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
2021-12-04 09:24:05	ga_ls9c_ard_3-2-1_091077_2021-12-03_final.stac-item
2021-12-09 11:19:28	ga_ls9c_ard_3-2-1_110072_2021-12-09_final.stac-item
2021-12-28 11:51:54	ga_ls9c_ard_3-2-1_115076_2021-12-28_final.stac-item
2021-12-29 09:21:47	ga_ls9c_ard_3-2-1_090087_2021-12-28_final.stac-item
2021-12-29 09:22:59	ga_ls9c_ard_3-2-1_090090_2021-12-28_final.stac-item
2022-01-01 11:26:22	ga_ls9c_ard_3-2-1_111074_2022-01-01_final.stac-item
2022-01-03 11:12:48	ga_ls9c_ard_3-2-1_109071_2022-01-03_final.stac-item
2022-01-08 09:58:02	ga_ls9c_ard_3-2-1_096085_2022-01-08_final.stac-item
2022-01-30 09:22:58	ga_ls9c_ard_3-2-1_090090_2022-01-29_final.stac-item
2022-02-07 11:44:53	ga_ls9c_ard_3-2-1_114074_2022-02-07_final.stac-item
2022-02-08 09:13:34	ga_ls9c_ard_3-2-1_089082_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
2022-02-21 10:17:26	ga_ls9c_ard_3-2-1_100072_2022-02-21_final.stac-item
2022-04-13 09:16:23	ga_ls9c_ard_3-2-1_089090_2022-04-12_final.stac-item
2022-04-29 09:16:15	ga_ls9c_ard_3-2-1_089090_2022-04-28_final.stac-item
2022-05-15 09:16:06	ga_ls9c_ard_3-2-1_089090_2022-05-14_final.stac-item
2022-05-26 10:27:34	ga_ls9c_ard_3-2-1_102068_2022-05-26_final.stac-item
2022-06-16 09:16:08	ga_ls9c_ard_3-2-1_089090_2022-06-15_final.stac-item
2022-06-16 10:52:14	ga_ls9c_ard_3-2-1_105083_2022-06-16_final.stac-item
2022-07-02 09:16:23	ga_ls9c_ard_3-2-1_089090_2022-07-01_final.stac-item
2022-07-06 10:25:20	ga_ls9c_ard_3-2-1_101077_2022-07-06_final.stac-item
2022-07-11 09:06:09	ga_ls9c_ard_3-2-1_088080_2022-07-10_final.stac-item
2022-07-16 09:24:41	ga_ls9c_ard_3-2-1_091080_2022-07-15_final.stac-item
2022-07-21 09:45:43	ga_ls9c_ard_3-2-1_094086_2022-07-21_final.stac-item
2022-07-27 09:06:20	ga_ls9c_ard_3-2-1_088080_2022-07-26_final.stac-item
2022-08-03 09:11:48	ga_ls9c_ard_3-2-1_089078_2022-08-02_final.stac-item
2022-08-03 10:52:41	ga_ls9c_ard_3-2-1_105083_2022-08-03_final.stac-item
2022-08-08 11:11:41	ga_ls9c_ard_3-2-1_108084_2022-08-08_final.stac-item
2022-08-15 09:39:02	ga_ls9c_ard_3-2-1_093084_2022-08-15_final.stac-item
2022-08-19 09:11:56	ga_ls9c_ard_3-2-1_089078_2022-08-18_final.stac-item
2022-08-19 09:16:19	ga_ls9c_ard_3-2-1_089089_2022-08-18_final.stac-item
2022-09-05 09:57:36	ga_ls9c_ard_3-2-1_096084_2022-09-05_final.stac-item
2022-09-06 10:36:04	ga_ls9c_ard_3-2-1_103072_2022-09-06_final.stac-item
