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
2021-11-02 10:53:16	ga_ls9c_ard_3-2-1_106074_2021-11-02_final.stac-item
2021-11-14 10:41:51	ga_ls9c_ard_3-2-1_103080_2021-11-14_final.stac-item
2021-12-04 09:27:17	ga_ls9c_ard_3-2-1_091085_2021-12-03_final.stac-item
2021-12-07 11:36:38	ga_ls9c_ard_3-2-1_112084_2021-12-07_final.stac-item
2021-12-13 09:22:36	ga_ls9c_ard_3-2-1_090089_2021-12-12_final.stac-item
2022-01-04 10:17:59	ga_ls9c_ard_3-2-1_100073_2022-01-04_final.stac-item
2022-01-05 11:00:50	ga_ls9c_ard_3-2-1_107072_2022-01-05_final.stac-item
2022-01-06 11:45:18	ga_ls9c_ard_3-2-1_114075_2022-01-06_final.stac-item
2022-01-30 09:19:46	ga_ls9c_ard_3-2-1_090082_2022-01-29_final.stac-item
2022-02-05 10:20:22	ga_ls9c_ard_3-2-1_100079_2022-02-05_final.stac-item
2022-02-06 09:26:20	ga_ls9c_ard_3-2-1_091083_2022-02-05_final.stac-item
2022-02-20 09:36:11	ga_ls9c_ard_3-2-1_093077_2022-02-20_final.stac-item
2022-02-23 10:09:27	ga_ls9c_ard_3-2-1_098083_2022-02-23_final.stac-item
2022-03-02 11:51:13	ga_ls9c_ard_3-2-1_115075_2022-03-02_final.stac-item
2022-03-04 09:57:11	ga_ls9c_ard_3-2-1_097068_2022-03-04_final.stac-item
2022-03-11 10:02:59	ga_ls9c_ard_3-2-1_098067_2022-03-11_final.stac-item
2022-03-12 09:16:08	ga_ls9c_ard_3-2-1_089089_2022-03-11_final.stac-item
2022-03-26 11:00:07	ga_ls9c_ard_3-2-1_107071_2022-03-26_final.stac-item
2022-03-26 11:04:54	ga_ls9c_ard_3-2-1_107083_2022-03-26_final.stac-item
2022-03-28 09:14:03	ga_ls9c_ard_3-2-1_089084_2022-03-27_final.stac-item
2022-04-02 09:29:24	ga_ls9c_ard_3-2-1_092076_2022-04-01_final.stac-item
2022-04-04 09:22:14	ga_ls9c_ard_3-2-1_090089_2022-04-03_final.stac-item
2022-04-05 10:03:29	ga_ls9c_ard_3-2-1_097084_2022-04-05_final.stac-item
2022-04-07 11:26:01	ga_ls9c_ard_3-2-1_111074_2022-04-07_final.stac-item
2022-04-09 09:37:33	ga_ls9c_ard_3-2-1_093081_2022-04-09_final.stac-item
2022-04-19 10:15:42	ga_ls9c_ard_3-2-1_099084_2022-04-19_final.stac-item
2022-04-21 10:03:19	ga_ls9c_ard_3-2-1_097084_2022-04-21_final.stac-item
2022-04-29 09:16:15	ga_ls9c_ard_3-2-1_089090_2022-04-28_final.stac-item
2022-05-04 11:05:40	ga_ls9c_ard_3-2-1_108070_2022-05-04_final.stac-item
2022-05-14 10:06:33	ga_ls9c_ard_3-2-1_098077_2022-05-14_final.stac-item
2022-05-27 11:14:49	ga_ls9c_ard_3-2-1_109078_2022-05-27_final.stac-item
2022-05-29 10:59:17	ga_ls9c_ard_3-2-1_107070_2022-05-29_final.stac-item
2022-06-01 11:35:47	ga_ls9c_ard_3-2-1_112084_2022-06-01_final.stac-item
