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
2021-11-10 11:18:09	ga_ls9c_ard_3-2-1_110077_2021-11-10_final.stac-item
2021-11-17 09:22:28	ga_ls9c_ard_3-2-1_091075_2021-11-16_final.stac-item
2021-12-04 11:00:35	ga_ls9c_ard_3-2-1_107071_2021-12-04_final.stac-item
2021-12-07 09:52:34	ga_ls9c_ard_3-2-1_096071_2021-12-07_final.stac-item
2022-01-01 09:46:17	ga_ls9c_ard_3-2-1_095071_2022-01-01_final.stac-item
2022-01-14 09:19:43	ga_ls9c_ard_3-2-1_090082_2022-01-13_final.stac-item
2022-02-09 09:58:01	ga_ls9c_ard_3-2-1_096085_2022-02-09_final.stac-item
2022-02-11 09:40:51	ga_ls9c_ard_3-2-1_094073_2022-02-11_final.stac-item
2022-02-13 11:06:58	ga_ls9c_ard_3-2-1_108072_2022-02-13_final.stac-item
2022-02-16 09:58:33	ga_ls9c_ard_3-2-1_097071_2022-02-16_final.stac-item
2022-02-25 09:57:27	ga_ls9c_ard_3-2-1_096084_2022-02-25_final.stac-item
2022-03-01 09:29:29	ga_ls9c_ard_3-2-1_092076_2022-02-28_final.stac-item
2022-03-03 10:55:36	ga_ls9c_ard_3-2-1_106075_2022-03-03_final.stac-item
2022-03-04 09:56:47	ga_ls9c_ard_3-2-1_097067_2022-03-04_final.stac-item
2022-03-09 11:57:49	ga_ls9c_ard_3-2-1_116076_2022-03-09_final.stac-item
2022-03-19 10:54:47	ga_ls9c_ard_3-2-1_106073_2022-03-19_final.stac-item
2022-03-27 10:07:17	ga_ls9c_ard_3-2-1_098078_2022-03-27_final.stac-item
2022-04-14 11:35:43	ga_ls9c_ard_3-2-1_112083_2022-04-14_final.stac-item
2022-04-16 09:40:27	ga_ls9c_ard_3-2-1_094073_2022-04-16_final.stac-item
2022-05-06 10:57:41	ga_ls9c_ard_3-2-1_106081_2022-05-06_final.stac-item
2022-05-18 09:40:34	ga_ls9c_ard_3-2-1_094074_2022-05-18_final.stac-item
2022-05-30 11:46:56	ga_ls9c_ard_3-2-1_114081_2022-05-30_final.stac-item
2022-07-29 10:28:30	ga_ls9c_ard_3-2-1_102069_2022-07-29_final.stac-item
2022-08-01 09:21:45	ga_ls9c_ard_3-2-1_091072_2022-07-31_final.stac-item
2022-08-08 09:33:59	ga_ls9c_ard_3-2-1_092087_2022-08-08_final.stac-item
2022-08-17 09:29:04	ga_ls9c_ard_3-2-1_091090_2022-08-16_final.stac-item
2022-08-24 09:32:05	ga_ls9c_ard_3-2-1_092082_2022-08-24_final.stac-item
2022-09-12 09:58:13	ga_ls9c_ard_3-2-1_097070_2022-09-12_final.stac-item
2022-10-04 09:26:02	ga_ls9c_ard_3-2-1_091082_2022-10-03_final.stac-item
2022-10-09 11:24:40	ga_ls9c_ard_3-2-1_110085_2022-10-09_final.stac-item
2022-10-29 10:56:01	ga_ls9c_ard_3-2-1_106075_2022-10-29_final.stac-item
2022-11-01 09:48:25	ga_ls9c_ard_3-2-1_095076_2022-11-01_final.stac-item
2022-12-07 11:01:48	ga_ls9c_ard_3-2-1_107074_2022-12-07_final.stac-item
