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 10:54:27	ga_ls9c_ard_3-2-1_106077_2021-11-02_final.stac-item
2021-11-07 09:23:03	ga_ls9c_ard_3-2-1_090089_2021-11-06_final.stac-item
2021-12-04 09:24:29	ga_ls9c_ard_3-2-1_091078_2021-12-03_final.stac-item
2021-12-07 09:57:45	ga_ls9c_ard_3-2-1_096084_2021-12-07_final.stac-item
2021-12-25 09:41:19	ga_ls9c_ard_3-2-1_094074_2021-12-25_final.stac-item
2022-01-09 10:38:06	ga_ls9c_ard_3-2-1_103077_2022-01-09_final.stac-item
2022-01-10 11:20:09	ga_ls9c_ard_3-2-1_110074_2022-01-10_final.stac-item
2022-03-07 10:30:06	ga_ls9c_ard_3-2-1_102073_2022-03-07_final.stac-item
2022-03-19 10:53:11	ga_ls9c_ard_3-2-1_106069_2022-03-19_final.stac-item
2022-04-16 11:19:44	ga_ls9c_ard_3-2-1_110074_2022-04-16_final.stac-item
2022-04-20 10:54:34	ga_ls9c_ard_3-2-1_106073_2022-04-20_final.stac-item
2022-05-09 09:50:52	ga_ls9c_ard_3-2-1_095084_2022-05-09_final.stac-item
2022-05-16 09:51:46	ga_ls9c_ard_3-2-1_096071_2022-05-16_final.stac-item
2022-05-28 10:19:12	ga_ls9c_ard_3-2-1_100078_2022-05-28_final.stac-item
2022-05-29 11:02:28	ga_ls9c_ard_3-2-1_107078_2022-05-29_final.stac-item
2022-06-16 10:46:14	ga_ls9c_ard_3-2-1_105068_2022-06-16_final.stac-item
2022-06-30 09:23:33	ga_ls9c_ard_3-2-1_091077_2022-06-29_final.stac-item
2022-07-02 10:48:05	ga_ls9c_ard_3-2-1_105072_2022-07-02_final.stac-item
2022-07-09 09:18:56	ga_ls9c_ard_3-2-1_090081_2022-07-08_final.stac-item
2022-07-23 11:05:53	ga_ls9c_ard_3-2-1_108070_2022-07-23_final.stac-item
2022-08-23 10:25:42	ga_ls9c_ard_3-2-1_101077_2022-08-23_final.stac-item
2022-09-16 09:35:08	ga_ls9c_ard_3-2-1_093074_2022-09-16_final.stac-item
2022-09-27 10:56:20	ga_ls9c_ard_3-2-1_106076_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
2022-10-05 11:46:58	ga_ls9c_ard_3-2-1_114079_2022-10-05_final.stac-item
2022-10-09 11:24:40	ga_ls9c_ard_3-2-1_110085_2022-10-09_final.stac-item
2022-10-12 11:51:37	ga_ls9c_ard_3-2-1_115075_2022-10-12_final.stac-item
2022-10-20 09:29:19	ga_ls9c_ard_3-2-1_091090_2022-10-19_final.stac-item
2022-10-27 09:29:55	ga_ls9c_ard_3-2-1_092076_2022-10-26_final.stac-item
2022-10-28 10:09:59	ga_ls9c_ard_3-2-1_099068_2022-10-28_final.stac-item
2022-11-01 11:25:43	ga_ls9c_ard_3-2-1_111072_2022-11-01_final.stac-item
2022-11-03 09:35:39	ga_ls9c_ard_3-2-1_093075_2022-11-03_final.stac-item
2022-11-06 10:10:09	ga_ls9c_ard_3-2-1_098084_2022-11-06_final.stac-item
2022-11-06 11:45:27	ga_ls9c_ard_3-2-1_114075_2022-11-06_final.stac-item
2022-11-14 09:18:22	ga_ls9c_ard_3-2-1_090078_2022-11-13_final.stac-item
2022-11-14 10:53:40	ga_ls9c_ard_3-2-1_106069_2022-11-14_final.stac-item
2022-11-15 10:00:02	ga_ls9c_ard_3-2-1_097074_2022-11-15_final.stac-item
2022-11-17 09:47:40	ga_ls9c_ard_3-2-1_095074_2022-11-17_final.stac-item
2022-11-19 09:35:19	ga_ls9c_ard_3-2-1_093074_2022-11-19_final.stac-item
2022-11-19 11:13:48	ga_ls9c_ard_3-2-1_109073_2022-11-19_final.stac-item
2022-11-22 11:47:29	ga_ls9c_ard_3-2-1_114080_2022-11-22_final.stac-item
2022-12-01 09:59:34	ga_ls9c_ard_3-2-1_097073_2022-12-01_final.stac-item
2022-12-02 10:44:49	ga_ls9c_ard_3-2-1_104078_2022-12-02_final.stac-item
2022-12-07 09:26:07	ga_ls9c_ard_3-2-1_091082_2022-12-06_final.stac-item
2022-12-08 11:45:28	ga_ls9c_ard_3-2-1_114075_2022-12-08_final.stac-item
2022-12-09 10:52:39	ga_ls9c_ard_3-2-1_105082_2022-12-09_final.stac-item
2022-12-11 10:39:29	ga_ls9c_ard_3-2-1_103080_2022-12-11_final.stac-item
2022-12-15 10:14:46	ga_ls9c_ard_3-2-1_099080_2022-12-15_final.stac-item
2022-12-19 11:25:43	ga_ls9c_ard_3-2-1_111072_2022-12-19_final.stac-item
