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
2021-11-06 10:15:47	ga_ls9c_ard_3-2-1_100074_2021-11-06_final.stac-item
2021-12-09 11:20:16	ga_ls9c_ard_3-2-1_110074_2021-12-09_final.stac-item
2022-01-10 09:42:04	ga_ls9c_ard_3-2-1_094076_2022-01-10_final.stac-item
2022-01-10 11:20:09	ga_ls9c_ard_3-2-1_110074_2022-01-10_final.stac-item
2022-02-03 10:33:56	ga_ls9c_ard_3-2-1_102082_2022-02-03_final.stac-item
2022-02-15 09:19:18	ga_ls9c_ard_3-2-1_090081_2022-02-14_final.stac-item
2022-03-28 09:13:39	ga_ls9c_ard_3-2-1_089083_2022-03-27_final.stac-item
2022-03-31 09:40:58	ga_ls9c_ard_3-2-1_094074_2022-03-31_final.stac-item
2022-05-02 09:40:45	ga_ls9c_ard_3-2-1_094074_2022-05-02_final.stac-item
2022-05-27 11:12:50	ga_ls9c_ard_3-2-1_109073_2022-05-27_final.stac-item
2022-06-05 11:05:05	ga_ls9c_ard_3-2-1_108069_2022-06-05_final.stac-item
2022-06-07 10:54:19	ga_ls9c_ard_3-2-1_106073_2022-06-07_final.stac-item
2022-06-16 10:45:51	ga_ls9c_ard_3-2-1_105067_2022-06-16_final.stac-item
2022-07-01 10:08:01	ga_ls9c_ard_3-2-1_098080_2022-07-01_final.stac-item
2022-07-09 09:19:44	ga_ls9c_ard_3-2-1_090083_2022-07-08_final.stac-item
2022-07-16 09:23:30	ga_ls9c_ard_3-2-1_091077_2022-07-15_final.stac-item
2022-08-13 09:50:35	ga_ls9c_ard_3-2-1_095082_2022-08-13_final.stac-item
2022-08-15 09:37:02	ga_ls9c_ard_3-2-1_093079_2022-08-15_final.stac-item
2022-08-17 11:01:34	ga_ls9c_ard_3-2-1_107074_2022-08-17_final.stac-item
2022-09-30 09:52:45	ga_ls9c_ard_3-2-1_095087_2022-09-30_final.stac-item
2022-10-04 09:24:02	ga_ls9c_ard_3-2-1_091077_2022-10-03_final.stac-item
2022-10-09 09:43:47	ga_ls9c_ard_3-2-1_094080_2022-10-09_final.stac-item
2022-10-18 09:35:17	ga_ls9c_ard_3-2-1_093074_2022-10-18_final.stac-item
2022-10-27 11:11:11	ga_ls9c_ard_3-2-1_108082_2022-10-27_final.stac-item
2022-10-29 09:19:32	ga_ls9c_ard_3-2-1_090081_2022-10-28_final.stac-item
2022-11-07 10:48:14	ga_ls9c_ard_3-2-1_105071_2022-11-07_final.stac-item
2022-11-08 11:36:18	ga_ls9c_ard_3-2-1_112083_2022-11-08_final.stac-item
2022-11-10 11:18:46	ga_ls9c_ard_3-2-1_110070_2022-11-10_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 09:37:18	ga_ls9c_ard_3-2-1_093079_2022-11-19_final.stac-item
2022-11-23 09:14:10	ga_ls9c_ard_3-2-1_089083_2022-11-22_final.stac-item
2022-11-29 11:53:37	ga_ls9c_ard_3-2-1_115080_2022-11-29_final.stac-item
2022-12-03 09:52:24	ga_ls9c_ard_3-2-1_095086_2022-12-03_final.stac-item
