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
2021-11-16 10:19:55	ga_ls9c_ard_3-2-1_100072_2021-11-16_final.stac-item
2021-11-18 11:40:38	ga_ls9c_ard_3-2-1_113074_2021-11-18_final.stac-item
2021-12-10 10:23:50	ga_ls9c_ard_3-2-1_101072_2021-12-10_final.stac-item
2021-12-17 10:30:44	ga_ls9c_ard_3-2-1_102074_2021-12-17_final.stac-item
2021-12-18 11:12:48	ga_ls9c_ard_3-2-1_109071_2021-12-18_final.stac-item
2021-12-21 10:07:37	ga_ls9c_ard_3-2-1_098078_2021-12-21_final.stac-item
2021-12-22 10:52:05	ga_ls9c_ard_3-2-1_105081_2021-12-22_final.stac-item
2022-01-03 09:40:18	ga_ls9c_ard_3-2-1_093087_2022-01-03_final.stac-item
2022-01-11 10:27:43	ga_ls9c_ard_3-2-1_101082_2022-01-11_final.stac-item
2022-01-22 10:03:37	ga_ls9c_ard_3-2-1_098068_2022-01-22_final.stac-item
2022-01-23 10:48:28	ga_ls9c_ard_3-2-1_105072_2022-01-23_final.stac-item
2022-01-24 09:52:03	ga_ls9c_ard_3-2-1_096070_2022-01-24_final.stac-item
2022-01-25 10:35:43	ga_ls9c_ard_3-2-1_103071_2022-01-25_final.stac-item
2022-02-27 11:19:58	ga_ls9c_ard_3-2-1_110074_2022-02-27_final.stac-item
2022-03-31 11:19:27	ga_ls9c_ard_3-2-1_110073_2022-03-31_final.stac-item
2022-04-02 09:34:12	ga_ls9c_ard_3-2-1_092088_2022-04-02_final.stac-item
2022-04-08 10:33:34	ga_ls9c_ard_3-2-1_102082_2022-04-08_final.stac-item
2022-04-12 10:03:14	ga_ls9c_ard_3-2-1_098068_2022-04-12_final.stac-item
2022-04-20 09:20:28	ga_ls9c_ard_3-2-1_090085_2022-04-19_final.stac-item
2022-05-05 11:52:07	ga_ls9c_ard_3-2-1_115078_2022-05-05_final.stac-item
2022-05-05 11:52:31	ga_ls9c_ard_3-2-1_115079_2022-05-05_final.stac-item
2022-05-06 10:54:53	ga_ls9c_ard_3-2-1_106074_2022-05-06_final.stac-item
2022-05-13 09:28:29	ga_ls9c_ard_3-2-1_091090_2022-05-12_final.stac-item
2022-05-13 11:04:35	ga_ls9c_ard_3-2-1_107083_2022-05-13_final.stac-item
2022-05-26 10:29:34	ga_ls9c_ard_3-2-1_102073_2022-05-26_final.stac-item
2022-05-26 10:32:46	ga_ls9c_ard_3-2-1_102081_2022-05-26_final.stac-item
2022-06-05 11:09:52	ga_ls9c_ard_3-2-1_108081_2022-06-05_final.stac-item
2022-06-07 09:20:38	ga_ls9c_ard_3-2-1_090086_2022-06-06_final.stac-item
2022-06-14 11:04:58	ga_ls9c_ard_3-2-1_107084_2022-06-14_final.stac-item
2022-07-02 09:16:23	ga_ls9c_ard_3-2-1_089090_2022-07-01_final.stac-item
2022-07-02 10:48:05	ga_ls9c_ard_3-2-1_105072_2022-07-02_final.stac-item
2022-07-03 11:32:08	ga_ls9c_ard_3-2-1_112074_2022-07-03_final.stac-item
2022-07-05 11:18:58	ga_ls9c_ard_3-2-1_110072_2022-07-05_final.stac-item
2022-07-08 10:15:45	ga_ls9c_ard_3-2-1_099084_2022-07-08_final.stac-item
2022-07-09 09:17:20	ga_ls9c_ard_3-2-1_090077_2022-07-08_final.stac-item
2022-07-09 10:53:49	ga_ls9c_ard_3-2-1_106071_2022-07-09_final.stac-item
2022-07-12 09:46:13	ga_ls9c_ard_3-2-1_095072_2022-07-12_final.stac-item
2022-07-18 09:16:22	ga_ls9c_ard_3-2-1_089090_2022-07-17_final.stac-item
2022-07-18 10:50:27	ga_ls9c_ard_3-2-1_105078_2022-07-18_final.stac-item
2022-07-24 11:52:46	ga_ls9c_ard_3-2-1_115079_2022-07-24_final.stac-item
2022-07-27 09:06:20	ga_ls9c_ard_3-2-1_088080_2022-07-26_final.stac-item
2022-07-27 10:42:25	ga_ls9c_ard_3-2-1_104073_2022-07-27_final.stac-item
2022-07-30 09:40:28	ga_ls9c_ard_3-2-1_093088_2022-07-30_final.stac-item
2022-07-31 10:18:57	ga_ls9c_ard_3-2-1_100076_2022-07-31_final.stac-item
2022-08-06 11:19:14	ga_ls9c_ard_3-2-1_110072_2022-08-06_final.stac-item
2022-08-21 10:34:28	ga_ls9c_ard_3-2-1_103068_2022-08-21_final.stac-item
2022-08-25 10:16:09	ga_ls9c_ard_3-2-1_099084_2022-08-25_final.stac-item
2022-08-31 09:40:40	ga_ls9c_ard_3-2-1_093088_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
2022-09-05 11:32:30	ga_ls9c_ard_3-2-1_112074_2022-09-05_final.stac-item
