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 10:14:59	ga_ls9c_ard_3-2-1_100072_2021-11-06_final.stac-item
2021-11-07 10:55:21	ga_ls9c_ard_3-2-1_106073_2021-11-07_final.stac-item
2021-11-22 11:06:43	ga_ls9c_ard_3-2-1_107083_2021-11-22_final.stac-item
2021-11-23 10:03:14	ga_ls9c_ard_3-2-1_098071_2021-11-23_final.stac-item
2021-12-09 09:41:23	ga_ls9c_ard_3-2-1_094074_2021-12-09_final.stac-item
2021-12-14 09:58:16	ga_ls9c_ard_3-2-1_097070_2021-12-14_final.stac-item
2021-12-16 11:24:46	ga_ls9c_ard_3-2-1_111070_2021-12-16_final.stac-item
2022-01-14 10:55:25	ga_ls9c_ard_3-2-1_106074_2022-01-14_final.stac-item
2022-01-21 09:26:44	ga_ls9c_ard_3-2-1_091084_2022-01-20_final.stac-item
2022-01-21 09:27:56	ga_ls9c_ard_3-2-1_091087_2022-01-20_final.stac-item
2022-01-30 09:22:10	ga_ls9c_ard_3-2-1_090088_2022-01-29_final.stac-item
2022-02-08 09:11:58	ga_ls9c_ard_3-2-1_089078_2022-02-07_final.stac-item
2022-02-08 09:13:10	ga_ls9c_ard_3-2-1_089081_2022-02-07_final.stac-item
2022-02-08 09:13:34	ga_ls9c_ard_3-2-1_089082_2022-02-07_final.stac-item
2022-03-02 10:09:33	ga_ls9c_ard_3-2-1_099068_2022-03-02_final.stac-item
2022-03-03 10:53:12	ga_ls9c_ard_3-2-1_106069_2022-03-03_final.stac-item
2022-03-06 11:24:07	ga_ls9c_ard_3-2-1_111069_2022-03-06_final.stac-item
2022-03-28 10:49:45	ga_ls9c_ard_3-2-1_105076_2022-03-28_final.stac-item
2022-03-29 11:32:13	ga_ls9c_ard_3-2-1_112074_2022-03-29_final.stac-item
2022-04-03 10:13:04	ga_ls9c_ard_3-2-1_099077_2022-04-03_final.stac-item
2022-04-05 09:57:06	ga_ls9c_ard_3-2-1_097068_2022-04-05_final.stac-item
2022-04-19 10:16:06	ga_ls9c_ard_3-2-1_099085_2022-04-19_final.stac-item
2022-04-20 09:20:28	ga_ls9c_ard_3-2-1_090085_2022-04-19_final.stac-item
2022-04-20 09:22:28	ga_ls9c_ard_3-2-1_090090_2022-04-19_final.stac-item
2022-04-22 09:06:05	ga_ls9c_ard_3-2-1_088080_2022-04-21_final.stac-item
2022-04-25 09:38:59	ga_ls9c_ard_3-2-1_093085_2022-04-25_final.stac-item
2022-05-02 11:18:26	ga_ls9c_ard_3-2-1_110071_2022-05-02_final.stac-item
2022-05-15 09:16:06	ga_ls9c_ard_3-2-1_089090_2022-05-14_final.stac-item
2022-05-23 11:37:57	ga_ls9c_ard_3-2-1_113074_2022-05-23_final.stac-item
2022-05-25 11:24:24	ga_ls9c_ard_3-2-1_111071_2022-05-25_final.stac-item
2022-05-31 10:51:43	ga_ls9c_ard_3-2-1_105082_2022-05-31_final.stac-item
2022-06-03 09:42:33	ga_ls9c_ard_3-2-1_094079_2022-06-03_final.stac-item
2022-06-22 11:53:00	ga_ls9c_ard_3-2-1_115080_2022-06-22_final.stac-item
2022-06-26 09:52:17	ga_ls9c_ard_3-2-1_095087_2022-06-26_final.stac-item
2022-06-28 11:14:00	ga_ls9c_ard_3-2-1_109075_2022-06-28_final.stac-item
2022-06-29 11:58:28	ga_ls9c_ard_3-2-1_116078_2022-06-29_final.stac-item
