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

71 results

Time (local)	Label
2021-11-13 11:38:10	ga_ls9c_ard_3-2-1_113074_2021-11-13_final.stac-item
2021-12-06 10:47:48	ga_ls9c_ard_3-2-1_105070_2021-12-06_final.stac-item
2021-12-16 09:50:16	ga_ls9c_ard_3-2-1_095081_2021-12-16_final.stac-item
2021-12-25 09:40:55	ga_ls9c_ard_3-2-1_094073_2021-12-25_final.stac-item
2022-01-04 10:21:34	ga_ls9c_ard_3-2-1_100082_2022-01-04_final.stac-item
2022-02-18 11:30:15	ga_ls9c_ard_3-2-1_111084_2022-02-18_final.stac-item
2022-03-04 09:56:47	ga_ls9c_ard_3-2-1_097067_2022-03-04_final.stac-item
2022-05-21 10:12:38	ga_ls9c_ard_3-2-1_099077_2022-05-21_final.stac-item
2022-05-25 09:45:55	ga_ls9c_ard_3-2-1_095072_2022-05-25_final.stac-item
2022-06-08 09:56:42	ga_ls9c_ard_3-2-1_097068_2022-06-08_final.stac-item
2022-06-21 11:07:19	ga_ls9c_ard_3-2-1_108074_2022-06-21_final.stac-item
2022-06-22 10:08:56	ga_ls9c_ard_3-2-1_099067_2022-06-22_final.stac-item
2022-07-22 10:25:00	ga_ls9c_ard_3-2-1_101076_2022-07-22_final.stac-item
2022-07-28 11:23:42	ga_ls9c_ard_3-2-1_111068_2022-07-28_final.stac-item
2022-09-07 11:19:20	ga_ls9c_ard_3-2-1_110072_2022-09-07_final.stac-item
2022-09-09 09:29:17	ga_ls9c_ard_3-2-1_092075_2022-09-08_final.stac-item
2022-09-14 11:25:34	ga_ls9c_ard_3-2-1_111072_2022-09-14_final.stac-item
2022-09-28 11:38:48	ga_ls9c_ard_3-2-1_113074_2022-09-28_final.stac-item
2022-10-02 11:13:41	ga_ls9c_ard_3-2-1_109073_2022-10-02_final.stac-item
2022-10-05 10:09:41	ga_ls9c_ard_3-2-1_098083_2022-10-05_final.stac-item
2022-11-12 11:11:36	ga_ls9c_ard_3-2-1_108083_2022-11-12_final.stac-item
2022-11-14 10:55:39	ga_ls9c_ard_3-2-1_106074_2022-11-14_final.stac-item
2022-11-25 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-11-25_final.stac-item
2022-11-28 11:06:23	ga_ls9c_ard_3-2-1_108070_2022-11-28_final.stac-item
2022-12-13 10:26:20	ga_ls9c_ard_3-2-1_101078_2022-12-13_final.stac-item
2022-12-23 09:24:04	ga_ls9c_ard_3-2-1_091077_2022-12-22_final.stac-item
2022-12-23 11:02:33	ga_ls9c_ard_3-2-1_107076_2022-12-23_final.stac-item
2022-12-29 10:24:43	ga_ls9c_ard_3-2-1_101074_2022-12-29_final.stac-item
2023-01-01 09:23:08	ga_ls9c_ard_3-2-1_090090_2022-12-31_final.stac-item
2023-01-17 09:22:14	ga_ls9c_ard_3-2-1_090088_2023-01-16_final.stac-item
2023-01-19 10:46:20	ga_ls9c_ard_3-2-1_104082_2023-01-19_final.stac-item
2023-01-21 10:30:21	ga_ls9c_ard_3-2-1_102073_2023-01-21_final.stac-item
2023-01-25 10:03:43	ga_ls9c_ard_3-2-1_098068_2023-01-25_final.stac-item
2023-02-13 10:36:20	ga_ls9c_ard_3-2-1_103072_2023-02-13_final.stac-item
2023-02-23 11:16:48	ga_ls9c_ard_3-2-1_109081_2023-02-23_final.stac-item
