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
2021-11-05 11:18:04	ga_ls9c_ard_3-2-1_109083_2021-11-05_final.stac-item
2021-11-07 10:58:56	ga_ls9c_ard_3-2-1_106082_2021-11-07_final.stac-item
2021-11-11 10:19:03	ga_ls9c_ard_3-2-1_100076_2021-11-11_final.stac-item
2021-11-23 10:03:14	ga_ls9c_ard_3-2-1_098071_2021-11-23_final.stac-item
2021-12-07 11:35:50	ga_ls9c_ard_3-2-1_112082_2021-12-07_final.stac-item
2021-12-12 11:51:56	ga_ls9c_ard_3-2-1_115076_2021-12-12_final.stac-item
2021-12-30 11:41:32	ga_ls9c_ard_3-2-1_113081_2021-12-30_final.stac-item
2022-01-03 09:37:55	ga_ls9c_ard_3-2-1_093081_2022-01-03_final.stac-item
2022-01-09 10:35:18	ga_ls9c_ard_3-2-1_103070_2022-01-09_final.stac-item
2022-01-09 10:39:17	ga_ls9c_ard_3-2-1_103080_2022-01-09_final.stac-item
2022-01-21 09:25:56	ga_ls9c_ard_3-2-1_091082_2022-01-20_final.stac-item
2022-01-28 09:32:32	ga_ls9c_ard_3-2-1_092083_2022-01-28_final.stac-item
2022-02-09 11:35:42	ga_ls9c_ard_3-2-1_112082_2022-02-09_final.stac-item
2022-02-10 10:34:53	ga_ls9c_ard_3-2-1_103069_2022-02-10_final.stac-item
2022-02-10 10:38:29	ga_ls9c_ard_3-2-1_103078_2022-02-10_final.stac-item
2022-02-20 11:15:28	ga_ls9c_ard_3-2-1_109078_2022-02-20_final.stac-item
2022-03-07 10:30:29	ga_ls9c_ard_3-2-1_102074_2022-03-07_final.stac-item
2022-03-08 09:35:16	ga_ls9c_ard_3-2-1_093075_2022-03-08_final.stac-item
2022-03-08 11:15:21	ga_ls9c_ard_3-2-1_109078_2022-03-08_final.stac-item
2022-03-09 11:58:37	ga_ls9c_ard_3-2-1_116078_2022-03-09_final.stac-item
2022-03-11 10:08:10	ga_ls9c_ard_3-2-1_098080_2022-03-11_final.stac-item
2022-03-28 09:13:39	ga_ls9c_ard_3-2-1_089083_2022-03-27_final.stac-item
2022-04-07 09:50:19	ga_ls9c_ard_3-2-1_095082_2022-04-07_final.stac-item
2022-04-13 09:14:23	ga_ls9c_ard_3-2-1_089085_2022-04-12_final.stac-item
2022-04-17 10:24:30	ga_ls9c_ard_3-2-1_101075_2022-04-17_final.stac-item
2022-04-25 09:33:24	ga_ls9c_ard_3-2-1_093071_2022-04-25_final.stac-item
2022-04-29 09:14:16	ga_ls9c_ard_3-2-1_089085_2022-04-28_final.stac-item
2022-05-06 10:54:05	ga_ls9c_ard_3-2-1_106072_2022-05-06_final.stac-item
2022-05-06 10:54:53	ga_ls9c_ard_3-2-1_106074_2022-05-06_final.stac-item
2022-05-11 11:12:34	ga_ls9c_ard_3-2-1_109072_2022-05-11_final.stac-item
2022-05-20 11:09:51	ga_ls9c_ard_3-2-1_108081_2022-05-20_final.stac-item
2022-05-31 09:15:38	ga_ls9c_ard_3-2-1_089089_2022-05-30_final.stac-item
2022-06-01 09:54:54	ga_ls9c_ard_3-2-1_096079_2022-06-01_final.stac-item
