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

75 results

Time (local)	Label
2021-11-03 11:33:13	ga_ls9c_ard_3-2-1_112074_2021-11-03_final.stac-item
2021-12-06 09:14:54	ga_ls9c_ard_3-2-1_089085_2021-12-05_final.stac-item
2022-01-01 09:47:05	ga_ls9c_ard_3-2-1_095073_2022-01-01_final.stac-item
2022-01-10 09:40:04	ga_ls9c_ard_3-2-1_094071_2022-01-10_final.stac-item
2022-01-12 11:08:11	ga_ls9c_ard_3-2-1_108075_2022-01-12_final.stac-item
2022-02-20 11:17:52	ga_ls9c_ard_3-2-1_109084_2022-02-20_final.stac-item
2022-02-27 11:20:22	ga_ls9c_ard_3-2-1_110075_2022-02-27_final.stac-item
2022-03-19 10:52:47	ga_ls9c_ard_3-2-1_106068_2022-03-19_final.stac-item
2022-03-23 10:28:50	ga_ls9c_ard_3-2-1_102070_2022-03-23_final.stac-item
2022-04-28 10:09:29	ga_ls9c_ard_3-2-1_098084_2022-04-28_final.stac-item
2022-05-05 10:13:38	ga_ls9c_ard_3-2-1_099079_2022-05-05_final.stac-item
2022-05-20 09:34:09	ga_ls9c_ard_3-2-1_092089_2022-05-20_final.stac-item
2022-05-23 11:37:09	ga_ls9c_ard_3-2-1_113072_2022-05-23_final.stac-item
2022-06-23 10:55:25	ga_ls9c_ard_3-2-1_106075_2022-06-23_final.stac-item
2022-07-05 09:46:04	ga_ls9c_ard_3-2-1_094087_2022-07-05_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 09:21:30	ga_ls9c_ard_3-2-1_091072_2022-07-15_final.stac-item
2022-07-16 09:27:05	ga_ls9c_ard_3-2-1_091086_2022-07-15_final.stac-item
2022-07-28 09:52:00	ga_ls9c_ard_3-2-1_095086_2022-07-28_final.stac-item
2022-08-01 09:22:09	ga_ls9c_ard_3-2-1_091073_2022-07-31_final.stac-item
2022-08-17 09:29:04	ga_ls9c_ard_3-2-1_091090_2022-08-16_final.stac-item
2022-09-02 09:27:54	ga_ls9c_ard_3-2-1_091087_2022-09-01_final.stac-item
2022-09-26 10:15:52	ga_ls9c_ard_3-2-1_099083_2022-09-26_final.stac-item
2022-09-27 09:17:51	ga_ls9c_ard_3-2-1_090077_2022-09-26_final.stac-item
2022-11-08 11:32:43	ga_ls9c_ard_3-2-1_112074_2022-11-08_final.stac-item
2022-11-12 11:08:25	ga_ls9c_ard_3-2-1_108075_2022-11-12_final.stac-item
2022-11-19 09:34:31	ga_ls9c_ard_3-2-1_093072_2022-11-19_final.stac-item
2022-12-01 09:58:22	ga_ls9c_ard_3-2-1_097070_2022-12-01_final.stac-item
2022-12-09 10:50:15	ga_ls9c_ard_3-2-1_105076_2022-12-09_final.stac-item
2022-12-15 10:09:35	ga_ls9c_ard_3-2-1_099067_2022-12-15_final.stac-item
2023-01-08 09:23:20	ga_ls9c_ard_3-2-1_091075_2023-01-07_final.stac-item
2023-01-11 11:31:54	ga_ls9c_ard_3-2-1_112072_2023-01-11_final.stac-item
2023-01-16 10:11:30	ga_ls9c_ard_3-2-1_099072_2023-01-16_final.stac-item
2023-01-17 10:54:20	ga_ls9c_ard_3-2-1_106071_2023-01-17_final.stac-item
2023-02-09 09:23:47	ga_ls9c_ard_3-2-1_091076_2023-02-08_final.stac-item
2023-03-28 10:19:41	ga_ls9c_ard_3-2-1_100078_2023-03-28_final.stac-item
2023-03-31 10:46:34	ga_ls9c_ard_3-2-1_105068_2023-03-31_final.stac-item