2022-12-23 09:28:52	ga_ls9c_ard_3-2-1_091089_2022-12-22_final.stac-item
2022-12-24 10:08:08	ga_ls9c_ard_3-2-1_098079_2022-12-24_final.stac-item
2022-12-28 09:45:50	ga_ls9c_ard_3-2-1_094085_2022-12-28_final.stac-item
2023-01-02 10:00:25	ga_ls9c_ard_3-2-1_097075_2023-01-02_final.stac-item
2023-01-14 10:23:29	ga_ls9c_ard_3-2-1_101071_2023-01-14_final.stac-item
2023-01-15 11:05:56	ga_ls9c_ard_3-2-1_108069_2023-01-15_final.stac-item
2023-01-22 09:40:20	ga_ls9c_ard_3-2-1_093087_2023-01-22_final.stac-item
2023-01-28 10:37:04	ga_ls9c_ard_3-2-1_103074_2023-01-28_final.stac-item
2023-01-28 10:38:15	ga_ls9c_ard_3-2-1_103077_2023-01-28_final.stac-item
2023-01-29 09:41:51	ga_ls9c_ard_3-2-1_094075_2023-01-29_final.stac-item
2023-01-31 11:11:35	ga_ls9c_ard_3-2-1_108083_2023-01-31_final.stac-item
2023-02-04 10:41:19	ga_ls9c_ard_3-2-1_104069_2023-02-04_final.stac-item
2023-02-05 11:26:35	ga_ls9c_ard_3-2-1_111074_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
2023-02-06 10:28:58	ga_ls9c_ard_3-2-1_102069_2023-02-06_final.stac-item
2023-02-07 11:13:50	ga_ls9c_ard_3-2-1_109073_2023-02-07_final.stac-item
2023-02-10 11:46:44	ga_ls9c_ard_3-2-1_114078_2023-02-10_final.stac-item
2023-04-23 10:53:25	ga_ls9c_ard_3-2-1_106070_2023-04-23_final.stac-item
2023-04-29 10:21:51	ga_ls9c_ard_3-2-1_100084_2023-04-29_final.stac-item
2023-04-30 11:05:06	ga_ls9c_ard_3-2-1_107084_2023-04-30_final.stac-item
2023-05-02 09:12:37	ga_ls9c_ard_3-2-1_089081_2023-05-01_final.stac-item
2023-05-02 10:51:30	ga_ls9c_ard_3-2-1_105081_2023-05-02_final.stac-item
2023-06-25 10:14:26	ga_ls9c_ard_3-2-1_099082_2023-06-25_final.stac-item
2023-06-25 11:52:07	ga_ls9c_ard_3-2-1_115079_2023-06-25_final.stac-item
2023-06-28 10:45:24	ga_ls9c_ard_3-2-1_104082_2023-06-28_final.stac-item
2023-07-19 09:24:29	ga_ls9c_ard_3-2-1_091080_2023-07-18_final.stac-item
2023-07-27 11:51:13	ga_ls9c_ard_3-2-1_115076_2023-07-27_final.stac-item
2023-07-27 11:51:37	ga_ls9c_ard_3-2-1_115077_2023-07-27_final.stac-item
2023-07-28 10:52:49	ga_ls9c_ard_3-2-1_106069_2023-07-28_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 09:26:12	ga_ls9c_ard_3-2-1_091084_2023-08-03_final.stac-item
2023-10-14 11:11:45	ga_ls9c_ard_3-2-1_108084_2023-10-14_final.stac-item
2023-10-16 10:53:49	ga_ls9c_ard_3-2-1_106070_2023-10-16_final.stac-item
2023-10-16 10:54:13	ga_ls9c_ard_3-2-1_106071_2023-10-16_final.stac-item
2023-10-17 09:58:12	ga_ls9c_ard_3-2-1_097070_2023-10-17_final.stac-item
2023-10-18 10:41:28	ga_ls9c_ard_3-2-1_104070_2023-10-18_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
2023-10-23 11:04:24	ga_ls9c_ard_3-2-1_107081_2023-10-23_final.stac-item
2023-10-28 11:24:06	ga_ls9c_ard_3-2-1_110084_2023-10-28_final.stac-item
2023-10-31 11:52:10	ga_ls9c_ard_3-2-1_115077_2023-10-31_final.stac-item
2023-11-01 09:18:03	ga_ls9c_ard_3-2-1_090078_2023-10-31_final.stac-item
2023-11-01 10:55:20	ga_ls9c_ard_3-2-1_106074_2023-11-01_final.stac-item
2023-11-05 10:33:48	ga_ls9c_ard_3-2-1_102082_2023-11-05_final.stac-item
2023-11-17 09:20:05	ga_ls9c_ard_3-2-1_090083_2023-11-16_final.stac-item
2023-11-22 11:13:36	ga_ls9c_ard_3-2-1_109073_2023-11-22_final.stac-item
2023-11-24 09:28:22	ga_ls9c_ard_3-2-1_091088_2023-11-23_final.stac-item
2023-11-25 10:07:14	ga_ls9c_ard_3-2-1_098077_2023-11-25_final.stac-item
2023-11-25 10:08:26	ga_ls9c_ard_3-2-1_098080_2023-11-25_final.stac-item
2023-11-25 11:46:31	ga_ls9c_ard_3-2-1_114078_2023-11-25_final.stac-item
2023-11-26 10:49:43	ga_ls9c_ard_3-2-1_105075_2023-11-26_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