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
2021-12-18 09:35:55	ga_ls9c_ard_3-2-1_093076_2021-12-18_final.stac-item
2022-01-01 09:47:53	ga_ls9c_ard_3-2-1_095075_2022-01-01_final.stac-item
2022-01-03 09:35:07	ga_ls9c_ard_3-2-1_093074_2022-01-03_final.stac-item
2022-01-17 09:47:51	ga_ls9c_ard_3-2-1_095075_2022-01-17_final.stac-item
2022-01-25 10:38:07	ga_ls9c_ard_3-2-1_103077_2022-01-25_final.stac-item
2022-02-03 10:33:56	ga_ls9c_ard_3-2-1_102082_2022-02-03_final.stac-item
2022-03-23 10:30:02	ga_ls9c_ard_3-2-1_102073_2022-03-23_final.stac-item
2022-05-29 10:59:17	ga_ls9c_ard_3-2-1_107070_2022-05-29_final.stac-item
2022-07-07 11:07:00	ga_ls9c_ard_3-2-1_108073_2022-07-07_final.stac-item
2022-07-15 10:17:06	ga_ls9c_ard_3-2-1_100072_2022-07-15_final.stac-item
2022-07-31 10:21:21	ga_ls9c_ard_3-2-1_100082_2022-07-31_final.stac-item
2022-08-08 11:07:17	ga_ls9c_ard_3-2-1_108073_2022-08-08_final.stac-item
2022-08-27 10:03:23	ga_ls9c_ard_3-2-1_097083_2022-08-27_final.stac-item
2022-09-17 10:22:00	ga_ls9c_ard_3-2-1_100083_2022-09-17_final.stac-item
2022-09-27 10:54:45	ga_ls9c_ard_3-2-1_106072_2022-09-27_final.stac-item
2022-09-30 09:51:09	ga_ls9c_ard_3-2-1_095083_2022-09-30_final.stac-item
2022-10-02 09:37:36	ga_ls9c_ard_3-2-1_093080_2022-10-02_final.stac-item
2022-10-29 09:20:44	ga_ls9c_ard_3-2-1_090084_2022-10-28_final.stac-item
2022-10-30 09:58:48	ga_ls9c_ard_3-2-1_097071_2022-10-30_final.stac-item
2022-11-01 09:48:01	ga_ls9c_ard_3-2-1_095075_2022-11-01_final.stac-item
2022-11-01 09:51:37	ga_ls9c_ard_3-2-1_095084_2022-11-01_final.stac-item
2022-11-05 09:26:29	ga_ls9c_ard_3-2-1_091083_2022-11-04_final.stac-item
2022-11-06 10:10:33	ga_ls9c_ard_3-2-1_098085_2022-11-06_final.stac-item
2022-11-08 09:53:26	ga_ls9c_ard_3-2-1_096073_2022-11-08_final.stac-item
2022-11-09 10:38:17	ga_ls9c_ard_3-2-1_103077_2022-11-09_final.stac-item
2022-11-10 11:19:10	ga_ls9c_ard_3-2-1_110071_2022-11-10_final.stac-item
2022-11-17 09:48:04	ga_ls9c_ard_3-2-1_095075_2022-11-17_final.stac-item
2022-11-28 11:07:35	ga_ls9c_ard_3-2-1_108073_2022-11-28_final.stac-item
2022-12-12 11:20:45	ga_ls9c_ard_3-2-1_110075_2022-12-12_final.stac-item
2022-12-14 09:32:42	ga_ls9c_ard_3-2-1_092083_2022-12-14_final.stac-item
2022-12-16 09:18:44	ga_ls9c_ard_3-2-1_090079_2022-12-15_final.stac-item
2022-12-20 10:30:05	ga_ls9c_ard_3-2-1_102072_2022-12-20_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 11:29:44	ga_ls9c_ard_3-2-1_111082_2023-01-04_final.stac-item
2023-01-19 10:43:56	ga_ls9c_ard_3-2-1_104076_2023-01-19_final.stac-item
2023-01-20 11:29:10	ga_ls9c_ard_3-2-1_111081_2023-01-20_final.stac-item
2023-01-22 11:17:14	ga_ls9c_ard_3-2-1_109082_2023-01-22_final.stac-item
2023-01-24 09:25:37	ga_ls9c_ard_3-2-1_091081_2023-01-23_final.stac-item
2023-01-24 09:28:01	ga_ls9c_ard_3-2-1_091087_2023-01-23_final.stac-item
2023-01-29 11:19:08	ga_ls9c_ard_3-2-1_110071_2023-01-29_final.stac-item
2023-01-29 11:23:32	ga_ls9c_ard_3-2-1_110082_2023-01-29_final.stac-item
2023-02-04 10:43:43	ga_ls9c_ard_3-2-1_104075_2023-02-04_final.stac-item
2023-02-05 11:29:47	ga_ls9c_ard_3-2-1_111082_2023-02-05_final.stac-item
2023-02-06 10:29:46	ga_ls9c_ard_3-2-1_102071_2023-02-06_final.stac-item
2023-02-07 11:13:02	ga_ls9c_ard_3-2-1_109071_2023-02-07_final.stac-item
2023-02-08 10:22:36	ga_ls9c_ard_3-2-1_100084_2023-02-08_final.stac-item
2023-02-10 10:09:51	ga_ls9c_ard_3-2-1_098083_2023-02-10_final.stac-item
2023-02-12 09:57:52	ga_ls9c_ard_3-2-1_096084_2023-02-12_final.stac-item
2023-04-21 09:32:54	ga_ls9c_ard_3-2-1_092085_2023-04-21_final.stac-item
2023-04-22 11:51:03	ga_ls9c_ard_3-2-1_115075_2023-04-22_final.stac-item
