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

93 results

Time (local)	Label
2021-11-12 09:19:57	ga_ls9c_ard_3-2-1_091075_2021-11-11_final.stac-item
2021-11-12 10:55:49	ga_ls9c_ard_3-2-1_106068_2021-11-12_final.stac-item
2021-11-15 11:19:25	ga_ls9c_ard_3-2-1_110074_2021-11-15_final.stac-item
2021-12-04 09:28:05	ga_ls9c_ard_3-2-1_091087_2021-12-03_final.stac-item
2021-12-06 10:47:24	ga_ls9c_ard_3-2-1_105069_2021-12-06_final.stac-item
2021-12-20 09:21:58	ga_ls9c_ard_3-2-1_091072_2021-12-19_final.stac-item
2022-01-10 09:40:52	ga_ls9c_ard_3-2-1_094073_2022-01-10_final.stac-item
2022-01-11 10:28:07	ga_ls9c_ard_3-2-1_101083_2022-01-11_final.stac-item
2022-01-12 11:06:35	ga_ls9c_ard_3-2-1_108071_2022-01-12_final.stac-item
2022-01-14 09:16:56	ga_ls9c_ard_3-2-1_090075_2022-01-13_final.stac-item
2022-01-19 11:14:47	ga_ls9c_ard_3-2-1_109076_2022-01-19_final.stac-item
2022-01-23 09:11:35	ga_ls9c_ard_3-2-1_089077_2022-01-22_final.stac-item
2022-02-04 11:14:23	ga_ls9c_ard_3-2-1_109075_2022-02-04_final.stac-item
2022-02-08 09:11:34	ga_ls9c_ard_3-2-1_089077_2022-02-07_final.stac-item
2022-02-09 09:52:02	ga_ls9c_ard_3-2-1_096070_2022-02-09_final.stac-item
2022-02-11 11:18:32	ga_ls9c_ard_3-2-1_110070_2022-02-11_final.stac-item
2022-02-14 10:09:20	ga_ls9c_ard_3-2-1_099067_2022-02-14_final.stac-item
2022-02-22 09:23:00	ga_ls9c_ard_3-2-1_091075_2022-02-21_final.stac-item
2022-03-24 09:33:37	ga_ls9c_ard_3-2-1_093071_2022-03-24_final.stac-item
2022-04-06 09:07:04	ga_ls9c_ard_3-2-1_088082_2022-04-05_final.stac-item
2022-04-09 09:34:21	ga_ls9c_ard_3-2-1_093073_2022-04-09_final.stac-item
2022-04-29 10:51:57	ga_ls9c_ard_3-2-1_105082_2022-04-29_final.stac-item
2022-05-13 11:01:47	ga_ls9c_ard_3-2-1_107076_2022-05-13_final.stac-item
2022-05-26 10:27:34	ga_ls9c_ard_3-2-1_102068_2022-05-26_final.stac-item
2022-07-03 09:51:39	ga_ls9c_ard_3-2-1_096070_2022-07-03_final.stac-item
2022-07-08 11:51:03	ga_ls9c_ard_3-2-1_115075_2022-07-08_final.stac-item
2022-07-09 09:22:07	ga_ls9c_ard_3-2-1_090089_2022-07-08_final.stac-item
2022-07-25 09:22:15	ga_ls9c_ard_3-2-1_090089_2022-07-24_final.stac-item
2022-07-31 10:19:21	ga_ls9c_ard_3-2-1_100077_2022-07-31_final.stac-item
2022-08-06 11:23:37	ga_ls9c_ard_3-2-1_110083_2022-08-06_final.stac-item
2022-09-17 10:17:13	ga_ls9c_ard_3-2-1_100071_2022-09-17_final.stac-item
2022-09-27 10:53:09	ga_ls9c_ard_3-2-1_106068_2022-09-27_final.stac-item
2022-10-09 09:45:47	ga_ls9c_ard_3-2-1_094085_2022-10-09_final.stac-item
2022-11-05 09:29:17	ga_ls9c_ard_3-2-1_091090_2022-11-04_final.stac-item
2022-11-13 10:13:59	ga_ls9c_ard_3-2-1_099078_2022-11-13_final.stac-item
2022-12-15 10:09:35	ga_ls9c_ard_3-2-1_099067_2022-12-15_final.stac-item
2022-12-20 10:33:41	ga_ls9c_ard_3-2-1_102081_2022-12-20_final.stac-item
2022-12-23 09:26:04	ga_ls9c_ard_3-2-1_091082_2022-12-22_final.stac-item
2023-01-25 10:10:06	ga_ls9c_ard_3-2-1_098084_2023-01-25_final.stac-item
2023-02-01 10:13:59	ga_ls9c_ard_3-2-1_099078_2023-02-01_final.stac-item
2023-02-02 10:55:40	ga_ls9c_ard_3-2-1_106074_2023-02-02_final.stac-item
2023-03-07 10:03:44	ga_ls9c_ard_3-2-1_097084_2023-03-07_final.stac-item
2023-03-12 10:19:03	ga_ls9c_ard_3-2-1_100076_2023-03-12_final.stac-item
2023-03-28 10:19:17	ga_ls9c_ard_3-2-1_100077_2023-03-28_final.stac-item
2023-03-31 09:12:04	ga_ls9c_ard_3-2-1_089079_2023-03-30_final.stac-item
2023-04-06 10:13:28	ga_ls9c_ard_3-2-1_099078_2023-04-06_final.stac-item
