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
2021-12-07 11:31:51	ga_ls9c_ard_3-2-1_112072_2021-12-07_final.stac-item
2021-12-08 10:34:37	ga_ls9c_ard_3-2-1_103068_2021-12-08_final.stac-item
2021-12-16 09:46:17	ga_ls9c_ard_3-2-1_095071_2021-12-16_final.stac-item
2021-12-26 10:25:46	ga_ls9c_ard_3-2-1_101077_2021-12-26_final.stac-item
2021-12-31 10:44:18	ga_ls9c_ard_3-2-1_104077_2021-12-31_final.stac-item
2021-12-31 10:46:18	ga_ls9c_ard_3-2-1_104082_2021-12-31_final.stac-item
2022-01-08 11:32:08	ga_ls9c_ard_3-2-1_112073_2022-01-08_final.stac-item
2022-01-22 10:03:13	ga_ls9c_ard_3-2-1_098067_2022-01-22_final.stac-item
2022-01-22 10:07:36	ga_ls9c_ard_3-2-1_098078_2022-01-22_final.stac-item
2022-01-24 11:32:08	ga_ls9c_ard_3-2-1_112073_2022-01-24_final.stac-item
2022-02-04 11:12:48	ga_ls9c_ard_3-2-1_109071_2022-02-04_final.stac-item
2022-02-06 11:00:02	ga_ls9c_ard_3-2-1_107070_2022-02-06_final.stac-item
2022-02-14 10:09:20	ga_ls9c_ard_3-2-1_099067_2022-02-14_final.stac-item
2022-03-01 09:29:05	ga_ls9c_ard_3-2-1_092075_2022-02-28_final.stac-item
2022-03-02 10:09:33	ga_ls9c_ard_3-2-1_099068_2022-03-02_final.stac-item
2022-03-11 10:02:59	ga_ls9c_ard_3-2-1_098067_2022-03-11_final.stac-item
2022-03-19 10:52:47	ga_ls9c_ard_3-2-1_106068_2022-03-19_final.stac-item
2022-04-03 10:09:28	ga_ls9c_ard_3-2-1_099068_2022-04-03_final.stac-item
2022-04-18 09:34:27	ga_ls9c_ard_3-2-1_092089_2022-04-18_final.stac-item
2022-04-20 09:22:04	ga_ls9c_ard_3-2-1_090089_2022-04-19_final.stac-item
2022-04-25 09:36:59	ga_ls9c_ard_3-2-1_093080_2022-04-25_final.stac-item
2022-04-25 11:14:17	ga_ls9c_ard_3-2-1_109076_2022-04-25_final.stac-item
2022-04-27 09:28:13	ga_ls9c_ard_3-2-1_091089_2022-04-26_final.stac-item
2022-05-12 10:16:32	ga_ls9c_ard_3-2-1_100071_2022-05-12_final.stac-item
2022-05-27 11:14:02	ga_ls9c_ard_3-2-1_109076_2022-05-27_final.stac-item
2022-06-03 09:39:21	ga_ls9c_ard_3-2-1_094071_2022-06-03_final.stac-item
2022-06-06 10:13:27	ga_ls9c_ard_3-2-1_099079_2022-06-06_final.stac-item
2022-06-08 09:57:30	ga_ls9c_ard_3-2-1_097070_2022-06-08_final.stac-item
2022-06-15 10:06:33	ga_ls9c_ard_3-2-1_098077_2022-06-15_final.stac-item
2022-06-21 09:28:25	ga_ls9c_ard_3-2-1_092074_2022-06-20_final.stac-item
2022-06-21 09:34:01	ga_ls9c_ard_3-2-1_092088_2022-06-21_final.stac-item
2022-07-02 09:15:59	ga_ls9c_ard_3-2-1_089089_2022-07-01_final.stac-item
2022-07-08 10:10:10	ga_ls9c_ard_3-2-1_099070_2022-07-08_final.stac-item
