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
2021-11-05 11:18:04	ga_ls9c_ard_3-2-1_109083_2021-11-05_final.stac-item
2021-11-10 11:17:21	ga_ls9c_ard_3-2-1_110075_2021-11-10_final.stac-item
2021-11-17 09:23:16	ga_ls9c_ard_3-2-1_091077_2021-11-16_final.stac-item
2021-11-20 11:21:53	ga_ls9c_ard_3-2-1_110074_2021-11-20_final.stac-item
2021-11-25 09:46:52	ga_ls9c_ard_3-2-1_095077_2021-11-25_final.stac-item
2021-12-06 10:49:48	ga_ls9c_ard_3-2-1_105075_2021-12-06_final.stac-item
2021-12-13 10:56:18	ga_ls9c_ard_3-2-1_106076_2021-12-13_final.stac-item
2021-12-24 10:39:20	ga_ls9c_ard_3-2-1_103080_2021-12-24_final.stac-item
2022-01-03 09:39:31	ga_ls9c_ard_3-2-1_093085_2022-01-03_final.stac-item
2022-01-12 09:31:18	ga_ls9c_ard_3-2-1_092080_2022-01-12_final.stac-item
2022-02-06 11:05:37	ga_ls9c_ard_3-2-1_107084_2022-02-06_final.stac-item
2022-02-20 09:33:48	ga_ls9c_ard_3-2-1_093071_2022-02-20_final.stac-item
2022-04-25 11:14:17	ga_ls9c_ard_3-2-1_109076_2022-04-25_final.stac-item
2022-05-13 09:24:06	ga_ls9c_ard_3-2-1_091079_2022-05-12_final.stac-item
2022-05-13 11:02:35	ga_ls9c_ard_3-2-1_107078_2022-05-13_final.stac-item
2022-05-20 11:08:15	ga_ls9c_ard_3-2-1_108077_2022-05-20_final.stac-item
2022-05-20 11:09:51	ga_ls9c_ard_3-2-1_108081_2022-05-20_final.stac-item
2022-05-30 11:44:33	ga_ls9c_ard_3-2-1_114075_2022-05-30_final.stac-item
2022-06-21 11:08:30	ga_ls9c_ard_3-2-1_108077_2022-06-21_final.stac-item
2022-06-30 11:04:02	ga_ls9c_ard_3-2-1_107081_2022-06-30_final.stac-item
2022-07-07 11:08:35	ga_ls9c_ard_3-2-1_108077_2022-07-07_final.stac-item
2022-07-16 11:01:59	ga_ls9c_ard_3-2-1_107076_2022-07-16_final.stac-item
2022-08-17 11:04:22	ga_ls9c_ard_3-2-1_107081_2022-08-17_final.stac-item
2022-08-20 09:57:35	ga_ls9c_ard_3-2-1_096084_2022-08-20_final.stac-item
2022-09-02 11:03:12	ga_ls9c_ard_3-2-1_107078_2022-09-02_final.stac-item
2022-09-11 10:57:49	ga_ls9c_ard_3-2-1_106080_2022-09-11_final.stac-item
2022-10-04 11:03:19	ga_ls9c_ard_3-2-1_107078_2022-10-04_final.stac-item
2022-10-06 10:49:45	ga_ls9c_ard_3-2-1_105075_2022-10-06_final.stac-item
2022-10-08 10:39:24	ga_ls9c_ard_3-2-1_103080_2022-10-08_final.stac-item
2022-10-18 11:14:58	ga_ls9c_ard_3-2-1_109076_2022-10-18_final.stac-item
2022-10-19 11:58:38	ga_ls9c_ard_3-2-1_116077_2022-10-19_final.stac-item
2022-10-21 11:47:53	ga_ls9c_ard_3-2-1_114081_2022-10-21_final.stac-item
2022-10-25 11:20:46	ga_ls9c_ard_3-2-1_110075_2022-10-25_final.stac-item