2023-04-24 09:57:00	ga_ls9c_ard_3-2-1_097068_2023-04-24_final.stac-item
2023-05-08 10:12:46	ga_ls9c_ard_3-2-1_099077_2023-05-08_final.stac-item
2023-05-24 10:08:13	ga_ls9c_ard_3-2-1_099066_2023-05-24_final.stac-item
2023-06-04 11:30:55	ga_ls9c_ard_3-2-1_112072_2023-06-04_final.stac-item
2023-06-06 09:45:39	ga_ls9c_ard_3-2-1_094087_2023-06-06_final.stac-item
2023-06-06 11:19:21	ga_ls9c_ard_3-2-1_110074_2023-06-06_final.stac-item
2023-06-08 09:28:05	ga_ls9c_ard_3-2-1_092074_2023-06-07_final.stac-item
2023-06-15 09:39:21	ga_ls9c_ard_3-2-1_093087_2023-06-15_final.stac-item
2023-06-20 09:57:30	ga_ls9c_ard_3-2-1_096086_2023-06-20_final.stac-item
2023-06-22 11:17:38	ga_ls9c_ard_3-2-1_110070_2023-06-22_final.stac-item
2023-06-26 09:20:49	ga_ls9c_ard_3-2-1_090087_2023-06-25_final.stac-item
2023-07-21 09:11:43	ga_ls9c_ard_3-2-1_089079_2023-07-20_final.stac-item
2023-08-06 10:48:45	ga_ls9c_ard_3-2-1_105074_2023-08-06_final.stac-item
2023-08-12 11:50:59	ga_ls9c_ard_3-2-1_115075_2023-08-12_final.stac-item
2023-08-21 10:09:33	ga_ls9c_ard_3-2-1_098084_2023-08-21_final.stac-item
2023-08-22 09:15:57	ga_ls9c_ard_3-2-1_089089_2023-08-21_final.stac-item
2023-08-28 10:09:50	ga_ls9c_ard_3-2-1_099069_2023-08-28_final.stac-item
2023-09-15 09:57:39	ga_ls9c_ard_3-2-1_097069_2023-09-15_final.stac-item
2023-09-19 09:34:31	ga_ls9c_ard_3-2-1_093073_2023-09-19_final.stac-item
2023-10-19 09:47:03	ga_ls9c_ard_3-2-1_095073_2023-10-19_final.stac-item
2023-10-21 09:34:18	ga_ls9c_ard_3-2-1_093072_2023-10-21_final.stac-item
2023-10-24 10:03:35	ga_ls9c_ard_3-2-1_098068_2023-10-24_final.stac-item
2023-10-25 10:49:14	ga_ls9c_ard_3-2-1_105074_2023-10-25_final.stac-item
2023-11-04 11:29:48	ga_ls9c_ard_3-2-1_111083_2023-11-04_final.stac-item
2023-11-15 09:28:02	ga_ls9c_ard_3-2-1_092072_2023-11-14_final.stac-item
2023-11-25 10:10:26	ga_ls9c_ard_3-2-1_098085_2023-11-25_final.stac-item
2023-11-26 09:10:26	ga_ls9c_ard_3-2-1_089074_2023-11-25_final.stac-item
2023-12-14 10:34:33	ga_ls9c_ard_3-2-1_103068_2023-12-14_final.stac-item
2023-12-24 11:18:04	ga_ls9c_ard_3-2-1_109084_2023-12-24_final.stac-item
2023-12-31 09:40:55	ga_ls9c_ard_3-2-1_094073_2023-12-31_final.stac-item
2024-01-13 09:15:11	ga_ls9c_ard_3-2-1_089086_2024-01-12_final.stac-item
2024-01-28 11:44:53	ga_ls9c_ard_3-2-1_114074_2024-01-28_final.stac-item
2024-01-31 10:39:43	ga_ls9c_ard_3-2-1_103081_2024-01-31_final.stac-item
2024-02-01 11:20:12	ga_ls9c_ard_3-2-1_110074_2024-02-01_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 09:40:02	ga_ls9c_ard_3-2-1_094071_2024-02-17_final.stac-item
2024-03-15 11:03:55	ga_ls9c_ard_3-2-1_107080_2024-03-15_final.stac-item
2024-03-20 11:18:27	ga_ls9c_ard_3-2-1_110070_2024-03-20_final.stac-item
2024-03-22 09:29:12	ga_ls9c_ard_3-2-1_092075_2024-03-21_final.stac-item
2024-04-12 09:52:20	ga_ls9c_ard_3-2-1_095087_2024-04-12_final.stac-item
2024-04-14 09:34:21	ga_ls9c_ard_3-2-1_093073_2024-04-14_final.stac-item
2024-04-17 10:03:12	ga_ls9c_ard_3-2-1_098068_2024-04-17_final.stac-item
2024-04-18 09:11:33	ga_ls9c_ard_3-2-1_089078_2024-04-17_final.stac-item
2024-04-25 10:52:25	ga_ls9c_ard_3-2-1_106068_2024-04-25_final.stac-item
2024-05-02 09:22:29	ga_ls9c_ard_3-2-1_091075_2024-05-01_final.stac-item
2024-05-04 10:51:48	ga_ls9c_ard_3-2-1_105082_2024-05-04_final.stac-item
2024-05-25 09:33:40	ga_ls9c_ard_3-2-1_092088_2024-05-25_nrt.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