ard_3-2-1_114081_2023-03-14_final.stac-item
2023-03-26 10:33:17	ga_ls9c_ard_3-2-1_102081_2023-03-26_final.stac-item
2023-03-30 11:47:22	ga_ls9c_ard_3-2-1_114081_2023-03-30_final.stac-item
2023-04-10 11:28:47	ga_ls9c_ard_3-2-1_111081_2023-04-10_final.stac-item
2023-04-11 10:33:09	ga_ls9c_ard_3-2-1_102081_2023-04-11_final.stac-item
2023-04-15 11:47:16	ga_ls9c_ard_3-2-1_114081_2023-04-15_final.stac-item
2023-04-26 11:28:41	ga_ls9c_ard_3-2-1_111081_2023-04-26_final.stac-item
2023-04-27 10:33:03	ga_ls9c_ard_3-2-1_102081_2023-04-27_final.stac-item
2023-05-01 11:47:08	ga_ls9c_ard_3-2-1_114081_2023-05-01_final.stac-item
2023-05-12 11:28:31	ga_ls9c_ard_3-2-1_111081_2023-05-12_final.stac-item
2023-05-13 10:32:53	ga_ls9c_ard_3-2-1_102081_2023-05-13_final.stac-item
2023-05-17 11:47:01	ga_ls9c_ard_3-2-1_114081_2023-05-17_final.stac-item
2023-05-28 11:28:21	ga_ls9c_ard_3-2-1_111081_2023-05-28_final.stac-item
2023-05-29 10:32:44	ga_ls9c_ard_3-2-1_102081_2023-05-29_final.stac-item
2023-06-02 11:46:53	ga_ls9c_ard_3-2-1_114081_2023-06-02_final.stac-item
2023-06-14 10:32:36	ga_ls9c_ard_3-2-1_102081_2023-06-14_final.stac-item
2023-06-18 11:46:45	ga_ls9c_ard_3-2-1_114081_2023-06-18_final.stac-item
2023-06-29 11:28:18	ga_ls9c_ard_3-2-1_111081_2023-06-29_final.stac-item
2023-06-30 10:32:42	ga_ls9c_ard_3-2-1_102081_2023-06-30_final.stac-item
2023-07-01 11:15:35	ga_ls9c_ard_3-2-1_109080_2023-07-01_final.stac-item
2023-07-04 11:46:56	ga_ls9c_ard_3-2-1_114081_2023-07-04_final.stac-item
2023-07-08 11:21:52	ga_ls9c_ard_3-2-1_110080_2023-07-08_final.stac-item
2023-07-20 11:47:01	ga_ls9c_ard_3-2-1_114081_2023-07-20_final.stac-item
2023-08-25 11:22:11	ga_ls9c_ard_3-2-1_110080_2023-08-25_final.stac-item
2023-09-06 11:47:25	ga_ls9c_ard_3-2-1_114081_2023-09-06_final.stac-item
2023-10-24 11:47:39	ga_ls9c_ard_3-2-1_114081_2023-10-24_final.stac-item
2024-02-13 11:47:42	ga_ls9c_ard_3-2-1_114081_2024-02-13_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