2023-04-25 10:45:50	ga_ls9c_ard_3-2-1_104082_2023-04-25_final.stac-item
2023-04-26 09:51:24	ga_ls9c_ard_3-2-1_095085_2023-04-26_final.stac-item
2023-04-26 11:29:05	ga_ls9c_ard_3-2-1_111082_2023-04-26_final.stac-item
2023-04-28 11:17:05	ga_ls9c_ard_3-2-1_109083_2023-04-28_final.stac-item
2023-04-30 09:25:25	ga_ls9c_ard_3-2-1_091082_2023-04-29_final.stac-item
2023-07-05 10:46:08	ga_ls9c_ard_3-2-1_105068_2023-07-05_final.stac-item
2023-07-16 10:27:40	ga_ls9c_ard_3-2-1_102068_2023-07-16_final.stac-item
2023-07-17 11:11:44	ga_ls9c_ard_3-2-1_109070_2023-07-17_final.stac-item
2023-07-18 10:16:55	ga_ls9c_ard_3-2-1_100072_2023-07-18_final.stac-item
2023-07-19 09:24:53	ga_ls9c_ard_3-2-1_091081_2023-07-18_final.stac-item
2023-07-20 11:45:26	ga_ls9c_ard_3-2-1_114077_2023-07-20_final.stac-item
2023-07-22 09:51:47	ga_ls9c_ard_3-2-1_096071_2023-07-22_final.stac-item
2023-07-26 11:07:32	ga_ls9c_ard_3-2-1_108075_2023-07-26_final.stac-item
2023-08-02 09:38:57	ga_ls9c_ard_3-2-1_093085_2023-08-02_final.stac-item
2023-08-02 11:11:50	ga_ls9c_ard_3-2-1_109070_2023-08-02_final.stac-item
2023-08-02 11:12:14	ga_ls9c_ard_3-2-1_109071_2023-08-02_final.stac-item
2023-08-02 11:17:02	ga_ls9c_ard_3-2-1_109083_2023-08-02_final.stac-item
2023-08-04 10:59:54	ga_ls9c_ard_3-2-1_107071_2023-08-04_final.stac-item
2023-08-05 10:06:41	ga_ls9c_ard_3-2-1_098077_2023-08-05_final.stac-item
2023-08-06 09:12:16	ga_ls9c_ard_3-2-1_089080_2023-08-05_final.stac-item
2023-08-06 09:13:52	ga_ls9c_ard_3-2-1_089084_2023-08-05_final.stac-item
2023-10-14 09:33:40	ga_ls9c_ard_3-2-1_092086_2023-10-14_final.stac-item
2023-10-15 10:11:45	ga_ls9c_ard_3-2-1_099073_2023-10-15_final.stac-item
2023-10-16 10:55:01	ga_ls9c_ard_3-2-1_106073_2023-10-16_final.stac-item
2023-10-16 10:56:13	ga_ls9c_ard_3-2-1_106076_2023-10-16_final.stac-item
2023-10-17 09:58:36	ga_ls9c_ard_3-2-1_097071_2023-10-17_final.stac-item
2023-10-19 09:47:27	ga_ls9c_ard_3-2-1_095074_2023-10-19_final.stac-item
2023-10-19 11:25:32	ga_ls9c_ard_3-2-1_111072_2023-10-19_final.stac-item
2023-10-22 10:21:56	ga_ls9c_ard_3-2-1_100083_2023-10-22_final.stac-item
2023-10-24 11:46:28	ga_ls9c_ard_3-2-1_114078_2023-10-24_final.stac-item
2023-10-25 10:47:14	ga_ls9c_ard_3-2-1_105069_2023-10-25_final.stac-item
2023-10-28 09:41:14	ga_ls9c_ard_3-2-1_094074_2023-10-28_final.stac-item
2023-10-28 11:21:18	ga_ls9c_ard_3-2-1_110077_2023-10-28_final.stac-item
2023-10-28 11:24:06	ga_ls9c_ard_3-2-1_110084_2023-10-28_final.stac-item
2023-10-29 10:23:41	ga_ls9c_ard_3-2-1_101072_2023-10-29_final.stac-item
2023-10-30 09:29:38	ga_ls9c_ard_3-2-1_092076_2023-10-29_final.stac-item
2023-11-04 11:30:12	ga_ls9c_ard_3-2-1_111084_2023-11-04_final.stac-item
2023-11-05 10:33:48	ga_ls9c_ard_3-2-1_102082_2023-11-05_final.stac-item
2023-11-14 10:24:03	ga_ls9c_ard_3-2-1_101073_2023-11-14_final.stac-item
2023-11-14 10:28:03	ga_ls9c_ard_3-2-1_101083_2023-11-14_final.stac-item
2023-11-15 11:05:43	ga_ls9c_ard_3-2-1_108069_2023-11-15_final.stac-item
2023-11-16 10:11:42	ga_ls9c_ard_3-2-1_099073_2023-11-16_final.stac-item
2023-11-19 10:41:03	ga_ls9c_ard_3-2-1_104069_2023-11-19_final.stac-item
2023-11-21 10:31:55	ga_ls9c_ard_3-2-1_102077_2023-11-21_final.stac-item
2023-11-22 11:14:48	ga_ls9c_ard_3-2-1_109076_2023-11-22_final.stac-item
2023-11-23 11:58:52	ga_ls9c_ard_3-2-1_116078_2023-11-23_final.stac-item
2023-11-24 11:03:39	ga_ls9c_ard_3-2-1_107079_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 10:03:15	ga_ls9c_ard_3-2-1_098067_2023-11-25_final.stac-item
2023-11-25 11:47:43	ga_ls9c_ard_3-2-1_114081_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