2022-06-16 10:52:14	ga_ls9c_ard_3-2-1_105083_2022-06-16_final.stac-item
2022-06-22 11:53:00	ga_ls9c_ard_3-2-1_115080_2022-06-22_final.stac-item
2022-07-08 11:53:03	ga_ls9c_ard_3-2-1_115080_2022-07-08_final.stac-item
2022-07-21 09:44:55	ga_ls9c_ard_3-2-1_094084_2022-07-21_final.stac-item
2022-08-03 09:14:36	ga_ls9c_ard_3-2-1_089085_2022-08-02_final.stac-item
2022-08-17 11:01:34	ga_ls9c_ard_3-2-1_107074_2022-08-17_final.stac-item
2022-08-26 09:17:44	ga_ls9c_ard_3-2-1_090077_2022-08-25_final.stac-item
2022-09-07 11:20:32	ga_ls9c_ard_3-2-1_110075_2022-09-07_final.stac-item
2022-09-12 11:42:18	ga_ls9c_ard_3-2-1_113083_2022-09-12_final.stac-item
2022-09-14 09:51:28	ga_ls9c_ard_3-2-1_095084_2022-09-14_final.stac-item
2022-09-27 10:56:20	ga_ls9c_ard_3-2-1_106076_2022-09-27_final.stac-item
2022-09-28 11:38:48	ga_ls9c_ard_3-2-1_113074_2022-09-28_final.stac-item
2022-10-08 10:35:25	ga_ls9c_ard_3-2-1_103070_2022-10-08_final.stac-item
2022-10-19 11:58:14	ga_ls9c_ard_3-2-1_116076_2022-10-19_final.stac-item
2022-10-20 09:28:55	ga_ls9c_ard_3-2-1_091089_2022-10-19_final.stac-item
2022-10-27 09:31:54	ga_ls9c_ard_3-2-1_092081_2022-10-27_final.stac-item
2022-11-13 10:16:47	ga_ls9c_ard_3-2-1_099085_2022-11-13_final.stac-item
2022-11-17 09:46:29	ga_ls9c_ard_3-2-1_095071_2022-11-17_final.stac-item
2022-11-23 10:51:04	ga_ls9c_ard_3-2-1_105078_2022-11-23_final.stac-item
2022-11-28 11:08:46	ga_ls9c_ard_3-2-1_108076_2022-11-28_final.stac-item
2022-11-30 10:55:36	ga_ls9c_ard_3-2-1_106074_2022-11-30_final.stac-item
2022-12-05 09:34:04	ga_ls9c_ard_3-2-1_093071_2022-12-05_final.stac-item
2022-12-07 09:26:07	ga_ls9c_ard_3-2-1_091082_2022-12-06_final.stac-item
2022-12-07 11:02:36	ga_ls9c_ard_3-2-1_107076_2022-12-07_final.stac-item
2022-12-09 09:14:10	ga_ls9c_ard_3-2-1_089083_2022-12-08_final.stac-item
2022-12-11 10:35:06	ga_ls9c_ard_3-2-1_103069_2022-12-11_final.stac-item
2022-12-12 11:21:33	ga_ls9c_ard_3-2-1_110077_2022-12-12_final.stac-item
2023-01-01 09:19:57	ga_ls9c_ard_3-2-1_090082_2022-12-31_final.stac-item
2023-01-03 10:44:28	ga_ls9c_ard_3-2-1_104077_2023-01-03_final.stac-item
2023-01-15 11:06:44	ga_ls9c_ard_3-2-1_108071_2023-01-15_final.stac-item
2023-01-17 09:19:51	ga_ls9c_ard_3-2-1_090082_2023-01-16_final.stac-item
2023-01-18 09:57:06	ga_ls9c_ard_3-2-1_097067_2023-01-18_final.stac-item
2023-01-20 11:25:10	ga_ls9c_ard_3-2-1_111071_2023-01-20_final.stac-item
2023-01-24 09:25:14	ga_ls9c_ard_3-2-1_091080_2023-01-23_final.stac-item
