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 11:33:13	ga_ls9c_ard_3-2-1_112074_2021-11-03_final.stac-item
2021-11-16 10:21:55	ga_ls9c_ard_3-2-1_100077_2021-11-16_final.stac-item
2021-11-17 09:21:17	ga_ls9c_ard_3-2-1_091072_2021-11-16_final.stac-item
2021-11-18 09:59:35	ga_ls9c_ard_3-2-1_097068_2021-11-18_final.stac-item
2021-12-05 10:03:21	ga_ls9c_ard_3-2-1_098067_2021-12-05_final.stac-item
2021-12-21 10:09:37	ga_ls9c_ard_3-2-1_098083_2021-12-21_final.stac-item
2021-12-28 10:16:36	ga_ls9c_ard_3-2-1_099085_2021-12-28_final.stac-item
2022-01-05 09:23:09	ga_ls9c_ard_3-2-1_091075_2022-01-04_final.stac-item
2022-02-04 11:12:48	ga_ls9c_ard_3-2-1_109071_2022-02-04_final.stac-item
2022-02-14 10:10:08	ga_ls9c_ard_3-2-1_099069_2022-02-14_final.stac-item
2022-02-18 11:25:03	ga_ls9c_ard_3-2-1_111071_2022-02-18_final.stac-item
2022-03-03 10:52:48	ga_ls9c_ard_3-2-1_106068_2022-03-03_final.stac-item
2022-03-03 10:58:24	ga_ls9c_ard_3-2-1_106082_2022-03-03_final.stac-item
2022-03-21 10:40:25	ga_ls9c_ard_3-2-1_104068_2022-03-21_final.stac-item
2022-03-22 11:24:52	ga_ls9c_ard_3-2-1_111071_2022-03-22_final.stac-item
2022-03-25 10:22:03	ga_ls9c_ard_3-2-1_100084_2022-03-25_final.stac-item
2022-03-29 11:32:13	ga_ls9c_ard_3-2-1_112074_2022-03-29_final.stac-item
2022-04-04 10:52:44	ga_ls9c_ard_3-2-1_106068_2022-04-04_final.stac-item
2022-04-18 11:07:21	ga_ls9c_ard_3-2-1_108074_2022-04-18_final.stac-item
2022-05-02 09:40:21	ga_ls9c_ard_3-2-1_094073_2022-05-02_final.stac-item
2022-05-12 10:18:56	ga_ls9c_ard_3-2-1_100077_2022-05-12_final.stac-item
2022-05-14 10:02:33	ga_ls9c_ard_3-2-1_098067_2022-05-14_final.stac-item
2022-05-17 10:33:49	ga_ls9c_ard_3-2-1_103068_2022-05-17_final.stac-item
2022-05-22 09:22:12	ga_ls9c_ard_3-2-1_090090_2022-05-21_final.stac-item
2022-05-27 09:33:33	ga_ls9c_ard_3-2-1_093072_2022-05-27_final.stac-item
2022-06-02 10:33:47	ga_ls9c_ard_3-2-1_103068_2022-06-02_final.stac-item
2022-06-04 10:27:01	ga_ls9c_ard_3-2-1_101082_2022-06-04_final.stac-item
2022-06-16 10:48:38	ga_ls9c_ard_3-2-1_105074_2022-06-16_final.stac-item
2022-06-30 09:26:45	ga_ls9c_ard_3-2-1_091085_2022-06-29_final.stac-item
2022-06-30 11:05:14	ga_ls9c_ard_3-2-1_107084_2022-06-30_final.stac-item
2022-07-02 10:49:16	ga_ls9c_ard_3-2-1_105075_2022-07-02_final.stac-item
2022-07-04 10:39:42	ga_ls9c_ard_3-2-1_103082_2022-07-04_final.stac-item
2022-07-08 10:13:46	ga_ls9c_ard_3-2-1_099079_2022-07-08_final.stac-item