2023-02-27 10:46:29	ga_ls9c_ard_3-2-1_105067_2023-02-27_final.stac-item
2023-03-20 11:07:40	ga_ls9c_ard_3-2-1_108074_2023-03-20_final.stac-item
2023-04-05 09:33:00	ga_ls9c_ard_3-2-1_092085_2023-04-05_final.stac-item
2023-04-06 11:51:09	ga_ls9c_ard_3-2-1_115075_2023-04-06_final.stac-item
2023-04-09 10:42:21	ga_ls9c_ard_3-2-1_104073_2023-04-09_final.stac-item
2023-04-11 10:29:58	ga_ls9c_ard_3-2-1_102073_2023-04-11_final.stac-item
2023-05-28 11:24:22	ga_ls9c_ard_3-2-1_111071_2023-05-28_final.stac-item
2023-06-04 09:57:38	ga_ls9c_ard_3-2-1_096086_2023-06-04_final.stac-item
2023-07-13 09:57:58	ga_ls9c_ard_3-2-1_097071_2023-07-13_final.stac-item
2023-07-21 10:46:12	ga_ls9c_ard_3-2-1_105068_2023-07-21_final.stac-item
2023-07-30 10:42:06	ga_ls9c_ard_3-2-1_104073_2023-07-30_final.stac-item
2023-08-01 10:28:34	ga_ls9c_ard_3-2-1_102070_2023-08-01_final.stac-item
2023-08-08 10:35:36	ga_ls9c_ard_3-2-1_103072_2023-08-08_final.stac-item
2023-08-09 09:39:35	ga_ls9c_ard_3-2-1_094071_2023-08-09_final.stac-item
2023-08-16 09:50:34	ga_ls9c_ard_3-2-1_095083_2023-08-16_final.stac-item
2023-08-16 09:51:45	ga_ls9c_ard_3-2-1_095086_2023-08-16_final.stac-item
2023-08-16 11:24:39	ga_ls9c_ard_3-2-1_111071_2023-08-16_final.stac-item
2023-09-16 10:42:30	ga_ls9c_ard_3-2-1_104073_2023-09-16_final.stac-item
2023-09-17 11:25:22	ga_ls9c_ard_3-2-1_111072_2023-09-17_final.stac-item
2023-10-06 10:17:01	ga_ls9c_ard_3-2-1_100071_2023-10-06_final.stac-item
2023-10-08 10:03:29	ga_ls9c_ard_3-2-1_098068_2023-10-08_final.stac-item
2023-10-08 10:04:40	ga_ls9c_ard_3-2-1_098071_2023-10-08_final.stac-item
2023-10-09 10:46:21	ga_ls9c_ard_3-2-1_105067_2023-10-09_final.stac-item
2023-11-08 11:03:08	ga_ls9c_ard_3-2-1_107078_2023-11-08_final.stac-item
2023-11-14 10:24:03	ga_ls9c_ard_3-2-1_101073_2023-11-14_final.stac-item
2023-12-18 11:52:44	ga_ls9c_ard_3-2-1_115078_2023-12-18_final.stac-item
2023-12-19 09:22:37	ga_ls9c_ard_3-2-1_090089_2023-12-18_final.stac-item
2023-12-20 11:39:59	ga_ls9c_ard_3-2-1_113077_2023-12-20_final.stac-item
2024-01-20 09:16:57	ga_ls9c_ard_3-2-1_090075_2024-01-19_final.stac-item
2024-02-08 11:26:00	ga_ls9c_ard_3-2-1_111073_2024-02-08_final.stac-item
2024-03-18 09:57:56	ga_ls9c_ard_3-2-1_096085_2024-03-18_final.stac-item
2024-03-20 11:18:27	ga_ls9c_ard_3-2-1_110070_2024-03-20_final.stac-item
2024-05-02 11:02:10	ga_ls9c_ard_3-2-1_107077_2024-05-02_final.stac-item
2024-05-18 11:00:50	ga_ls9c_ard_3-2-1_107074_2024-05-18_nrt.stac-item
2024-06-02 11:57:33	ga_ls9c_ard_3-2-1_116077_2024-06-02_nrt.stac-item
2024-06-03 09:27:26	ga_ls9c_ard_3-2-1_091088_2024-06-02_nrt.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