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
2021-11-02 09:17:23	ga_ls9c_ard_3-2-1_090081_2021-11-01_final.stac-item
2021-11-05 09:37:49	ga_ls9c_ard_3-2-1_093079_2021-11-05_final.stac-item
2021-11-16 10:24:18	ga_ls9c_ard_3-2-1_100083_2021-11-16_final.stac-item
2021-11-22 11:07:07	ga_ls9c_ard_3-2-1_107084_2021-11-22_final.stac-item
2021-12-11 09:29:24	ga_ls9c_ard_3-2-1_092075_2021-12-10_final.stac-item
2021-12-16 09:52:40	ga_ls9c_ard_3-2-1_095087_2021-12-16_final.stac-item
2021-12-30 11:39:56	ga_ls9c_ard_3-2-1_113077_2021-12-30_final.stac-item
2022-01-03 09:35:31	ga_ls9c_ard_3-2-1_093075_2022-01-03_final.stac-item
2022-01-08 11:36:31	ga_ls9c_ard_3-2-1_112084_2022-01-08_final.stac-item
2022-01-12 09:31:18	ga_ls9c_ard_3-2-1_092080_2022-01-12_final.stac-item
2022-02-06 09:26:44	ga_ls9c_ard_3-2-1_091084_2022-02-05_final.stac-item
2022-02-08 10:47:39	ga_ls9c_ard_3-2-1_105070_2022-02-08_final.stac-item
2022-02-25 11:35:56	ga_ls9c_ard_3-2-1_112083_2022-02-25_final.stac-item
2022-02-27 11:19:58	ga_ls9c_ard_3-2-1_110074_2022-02-27_final.stac-item
2022-03-03 10:56:00	ga_ls9c_ard_3-2-1_106076_2022-03-03_final.stac-item
2022-03-10 09:28:30	ga_ls9c_ard_3-2-1_091089_2022-03-09_final.stac-item
2022-03-25 10:18:04	ga_ls9c_ard_3-2-1_100074_2022-03-25_final.stac-item
2022-04-02 09:29:48	ga_ls9c_ard_3-2-1_092077_2022-04-01_final.stac-item
2022-04-11 09:24:46	ga_ls9c_ard_3-2-1_091080_2022-04-10_final.stac-item
2022-04-13 10:47:17	ga_ls9c_ard_3-2-1_105070_2022-04-13_final.stac-item
2022-05-08 10:44:06	ga_ls9c_ard_3-2-1_104078_2022-05-08_final.stac-item
2022-05-14 10:09:44	ga_ls9c_ard_3-2-1_098085_2022-05-14_final.stac-item
2022-05-19 10:24:12	ga_ls9c_ard_3-2-1_101075_2022-05-19_final.stac-item
2022-05-27 11:16:49	ga_ls9c_ard_3-2-1_109083_2022-05-27_final.stac-item
2022-06-05 11:05:53	ga_ls9c_ard_3-2-1_108071_2022-06-05_final.stac-item
2022-06-09 10:42:45	ga_ls9c_ard_3-2-1_104075_2022-06-09_final.stac-item
2022-06-28 09:35:07	ga_ls9c_ard_3-2-1_093075_2022-06-28_final.stac-item
2022-07-03 11:34:56	ga_ls9c_ard_3-2-1_112081_2022-07-03_final.stac-item
2022-07-05 09:45:16	ga_ls9c_ard_3-2-1_094085_2022-07-05_final.stac-item
2022-07-07 09:28:55	ga_ls9c_ard_3-2-1_092075_2022-07-06_final.stac-item
2022-08-09 10:15:40	ga_ls9c_ard_3-2-1_099083_2022-08-09_final.stac-item
2022-08-13 11:29:04	ga_ls9c_ard_3-2-1_111081_2022-08-13_final.stac-item
2022-08-24 11:06:35	ga_ls9c_ard_3-2-1_108071_2022-08-24_final.stac-item