2022-10-05 10:04:54	ga_ls9c_ard_3-2-1_098071_2022-10-05_final.stac-item
2022-10-11 09:33:27	ga_ls9c_ard_3-2-1_092085_2022-10-11_final.stac-item
2022-10-12 10:09:56	ga_ls9c_ard_3-2-1_099068_2022-10-12_final.stac-item
2022-10-12 10:11:32	ga_ls9c_ard_3-2-1_099072_2022-10-12_final.stac-item
2022-10-16 09:52:50	ga_ls9c_ard_3-2-1_095087_2022-10-16_final.stac-item
2022-10-29 10:53:38	ga_ls9c_ard_3-2-1_106069_2022-10-29_final.stac-item
2022-11-04 10:19:18	ga_ls9c_ard_3-2-1_100076_2022-11-04_final.stac-item
2022-11-05 09:29:17	ga_ls9c_ard_3-2-1_091090_2022-11-04_final.stac-item
2022-11-06 10:07:46	ga_ls9c_ard_3-2-1_098078_2022-11-06_final.stac-item
2022-11-09 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-11-09_final.stac-item
2022-11-16 09:06:48	ga_ls9c_ard_3-2-1_088080_2022-11-15_final.stac-item
2022-11-26 11:20:21	ga_ls9c_ard_3-2-1_110074_2022-11-26_final.stac-item
2022-12-05 09:35:40	ga_ls9c_ard_3-2-1_093075_2022-12-05_final.stac-item
2022-12-06 10:17:20	ga_ls9c_ard_3-2-1_100071_2022-12-06_final.stac-item
2022-12-06 10:19:20	ga_ls9c_ard_3-2-1_100076_2022-12-06_final.stac-item
2022-12-09 09:14:33	ga_ls9c_ard_3-2-1_089084_2022-12-08_final.stac-item
2022-12-10 09:52:38	ga_ls9c_ard_3-2-1_096071_2022-12-10_final.stac-item
2022-12-16 10:59:13	ga_ls9c_ard_3-2-1_106083_2022-12-16_final.stac-item
2022-12-19 11:26:31	ga_ls9c_ard_3-2-1_111074_2022-12-19_final.stac-item
2022-12-22 10:22:30	ga_ls9c_ard_3-2-1_100084_2022-12-22_final.stac-item
2022-12-23 09:27:16	ga_ls9c_ard_3-2-1_091085_2022-12-22_final.stac-item
2022-12-26 11:32:41	ga_ls9c_ard_3-2-1_112074_2022-12-26_final.stac-item
2023-01-08 11:01:01	ga_ls9c_ard_3-2-1_107072_2023-01-08_final.stac-item
2023-01-09 10:05:23	ga_ls9c_ard_3-2-1_098072_2023-01-09_final.stac-item
2023-01-09 10:07:23	ga_ls9c_ard_3-2-1_098077_2023-01-09_final.stac-item
2023-01-09 10:10:35	ga_ls9c_ard_3-2-1_098085_2023-01-09_final.stac-item
2023-01-10 10:50:14	ga_ls9c_ard_3-2-1_105076_2023-01-10_final.stac-item
2023-01-15 11:08:20	ga_ls9c_ard_3-2-1_108075_2023-01-15_final.stac-item
2023-01-17 10:55:08	ga_ls9c_ard_3-2-1_106073_2023-01-17_final.stac-item
2023-01-22 09:38:44	ga_ls9c_ard_3-2-1_093083_2023-01-22_final.stac-item
2023-01-22 11:12:26	ga_ls9c_ard_3-2-1_109070_2023-01-22_final.stac-item
2023-01-23 10:17:14	ga_ls9c_ard_3-2-1_100071_2023-01-23_final.stac-item
2023-01-25 10:07:42	ga_ls9c_ard_3-2-1_098078_2023-01-25_final.stac-item
2023-01-25 11:47:47	ga_ls9c_ard_3-2-1_114081_2023-01-25_final.stac-item