2022-06-01 11:34:35	ga_ls9c_ard_3-2-1_112081_2022-06-01_final.stac-item
2022-06-21 09:34:25	ga_ls9c_ard_3-2-1_092089_2022-06-21_final.stac-item
2022-06-22 11:53:00	ga_ls9c_ard_3-2-1_115080_2022-06-22_final.stac-item
2022-07-11 10:42:15	ga_ls9c_ard_3-2-1_104073_2022-07-11_final.stac-item
2022-07-14 11:13:07	ga_ls9c_ard_3-2-1_109073_2022-07-14_final.stac-item
2022-07-14 11:14:43	ga_ls9c_ard_3-2-1_109077_2022-07-14_final.stac-item
2022-07-15 10:19:54	ga_ls9c_ard_3-2-1_100079_2022-07-15_final.stac-item
2022-07-18 09:14:46	ga_ls9c_ard_3-2-1_089086_2022-07-17_final.stac-item
2022-07-30 09:39:40	ga_ls9c_ard_3-2-1_093086_2022-07-30_final.stac-item
2022-07-31 10:20:33	ga_ls9c_ard_3-2-1_100080_2022-07-31_final.stac-item
2022-08-10 09:22:03	ga_ls9c_ard_3-2-1_090088_2022-08-09_final.stac-item
2022-08-10 10:57:44	ga_ls9c_ard_3-2-1_106080_2022-08-10_final.stac-item
2022-08-11 11:41:24	ga_ls9c_ard_3-2-1_113081_2022-08-11_final.stac-item
2022-08-14 10:31:51	ga_ls9c_ard_3-2-1_102077_2022-08-14_final.stac-item
2022-08-17 11:02:22	ga_ls9c_ard_3-2-1_107076_2022-08-17_final.stac-item
2022-08-22 09:44:02	ga_ls9c_ard_3-2-1_094081_2022-08-22_final.stac-item
2022-08-26 09:20:31	ga_ls9c_ard_3-2-1_090084_2022-08-25_final.stac-item
2022-08-31 09:37:52	ga_ls9c_ard_3-2-1_093081_2022-08-31_final.stac-item
2022-09-02 11:00:48	ga_ls9c_ard_3-2-1_107072_2022-09-02_final.stac-item
2022-09-03 10:09:34	ga_ls9c_ard_3-2-1_098083_2022-09-03_final.stac-item
2022-09-07 09:41:39	ga_ls9c_ard_3-2-1_094075_2022-09-07_final.stac-item
2022-09-12 09:59:01	ga_ls9c_ard_3-2-1_097072_2022-09-12_final.stac-item
2022-09-16 11:13:37	ga_ls9c_ard_3-2-1_109073_2022-09-16_final.stac-item
2022-10-08 10:36:36	ga_ls9c_ard_3-2-1_103073_2022-10-08_final.stac-item
2022-10-09 11:21:05	ga_ls9c_ard_3-2-1_110076_2022-10-09_final.stac-item
2022-10-18 09:40:05	ga_ls9c_ard_3-2-1_093086_2022-10-18_final.stac-item
2022-10-21 11:45:05	ga_ls9c_ard_3-2-1_114074_2022-10-21_final.stac-item
2022-11-19 11:16:59	ga_ls9c_ard_3-2-1_109081_2022-11-19_final.stac-item
2022-11-23 10:48:40	ga_ls9c_ard_3-2-1_105072_2022-11-23_final.stac-item
2022-11-30 09:20:18	ga_ls9c_ard_3-2-1_090083_2022-11-29_final.stac-item
2022-12-03 09:51:36	ga_ls9c_ard_3-2-1_095084_2022-12-03_final.stac-item
2022-12-04 10:32:05	ga_ls9c_ard_3-2-1_102077_2022-12-04_final.stac-item
2022-12-05 11:16:57	ga_ls9c_ard_3-2-1_109081_2022-12-05_final.stac-item
2022-12-12 11:21:33	ga_ls9c_ard_3-2-1_110077_2022-12-12_final.stac-item
