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
2021-11-18 10:01:10	ga_ls9c_ard_3-2-1_097072_2021-11-18_final.stac-item
2021-12-31 10:41:31	ga_ls9c_ard_3-2-1_104070_2021-12-31_final.stac-item
2022-01-21 09:25:08	ga_ls9c_ard_3-2-1_091080_2022-01-20_final.stac-item
2022-02-15 09:19:42	ga_ls9c_ard_3-2-1_090082_2022-02-14_final.stac-item
2022-02-19 10:30:13	ga_ls9c_ard_3-2-1_102073_2022-02-19_final.stac-item
2022-02-20 09:34:59	ga_ls9c_ard_3-2-1_093074_2022-02-20_final.stac-item
2022-02-20 11:13:28	ga_ls9c_ard_3-2-1_109073_2022-02-20_final.stac-item
2022-03-01 09:31:05	ga_ls9c_ard_3-2-1_092080_2022-03-01_final.stac-item
2022-03-05 10:42:27	ga_ls9c_ard_3-2-1_104073_2022-03-05_final.stac-item
2022-03-27 11:46:34	ga_ls9c_ard_3-2-1_114079_2022-03-27_final.stac-item
2022-04-11 09:25:10	ga_ls9c_ard_3-2-1_091081_2022-04-10_final.stac-item
2022-04-25 09:39:47	ga_ls9c_ard_3-2-1_093087_2022-04-25_final.stac-item
2022-05-09 09:51:16	ga_ls9c_ard_3-2-1_095085_2022-05-09_final.stac-item
2022-05-13 10:59:47	ga_ls9c_ard_3-2-1_107071_2022-05-13_final.stac-item
2022-05-31 10:46:56	ga_ls9c_ard_3-2-1_105070_2022-05-31_final.stac-item
2022-06-07 10:54:19	ga_ls9c_ard_3-2-1_106073_2022-06-07_final.stac-item
2022-06-08 10:00:42	ga_ls9c_ard_3-2-1_097078_2022-06-08_final.stac-item
2022-06-12 11:12:06	ga_ls9c_ard_3-2-1_109071_2022-06-12_final.stac-item
2022-06-14 09:24:29	ga_ls9c_ard_3-2-1_091080_2022-06-13_final.stac-item
2022-06-14 09:24:53	ga_ls9c_ard_3-2-1_091081_2022-06-13_final.stac-item
2022-06-24 10:01:01	ga_ls9c_ard_3-2-1_097078_2022-06-24_final.stac-item
2022-07-01 10:08:01	ga_ls9c_ard_3-2-1_098080_2022-07-01_final.stac-item
2022-07-14 11:12:19	ga_ls9c_ard_3-2-1_109071_2022-07-14_final.stac-item
2022-07-23 11:05:53	ga_ls9c_ard_3-2-1_108070_2022-07-23_final.stac-item
2022-07-26 11:41:37	ga_ls9c_ard_3-2-1_113082_2022-07-26_final.stac-item
2022-08-03 10:52:41	ga_ls9c_ard_3-2-1_105083_2022-08-03_final.stac-item
2022-08-04 09:52:17	ga_ls9c_ard_3-2-1_096071_2022-08-04_final.stac-item
2022-08-06 11:23:13	ga_ls9c_ard_3-2-1_110082_2022-08-06_final.stac-item
2022-08-18 11:44:50	ga_ls9c_ard_3-2-1_114074_2022-08-18_final.stac-item
2022-08-24 11:06:35	ga_ls9c_ard_3-2-1_108071_2022-08-24_final.stac-item
2022-08-26 09:20:31	ga_ls9c_ard_3-2-1_090084_2022-08-25_final.stac-item
2022-09-05 11:32:06	ga_ls9c_ard_3-2-1_112073_2022-09-05_final.stac-item
2022-09-09 11:06:34	ga_ls9c_ard_3-2-1_108071_2022-09-09_final.stac-item
2022-09-16 11:12:26	ga_ls9c_ard_3-2-1_109070_2022-09-16_final.stac-item
2022-09-20 09:13:14	ga_ls9c_ard_3-2-1_089081_2022-09-19_final.stac-item
2022-09-27 10:55:09	ga_ls9c_ard_3-2-1_106073_2022-09-27_final.stac-item
2022-09-28 10:01:55	ga_ls9c_ard_3-2-1_097079_2022-09-28_final.stac-item
2022-10-09 09:43:47	ga_ls9c_ard_3-2-1_094080_2022-10-09_final.stac-item
2022-10-20 11:01:01	ga_ls9c_ard_3-2-1_107072_2022-10-20_final.stac-item
2022-10-25 09:43:52	ga_ls9c_ard_3-2-1_094080_2022-10-25_final.stac-item
2022-10-30 09:58:24	ga_ls9c_ard_3-2-1_097070_2022-10-30_final.stac-item
2022-11-07 10:48:14	ga_ls9c_ard_3-2-1_105071_2022-11-07_final.stac-item
2022-11-08 09:53:26	ga_ls9c_ard_3-2-1_096073_2022-11-08_final.stac-item
2022-11-10 11:18:46	ga_ls9c_ard_3-2-1_110070_2022-11-10_final.stac-item
2022-11-15 10:00:02	ga_ls9c_ard_3-2-1_097074_2022-11-15_final.stac-item
2022-11-16 10:41:18	ga_ls9c_ard_3-2-1_104069_2022-11-16_final.stac-item
2022-11-17 09:47:40	ga_ls9c_ard_3-2-1_095074_2022-11-17_final.stac-item
2022-11-23 10:53:03	ga_ls9c_ard_3-2-1_105083_2022-11-23_final.stac-item
2022-11-28 11:07:11	ga_ls9c_ard_3-2-1_108072_2022-11-28_final.stac-item