2023-01-26 09:13:18	ga_ls9c_ard_3-2-1_089081_2023-01-25_final.stac-item
2023-01-26 09:13:42	ga_ls9c_ard_3-2-1_089082_2023-01-25_final.stac-item
2023-01-26 10:47:48	ga_ls9c_ard_3-2-1_105070_2023-01-26_final.stac-item
2023-01-31 09:29:31	ga_ls9c_ard_3-2-1_092075_2023-01-30_final.stac-item
2023-02-01 10:16:47	ga_ls9c_ard_3-2-1_099085_2023-02-01_final.stac-item
2023-02-01 11:52:52	ga_ls9c_ard_3-2-1_115078_2023-02-01_final.stac-item
2023-02-02 09:21:10	ga_ls9c_ard_3-2-1_090085_2023-02-01_final.stac-item
2023-02-03 09:58:03	ga_ls9c_ard_3-2-1_097069_2023-02-03_final.stac-item
2023-02-14 09:41:30	ga_ls9c_ard_3-2-1_094074_2023-02-14_final.stac-item
2023-02-27 09:13:35	ga_ls9c_ard_3-2-1_089082_2023-02-26_final.stac-item
2023-03-08 10:42:35	ga_ls9c_ard_3-2-1_104073_2023-03-08_final.stac-item
2023-04-22 11:53:03	ga_ls9c_ard_3-2-1_115080_2023-04-22_final.stac-item
2023-04-29 10:17:04	ga_ls9c_ard_3-2-1_100072_2023-04-29_final.stac-item
2023-05-11 09:06:23	ga_ls9c_ard_3-2-1_088081_2023-05-10_final.stac-item
2023-05-18 09:11:18	ga_ls9c_ard_3-2-1_089078_2023-05-17_final.stac-item
2023-05-23 09:27:22	ga_ls9c_ard_3-2-1_092072_2023-05-22_final.stac-item
2023-06-30 10:27:31	ga_ls9c_ard_3-2-1_102068_2023-06-30_final.stac-item
2023-07-01 11:13:36	ga_ls9c_ard_3-2-1_109075_2023-07-01_final.stac-item
2023-07-02 10:20:47	ga_ls9c_ard_3-2-1_100082_2023-07-02_final.stac-item
2023-07-25 10:25:03	ga_ls9c_ard_3-2-1_101077_2023-07-25_final.stac-item
2023-07-26 09:33:03	ga_ls9c_ard_3-2-1_092086_2023-07-26_final.stac-item
2023-07-29 09:57:37	ga_ls9c_ard_3-2-1_097070_2023-07-29_final.stac-item
2023-07-31 11:25:22	ga_ls9c_ard_3-2-1_111073_2023-07-31_final.stac-item
2023-10-15 10:10:57	ga_ls9c_ard_3-2-1_099071_2023-10-15_final.stac-item
2023-10-16 10:53:02	ga_ls9c_ard_3-2-1_106068_2023-10-16_final.stac-item
2023-10-19 09:46:39	ga_ls9c_ard_3-2-1_095072_2023-10-19_final.stac-item
2023-10-22 10:19:09	ga_ls9c_ard_3-2-1_100076_2023-10-22_final.stac-item
2023-10-25 09:13:33	ga_ls9c_ard_3-2-1_089082_2023-10-24_final.stac-item
2023-10-26 11:32:29	ga_ls9c_ard_3-2-1_112074_2023-10-26_final.stac-item
2023-10-27 10:39:39	ga_ls9c_ard_3-2-1_103081_2023-10-27_final.stac-item
2023-10-30 11:06:08	ga_ls9c_ard_3-2-1_108070_2023-10-30_final.stac-item
2023-11-01 10:52:56	ga_ls9c_ard_3-2-1_106068_2023-11-01_final.stac-item
2023-11-23 10:19:11	ga_ls9c_ard_3-2-1_100076_2023-11-23_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