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

85 results

Time (local)	Label
2022-01-23 09:12:23	ga_ls9c_ard_3-2-1_089079_2022-01-22_final.stac-item
2022-02-15 10:54:11	ga_ls9c_ard_3-2-1_106071_2022-02-15_final.stac-item
2022-03-03 10:53:12	ga_ls9c_ard_3-2-1_106069_2022-03-03_final.stac-item
2022-03-22 09:46:23	ga_ls9c_ard_3-2-1_095072_2022-03-22_final.stac-item
2022-04-09 09:35:09	ga_ls9c_ard_3-2-1_093075_2022-04-09_final.stac-item
2022-05-13 11:01:47	ga_ls9c_ard_3-2-1_107076_2022-05-13_final.stac-item
2022-05-21 10:13:02	ga_ls9c_ard_3-2-1_099078_2022-05-21_final.stac-item
2022-05-29 09:25:59	ga_ls9c_ard_3-2-1_091084_2022-05-28_final.stac-item
2022-05-30 10:09:39	ga_ls9c_ard_3-2-1_098085_2022-05-30_final.stac-item
2022-06-03 11:19:50	ga_ls9c_ard_3-2-1_110075_2022-06-03_final.stac-item
2022-06-29 10:21:34	ga_ls9c_ard_3-2-1_100083_2022-06-29_final.stac-item
2022-07-19 09:57:39	ga_ls9c_ard_3-2-1_096085_2022-07-19_final.stac-item
2022-08-03 10:46:42	ga_ls9c_ard_3-2-1_105068_2022-08-03_final.stac-item
2022-08-22 11:18:08	ga_ls9c_ard_3-2-1_110069_2022-08-22_final.stac-item
2022-09-07 09:40:51	ga_ls9c_ard_3-2-1_094073_2022-09-07_final.stac-item
2022-09-07 11:19:44	ga_ls9c_ard_3-2-1_110073_2022-09-07_final.stac-item
2022-09-15 10:28:21	ga_ls9c_ard_3-2-1_102068_2022-09-15_final.stac-item
2022-09-30 11:26:03	ga_ls9c_ard_3-2-1_111073_2022-09-30_final.stac-item
2022-10-06 10:47:21	ga_ls9c_ard_3-2-1_105069_2022-10-06_final.stac-item
2022-10-23 11:36:43	ga_ls9c_ard_3-2-1_112084_2022-10-23_final.stac-item
2022-10-31 09:07:34	ga_ls9c_ard_3-2-1_088082_2022-10-30_final.stac-item
2022-11-07 09:12:33	ga_ls9c_ard_3-2-1_089079_2022-11-06_final.stac-item
2022-11-14 09:21:10	ga_ls9c_ard_3-2-1_090085_2022-11-13_final.stac-item
2022-11-15 11:38:55	ga_ls9c_ard_3-2-1_113074_2022-11-15_final.stac-item
2022-11-18 10:30:56	ga_ls9c_ard_3-2-1_102074_2022-11-18_final.stac-item
2022-11-25 10:36:18	ga_ls9c_ard_3-2-1_103072_2022-11-25_final.stac-item
2022-11-26 09:41:04	ga_ls9c_ard_3-2-1_094073_2022-11-26_final.stac-item
2022-11-28 11:07:35	ga_ls9c_ard_3-2-1_108073_2022-11-28_final.stac-item
2022-12-28 11:21:08	ga_ls9c_ard_3-2-1_110076_2022-12-28_final.stac-item
2023-01-10 09:10:33	ga_ls9c_ard_3-2-1_089074_2023-01-09_final.stac-item
2023-01-10 09:15:21	ga_ls9c_ard_3-2-1_089086_2023-01-09_final.stac-item
2023-01-17 10:59:08	ga_ls9c_ard_3-2-1_106083_2023-01-17_final.stac-item
2023-02-02 09:21:10	ga_ls9c_ard_3-2-1_090085_2023-02-01_final.stac-item
2023-02-21 09:52:20	ga_ls9c_ard_3-2-1_095086_2023-02-21_final.stac-item
2023-02-27 10:52:28	ga_ls9c_ard_3-2-1_105082_2023-02-27_final.stac-item
2023-03-10 10:29:00	ga_ls9c_ard_3-2-1_102070_2023-03-10_final.stac-item
2023-03-13 10:59:55	ga_ls9c_ard_3-2-1_107070_2023-03-13_final.stac-item
2023-03-23 09:58:51	ga_ls9c_ard_3-2-1_097072_2023-03-23_final.stac-item
2023-04-22 10:16:09	ga_ls9c_ard_3-2-1_099085_2023-04-22_final.stac-item
2023-04-25 10:45:50	ga_ls9c_ard_3-2-1_104082_2023-04-25_final.stac-item
2023-05-07 09:33:30	ga_ls9c_ard_3-2-1_092087_2023-05-07_final.stac-item
2023-05-16 09:21:17	ga_ls9c_ard_3-2-1_091072_2023-05-15_final.stac-item