2022-07-12 11:23:54	ga_ls9c_ard_3-2-1_111069_2022-07-12_final.stac-item
2022-07-13 10:33:28	ga_ls9c_ard_3-2-1_102082_2022-07-13_final.stac-item
2022-07-16 10:59:35	ga_ls9c_ard_3-2-1_107070_2022-07-16_final.stac-item
2022-07-19 11:31:21	ga_ls9c_ard_3-2-1_112072_2022-07-19_final.stac-item
2022-08-08 11:11:17	ga_ls9c_ard_3-2-1_108083_2022-08-08_final.stac-item
2022-08-25 10:10:57	ga_ls9c_ard_3-2-1_099071_2022-08-25_final.stac-item
2022-09-08 10:28:06	ga_ls9c_ard_3-2-1_101083_2022-09-08_final.stac-item
2022-09-10 10:14:09	ga_ls9c_ard_3-2-1_099079_2022-09-10_final.stac-item
2022-09-22 10:36:11	ga_ls9c_ard_3-2-1_103072_2022-09-22_final.stac-item
2022-10-08 10:39:48	ga_ls9c_ard_3-2-1_103081_2022-10-08_final.stac-item
2022-10-16 11:25:20	ga_ls9c_ard_3-2-1_111071_2022-10-16_final.stac-item
2022-10-23 11:36:43	ga_ls9c_ard_3-2-1_112084_2022-10-23_final.stac-item
2022-10-24 10:36:18	ga_ls9c_ard_3-2-1_103072_2022-10-24_final.stac-item
2022-11-07 09:12:09	ga_ls9c_ard_3-2-1_089078_2022-11-06_final.stac-item
2022-11-09 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-11-09_final.stac-item
2022-11-12 09:31:31	ga_ls9c_ard_3-2-1_092080_2022-11-12_final.stac-item
2022-11-14 09:21:10	ga_ls9c_ard_3-2-1_090085_2022-11-13_final.stac-item
2022-11-16 10:40:54	ga_ls9c_ard_3-2-1_104068_2022-11-16_final.stac-item
2022-11-19 11:18:11	ga_ls9c_ard_3-2-1_109084_2022-11-19_final.stac-item
2022-11-20 10:17:22	ga_ls9c_ard_3-2-1_100071_2022-11-20_final.stac-item
2022-11-22 10:03:25	ga_ls9c_ard_3-2-1_098067_2022-11-22_final.stac-item
2022-11-26 09:40:16	ga_ls9c_ard_3-2-1_094071_2022-11-26_final.stac-item
2022-12-01 11:38:51	ga_ls9c_ard_3-2-1_113074_2022-12-01_final.stac-item
2022-12-09 10:49:27	ga_ls9c_ard_3-2-1_105074_2022-12-09_final.stac-item
2022-12-16 09:17:09	ga_ls9c_ard_3-2-1_090075_2022-12-15_final.stac-item
2022-12-22 10:18:06	ga_ls9c_ard_3-2-1_100073_2022-12-22_final.stac-item
2022-12-24 10:10:07	ga_ls9c_ard_3-2-1_098084_2022-12-24_final.stac-item
2022-12-30 11:07:35	ga_ls9c_ard_3-2-1_108073_2022-12-30_final.stac-item
2023-01-12 10:34:40	ga_ls9c_ard_3-2-1_103068_2023-01-12_final.stac-item
2023-01-24 11:02:07	ga_ls9c_ard_3-2-1_107075_2023-01-24_final.stac-item
2023-02-01 10:16:47	ga_ls9c_ard_3-2-1_099085_2023-02-01_final.stac-item
2023-02-02 09:21:34	ga_ls9c_ard_3-2-1_090086_2023-02-01_final.stac-item
2023-02-26 10:09:36	ga_ls9c_ard_3-2-1_098083_2023-02-26_final.stac-item
2023-03-05 10:09:21	ga_ls9c_ard_3-2-1_099067_2023-03-05_final.stac-item