2022-09-18 09:27:11	ga_ls9c_ard_3-2-1_091085_2022-09-17_final.stac-item
2022-09-24 10:23:26	ga_ls9c_ard_3-2-1_101071_2022-09-24_final.stac-item
2022-09-25 09:29:49	ga_ls9c_ard_3-2-1_092076_2022-09-24_final.stac-item
2022-09-25 11:07:30	ga_ls9c_ard_3-2-1_108073_2022-09-25_final.stac-item
2022-10-13 10:53:37	ga_ls9c_ard_3-2-1_106069_2022-10-13_final.stac-item
2022-10-14 11:38:52	ga_ls9c_ard_3-2-1_113074_2022-10-14_final.stac-item
2022-10-16 09:51:14	ga_ls9c_ard_3-2-1_095083_2022-10-16_final.stac-item
2022-10-21 10:07:24	ga_ls9c_ard_3-2-1_098077_2022-10-21_final.stac-item
2022-10-26 10:23:56	ga_ls9c_ard_3-2-1_101072_2022-10-26_final.stac-item
2022-10-29 09:21:32	ga_ls9c_ard_3-2-1_090086_2022-10-28_final.stac-item
2022-11-03 11:12:08	ga_ls9c_ard_3-2-1_109069_2022-11-03_final.stac-item
2022-11-03 11:14:56	ga_ls9c_ard_3-2-1_109076_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
2022-11-15 09:58:50	ga_ls9c_ard_3-2-1_097071_2022-11-15_final.stac-item
2022-11-22 10:04:13	ga_ls9c_ard_3-2-1_098069_2022-11-22_final.stac-item
2022-11-26 09:45:27	ga_ls9c_ard_3-2-1_094084_2022-11-26_final.stac-item
2022-12-05 11:15:21	ga_ls9c_ard_3-2-1_109077_2022-12-05_final.stac-item
2022-12-08 11:47:28	ga_ls9c_ard_3-2-1_114080_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
2022-12-15 11:52:27	ga_ls9c_ard_3-2-1_115077_2022-12-15_final.stac-item
2022-12-18 10:43:15	ga_ls9c_ard_3-2-1_104074_2022-12-18_final.stac-item
2022-12-25 09:14:55	ga_ls9c_ard_3-2-1_089085_2022-12-24_final.stac-item
2023-01-09 10:10:35	ga_ls9c_ard_3-2-1_098085_2023-01-09_final.stac-item
2023-01-14 10:23:29	ga_ls9c_ard_3-2-1_101071_2023-01-14_final.stac-item
2023-01-24 09:26:49	ga_ls9c_ard_3-2-1_091084_2023-01-23_final.stac-item
2023-01-24 09:29:13	ga_ls9c_ard_3-2-1_091090_2023-01-23_final.stac-item
2023-01-25 10:10:30	ga_ls9c_ard_3-2-1_098085_2023-01-25_final.stac-item
2023-01-26 09:16:54	ga_ls9c_ard_3-2-1_089090_2023-01-25_final.stac-item
2023-01-26 10:50:11	ga_ls9c_ard_3-2-1_105076_2023-01-26_final.stac-item
2023-02-17 11:53:14	ga_ls9c_ard_3-2-1_115079_2023-02-17_final.stac-item
2023-02-26 11:44:54	ga_ls9c_ard_3-2-1_114074_2023-02-26_final.stac-item
2023-03-15 10:49:33	ga_ls9c_ard_3-2-1_105075_2023-03-15_final.stac-item
2023-03-26 10:28:06	ga_ls9c_ard_3-2-1_102068_2023-03-26_final.stac-item
2023-03-29 09:25:14	ga_ls9c_ard_3-2-1_091081_2023-03-28_final.stac-item
2023-04-08 11:41:10	ga_ls9c_ard_3-2-1_113081_2023-04-08_final.stac-item
2023-05-02 09:13:01	ga_ls9c_ard_3-2-1_089082_2023-05-01_final.stac-item
2023-05-10 10:01:12	ga_ls9c_ard_3-2-1_097079_2023-05-10_final.stac-item
2023-05-14 11:16:32	ga_ls9c_ard_3-2-1_109082_2023-05-14_final.stac-item
2023-06-08 11:06:34	ga_ls9c_ard_3-2-1_108073_2023-06-08_final.stac-item
2023-07-01 09:36:18	ga_ls9c_ard_3-2-1_093079_2023-07-01_final.stac-item
2023-07-03 09:26:22	ga_ls9c_ard_3-2-1_091085_2023-07-02_final.stac-item
2023-07-04 10:03:40	ga_ls9c_ard_3-2-1_098070_2023-07-04_final.stac-item
2023-07-16 10:28:04	ga_ls9c_ard_3-2-1_102069_2023-07-16_final.stac-item
2023-08-13 09:21:40	ga_ls9c_ard_3-2-1_090088_2023-08-12_final.stac-item
2023-10-20 10:28:19	ga_ls9c_ard_3-2-1_102068_2023-10-20_final.stac-item
2023-10-23 11:00:01	ga_ls9c_ard_3-2-1_107070_2023-10-23_final.stac-item
2023-10-31 10:09:18	ga_ls9c_ard_3-2-1_099067_2023-10-31_final.stac-item
2023-11-01 09:22:50	ga_ls9c_ard_3-2-1_090090_2023-10-31_final.stac-item
2023-11-15 09:33:37	ga_ls9c_ard_3-2-1_092086_2023-11-15_final.stac-item
2023-11-18 10:01:46	ga_ls9c_ard_3-2-1_097079_2023-11-18_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