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 09:37:25	ga_ls9c_ard_3-2-1_093078_2021-11-05_final.stac-item
2021-11-06 10:16:35	ga_ls9c_ard_3-2-1_100076_2021-11-06_final.stac-item
2021-11-23 11:45:04	ga_ls9c_ard_3-2-1_114079_2021-11-23_final.stac-item
2021-12-12 11:53:31	ga_ls9c_ard_3-2-1_115080_2021-12-12_final.stac-item
2021-12-22 09:16:24	ga_ls9c_ard_3-2-1_089089_2021-12-21_final.stac-item
2021-12-29 09:18:11	ga_ls9c_ard_3-2-1_090078_2021-12-28_final.stac-item
2022-01-05 09:28:44	ga_ls9c_ard_3-2-1_091089_2022-01-04_final.stac-item
2022-01-06 11:45:41	ga_ls9c_ard_3-2-1_114076_2022-01-06_final.stac-item
2022-01-13 11:52:14	ga_ls9c_ard_3-2-1_115077_2022-01-13_final.stac-item
2022-01-15 09:58:36	ga_ls9c_ard_3-2-1_097071_2022-01-15_final.stac-item
2022-01-22 11:46:05	ga_ls9c_ard_3-2-1_114077_2022-01-22_final.stac-item
2022-01-29 11:52:17	ga_ls9c_ard_3-2-1_115077_2022-01-29_final.stac-item
2022-02-01 09:07:00	ga_ls9c_ard_3-2-1_088081_2022-01-31_final.stac-item
2022-02-07 10:07:36	ga_ls9c_ard_3-2-1_098078_2022-02-07_final.stac-item
2022-02-07 11:45:41	ga_ls9c_ard_3-2-1_114076_2022-02-07_final.stac-item
2022-02-13 09:34:52	ga_ls9c_ard_3-2-1_092089_2022-02-13_final.stac-item
2022-02-25 09:52:40	ga_ls9c_ard_3-2-1_096072_2022-02-25_final.stac-item
2022-03-03 09:22:18	ga_ls9c_ard_3-2-1_090089_2022-03-02_final.stac-item
2022-03-05 09:06:45	ga_ls9c_ard_3-2-1_088081_2022-03-04_final.stac-item
2022-03-31 09:40:10	ga_ls9c_ard_3-2-1_094072_2022-03-31_final.stac-item
2022-04-03 10:13:52	ga_ls9c_ard_3-2-1_099079_2022-04-03_final.stac-item
2022-04-03 11:51:09	ga_ls9c_ard_3-2-1_115075_2022-04-03_final.stac-item
2022-04-20 10:52:34	ga_ls9c_ard_3-2-1_106068_2022-04-20_final.stac-item
2022-05-05 11:52:55	ga_ls9c_ard_3-2-1_115080_2022-05-05_final.stac-item
2022-05-13 09:21:42	ga_ls9c_ard_3-2-1_091073_2022-05-12_final.stac-item
2022-05-14 10:04:09	ga_ls9c_ard_3-2-1_098071_2022-05-14_final.stac-item
2022-05-22 09:20:12	ga_ls9c_ard_3-2-1_090085_2022-05-21_final.stac-item
2022-06-06 10:12:39	ga_ls9c_ard_3-2-1_099077_2022-06-06_final.stac-item
2022-06-06 10:13:27	ga_ls9c_ard_3-2-1_099079_2022-06-06_final.stac-item
2022-06-16 09:12:33	ga_ls9c_ard_3-2-1_089081_2022-06-15_final.stac-item
2022-07-09 09:21:44	ga_ls9c_ard_3-2-1_090088_2022-07-08_final.stac-item
2022-07-12 11:29:29	ga_ls9c_ard_3-2-1_111083_2022-07-12_final.stac-item
2022-07-18 09:13:10	ga_ls9c_ard_3-2-1_089082_2022-07-17_final.stac-item
2022-08-01 09:24:56	ga_ls9c_ard_3-2-1_091080_2022-07-31_final.stac-item
2022-08-03 09:11:48	ga_ls9c_ard_3-2-1_089078_2022-08-02_final.stac-item
2022-08-10 09:19:15	ga_ls9c_ard_3-2-1_090081_2022-08-09_final.stac-item
2022-08-15 09:39:26	ga_ls9c_ard_3-2-1_093085_2022-08-15_final.stac-item
2022-08-19 10:46:26	ga_ls9c_ard_3-2-1_105067_2022-08-19_final.stac-item
2022-08-31 11:12:22	ga_ls9c_ard_3-2-1_109070_2022-08-31_final.stac-item
2022-09-04 09:11:57	ga_ls9c_ard_3-2-1_089078_2022-09-03_final.stac-item
2022-09-04 09:13:09	ga_ls9c_ard_3-2-1_089081_2022-09-03_final.stac-item
2022-09-04 10:46:27	ga_ls9c_ard_3-2-1_105067_2022-09-04_final.stac-item
2022-09-07 11:23:19	ga_ls9c_ard_3-2-1_110082_2022-09-07_final.stac-item
2022-09-10 11:52:38	ga_ls9c_ard_3-2-1_115078_2022-09-10_final.stac-item
2022-09-25 11:11:29	ga_ls9c_ard_3-2-1_108083_2022-09-25_final.stac-item
2022-10-02 09:35:36	ga_ls9c_ard_3-2-1_093075_2022-10-02_final.stac-item
2022-10-12 10:13:32	ga_ls9c_ard_3-2-1_099077_2022-10-12_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 11:12:35	ga_ls9c_ard_3-2-1_109070_2022-10-18_final.stac-item