2023-01-27 11:32:16	ga_ls9c_ard_3-2-1_112073_2023-01-27_final.stac-item
2023-02-17 10:14:45	ga_ls9c_ard_3-2-1_099080_2023-02-17_final.stac-item
2023-02-21 09:51:08	ga_ls9c_ard_3-2-1_095083_2023-02-21_final.stac-item
2023-03-04 09:33:17	ga_ls9c_ard_3-2-1_092085_2023-03-04_final.stac-item
2023-03-28 10:21:41	ga_ls9c_ard_3-2-1_100083_2023-03-28_final.stac-item
2023-03-30 10:08:05	ga_ls9c_ard_3-2-1_098080_2023-03-30_final.stac-item
2023-04-12 11:12:49	ga_ls9c_ard_3-2-1_109072_2023-04-12_final.stac-item
2023-04-21 09:32:54	ga_ls9c_ard_3-2-1_092085_2023-04-21_final.stac-item
2023-04-24 10:03:23	ga_ls9c_ard_3-2-1_097084_2023-04-24_final.stac-item
2023-04-30 11:01:30	ga_ls9c_ard_3-2-1_107075_2023-04-30_final.stac-item
2023-05-13 10:33:17	ga_ls9c_ard_3-2-1_102082_2023-05-13_final.stac-item
2023-05-23 11:11:02	ga_ls9c_ard_3-2-1_108084_2023-05-23_final.stac-item
2023-05-26 09:57:26	ga_ls9c_ard_3-2-1_097070_2023-05-26_final.stac-item
2023-05-26 11:41:31	ga_ls9c_ard_3-2-1_113083_2023-05-26_final.stac-item
2023-05-30 11:12:00	ga_ls9c_ard_3-2-1_109071_2023-05-30_final.stac-item
2023-06-01 11:03:14	ga_ls9c_ard_3-2-1_107080_2023-06-01_final.stac-item
2023-06-02 10:03:37	ga_ls9c_ard_3-2-1_098070_2023-06-02_final.stac-item
2023-06-18 11:45:57	ga_ls9c_ard_3-2-1_114079_2023-06-18_final.stac-item
2023-06-22 11:18:50	ga_ls9c_ard_3-2-1_110073_2023-06-22_final.stac-item
2023-07-09 10:24:15	ga_ls9c_ard_3-2-1_101075_2023-07-09_final.stac-item
2023-07-21 10:45:49	ga_ls9c_ard_3-2-1_105067_2023-07-21_final.stac-item
2023-07-25 10:25:27	ga_ls9c_ard_3-2-1_101078_2023-07-25_final.stac-item
2023-08-04 10:59:54	ga_ls9c_ard_3-2-1_107071_2023-08-04_final.stac-item
2023-08-06 09:13:52	ga_ls9c_ard_3-2-1_089084_2023-08-05_final.stac-item
2023-08-16 09:46:34	ga_ls9c_ard_3-2-1_095073_2023-08-16_final.stac-item
2023-10-13 10:28:05	ga_ls9c_ard_3-2-1_101083_2023-10-13_final.stac-item
2023-10-15 11:52:38	ga_ls9c_ard_3-2-1_115078_2023-10-15_final.stac-item
2023-10-16 10:53:49	ga_ls9c_ard_3-2-1_106070_2023-10-16_final.stac-item
2023-10-21 11:14:46	ga_ls9c_ard_3-2-1_109076_2023-10-21_final.stac-item
2023-10-22 10:22:20	ga_ls9c_ard_3-2-1_100084_2023-10-22_final.stac-item
2023-10-23 11:02:00	ga_ls9c_ard_3-2-1_107075_2023-10-23_final.stac-item
2023-11-01 09:22:02	ga_ls9c_ard_3-2-1_090088_2023-10-31_final.stac-item
2023-11-18 11:42:15	ga_ls9c_ard_3-2-1_113083_2023-11-18_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