2022-12-03 11:25:42	ga_ls9c_ard_3-2-1_111072_2022-12-03_final.stac-item
2022-12-04 10:28:53	ga_ls9c_ard_3-2-1_102069_2022-12-04_final.stac-item
2022-12-09 10:46:40	ga_ls9c_ard_3-2-1_105067_2022-12-09_final.stac-item
2022-12-10 09:53:26	ga_ls9c_ard_3-2-1_096073_2022-12-10_final.stac-item
2022-12-16 09:18:44	ga_ls9c_ard_3-2-1_090079_2022-12-15_final.stac-item
2022-12-19 11:30:30	ga_ls9c_ard_3-2-1_111084_2022-12-19_final.stac-item
2022-12-24 11:47:25	ga_ls9c_ard_3-2-1_114080_2022-12-24_final.stac-item
2022-12-29 10:27:07	ga_ls9c_ard_3-2-1_101080_2022-12-29_final.stac-item
2022-12-31 11:51:15	ga_ls9c_ard_3-2-1_115074_2022-12-31_final.stac-item
2023-01-02 11:41:42	ga_ls9c_ard_3-2-1_113081_2023-01-02_final.stac-item
2023-01-04 09:46:28	ga_ls9c_ard_3-2-1_095071_2023-01-04_final.stac-item
2023-01-04 09:49:39	ga_ls9c_ard_3-2-1_095079_2023-01-04_final.stac-item
2023-01-07 10:22:33	ga_ls9c_ard_3-2-1_100084_2023-01-07_final.stac-item
2023-01-10 10:50:38	ga_ls9c_ard_3-2-1_105077_2023-01-10_final.stac-item
2023-01-12 10:37:52	ga_ls9c_ard_3-2-1_103076_2023-01-12_final.stac-item
2023-01-20 11:30:22	ga_ls9c_ard_3-2-1_111084_2023-01-20_final.stac-item
2023-01-23 11:58:07	ga_ls9c_ard_3-2-1_116076_2023-01-23_final.stac-item
2023-01-24 11:01:43	ga_ls9c_ard_3-2-1_107074_2023-01-24_final.stac-item
2023-01-25 11:45:00	ga_ls9c_ard_3-2-1_114074_2023-01-25_final.stac-item
2023-01-25 11:46:12	ga_ls9c_ard_3-2-1_114077_2023-01-25_final.stac-item
2023-01-29 11:19:08	ga_ls9c_ard_3-2-1_110071_2023-01-29_final.stac-item
2023-01-31 09:35:06	ga_ls9c_ard_3-2-1_092089_2023-01-31_final.stac-item
2023-01-31 11:08:48	ga_ls9c_ard_3-2-1_108076_2023-01-31_final.stac-item
2023-02-03 10:01:39	ga_ls9c_ard_3-2-1_097078_2023-02-03_final.stac-item
2023-02-03 10:02:50	ga_ls9c_ard_3-2-1_097081_2023-02-03_final.stac-item
2023-02-07 09:40:08	ga_ls9c_ard_3-2-1_093086_2023-02-07_final.stac-item
2023-02-10 10:06:39	ga_ls9c_ard_3-2-1_098075_2023-02-10_final.stac-item
2023-02-10 11:45:56	ga_ls9c_ard_3-2-1_114076_2023-02-10_final.stac-item
2023-02-11 09:14:13	ga_ls9c_ard_3-2-1_089083_2023-02-10_final.stac-item
2023-03-02 09:40:53	ga_ls9c_ard_3-2-1_094073_2023-03-02_final.stac-item
2023-03-06 10:56:11	ga_ls9c_ard_3-2-1_106076_2023-03-06_final.stac-item
2023-03-11 11:13:28	ga_ls9c_ard_3-2-1_109073_2023-03-11_final.stac-item
2023-03-29 09:28:26	ga_ls9c_ard_3-2-1_091089_2023-03-28_final.stac-item
2023-04-26 09:50:12	ga_ls9c_ard_3-2-1_095082_2023-04-26_final.stac-item