2023-05-18 10:49:23	ga_ls9c_ard_3-2-1_105076_2023-05-18_final.stac-item
2023-05-30 11:13:12	ga_ls9c_ard_3-2-1_109074_2023-05-30_final.stac-item
2023-06-13 11:23:51	ga_ls9c_ard_3-2-1_111070_2023-06-13_final.stac-item
2023-06-13 11:24:15	ga_ls9c_ard_3-2-1_111071_2023-06-13_final.stac-item
2023-06-18 11:46:45	ga_ls9c_ard_3-2-1_114081_2023-06-18_final.stac-item
2023-06-26 09:22:01	ga_ls9c_ard_3-2-1_090090_2023-06-25_final.stac-item
2023-06-29 11:24:18	ga_ls9c_ard_3-2-1_111071_2023-06-29_final.stac-item
2023-08-02 09:33:21	ga_ls9c_ard_3-2-1_093071_2023-08-02_final.stac-item
2023-08-18 09:39:24	ga_ls9c_ard_3-2-1_093086_2023-08-18_final.stac-item
2023-08-19 10:21:05	ga_ls9c_ard_3-2-1_100082_2023-08-19_final.stac-item
2023-09-11 10:25:32	ga_ls9c_ard_3-2-1_101077_2023-09-11_final.stac-item
2023-09-17 11:24:34	ga_ls9c_ard_3-2-1_111070_2023-09-17_final.stac-item
2023-09-19 11:17:48	ga_ls9c_ard_3-2-1_109084_2023-09-19_final.stac-item
2023-10-07 09:23:00	ga_ls9c_ard_3-2-1_091075_2023-10-06_final.stac-item
2023-10-12 11:20:30	ga_ls9c_ard_3-2-1_110075_2023-10-12_final.stac-item
2023-10-13 10:27:41	ga_ls9c_ard_3-2-1_101082_2023-10-13_final.stac-item
2023-10-14 09:28:53	ga_ls9c_ard_3-2-1_092074_2023-10-13_final.stac-item
2023-11-16 10:14:29	ga_ls9c_ard_3-2-1_099080_2023-11-16_final.stac-item
2023-11-26 10:49:19	ga_ls9c_ard_3-2-1_105074_2023-11-26_final.stac-item
2023-12-02 10:11:25	ga_ls9c_ard_3-2-1_099072_2023-12-02_final.stac-item
2023-12-04 09:57:50	ga_ls9c_ard_3-2-1_097069_2023-12-04_final.stac-item
2023-12-11 10:02:49	ga_ls9c_ard_3-2-1_098066_2023-12-11_final.stac-item
2023-12-11 10:05:12	ga_ls9c_ard_3-2-1_098072_2023-12-11_final.stac-item
2023-12-12 09:11:36	ga_ls9c_ard_3-2-1_089077_2023-12-11_final.stac-item
2023-12-12 10:46:53	ga_ls9c_ard_3-2-1_105068_2023-12-12_final.stac-item
2023-12-18 10:13:51	ga_ls9c_ard_3-2-1_099078_2023-12-18_final.stac-item
2023-12-28 10:46:56	ga_ls9c_ard_3-2-1_105068_2023-12-28_final.stac-item
2024-01-12 10:07:37	ga_ls9c_ard_3-2-1_098078_2024-01-12_final.stac-item
2024-01-13 10:50:05	ga_ls9c_ard_3-2-1_105076_2024-01-13_final.stac-item
2024-01-28 11:44:53	ga_ls9c_ard_3-2-1_114074_2024-01-28_final.stac-item
2024-01-29 10:46:53	ga_ls9c_ard_3-2-1_105068_2024-01-29_final.stac-item
2024-02-09 10:29:11	ga_ls9c_ard_3-2-1_102070_2024-02-09_final.stac-item
2024-02-15 11:32:31	ga_ls9c_ard_3-2-1_112074_2024-02-15_final.stac-item
2024-02-17 11:18:07	ga_ls9c_ard_3-2-1_110069_2024-02-17_final.stac-item
2024-02-27 10:18:14	ga_ls9c_ard_3-2-1_100074_2024-02-27_final.stac-item
2024-03-07 11:52:35	ga_ls9c_ard_3-2-1_115078_2024-03-07_final.stac-item
2024-03-29 11:13:44	ga_ls9c_ard_3-2-1_109074_2024-03-29_final.stac-item
2024-04-14 11:17:37	ga_ls9c_ard_3-2-1_109084_2024-04-14_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