2022-10-28 10:11:10	ga_ls9c_ard_3-2-1_099071_2022-10-28_final.stac-item
2022-11-01 11:24:31	ga_ls9c_ard_3-2-1_111069_2022-11-01_final.stac-item
2022-11-01 11:26:06	ga_ls9c_ard_3-2-1_111073_2022-11-01_final.stac-item
2022-11-07 10:46:39	ga_ls9c_ard_3-2-1_105067_2022-11-07_final.stac-item
2022-11-07 10:51:50	ga_ls9c_ard_3-2-1_105080_2022-11-07_final.stac-item
2022-11-10 09:44:16	ga_ls9c_ard_3-2-1_094081_2022-11-10_final.stac-item
2022-11-12 11:11:12	ga_ls9c_ard_3-2-1_108082_2022-11-12_final.stac-item
2022-11-14 10:56:27	ga_ls9c_ard_3-2-1_106076_2022-11-14_final.stac-item
2022-11-26 09:44:40	ga_ls9c_ard_3-2-1_094082_2022-11-26_final.stac-item
2022-12-02 10:46:01	ga_ls9c_ard_3-2-1_104081_2022-12-02_final.stac-item
2022-12-14 09:31:30	ga_ls9c_ard_3-2-1_092080_2022-12-14_final.stac-item
2022-12-23 09:27:16	ga_ls9c_ard_3-2-1_091085_2022-12-22_final.stac-item
2022-12-23 11:02:57	ga_ls9c_ard_3-2-1_107077_2022-12-23_final.stac-item
2022-12-30 09:32:42	ga_ls9c_ard_3-2-1_092083_2022-12-30_final.stac-item
2023-01-08 11:03:01	ga_ls9c_ard_3-2-1_107077_2023-01-08_final.stac-item
2023-01-08 11:05:00	ga_ls9c_ard_3-2-1_107082_2023-01-08_final.stac-item
2023-01-15 11:10:43	ga_ls9c_ard_3-2-1_108081_2023-01-15_final.stac-item
2023-01-22 09:38:21	ga_ls9c_ard_3-2-1_093082_2023-01-22_final.stac-item
2023-02-02 09:21:34	ga_ls9c_ard_3-2-1_090086_2023-02-01_final.stac-item
2023-02-02 10:56:27	ga_ls9c_ard_3-2-1_106076_2023-02-02_final.stac-item
2023-02-05 09:52:05	ga_ls9c_ard_3-2-1_095085_2023-02-05_final.stac-item
2023-02-05 11:30:35	ga_ls9c_ard_3-2-1_111084_2023-02-05_final.stac-item
2023-02-08 10:22:36	ga_ls9c_ard_3-2-1_100084_2023-02-08_final.stac-item
2023-02-09 09:27:23	ga_ls9c_ard_3-2-1_091085_2023-02-08_final.stac-item
2023-02-11 10:50:18	ga_ls9c_ard_3-2-1_105076_2023-02-11_final.stac-item
2023-03-04 09:29:18	ga_ls9c_ard_3-2-1_092075_2023-03-03_final.stac-item
2023-03-06 10:57:47	ga_ls9c_ard_3-2-1_106080_2023-03-06_final.stac-item
2023-03-08 10:41:00	ga_ls9c_ard_3-2-1_104069_2023-03-08_final.stac-item
2023-03-11 09:35:47	ga_ls9c_ard_3-2-1_093076_2023-03-11_final.stac-item
2023-04-03 11:20:16	ga_ls9c_ard_3-2-1_110075_2023-04-03_final.stac-item
2023-04-05 11:07:54	ga_ls9c_ard_3-2-1_108075_2023-04-05_final.stac-item
2023-04-07 10:57:31	ga_ls9c_ard_3-2-1_106080_2023-04-07_final.stac-item
2023-04-23 10:55:49	ga_ls9c_ard_3-2-1_106076_2023-04-23_final.stac-item
