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
2021-12-05 10:05:21	ga_ls9c_ard_3-2-1_098072_2021-12-05_final.stac-item
2021-12-14 09:58:16	ga_ls9c_ard_3-2-1_097070_2021-12-14_final.stac-item
2022-01-21 09:21:57	ga_ls9c_ard_3-2-1_091072_2022-01-20_final.stac-item
2022-01-21 11:05:37	ga_ls9c_ard_3-2-1_107084_2022-01-21_final.stac-item
2022-01-23 09:13:59	ga_ls9c_ard_3-2-1_089083_2022-01-22_final.stac-item
2022-01-28 09:34:07	ga_ls9c_ard_3-2-1_092087_2022-01-28_final.stac-item
2022-01-30 09:19:46	ga_ls9c_ard_3-2-1_090082_2022-01-29_final.stac-item
2022-02-07 10:08:24	ga_ls9c_ard_3-2-1_098080_2022-02-07_final.stac-item
2022-02-14 10:14:08	ga_ls9c_ard_3-2-1_099079_2022-02-14_final.stac-item
2022-03-10 09:24:06	ga_ls9c_ard_3-2-1_091078_2022-03-09_final.stac-item
2022-03-12 09:12:09	ga_ls9c_ard_3-2-1_089079_2022-03-11_final.stac-item
2022-04-16 11:18:56	ga_ls9c_ard_3-2-1_110072_2022-04-16_final.stac-item
2022-05-10 10:33:19	ga_ls9c_ard_3-2-1_102082_2022-05-10_final.stac-item
2022-06-14 11:04:58	ga_ls9c_ard_3-2-1_107084_2022-06-14_final.stac-item
2022-06-22 10:10:55	ga_ls9c_ard_3-2-1_099072_2022-06-22_final.stac-item
2022-07-04 10:39:18	ga_ls9c_ard_3-2-1_103081_2022-07-04_final.stac-item
2022-07-11 09:06:09	ga_ls9c_ard_3-2-1_088080_2022-07-10_final.stac-item
2022-07-21 09:40:56	ga_ls9c_ard_3-2-1_094074_2022-07-21_final.stac-item
2022-08-03 09:13:48	ga_ls9c_ard_3-2-1_089083_2022-08-02_final.stac-item
2022-08-13 09:46:59	ga_ls9c_ard_3-2-1_095073_2022-08-13_final.stac-item
2022-08-15 09:39:02	ga_ls9c_ard_3-2-1_093084_2022-08-15_final.stac-item
2022-09-20 10:46:32	ga_ls9c_ard_3-2-1_105067_2022-09-20_final.stac-item
2022-09-24 10:23:26	ga_ls9c_ard_3-2-1_101071_2022-09-24_final.stac-item
2022-10-16 09:46:51	ga_ls9c_ard_3-2-1_095072_2022-10-16_final.stac-item
2022-10-18 09:35:41	ga_ls9c_ard_3-2-1_093075_2022-10-18_final.stac-item
2022-10-18 09:39:41	ga_ls9c_ard_3-2-1_093085_2022-10-18_final.stac-item
2022-10-27 09:29:31	ga_ls9c_ard_3-2-1_092075_2022-10-26_final.stac-item
2022-11-06 10:04:34	ga_ls9c_ard_3-2-1_098070_2022-11-06_final.stac-item
2022-11-11 10:27:56	ga_ls9c_ard_3-2-1_101082_2022-11-11_final.stac-item
2022-11-12 11:06:25	ga_ls9c_ard_3-2-1_108070_2022-11-12_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 10:54:51	ga_ls9c_ard_3-2-1_106072_2022-11-14_final.stac-item
2022-11-17 11:30:33	ga_ls9c_ard_3-2-1_111084_2022-11-17_final.stac-item
2022-11-19 11:12:12	ga_ls9c_ard_3-2-1_109069_2022-11-19_final.stac-item
2022-11-20 10:22:34	ga_ls9c_ard_3-2-1_100084_2022-11-20_final.stac-item
2022-11-28 09:29:30	ga_ls9c_ard_3-2-1_092075_2022-11-27_final.stac-item
2022-11-28 11:07:35	ga_ls9c_ard_3-2-1_108073_2022-11-28_final.stac-item
2022-11-28 11:11:34	ga_ls9c_ard_3-2-1_108083_2022-11-28_final.stac-item
2022-12-03 11:30:29	ga_ls9c_ard_3-2-1_111084_2022-12-03_final.stac-item
2022-12-04 10:30:05	ga_ls9c_ard_3-2-1_102072_2022-12-04_final.stac-item
2022-12-05 11:13:45	ga_ls9c_ard_3-2-1_109073_2022-12-05_final.stac-item
2022-12-10 09:52:14	ga_ls9c_ard_3-2-1_096070_2022-12-10_final.stac-item
2022-12-12 11:19:34	ga_ls9c_ard_3-2-1_110072_2022-12-12_final.stac-item
2022-12-15 11:52:27	ga_ls9c_ard_3-2-1_115077_2022-12-15_final.stac-item
2022-12-17 09:57:13	ga_ls9c_ard_3-2-1_097067_2022-12-17_final.stac-item
2022-12-17 11:42:05	ga_ls9c_ard_3-2-1_113082_2022-12-17_final.stac-item
2022-12-24 10:10:31	ga_ls9c_ard_3-2-1_098085_2022-12-24_final.stac-item
2022-12-27 10:35:04	ga_ls9c_ard_3-2-1_103069_2022-12-27_final.stac-item
2022-12-28 11:20:20	ga_ls9c_ard_3-2-1_110074_2022-12-28_final.stac-item
2022-12-29 10:25:07	ga_ls9c_ard_3-2-1_101075_2022-12-29_final.stac-item