2022-07-10 09:57:00	ga_ls9c_ard_3-2-1_097068_2022-07-10_final.stac-item
2022-07-16 09:22:42	ga_ls9c_ard_3-2-1_091075_2022-07-15_final.stac-item
2022-07-30 09:40:04	ga_ls9c_ard_3-2-1_093087_2022-07-30_final.stac-item
2022-08-17 09:28:40	ga_ls9c_ard_3-2-1_091089_2022-08-16_final.stac-item
2022-08-17 09:29:04	ga_ls9c_ard_3-2-1_091090_2022-08-16_final.stac-item
2022-09-09 09:33:40	ga_ls9c_ard_3-2-1_092086_2022-09-09_final.stac-item
2022-09-27 09:22:39	ga_ls9c_ard_3-2-1_090089_2022-09-26_final.stac-item
2022-09-28 09:57:32	ga_ls9c_ard_3-2-1_097068_2022-09-28_final.stac-item
2022-10-05 10:04:30	ga_ls9c_ard_3-2-1_098070_2022-10-05_final.stac-item
2022-10-07 09:58:31	ga_ls9c_ard_3-2-1_096086_2022-10-07_final.stac-item
2022-10-11 09:29:52	ga_ls9c_ard_3-2-1_092076_2022-10-10_final.stac-item
2022-10-11 09:33:03	ga_ls9c_ard_3-2-1_092084_2022-10-11_final.stac-item
2022-10-12 10:10:44	ga_ls9c_ard_3-2-1_099070_2022-10-12_final.stac-item
2022-11-08 09:57:49	ga_ls9c_ard_3-2-1_096084_2022-11-08_final.stac-item
2022-11-10 09:45:04	ga_ls9c_ard_3-2-1_094083_2022-11-10_final.stac-item
2022-11-14 10:53:16	ga_ls9c_ard_3-2-1_106068_2022-11-14_final.stac-item
2022-11-15 09:58:02	ga_ls9c_ard_3-2-1_097069_2022-11-15_final.stac-item
2022-11-20 10:20:10	ga_ls9c_ard_3-2-1_100078_2022-11-20_final.stac-item
2022-11-23 09:12:35	ga_ls9c_ard_3-2-1_089079_2022-11-22_final.stac-item
2022-11-26 09:40:16	ga_ls9c_ard_3-2-1_094071_2022-11-26_final.stac-item
2022-11-29 10:11:33	ga_ls9c_ard_3-2-1_099072_2022-11-29_final.stac-item
2022-12-09 09:12:34	ga_ls9c_ard_3-2-1_089079_2022-12-08_final.stac-item
2022-12-14 09:30:18	ga_ls9c_ard_3-2-1_092077_2022-12-14_final.stac-item
2022-12-25 09:14:31	ga_ls9c_ard_3-2-1_089084_2022-12-24_final.stac-item
2023-01-04 11:26:56	ga_ls9c_ard_3-2-1_111075_2023-01-04_final.stac-item
2023-01-08 09:28:07	ga_ls9c_ard_3-2-1_091087_2023-01-07_final.stac-item
2023-01-16 10:11:30	ga_ls9c_ard_3-2-1_099072_2023-01-16_final.stac-item
2023-01-16 11:53:10	ga_ls9c_ard_3-2-1_115079_2023-01-16_final.stac-item
2023-01-18 10:04:17	ga_ls9c_ard_3-2-1_097085_2023-01-18_final.stac-item
2023-01-31 09:29:55	ga_ls9c_ard_3-2-1_092076_2023-01-30_final.stac-item
2023-03-02 11:19:22	ga_ls9c_ard_3-2-1_110072_2023-03-02_final.stac-item
2023-03-05 10:10:57	ga_ls9c_ard_3-2-1_099071_2023-03-05_final.stac-item
2023-03-06 09:16:54	ga_ls9c_ard_3-2-1_090075_2023-03-05_final.stac-item
2023-03-12 10:19:03	ga_ls9c_ard_3-2-1_100076_2023-03-12_final.stac-item