2023-04-23 10:58:37	ga_ls9c_ard_3-2-1_106083_2023-04-23_final.stac-item
2023-04-26 09:51:24	ga_ls9c_ard_3-2-1_095085_2023-04-26_final.stac-item
2023-05-08 10:15:58	ga_ls9c_ard_3-2-1_099085_2023-05-08_final.stac-item
2023-05-12 09:51:38	ga_ls9c_ard_3-2-1_095086_2023-05-12_final.stac-item
2023-05-16 11:01:46	ga_ls9c_ard_3-2-1_107076_2023-05-16_final.stac-item
2023-05-16 11:02:10	ga_ls9c_ard_3-2-1_107077_2023-05-16_final.stac-item
2023-05-16 11:04:34	ga_ls9c_ard_3-2-1_107083_2023-05-16_final.stac-item
2023-06-20 09:57:06	ga_ls9c_ard_3-2-1_096085_2023-06-20_final.stac-item
2023-06-22 11:19:14	ga_ls9c_ard_3-2-1_110074_2023-06-22_final.stac-item
2023-06-22 11:19:38	ga_ls9c_ard_3-2-1_110075_2023-06-22_final.stac-item
2023-06-28 10:45:00	ga_ls9c_ard_3-2-1_104081_2023-06-28_final.stac-item
2023-07-01 09:35:54	ga_ls9c_ard_3-2-1_093078_2023-07-01_final.stac-item
2023-07-21 10:45:49	ga_ls9c_ard_3-2-1_105067_2023-07-21_final.stac-item
2023-07-26 11:07:56	ga_ls9c_ard_3-2-1_108076_2023-07-26_final.stac-item
2023-07-26 11:08:20	ga_ls9c_ard_3-2-1_108077_2023-07-26_final.stac-item
2023-07-28 10:58:25	ga_ls9c_ard_3-2-1_106083_2023-07-28_final.stac-item
2023-08-02 11:14:14	ga_ls9c_ard_3-2-1_109076_2023-08-02_final.stac-item
2023-08-04 11:02:18	ga_ls9c_ard_3-2-1_107077_2023-08-04_final.stac-item
2023-08-08 10:34:01	ga_ls9c_ard_3-2-1_103068_2023-08-08_final.stac-item
2023-08-11 11:08:31	ga_ls9c_ard_3-2-1_108077_2023-08-11_final.stac-item
2023-10-14 09:34:52	ga_ls9c_ard_3-2-1_092089_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
2023-10-14 11:10:33	ga_ls9c_ard_3-2-1_108081_2023-10-14_final.stac-item
2023-10-16 10:58:13	ga_ls9c_ard_3-2-1_106081_2023-10-16_final.stac-item
2023-10-19 09:51:50	ga_ls9c_ard_3-2-1_095085_2023-10-19_final.stac-item
2023-10-25 10:49:38	ga_ls9c_ard_3-2-1_105075_2023-10-25_final.stac-item
2023-10-25 10:51:38	ga_ls9c_ard_3-2-1_105080_2023-10-25_final.stac-item
2023-10-30 11:07:43	ga_ls9c_ard_3-2-1_108074_2023-10-30_final.stac-item
2023-11-15 09:32:25	ga_ls9c_ard_3-2-1_092083_2023-11-15_final.stac-item
2023-11-19 10:45:50	ga_ls9c_ard_3-2-1_104081_2023-11-19_final.stac-item
2023-11-21 10:28:20	ga_ls9c_ard_3-2-1_102068_2023-11-21_final.stac-item
2023-11-29 09:40:56	ga_ls9c_ard_3-2-1_094073_2023-11-29_final.stac-item
2024-02-16 10:36:04	ga_ls9c_ard_3-2-1_103072_2024-02-16_final.stac-item
2024-02-16 10:39:16	ga_ls9c_ard_3-2-1_103080_2024-02-16_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