2022-09-03 10:06:22	ga_ls9c_ard_3-2-1_098075_2022-09-03_final.stac-item
2022-09-15 10:28:45	ga_ls9c_ard_3-2-1_102069_2022-09-15_final.stac-item
2022-09-29 10:46:23	ga_ls9c_ard_3-2-1_104082_2022-09-29_final.stac-item
2022-10-21 10:08:12	ga_ls9c_ard_3-2-1_098079_2022-10-21_final.stac-item
2022-10-23 11:35:31	ga_ls9c_ard_3-2-1_112081_2022-10-23_final.stac-item
2022-11-14 10:55:39	ga_ls9c_ard_3-2-1_106074_2022-11-14_final.stac-item
2022-11-15 10:00:02	ga_ls9c_ard_3-2-1_097074_2022-11-15_final.stac-item
2022-11-19 11:13:00	ga_ls9c_ard_3-2-1_109071_2022-11-19_final.stac-item
2022-11-28 11:11:10	ga_ls9c_ard_3-2-1_108082_2022-11-28_final.stac-item
2022-12-03 09:52:48	ga_ls9c_ard_3-2-1_095087_2022-12-03_final.stac-item
2022-12-05 09:36:52	ga_ls9c_ard_3-2-1_093078_2022-12-05_final.stac-item
2022-12-19 09:49:14	ga_ls9c_ard_3-2-1_095078_2022-12-19_final.stac-item
2023-01-16 10:15:05	ga_ls9c_ard_3-2-1_099081_2023-01-16_final.stac-item
2023-01-17 09:19:51	ga_ls9c_ard_3-2-1_090082_2023-01-16_final.stac-item
2023-01-22 11:15:38	ga_ls9c_ard_3-2-1_109078_2023-01-22_final.stac-item
2023-01-27 09:58:10	ga_ls9c_ard_3-2-1_096085_2023-01-27_final.stac-item
2023-02-19 10:01:09	ga_ls9c_ard_3-2-1_097077_2023-02-19_final.stac-item
2023-02-19 11:41:37	ga_ls9c_ard_3-2-1_113081_2023-02-19_final.stac-item
2023-02-24 10:21:33	ga_ls9c_ard_3-2-1_100082_2023-02-24_final.stac-item
2023-03-02 09:40:05	ga_ls9c_ard_3-2-1_094071_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
2023-03-11 11:14:40	ga_ls9c_ard_3-2-1_109076_2023-03-11_final.stac-item
2023-03-14 11:45:58	ga_ls9c_ard_3-2-1_114077_2023-03-14_final.stac-item
2023-03-19 10:25:13	ga_ls9c_ard_3-2-1_101076_2023-03-19_final.stac-item
2023-04-17 11:35:43	ga_ls9c_ard_3-2-1_112083_2023-04-17_final.stac-item
2023-04-23 09:18:32	ga_ls9c_ard_3-2-1_090080_2023-04-22_final.stac-item
2023-04-28 11:16:17	ga_ls9c_ard_3-2-1_109081_2023-04-28_final.stac-item
2023-04-29 10:20:39	ga_ls9c_ard_3-2-1_100081_2023-04-29_final.stac-item
2023-05-01 10:02:40	ga_ls9c_ard_3-2-1_098067_2023-05-01_final.stac-item
2023-05-10 10:01:36	ga_ls9c_ard_3-2-1_097080_2023-05-10_final.stac-item
2023-05-18 09:12:06	ga_ls9c_ard_3-2-1_089080_2023-05-17_final.stac-item
2023-05-20 10:33:48	ga_ls9c_ard_3-2-1_103068_2023-05-20_final.stac-item
2023-05-21 09:44:09	ga_ls9c_ard_3-2-1_094083_2023-05-21_final.stac-item
2023-05-26 10:03:02	ga_ls9c_ard_3-2-1_097084_2023-05-26_final.stac-item
