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 10:19:22	ga_ls9c_ard_3-2-1_100083_2021-11-06_final.stac-item
2021-11-08 11:35:42	ga_ls9c_ard_3-2-1_113074_2021-11-08_final.stac-item
2021-11-10 09:37:06	ga_ls9c_ard_3-2-1_094071_2021-11-10_final.stac-item
2021-11-20 11:23:05	ga_ls9c_ard_3-2-1_110077_2021-11-20_final.stac-item
2021-12-12 10:11:27	ga_ls9c_ard_3-2-1_099072_2021-12-12_final.stac-item
2021-12-18 11:14:24	ga_ls9c_ard_3-2-1_109075_2021-12-18_final.stac-item
2021-12-20 09:22:46	ga_ls9c_ard_3-2-1_091074_2021-12-19_final.stac-item
2021-12-22 09:13:36	ga_ls9c_ard_3-2-1_089082_2021-12-21_final.stac-item
2021-12-29 10:56:16	ga_ls9c_ard_3-2-1_106076_2021-12-29_final.stac-item
2021-12-30 11:38:44	ga_ls9c_ard_3-2-1_113074_2021-12-30_final.stac-item
2022-01-13 10:16:09	ga_ls9c_ard_3-2-1_099084_2022-01-13_final.stac-item
2022-01-19 09:40:41	ga_ls9c_ard_3-2-1_093088_2022-01-19_final.stac-item
2022-01-30 10:59:03	ga_ls9c_ard_3-2-1_106083_2022-01-30_final.stac-item
2022-02-07 10:09:59	ga_ls9c_ard_3-2-1_098084_2022-02-07_final.stac-item
2022-02-10 10:34:29	ga_ls9c_ard_3-2-1_103068_2022-02-10_final.stac-item
2022-02-15 09:16:54	ga_ls9c_ard_3-2-1_090075_2022-02-14_final.stac-item
2022-02-28 10:25:55	ga_ls9c_ard_3-2-1_101078_2022-02-28_final.stac-item
2022-03-02 10:09:09	ga_ls9c_ard_3-2-1_099067_2022-03-02_final.stac-item
2022-04-04 09:16:38	ga_ls9c_ard_3-2-1_090075_2022-04-03_final.stac-item
2022-04-08 10:27:59	ga_ls9c_ard_3-2-1_102068_2022-04-08_final.stac-item
2022-04-20 10:55:21	ga_ls9c_ard_3-2-1_106075_2022-04-20_final.stac-item
2022-04-26 10:21:27	ga_ls9c_ard_3-2-1_100083_2022-04-26_final.stac-item
2022-04-29 09:15:51	ga_ls9c_ard_3-2-1_089089_2022-04-28_final.stac-item
2022-05-08 09:07:13	ga_ls9c_ard_3-2-1_088083_2022-05-07_final.stac-item
2022-05-26 10:28:22	ga_ls9c_ard_3-2-1_102070_2022-05-26_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 11:18:38	ga_ls9c_ard_3-2-1_110072_2022-06-03_final.stac-item
2022-06-17 11:31:07	ga_ls9c_ard_3-2-1_112072_2022-06-17_final.stac-item
2022-06-28 11:14:24	ga_ls9c_ard_3-2-1_109076_2022-06-28_final.stac-item
2022-07-01 10:04:25	ga_ls9c_ard_3-2-1_098071_2022-07-01_final.stac-item
2022-07-05 09:45:40	ga_ls9c_ard_3-2-1_094086_2022-07-05_final.stac-item
2022-07-07 11:07:47	ga_ls9c_ard_3-2-1_108075_2022-07-07_final.stac-item
2022-07-10 09:56:36	ga_ls9c_ard_3-2-1_097067_2022-07-10_final.stac-item
2022-07-15 11:58:23	ga_ls9c_ard_3-2-1_116078_2022-07-15_final.stac-item
2022-08-01 09:28:32	ga_ls9c_ard_3-2-1_091089_2022-07-31_final.stac-item
2022-08-02 11:44:42	ga_ls9c_ard_3-2-1_114074_2022-08-02_final.stac-item
2022-08-04 11:31:34	ga_ls9c_ard_3-2-1_112072_2022-08-04_final.stac-item
2022-08-08 09:33:35	ga_ls9c_ard_3-2-1_092086_2022-08-08_final.stac-item
2022-08-15 09:33:50	ga_ls9c_ard_3-2-1_093071_2022-08-15_final.stac-item
2022-08-19 10:49:13	ga_ls9c_ard_3-2-1_105074_2022-08-19_final.stac-item
2022-08-25 11:51:50	ga_ls9c_ard_3-2-1_115076_2022-08-25_final.stac-item
2022-08-25 11:52:38	ga_ls9c_ard_3-2-1_115078_2022-08-25_final.stac-item
2022-09-02 11:05:11	ga_ls9c_ard_3-2-1_107083_2022-09-02_final.stac-item
2022-09-04 09:12:21	ga_ls9c_ard_3-2-1_089079_2022-09-03_final.stac-item
2022-09-18 09:27:59	ga_ls9c_ard_3-2-1_091087_2022-09-17_final.stac-item
2022-09-22 10:36:11	ga_ls9c_ard_3-2-1_103072_2022-09-22_final.stac-item
2022-09-26 10:09:53	ga_ls9c_ard_3-2-1_099068_2022-09-26_final.stac-item
2022-09-26 10:11:05	ga_ls9c_ard_3-2-1_099071_2022-09-26_final.stac-item
2022-09-27 09:17:27	ga_ls9c_ard_3-2-1_090076_2022-09-26_final.stac-item
2022-09-30 09:51:09	ga_ls9c_ard_3-2-1_095083_2022-09-30_final.stac-item