2022-12-15 10:15:58	ga_ls9c_ard_3-2-1_099083_2022-12-15_final.stac-item
2023-01-03 10:45:16	ga_ls9c_ard_3-2-1_104079_2023-01-03_final.stac-item
2023-01-08 09:28:31	ga_ls9c_ard_3-2-1_091088_2023-01-07_final.stac-item
2023-01-13 09:44:38	ga_ls9c_ard_3-2-1_094082_2023-01-13_final.stac-item
2023-01-23 10:19:38	ga_ls9c_ard_3-2-1_100077_2023-01-23_final.stac-item
2023-01-29 11:24:20	ga_ls9c_ard_3-2-1_110084_2023-01-29_final.stac-item
2023-01-31 09:33:54	ga_ls9c_ard_3-2-1_092086_2023-01-31_final.stac-item
2023-02-10 10:04:39	ga_ls9c_ard_3-2-1_098070_2023-02-10_final.stac-item
2023-03-01 10:39:42	ga_ls9c_ard_3-2-1_103081_2023-03-01_final.stac-item
2023-03-02 09:44:28	ga_ls9c_ard_3-2-1_094082_2023-03-02_final.stac-item
2023-03-10 10:29:00	ga_ls9c_ard_3-2-1_102070_2023-03-10_final.stac-item
2023-03-12 11:57:56	ga_ls9c_ard_3-2-1_116076_2023-03-12_final.stac-item
2023-03-13 09:29:01	ga_ls9c_ard_3-2-1_091090_2023-03-12_final.stac-item
2023-03-22 09:17:12	ga_ls9c_ard_3-2-1_090076_2023-03-21_final.stac-item
2023-03-22 09:22:47	ga_ls9c_ard_3-2-1_090090_2023-03-21_final.stac-item
2023-03-26 10:28:06	ga_ls9c_ard_3-2-1_102068_2023-03-26_final.stac-item
2023-04-08 11:41:58	ga_ls9c_ard_3-2-1_113083_2023-04-08_final.stac-item
2023-05-05 09:43:52	ga_ls9c_ard_3-2-1_094082_2023-05-05_final.stac-item
2023-05-10 10:03:12	ga_ls9c_ard_3-2-1_097084_2023-05-10_final.stac-item
2023-05-15 11:57:00	ga_ls9c_ard_3-2-1_116075_2023-05-15_final.stac-item
2023-05-15 11:57:24	ga_ls9c_ard_3-2-1_116076_2023-05-15_final.stac-item
2023-05-21 09:43:45	ga_ls9c_ard_3-2-1_094082_2023-05-21_final.stac-item
2023-06-01 09:28:20	ga_ls9c_ard_3-2-1_091090_2023-05-31_final.stac-item
2023-06-03 09:13:34	ga_ls9c_ard_3-2-1_089084_2023-06-02_final.stac-item
2023-06-06 09:44:03	ga_ls9c_ard_3-2-1_094083_2023-06-06_final.stac-item
2023-07-02 10:21:11	ga_ls9c_ard_3-2-1_100083_2023-07-02_final.stac-item
2023-07-11 10:09:07	ga_ls9c_ard_3-2-1_099068_2023-07-11_final.stac-item
2023-07-20 10:09:20	ga_ls9c_ard_3-2-1_098084_2023-07-20_final.stac-item
2023-08-06 09:15:28	ga_ls9c_ard_3-2-1_089088_2023-08-05_final.stac-item
2023-08-06 10:49:33	ga_ls9c_ard_3-2-1_105076_2023-08-06_final.stac-item
2023-08-14 11:41:49	ga_ls9c_ard_3-2-1_113083_2023-08-14_final.stac-item
2023-09-05 10:59:45	ga_ls9c_ard_3-2-1_107070_2023-09-05_final.stac-item
2023-09-29 10:10:20	ga_ls9c_ard_3-2-1_099070_2023-09-29_final.stac-item
2023-10-02 09:07:36	ga_ls9c_ard_3-2-1_088083_2023-10-01_final.stac-item