2023-05-25 10:52:16	ga_ls9c_ard_3-2-1_106068_2023-05-25_final.stac-item
2023-06-11 11:41:01	ga_ls9c_ard_3-2-1_113082_2023-06-11_final.stac-item
2023-06-16 10:19:01	ga_ls9c_ard_3-2-1_100078_2023-06-16_final.stac-item
2023-06-20 11:35:35	ga_ls9c_ard_3-2-1_112084_2023-06-20_final.stac-item
2023-06-29 09:51:48	ga_ls9c_ard_3-2-1_095087_2023-06-29_final.stac-item
2023-07-12 09:16:17	ga_ls9c_ard_3-2-1_090075_2023-07-11_final.stac-item
2023-07-12 09:21:53	ga_ls9c_ard_3-2-1_090089_2023-07-11_final.stac-item
2023-07-15 09:46:24	ga_ls9c_ard_3-2-1_095073_2023-07-15_final.stac-item
2023-07-21 10:49:00	ga_ls9c_ard_3-2-1_105075_2023-07-21_final.stac-item
2023-07-27 10:10:20	ga_ls9c_ard_3-2-1_099071_2023-07-27_final.stac-item
2023-07-29 09:57:13	ga_ls9c_ard_3-2-1_097069_2023-07-29_final.stac-item
2023-08-07 11:33:37	ga_ls9c_ard_3-2-1_112078_2023-08-07_final.stac-item
2023-08-19 10:21:29	ga_ls9c_ard_3-2-1_100083_2023-08-19_final.stac-item
2023-08-20 10:59:34	ga_ls9c_ard_3-2-1_107070_2023-08-20_final.stac-item
2023-09-21 09:22:33	ga_ls9c_ard_3-2-1_091074_2023-09-20_final.stac-item
2023-10-01 10:04:00	ga_ls9c_ard_3-2-1_097085_2023-10-01_final.stac-item
2023-10-16 10:53:25	ga_ls9c_ard_3-2-1_106069_2023-10-16_final.stac-item
2023-10-24 10:03:35	ga_ls9c_ard_3-2-1_098068_2023-10-24_final.stac-item
2023-11-26 10:52:30	ga_ls9c_ard_3-2-1_105082_2023-11-26_final.stac-item
2023-11-27 09:58:05	ga_ls9c_ard_3-2-1_096085_2023-11-27_final.stac-item
2023-12-06 09:46:39	ga_ls9c_ard_3-2-1_095072_2023-12-06_final.stac-item
2023-12-14 10:39:44	ga_ls9c_ard_3-2-1_103081_2023-12-14_final.stac-item
2023-12-27 10:03:17	ga_ls9c_ard_3-2-1_098067_2023-12-27_final.stac-item
2023-12-28 10:52:08	ga_ls9c_ard_3-2-1_105081_2023-12-28_final.stac-item
2024-01-09 11:14:47	ga_ls9c_ard_3-2-1_109076_2024-01-09_final.stac-item
2024-01-20 09:18:09	ga_ls9c_ard_3-2-1_090078_2024-01-19_final.stac-item
2024-01-20 10:56:14	ga_ls9c_ard_3-2-1_106076_2024-01-20_final.stac-item
2024-01-25 11:14:44	ga_ls9c_ard_3-2-1_109076_2024-01-25_final.stac-item
2024-01-26 10:17:08	ga_ls9c_ard_3-2-1_100071_2024-01-26_final.stac-item
2024-01-26 10:22:19	ga_ls9c_ard_3-2-1_100084_2024-01-26_final.stac-item
2024-02-12 09:23:34	ga_ls9c_ard_3-2-1_091076_2024-02-11_final.stac-item
2024-02-14 10:49:40	ga_ls9c_ard_3-2-1_105075_2024-02-14_final.stac-item
2024-02-19 09:28:02	ga_ls9c_ard_3-2-1_092072_2024-02-18_final.stac-item
2024-02-28 10:59:54	ga_ls9c_ard_3-2-1_107070_2024-02-28_final.stac-item
2024-03-02 11:35:13	ga_ls9c_ard_3-2-1_112081_2024-03-02_final.stac-item
2024-03-06 09:33:14	ga_ls9c_ard_3-2-1_092085_2024-03-06_final.stac-item
2024-03-12 10:29:26	ga_ls9c_ard_3-2-1_102071_2024-03-12_final.stac-item
2024-03-24 09:21:36	ga_ls9c_ard_3-2-1_090087_2024-03-23_final.stac-item
2024-04-14 09:40:20	ga_ls9c_ard_3-2-1_093088_2024-04-14_final.stac-item
2024-04-30 11:17:20	ga_ls9c_ard_3-2-1_109084_2024-04-30_final.stac-item
2024-05-16 11:11:13	ga_ls9c_ard_3-2-1_109069_2024-05-16_nrt.stac-item
2024-05-29 09:06:29	ga_ls9c_ard_3-2-1_088082_2024-05-28_nrt.stac-item
2024-06-03 11:04:43	ga_ls9c_ard_3-2-1_107084_2024-06-03_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