2022-12-13 10:26:44	ga_ls9c_ard_3-2-1_101079_2022-12-13_final.stac-item
2022-12-17 11:39:17	ga_ls9c_ard_3-2-1_113075_2022-12-17_final.stac-item
2022-12-21 09:37:15	ga_ls9c_ard_3-2-1_093079_2022-12-21_final.stac-item
2022-12-21 11:17:20	ga_ls9c_ard_3-2-1_109082_2022-12-21_final.stac-item
2022-12-24 10:06:32	ga_ls9c_ard_3-2-1_098075_2022-12-24_final.stac-item
2023-01-02 11:41:18	ga_ls9c_ard_3-2-1_113080_2023-01-02_final.stac-item
2023-01-07 10:22:33	ga_ls9c_ard_3-2-1_100084_2023-01-07_final.stac-item
2023-01-13 11:22:19	ga_ls9c_ard_3-2-1_110079_2023-01-13_final.stac-item
2023-01-18 11:37:59	ga_ls9c_ard_3-2-1_113072_2023-01-18_final.stac-item
2023-01-18 11:41:58	ga_ls9c_ard_3-2-1_113082_2023-01-18_final.stac-item
2023-01-28 10:38:15	ga_ls9c_ard_3-2-1_103077_2023-01-28_final.stac-item
2023-02-10 11:45:32	ga_ls9c_ard_3-2-1_114075_2023-02-10_final.stac-item
2023-02-19 11:41:13	ga_ls9c_ard_3-2-1_113080_2023-02-19_final.stac-item
2023-02-23 09:40:19	ga_ls9c_ard_3-2-1_093087_2023-02-23_final.stac-item
2023-03-11 09:40:10	ga_ls9c_ard_3-2-1_093087_2023-03-11_final.stac-item
2023-03-18 11:23:14	ga_ls9c_ard_3-2-1_110082_2023-03-18_final.stac-item
2023-03-19 10:26:01	ga_ls9c_ard_3-2-1_101078_2023-03-19_final.stac-item
2023-03-26 10:30:54	ga_ls9c_ard_3-2-1_102075_2023-03-26_final.stac-item
2023-03-27 11:13:20	ga_ls9c_ard_3-2-1_109073_2023-03-27_final.stac-item
2023-03-27 11:13:44	ga_ls9c_ard_3-2-1_109074_2023-03-27_final.stac-item
2023-04-05 11:08:42	ga_ls9c_ard_3-2-1_108077_2023-04-05_final.stac-item
2023-04-10 09:49:06	ga_ls9c_ard_3-2-1_095079_2023-04-10_final.stac-item
2023-04-21 11:11:23	ga_ls9c_ard_3-2-1_108084_2023-04-21_final.stac-item
2023-04-23 09:17:44	ga_ls9c_ard_3-2-1_090078_2023-04-22_final.stac-item
2023-05-03 09:52:40	ga_ls9c_ard_3-2-1_096073_2023-05-03_final.stac-item
2023-05-26 11:40:19	ga_ls9c_ard_3-2-1_113080_2023-05-26_final.stac-item
2023-06-05 10:34:06	ga_ls9c_ard_3-2-1_103069_2023-06-05_final.stac-item
2023-06-10 09:16:30	ga_ls9c_ard_3-2-1_090076_2023-06-09_final.stac-item
2023-06-16 10:21:01	ga_ls9c_ard_3-2-1_100083_2023-06-16_final.stac-item
2023-06-20 11:33:11	ga_ls9c_ard_3-2-1_112078_2023-06-20_final.stac-item
2023-07-03 11:03:16	ga_ls9c_ard_3-2-1_107080_2023-07-03_final.stac-item
2023-07-10 09:29:02	ga_ls9c_ard_3-2-1_092076_2023-07-09_final.stac-item
2023-09-04 10:20:52	ga_ls9c_ard_3-2-1_100081_2023-09-04_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years