2023-03-27 09:34:03	ga_ls9c_ard_3-2-1_093072_2023-03-27_final.stac-item
2023-04-09 09:07:03	ga_ls9c_ard_3-2-1_088082_2023-04-08_final.stac-item
2023-04-15 10:03:59	ga_ls9c_ard_3-2-1_098070_2023-04-15_final.stac-item
2023-04-17 09:58:01	ga_ls9c_ard_3-2-1_096086_2023-04-17_final.stac-item
2023-04-17 11:31:19	ga_ls9c_ard_3-2-1_112072_2023-04-17_final.stac-item
2023-04-26 09:46:12	ga_ls9c_ard_3-2-1_095072_2023-04-26_final.stac-item
2023-04-30 09:21:25	ga_ls9c_ard_3-2-1_091072_2023-04-29_final.stac-item
2023-05-05 09:39:52	ga_ls9c_ard_3-2-1_094072_2023-05-05_final.stac-item
2023-05-07 09:28:19	ga_ls9c_ard_3-2-1_092074_2023-05-06_final.stac-item
2023-05-31 11:57:16	ga_ls9c_ard_3-2-1_116076_2023-05-31_final.stac-item
2023-06-09 10:15:19	ga_ls9c_ard_3-2-1_099084_2023-06-09_final.stac-item
2023-06-10 09:21:17	ga_ls9c_ard_3-2-1_090088_2023-06-09_final.stac-item
2023-06-12 09:06:30	ga_ls9c_ard_3-2-1_088082_2023-06-11_final.stac-item
2023-06-27 09:57:19	ga_ls9c_ard_3-2-1_097070_2023-06-27_final.stac-item
2023-07-05 10:50:55	ga_ls9c_ard_3-2-1_105080_2023-07-05_final.stac-item
2023-07-18 11:57:23	ga_ls9c_ard_3-2-1_116076_2023-07-18_final.stac-item
2023-07-31 11:23:47	ga_ls9c_ard_3-2-1_111069_2023-07-31_final.stac-item
2023-08-02 09:39:44	ga_ls9c_ard_3-2-1_093087_2023-08-02_final.stac-item
2023-08-05 10:03:29	ga_ls9c_ard_3-2-1_098069_2023-08-05_final.stac-item
2023-08-12 10:10:06	ga_ls9c_ard_3-2-1_099070_2023-08-12_final.stac-item
2023-08-12 10:10:54	ga_ls9c_ard_3-2-1_099072_2023-08-12_final.stac-item
2023-09-01 11:25:38	ga_ls9c_ard_3-2-1_111073_2023-09-01_final.stac-item
2023-10-15 10:10:33	ga_ls9c_ard_3-2-1_099070_2023-10-15_final.stac-item
2023-10-18 10:42:40	ga_ls9c_ard_3-2-1_104073_2023-10-18_final.stac-item
2023-10-24 10:07:35	ga_ls9c_ard_3-2-1_098078_2023-10-24_final.stac-item
2023-10-24 10:10:22	ga_ls9c_ard_3-2-1_098085_2023-10-24_final.stac-item
2023-10-31 10:14:29	ga_ls9c_ard_3-2-1_099080_2023-10-31_final.stac-item
2023-11-01 09:16:51	ga_ls9c_ard_3-2-1_090075_2023-10-31_final.stac-item
2023-11-04 11:25:01	ga_ls9c_ard_3-2-1_111071_2023-11-04_final.stac-item
2023-11-15 09:31:13	ga_ls9c_ard_3-2-1_092080_2023-11-15_final.stac-item
2023-11-19 09:07:21	ga_ls9c_ard_3-2-1_088082_2023-11-18_final.stac-item
2023-11-26 09:14:49	ga_ls9c_ard_3-2-1_089085_2023-11-25_final.stac-item
2023-11-27 09:52:54	ga_ls9c_ard_3-2-1_096072_2023-11-27_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