2023-06-11 10:00:33	ga_ls9c_ard_3-2-1_097078_2023-06-11_final.stac-item
2023-06-19 10:45:32	ga_ls9c_ard_3-2-1_105067_2023-06-19_final.stac-item
2023-07-17 09:39:38	ga_ls9c_ard_3-2-1_093087_2023-07-17_final.stac-item
2023-07-19 09:25:41	ga_ls9c_ard_3-2-1_091083_2023-07-18_final.stac-item
2023-07-22 11:31:04	ga_ls9c_ard_3-2-1_112072_2023-07-22_final.stac-item
2023-08-12 11:50:35	ga_ls9c_ard_3-2-1_115074_2023-08-12_final.stac-item
2023-08-13 09:16:28	ga_ls9c_ard_3-2-1_090075_2023-08-12_final.stac-item
2023-08-22 09:14:45	ga_ls9c_ard_3-2-1_089086_2023-08-21_final.stac-item
2023-08-29 09:18:13	ga_ls9c_ard_3-2-1_090079_2023-08-28_final.stac-item
2023-09-06 11:46:13	ga_ls9c_ard_3-2-1_114078_2023-09-06_final.stac-item
2023-09-12 11:07:36	ga_ls9c_ard_3-2-1_108074_2023-09-12_final.stac-item
2023-09-14 09:17:58	ga_ls9c_ard_3-2-1_090078_2023-09-13_final.stac-item
2023-09-20 10:21:22	ga_ls9c_ard_3-2-1_100082_2023-09-20_final.stac-item
2023-10-12 11:19:42	ga_ls9c_ard_3-2-1_110073_2023-10-12_final.stac-item
2023-11-01 10:58:55	ga_ls9c_ard_3-2-1_106083_2023-11-01_final.stac-item
2023-11-02 09:58:53	ga_ls9c_ard_3-2-1_097072_2023-11-02_final.stac-item
2023-11-06 11:17:28	ga_ls9c_ard_3-2-1_109083_2023-11-06_final.stac-item
2023-11-08 11:03:32	ga_ls9c_ard_3-2-1_107079_2023-11-08_final.stac-item
2023-11-20 09:50:38	ga_ls9c_ard_3-2-1_095082_2023-11-20_final.stac-item
2023-11-22 11:17:11	ga_ls9c_ard_3-2-1_109082_2023-11-22_final.stac-item
2023-12-01 11:07:51	ga_ls9c_ard_3-2-1_108074_2023-12-01_final.stac-item
2023-12-03 10:55:28	ga_ls9c_ard_3-2-1_106074_2023-12-03_final.stac-item
2023-12-10 11:02:01	ga_ls9c_ard_3-2-1_107075_2023-12-10_final.stac-item
2023-12-13 09:58:04	ga_ls9c_ard_3-2-1_096085_2023-12-13_final.stac-item
2023-12-15 09:43:43	ga_ls9c_ard_3-2-1_094080_2023-12-15_final.stac-item
2023-12-27 10:06:29	ga_ls9c_ard_3-2-1_098075_2023-12-27_final.stac-item
2023-12-30 10:34:34	ga_ls9c_ard_3-2-1_103068_2023-12-30_final.stac-item
2024-01-07 09:49:02	ga_ls9c_ard_3-2-1_095078_2024-01-07_final.stac-item
2024-01-10 10:20:22	ga_ls9c_ard_3-2-1_100079_2024-01-10_final.stac-item
2024-01-10 10:21:57	ga_ls9c_ard_3-2-1_100083_2024-01-10_final.stac-item
2024-01-21 11:37:54	ga_ls9c_ard_3-2-1_113072_2024-01-21_final.stac-item
2024-02-01 09:45:42	ga_ls9c_ard_3-2-1_094085_2024-02-01_final.stac-item
2024-02-19 11:07:43	ga_ls9c_ard_3-2-1_108074_2024-02-19_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