2022-12-07 09:25:43	ga_ls9c_ard_3-2-1_091081_2022-12-06_final.stac-item
2022-12-08 11:45:04	ga_ls9c_ard_3-2-1_114074_2022-12-08_final.stac-item
2022-12-09 10:53:03	ga_ls9c_ard_3-2-1_105083_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
2022-12-12 09:44:16	ga_ls9c_ard_3-2-1_094081_2022-12-12_final.stac-item
2022-12-15 11:51:15	ga_ls9c_ard_3-2-1_115074_2022-12-15_final.stac-item
2022-12-17 09:59:12	ga_ls9c_ard_3-2-1_097072_2022-12-17_final.stac-item
2022-12-17 11:41:41	ga_ls9c_ard_3-2-1_113081_2022-12-17_final.stac-item
2022-12-25 10:53:00	ga_ls9c_ard_3-2-1_105083_2022-12-25_final.stac-item
2022-12-31 10:16:45	ga_ls9c_ard_3-2-1_099085_2022-12-31_final.stac-item
2023-01-02 11:42:29	ga_ls9c_ard_3-2-1_113083_2023-01-02_final.stac-item
2023-01-22 11:14:50	ga_ls9c_ard_3-2-1_109076_2023-01-22_final.stac-item
2023-01-27 11:33:04	ga_ls9c_ard_3-2-1_112075_2023-01-27_final.stac-item
2023-01-28 10:38:15	ga_ls9c_ard_3-2-1_103077_2023-01-28_final.stac-item
2023-02-07 09:37:21	ga_ls9c_ard_3-2-1_093079_2023-02-07_final.stac-item
2023-02-11 09:13:25	ga_ls9c_ard_3-2-1_089081_2023-02-10_final.stac-item
2023-02-11 10:52:18	ga_ls9c_ard_3-2-1_105081_2023-02-11_final.stac-item
2023-02-27 10:52:04	ga_ls9c_ard_3-2-1_105081_2023-02-27_final.stac-item
2023-03-13 09:24:14	ga_ls9c_ard_3-2-1_091078_2023-03-12_final.stac-item
2023-04-21 11:10:59	ga_ls9c_ard_3-2-1_108083_2023-04-21_final.stac-item
2023-04-22 10:15:45	ga_ls9c_ard_3-2-1_099084_2023-04-22_final.stac-item
2023-04-28 09:35:01	ga_ls9c_ard_3-2-1_093075_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
2023-05-05 11:18:45	ga_ls9c_ard_3-2-1_110072_2023-05-05_final.stac-item
2023-05-06 10:22:44	ga_ls9c_ard_3-2-1_101071_2023-05-06_final.stac-item
2023-05-06 10:26:43	ga_ls9c_ard_3-2-1_101081_2023-05-06_final.stac-item
2023-05-09 09:19:56	ga_ls9c_ard_3-2-1_090084_2023-05-08_final.stac-item
2023-05-15 10:21:42	ga_ls9c_ard_3-2-1_100084_2023-05-15_final.stac-item
2023-05-19 11:35:49	ga_ls9c_ard_3-2-1_112084_2023-05-19_final.stac-item
2023-06-02 10:04:25	ga_ls9c_ard_3-2-1_098072_2023-06-02_final.stac-item
2023-06-04 09:55:38	ga_ls9c_ard_3-2-1_096081_2023-06-04_final.stac-item
2023-06-26 09:20:25	ga_ls9c_ard_3-2-1_090086_2023-06-25_final.stac-item
2023-06-29 09:50:37	ga_ls9c_ard_3-2-1_095084_2023-06-29_final.stac-item
2023-06-29 11:28:42	ga_ls9c_ard_3-2-1_111082_2023-06-29_final.stac-item
2023-07-01 11:16:47	ga_ls9c_ard_3-2-1_109083_2023-07-01_final.stac-item
2023-07-27 11:51:13	ga_ls9c_ard_3-2-1_115076_2023-07-27_final.stac-item
2023-08-02 11:13:02	ga_ls9c_ard_3-2-1_109073_2023-08-02_final.stac-item
2023-08-03 10:21:25	ga_ls9c_ard_3-2-1_100083_2023-08-03_final.stac-item
2023-08-06 09:12:40	ga_ls9c_ard_3-2-1_089081_2023-08-05_final.stac-item
2023-08-09 09:40:47	ga_ls9c_ard_3-2-1_094074_2023-08-09_final.stac-item
2023-08-09 09:44:47	ga_ls9c_ard_3-2-1_094084_2023-08-09_final.stac-item
2023-08-14 10:01:20	ga_ls9c_ard_3-2-1_097079_2023-08-14_final.stac-item
2023-11-01 10:54:32	ga_ls9c_ard_3-2-1_106072_2023-11-01_final.stac-item
2023-11-02 11:42:10	ga_ls9c_ard_3-2-1_113083_2023-11-02_final.stac-item
2023-11-04 11:29:01	ga_ls9c_ard_3-2-1_111081_2023-11-04_final.stac-item
2023-11-18 10:01:22	ga_ls9c_ard_3-2-1_097078_2023-11-18_final.stac-item
2023-11-21 10:29:07	ga_ls9c_ard_3-2-1_102070_2023-11-21_final.stac-item
2023-11-21 10:29:55	ga_ls9c_ard_3-2-1_102072_2023-11-21_final.stac-item
2023-11-22 09:39:54	ga_ls9c_ard_3-2-1_093086_2023-11-22_final.stac-item
2023-11-24 09:24:46	ga_ls9c_ard_3-2-1_091079_2023-11-23_final.stac-item
2023-11-25 11:45:44	ga_ls9c_ard_3-2-1_114076_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