2023-05-02 09:12:13	ga_ls9c_ard_3-2-1_089080_2023-05-01_final.stac-item
2023-05-02 10:46:42	ga_ls9c_ard_3-2-1_105069_2023-05-02_final.stac-item
2023-05-03 11:35:56	ga_ls9c_ard_3-2-1_112084_2023-05-03_final.stac-item
2023-05-06 10:22:20	ga_ls9c_ard_3-2-1_101070_2023-05-06_final.stac-item
2023-05-10 10:03:12	ga_ls9c_ard_3-2-1_097084_2023-05-10_final.stac-item
2023-05-29 10:27:57	ga_ls9c_ard_3-2-1_102069_2023-05-29_final.stac-item
2023-06-19 10:46:20	ga_ls9c_ard_3-2-1_105069_2023-06-19_final.stac-item
2023-06-20 09:51:31	ga_ls9c_ard_3-2-1_096071_2023-06-20_final.stac-item
2023-06-26 09:20:25	ga_ls9c_ard_3-2-1_090086_2023-06-25_final.stac-item
2023-06-27 11:40:36	ga_ls9c_ard_3-2-1_113081_2023-06-27_final.stac-item
2023-07-05 10:45:44	ga_ls9c_ard_3-2-1_105067_2023-07-05_final.stac-item
2023-07-21 09:14:30	ga_ls9c_ard_3-2-1_089086_2023-07-20_final.stac-item
2023-07-24 11:19:29	ga_ls9c_ard_3-2-1_110074_2023-07-24_final.stac-item
2023-07-26 09:28:39	ga_ls9c_ard_3-2-1_092075_2023-07-25_final.stac-item
2023-07-29 09:59:13	ga_ls9c_ard_3-2-1_097074_2023-07-29_final.stac-item
2023-08-02 11:12:14	ga_ls9c_ard_3-2-1_109071_2023-08-02_final.stac-item
2023-08-04 09:23:01	ga_ls9c_ard_3-2-1_091076_2023-08-03_final.stac-item
2023-08-05 11:46:46	ga_ls9c_ard_3-2-1_114080_2023-08-05_final.stac-item
2023-08-06 10:49:09	ga_ls9c_ard_3-2-1_105075_2023-08-06_final.stac-item
2023-08-06 10:52:21	ga_ls9c_ard_3-2-1_105083_2023-08-06_final.stac-item
2023-10-24 11:46:52	ga_ls9c_ard_3-2-1_114079_2023-10-24_final.stac-item
2023-10-28 09:46:25	ga_ls9c_ard_3-2-1_094087_2023-10-28_final.stac-item
2023-11-14 10:24:03	ga_ls9c_ard_3-2-1_101073_2023-11-14_final.stac-item
2023-11-14 10:28:03	ga_ls9c_ard_3-2-1_101083_2023-11-14_final.stac-item
2023-11-15 09:34:49	ga_ls9c_ard_3-2-1_092089_2023-11-15_final.stac-item
2023-11-17 09:19:17	ga_ls9c_ard_3-2-1_090081_2023-11-16_final.stac-item
2023-11-18 09:58:34	ga_ls9c_ard_3-2-1_097071_2023-11-18_final.stac-item
2023-11-18 09:59:46	ga_ls9c_ard_3-2-1_097074_2023-11-18_final.stac-item
2023-11-22 09:36:18	ga_ls9c_ard_3-2-1_093077_2023-11-22_final.stac-item
2023-11-22 11:13:12	ga_ls9c_ard_3-2-1_109072_2023-11-22_final.stac-item
2023-11-23 10:20:23	ga_ls9c_ard_3-2-1_100079_2023-11-23_final.stac-item
2023-11-25 10:06:03	ga_ls9c_ard_3-2-1_098074_2023-11-25_final.stac-item
2023-11-25 11:46:55	ga_ls9c_ard_3-2-1_114079_2023-11-25_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