2022-10-06 10:46:57	ga_ls9c_ard_3-2-1_105068_2022-10-06_final.stac-item
2022-10-11 09:29:28	ga_ls9c_ard_3-2-1_092075_2022-10-10_final.stac-item
2022-10-21 10:05:24	ga_ls9c_ard_3-2-1_098072_2022-10-21_final.stac-item
2022-10-25 09:40:41	ga_ls9c_ard_3-2-1_094072_2022-10-25_final.stac-item
2022-10-29 10:53:38	ga_ls9c_ard_3-2-1_106069_2022-10-29_final.stac-item
2022-11-13 10:10:00	ga_ls9c_ard_3-2-1_099068_2022-11-13_final.stac-item
2022-11-13 10:11:36	ga_ls9c_ard_3-2-1_099072_2022-11-13_final.stac-item
2022-11-16 09:07:12	ga_ls9c_ard_3-2-1_088081_2022-11-15_final.stac-item
2022-11-16 10:40:54	ga_ls9c_ard_3-2-1_104068_2022-11-16_final.stac-item
2022-11-22 10:05:01	ga_ls9c_ard_3-2-1_098071_2022-11-22_final.stac-item
2022-11-25 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-11-25_final.stac-item
2022-11-26 11:23:56	ga_ls9c_ard_3-2-1_110083_2022-11-26_final.stac-item
2022-11-30 10:53:36	ga_ls9c_ard_3-2-1_106069_2022-11-30_final.stac-item
2022-12-01 11:38:51	ga_ls9c_ard_3-2-1_113074_2022-12-01_final.stac-item
2022-12-09 09:14:33	ga_ls9c_ard_3-2-1_089084_2022-12-08_final.stac-item
2022-12-12 11:18:22	ga_ls9c_ard_3-2-1_110069_2022-12-12_final.stac-item
2022-12-22 10:22:30	ga_ls9c_ard_3-2-1_100084_2022-12-22_final.stac-item
2022-12-24 10:04:56	ga_ls9c_ard_3-2-1_098071_2022-12-24_final.stac-item
2022-12-25 09:16:30	ga_ls9c_ard_3-2-1_089089_2022-12-24_final.stac-item
2022-12-26 09:52:12	ga_ls9c_ard_3-2-1_096070_2022-12-26_final.stac-item
2023-01-04 11:26:56	ga_ls9c_ard_3-2-1_111075_2023-01-04_final.stac-item
2023-01-06 11:12:11	ga_ls9c_ard_3-2-1_109069_2023-01-06_final.stac-item
2023-01-09 10:03:48	ga_ls9c_ard_3-2-1_098068_2023-01-09_final.stac-item
2023-01-09 10:04:11	ga_ls9c_ard_3-2-1_098069_2023-01-09_final.stac-item
2023-01-30 10:23:56	ga_ls9c_ard_3-2-1_101072_2023-01-30_final.stac-item
2023-02-05 11:26:11	ga_ls9c_ard_3-2-1_111073_2023-02-05_final.stac-item
2023-03-14 10:03:30	ga_ls9c_ard_3-2-1_098068_2023-03-14_final.stac-item
2023-03-15 10:49:57	ga_ls9c_ard_3-2-1_105076_2023-03-15_final.stac-item
2023-03-25 09:52:27	ga_ls9c_ard_3-2-1_095087_2023-03-25_final.stac-item
2023-03-29 11:01:19	ga_ls9c_ard_3-2-1_107074_2023-03-29_final.stac-item
2023-04-24 09:57:00	ga_ls9c_ard_3-2-1_097068_2023-04-24_final.stac-item
2023-04-25 09:06:57	ga_ls9c_ard_3-2-1_088082_2023-04-24_final.stac-item
2023-04-26 09:46:36	ga_ls9c_ard_3-2-1_095073_2023-04-26_final.stac-item
2023-05-07 09:33:30	ga_ls9c_ard_3-2-1_092087_2023-05-07_final.stac-item
2023-05-08 11:52:27	ga_ls9c_ard_3-2-1_115079_2023-05-08_final.stac-item
2023-05-14 11:11:21	ga_ls9c_ard_3-2-1_109069_2023-05-14_final.stac-item
2023-05-21 09:39:46	ga_ls9c_ard_3-2-1_094072_2023-05-21_final.stac-item
2023-06-01 09:26:44	ga_ls9c_ard_3-2-1_091086_2023-05-31_final.stac-item
2023-06-04 11:31:43	ga_ls9c_ard_3-2-1_112074_2023-06-04_final.stac-item
2023-06-07 10:27:18	ga_ls9c_ard_3-2-1_101083_2023-06-07_final.stac-item
2023-06-10 10:52:11	ga_ls9c_ard_3-2-1_106068_2023-06-10_final.stac-item
2023-06-24 09:33:34	ga_ls9c_ard_3-2-1_092088_2023-06-24_final.stac-item
2023-07-04 10:02:52	ga_ls9c_ard_3-2-1_098068_2023-07-04_final.stac-item
2023-07-11 11:50:47	ga_ls9c_ard_3-2-1_115075_2023-07-11_final.stac-item
2023-07-28 09:21:31	ga_ls9c_ard_3-2-1_090088_2023-07-27_final.stac-item
2023-07-29 11:41:18	ga_ls9c_ard_3-2-1_113082_2023-07-29_final.stac-item
2023-10-25 09:11:57	ga_ls9c_ard_3-2-1_089078_2023-10-24_final.stac-item
2023-10-25 09:16:20	ga_ls9c_ard_3-2-1_089089_2023-10-24_final.stac-item
2023-10-29 10:27:40	ga_ls9c_ard_3-2-1_101082_2023-10-29_final.stac-item
2023-11-16 11:52:34	ga_ls9c_ard_3-2-1_115078_2023-11-16_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