2023-03-05 10:16:08	ga_ls9c_ard_3-2-1_099084_2023-03-05_final.stac-item
2023-03-07 10:03:44	ga_ls9c_ard_3-2-1_097084_2023-03-07_final.stac-item
2023-03-28 10:19:17	ga_ls9c_ard_3-2-1_100077_2023-03-28_final.stac-item
2023-04-01 11:35:49	ga_ls9c_ard_3-2-1_112083_2023-04-01_final.stac-item
2023-04-16 10:49:39	ga_ls9c_ard_3-2-1_105076_2023-04-16_final.stac-item
2023-05-30 11:14:00	ga_ls9c_ard_3-2-1_109076_2023-05-30_final.stac-item
2023-06-03 10:52:03	ga_ls9c_ard_3-2-1_105083_2023-06-03_final.stac-item
2023-06-07 10:26:54	ga_ls9c_ard_3-2-1_101082_2023-06-07_final.stac-item
2023-06-09 10:10:08	ga_ls9c_ard_3-2-1_099071_2023-06-09_final.stac-item
2023-06-18 10:02:16	ga_ls9c_ard_3-2-1_098067_2023-06-18_final.stac-item
2023-06-18 11:46:21	ga_ls9c_ard_3-2-1_114080_2023-06-18_final.stac-item
2023-06-24 11:10:27	ga_ls9c_ard_3-2-1_108083_2023-06-24_final.stac-item
2023-07-09 10:27:27	ga_ls9c_ard_3-2-1_101083_2023-07-09_final.stac-item
2023-07-26 11:07:08	ga_ls9c_ard_3-2-1_108074_2023-07-26_final.stac-item
2023-07-29 11:41:18	ga_ls9c_ard_3-2-1_113082_2023-07-29_final.stac-item
2023-08-01 10:33:21	ga_ls9c_ard_3-2-1_102082_2023-08-01_final.stac-item
2023-08-05 11:47:10	ga_ls9c_ard_3-2-1_114081_2023-08-05_final.stac-item
2023-08-13 10:55:45	ga_ls9c_ard_3-2-1_106076_2023-08-13_final.stac-item
2023-08-21 10:09:33	ga_ls9c_ard_3-2-1_098084_2023-08-21_final.stac-item
2023-08-27 09:33:45	ga_ls9c_ard_3-2-1_092087_2023-08-27_final.stac-item
2023-08-27 09:34:09	ga_ls9c_ard_3-2-1_092088_2023-08-27_final.stac-item
2023-09-01 09:51:56	ga_ls9c_ard_3-2-1_095086_2023-09-01_final.stac-item
2023-09-01 11:24:02	ga_ls9c_ard_3-2-1_111069_2023-09-01_final.stac-item
2023-09-05 11:01:45	ga_ls9c_ard_3-2-1_107075_2023-09-05_final.stac-item
2023-10-16 10:56:13	ga_ls9c_ard_3-2-1_106076_2023-10-16_final.stac-item
2023-10-19 09:47:03	ga_ls9c_ard_3-2-1_095073_2023-10-19_final.stac-item
2023-10-31 10:10:05	ga_ls9c_ard_3-2-1_099069_2023-10-31_final.stac-item
2023-11-04 11:25:49	ga_ls9c_ard_3-2-1_111073_2023-11-04_final.stac-item
2023-11-06 11:11:53	ga_ls9c_ard_3-2-1_109069_2023-11-06_final.stac-item
2023-11-17 09:22:53	ga_ls9c_ard_3-2-1_090090_2023-11-16_final.stac-item
2023-11-23 10:19:35	ga_ls9c_ard_3-2-1_100077_2023-11-23_final.stac-item
2023-11-29 09:40:56	ga_ls9c_ard_3-2-1_094073_2023-11-29_final.stac-item
2023-12-02 10:16:13	ga_ls9c_ard_3-2-1_099084_2023-12-02_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