2023-01-02 10:02:01	ga_ls9c_ard_3-2-1_097079_2023-01-02_final.stac-item
2023-01-09 10:10:35	ga_ls9c_ard_3-2-1_098085_2023-01-09_final.stac-item
2023-01-15 11:05:56	ga_ls9c_ard_3-2-1_108069_2023-01-15_final.stac-item
2023-01-17 09:20:39	ga_ls9c_ard_3-2-1_090084_2023-01-16_final.stac-item
2023-01-19 10:42:44	ga_ls9c_ard_3-2-1_104073_2023-01-19_final.stac-item
2023-01-20 11:23:59	ga_ls9c_ard_3-2-1_111068_2023-01-20_final.stac-item
2023-01-26 10:50:11	ga_ls9c_ard_3-2-1_105076_2023-01-26_final.stac-item
2023-01-29 09:41:03	ga_ls9c_ard_3-2-1_094073_2023-01-29_final.stac-item
2023-01-29 11:18:21	ga_ls9c_ard_3-2-1_110069_2023-01-29_final.stac-item
2023-02-09 11:01:29	ga_ls9c_ard_3-2-1_107073_2023-02-09_final.stac-item
2023-02-11 09:15:01	ga_ls9c_ard_3-2-1_089085_2023-02-10_final.stac-item
2023-02-23 11:14:48	ga_ls9c_ard_3-2-1_109076_2023-02-23_final.stac-item
2023-02-24 10:21:57	ga_ls9c_ard_3-2-1_100083_2023-02-24_final.stac-item
2023-03-01 10:37:42	ga_ls9c_ard_3-2-1_103076_2023-03-01_final.stac-item
2023-03-02 09:41:16	ga_ls9c_ard_3-2-1_094074_2023-03-02_final.stac-item
2023-03-02 11:24:09	ga_ls9c_ard_3-2-1_110084_2023-03-02_final.stac-item
2023-03-03 10:27:43	ga_ls9c_ard_3-2-1_101082_2023-03-03_final.stac-item
2023-03-17 10:35:12	ga_ls9c_ard_3-2-1_103070_2023-03-17_final.stac-item
2023-03-27 11:13:44	ga_ls9c_ard_3-2-1_109074_2023-03-27_final.stac-item
2023-03-31 10:46:58	ga_ls9c_ard_3-2-1_105069_2023-03-31_final.stac-item
2023-04-21 11:05:24	ga_ls9c_ard_3-2-1_108069_2023-04-21_final.stac-item
2023-04-28 09:33:25	ga_ls9c_ard_3-2-1_093071_2023-04-28_final.stac-item
2023-04-28 09:39:48	ga_ls9c_ard_3-2-1_093087_2023-04-28_final.stac-item
2023-05-01 10:03:04	ga_ls9c_ard_3-2-1_098068_2023-05-01_final.stac-item
2023-05-05 11:19:57	ga_ls9c_ard_3-2-1_110075_2023-05-05_final.stac-item
2023-05-07 09:34:18	ga_ls9c_ard_3-2-1_092089_2023-05-07_final.stac-item
2023-05-17 10:04:32	ga_ls9c_ard_3-2-1_098072_2023-05-17_final.stac-item
2023-05-20 10:38:35	ga_ls9c_ard_3-2-1_103080_2023-05-20_final.stac-item
2023-05-31 10:20:46	ga_ls9c_ard_3-2-1_100082_2023-05-31_final.stac-item
2023-06-05 10:35:18	ga_ls9c_ard_3-2-1_103072_2023-06-05_final.stac-item
2023-06-25 10:10:26	ga_ls9c_ard_3-2-1_099072_2023-06-25_final.stac-item
2023-07-15 09:46:24	ga_ls9c_ard_3-2-1_095073_2023-07-15_final.stac-item
2023-07-22 11:31:04	ga_ls9c_ard_3-2-1_112072_2023-07-22_final.stac-item
2023-07-23 10:38:14	ga_ls9c_ard_3-2-1_103079_2023-07-23_final.stac-item
2023-07-24 09:44:59	ga_ls9c_ard_3-2-1_094085_2023-07-24_final.stac-item
2023-07-26 09:32:39	ga_ls9c_ard_3-2-1_092085_2023-07-26_final.stac-item
2023-07-26 09:33:03	ga_ls9c_ard_3-2-1_092086_2023-07-26_final.stac-item
2023-07-28 09:17:08	ga_ls9c_ard_3-2-1_090077_2023-07-27_final.stac-item
2023-07-31 11:23:23	ga_ls9c_ard_3-2-1_111068_2023-07-31_final.stac-item
2023-07-31 11:24:58	ga_ls9c_ard_3-2-1_111072_2023-07-31_final.stac-item
2023-08-04 09:21:25	ga_ls9c_ard_3-2-1_091072_2023-08-03_final.stac-item
2023-08-11 11:06:55	ga_ls9c_ard_3-2-1_108073_2023-08-11_final.stac-item
2023-08-13 09:20:28	ga_ls9c_ard_3-2-1_090085_2023-08-12_final.stac-item
2023-08-14 09:56:33	ga_ls9c_ard_3-2-1_097067_2023-08-14_final.stac-item
2023-10-15 10:15:45	ga_ls9c_ard_3-2-1_099083_2023-10-15_final.stac-item
2023-10-23 09:27:55	ga_ls9c_ard_3-2-1_091087_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
2023-10-25 09:11:33	ga_ls9c_ard_3-2-1_089077_2023-10-24_final.stac-item
2023-11-04 11:26:13	ga_ls9c_ard_3-2-1_111074_2023-11-04_final.stac-item
2023-11-17 10:58:58	ga_ls9c_ard_3-2-1_106083_2023-11-17_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