2022-11-03 11:12:32	ga_ls9c_ard_3-2-1_109070_2022-11-03_final.stac-item
2022-11-08 09:52:14	ga_ls9c_ard_3-2-1_096070_2022-11-08_final.stac-item
2022-11-13 10:09:36	ga_ls9c_ard_3-2-1_099067_2022-11-13_final.stac-item
2022-11-20 10:19:46	ga_ls9c_ard_3-2-1_100077_2022-11-20_final.stac-item
2022-11-21 09:22:57	ga_ls9c_ard_3-2-1_091074_2022-11-20_final.stac-item
2022-11-23 09:12:58	ga_ls9c_ard_3-2-1_089080_2022-11-22_final.stac-item
2022-11-23 09:16:58	ga_ls9c_ard_3-2-1_089090_2022-11-22_final.stac-item
2022-12-21 09:35:39	ga_ls9c_ard_3-2-1_093075_2022-12-21_final.stac-item
2022-12-22 10:19:18	ga_ls9c_ard_3-2-1_100076_2022-12-22_final.stac-item
2022-12-23 09:22:52	ga_ls9c_ard_3-2-1_091074_2022-12-22_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 11:45:52	ga_ls9c_ard_3-2-1_114076_2023-01-09_final.stac-item
2023-01-16 11:52:22	ga_ls9c_ard_3-2-1_115077_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
2023-01-22 09:38:44	ga_ls9c_ard_3-2-1_093083_2023-01-22_final.stac-item
2023-01-25 11:45:48	ga_ls9c_ard_3-2-1_114076_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
2023-02-01 11:52:04	ga_ls9c_ard_3-2-1_115076_2023-02-01_final.stac-item
2023-02-07 11:12:38	ga_ls9c_ard_3-2-1_109070_2023-02-07_final.stac-item
2023-02-11 09:13:49	ga_ls9c_ard_3-2-1_089082_2023-02-10_final.stac-item
2023-02-27 09:13:35	ga_ls9c_ard_3-2-1_089082_2023-02-26_final.stac-item
2023-03-15 10:52:45	ga_ls9c_ard_3-2-1_105083_2023-03-15_final.stac-item
2023-03-28 10:19:41	ga_ls9c_ard_3-2-1_100078_2023-03-28_final.stac-item
2023-04-12 11:12:01	ga_ls9c_ard_3-2-1_109070_2023-04-12_final.stac-item
2023-04-13 10:16:46	ga_ls9c_ard_3-2-1_100071_2023-04-13_final.stac-item
2023-04-16 09:11:34	ga_ls9c_ard_3-2-1_089078_2023-04-15_final.stac-item
2023-04-16 09:11:58	ga_ls9c_ard_3-2-1_089079_2023-04-15_final.stac-item
2023-04-25 10:42:14	ga_ls9c_ard_3-2-1_104073_2023-04-25_final.stac-item
2023-05-02 09:15:48	ga_ls9c_ard_3-2-1_089089_2023-05-01_final.stac-item
2023-05-18 09:15:41	ga_ls9c_ard_3-2-1_089089_2023-05-17_final.stac-item
2023-06-03 09:12:23	ga_ls9c_ard_3-2-1_089081_2023-06-02_final.stac-item
2023-06-22 11:17:38	ga_ls9c_ard_3-2-1_110070_2023-06-22_final.stac-item
2023-06-26 09:17:37	ga_ls9c_ard_3-2-1_090079_2023-06-25_final.stac-item
2023-07-02 10:20:47	ga_ls9c_ard_3-2-1_100082_2023-07-02_final.stac-item
2023-07-04 10:07:15	ga_ls9c_ard_3-2-1_098079_2023-07-04_final.stac-item
2023-07-24 09:45:23	ga_ls9c_ard_3-2-1_094086_2023-07-24_final.stac-item
2023-07-27 11:52:01	ga_ls9c_ard_3-2-1_115078_2023-07-27_final.stac-item
2023-08-05 10:04:17	ga_ls9c_ard_3-2-1_098071_2023-08-05_final.stac-item
2023-08-06 09:16:15	ga_ls9c_ard_3-2-1_089090_2023-08-05_final.stac-item
2023-08-12 11:51:23	ga_ls9c_ard_3-2-1_115076_2023-08-12_final.stac-item
2023-08-13 10:58:09	ga_ls9c_ard_3-2-1_106082_2023-08-13_final.stac-item
2023-08-18 09:39:24	ga_ls9c_ard_3-2-1_093086_2023-08-18_final.stac-item
2023-10-15 10:09:45	ga_ls9c_ard_3-2-1_099068_2023-10-15_final.stac-item
2023-10-15 11:52:38	ga_ls9c_ard_3-2-1_115078_2023-10-15_final.stac-item
2023-10-21 09:40:41	ga_ls9c_ard_3-2-1_093088_2023-10-21_final.stac-item
2023-10-24 10:04:47	ga_ls9c_ard_3-2-1_098071_2023-10-24_final.stac-item
2023-10-31 10:09:42	ga_ls9c_ard_3-2-1_099068_2023-10-31_final.stac-item
2023-11-02 09:58:06	ga_ls9c_ard_3-2-1_097070_2023-11-02_final.stac-item
2023-11-17 09:22:05	ga_ls9c_ard_3-2-1_090088_2023-11-16_final.stac-item
2023-11-18 09:57:46	ga_ls9c_ard_3-2-1_097069_2023-11-18_final.stac-item
2023-11-22 09:35:55	ga_ls9c_ard_3-2-1_093076_2023-11-22_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