2023-10-07 11:02:17	ga_ls9c_ard_3-2-1_107076_2023-10-07_final.stac-item
2023-10-09 09:15:51	ga_ls9c_ard_3-2-1_089088_2023-10-08_final.stac-item
2023-11-27 09:52:54	ga_ls9c_ard_3-2-1_096072_2023-11-27_final.stac-item
2023-11-28 10:35:46	ga_ls9c_ard_3-2-1_103071_2023-11-28_final.stac-item
2023-12-02 11:53:06	ga_ls9c_ard_3-2-1_115079_2023-12-02_final.stac-item
2023-12-07 10:33:29	ga_ls9c_ard_3-2-1_102081_2023-12-07_final.stac-item
2023-12-10 09:26:43	ga_ls9c_ard_3-2-1_091084_2023-12-09_final.stac-item
2023-12-10 11:01:37	ga_ls9c_ard_3-2-1_107074_2023-12-10_final.stac-item
2023-12-11 11:47:41	ga_ls9c_ard_3-2-1_114081_2023-12-11_final.stac-item
2023-12-14 10:39:20	ga_ls9c_ard_3-2-1_103080_2023-12-14_final.stac-item
2023-12-27 10:05:17	ga_ls9c_ard_3-2-1_098072_2023-12-27_final.stac-item
2023-12-31 11:20:36	ga_ls9c_ard_3-2-1_110075_2023-12-31_final.stac-item
2024-01-04 10:55:26	ga_ls9c_ard_3-2-1_106074_2024-01-04_final.stac-item
2024-01-07 09:46:38	ga_ls9c_ard_3-2-1_095072_2024-01-07_final.stac-item
2024-01-07 11:30:19	ga_ls9c_ard_3-2-1_111084_2024-01-07_final.stac-item
2024-01-09 09:39:05	ga_ls9c_ard_3-2-1_093084_2024-01-09_final.stac-item
2024-01-12 11:47:42	ga_ls9c_ard_3-2-1_114081_2024-01-12_final.stac-item
2024-01-15 10:39:43	ga_ls9c_ard_3-2-1_103081_2024-01-15_final.stac-item
2024-01-27 09:22:44	ga_ls9c_ard_3-2-1_091074_2024-01-26_final.stac-item
2024-01-28 10:07:12	ga_ls9c_ard_3-2-1_098077_2024-01-28_final.stac-item
2024-02-09 10:33:58	ga_ls9c_ard_3-2-1_102082_2024-02-09_final.stac-item
2024-02-13 10:04:01	ga_ls9c_ard_3-2-1_098069_2024-02-13_final.stac-item
2024-02-19 09:30:49	ga_ls9c_ard_3-2-1_092079_2024-02-19_final.stac-item
2024-02-28 11:01:30	ga_ls9c_ard_3-2-1_107074_2024-02-28_final.stac-item
2024-03-10 10:42:12	ga_ls9c_ard_3-2-1_104072_2024-03-10_final.stac-item
2024-03-13 11:12:17	ga_ls9c_ard_3-2-1_109070_2024-03-13_final.stac-item
2024-03-14 08:42:34	ga_ls9c_ard_3-2-1_084082_2024-03-13_final.stac-item
2024-03-15 09:23:26	ga_ls9c_ard_3-2-1_091076_2024-03-14_final.stac-item
2024-03-16 10:09:53	ga_ls9c_ard_3-2-1_098084_2024-03-16_final.stac-item
2024-03-25 11:42:08	ga_ls9c_ard_3-2-1_113083_2024-03-25_final.stac-item
2024-03-29 11:11:44	ga_ls9c_ard_3-2-1_109069_2024-03-29_final.stac-item
2024-04-05 11:24:18	ga_ls9c_ard_3-2-1_110085_2024-04-05_final.stac-item
2024-04-12 11:23:38	ga_ls9c_ard_3-2-1_111068_2024-04-12_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