2022-07-16 09:22:18	ga_ls9c_ard_3-2-1_091074_2022-07-15_final.stac-item
2022-07-30 09:39:16	ga_ls9c_ard_3-2-1_093085_2022-07-30_final.stac-item
2022-08-02 10:03:49	ga_ls9c_ard_3-2-1_098069_2022-08-02_final.stac-item
2022-08-11 09:57:44	ga_ls9c_ard_3-2-1_097069_2022-08-11_final.stac-item
2022-08-25 11:52:14	ga_ls9c_ard_3-2-1_115077_2022-08-25_final.stac-item
2022-08-29 11:24:20	ga_ls9c_ard_3-2-1_111069_2022-08-29_final.stac-item
2022-09-02 09:27:30	ga_ls9c_ard_3-2-1_091086_2022-09-01_final.stac-item
2022-09-03 10:04:23	ga_ls9c_ard_3-2-1_098070_2022-09-03_final.stac-item
2022-09-16 11:14:25	ga_ls9c_ard_3-2-1_109075_2022-09-16_final.stac-item
2022-09-17 10:17:13	ga_ls9c_ard_3-2-1_100071_2022-09-17_final.stac-item
2022-09-23 09:45:21	ga_ls9c_ard_3-2-1_094084_2022-09-23_final.stac-item
2022-09-25 11:06:18	ga_ls9c_ard_3-2-1_108070_2022-09-25_final.stac-item
2022-10-05 10:03:18	ga_ls9c_ard_3-2-1_098067_2022-10-05_final.stac-item
2022-10-09 09:44:35	ga_ls9c_ard_3-2-1_094082_2022-10-09_final.stac-item
2022-10-11 11:08:21	ga_ls9c_ard_3-2-1_108075_2022-10-11_final.stac-item
2022-10-14 10:03:59	ga_ls9c_ard_3-2-1_097084_2022-10-14_final.stac-item
2022-10-16 09:52:02	ga_ls9c_ard_3-2-1_095085_2022-10-16_final.stac-item
2022-11-13 10:10:48	ga_ls9c_ard_3-2-1_099070_2022-11-13_final.stac-item
2022-11-14 10:56:03	ga_ls9c_ard_3-2-1_106075_2022-11-14_final.stac-item
2022-11-17 11:26:57	ga_ls9c_ard_3-2-1_111075_2022-11-17_final.stac-item
2022-11-21 11:03:26	ga_ls9c_ard_3-2-1_107078_2022-11-21_final.stac-item
2022-11-30 09:21:30	ga_ls9c_ard_3-2-1_090086_2022-11-29_final.stac-item
2022-12-07 09:28:07	ga_ls9c_ard_3-2-1_091087_2022-12-06_final.stac-item
2023-01-09 10:10:11	ga_ls9c_ard_3-2-1_098084_2023-01-09_final.stac-item
2023-01-16 11:52:46	ga_ls9c_ard_3-2-1_115078_2023-01-16_final.stac-item
2023-01-17 10:53:08	ga_ls9c_ard_3-2-1_106068_2023-01-17_final.stac-item
2023-01-22 09:39:32	ga_ls9c_ard_3-2-1_093085_2023-01-22_final.stac-item
2023-02-02 09:21:10	ga_ls9c_ard_3-2-1_090085_2023-02-01_final.stac-item
2023-02-08 11:58:42	ga_ls9c_ard_3-2-1_116077_2023-02-08_final.stac-item
2023-02-11 10:52:42	ga_ls9c_ard_3-2-1_105082_2023-02-11_final.stac-item
2023-02-19 11:40:02	ga_ls9c_ard_3-2-1_113077_2023-02-19_final.stac-item
2023-02-20 10:41:35	ga_ls9c_ard_3-2-1_104070_2023-02-20_final.stac-item
2023-02-24 10:21:57	ga_ls9c_ard_3-2-1_100083_2023-02-24_final.stac-item
2023-02-27 10:52:04	ga_ls9c_ard_3-2-1_105081_2023-02-27_final.stac-item
2023-03-02 09:41:16	ga_ls9c_ard_3-2-1_094074_2023-03-02_final.stac-item
2023-03-04 11:06:35	ga_ls9c_ard_3-2-1_108071_2023-03-04_final.stac-item
2023-03-05 10:12:56	ga_ls9c_ard_3-2-1_099076_2023-03-05_final.stac-item
2023-03-05 11:53:25	ga_ls9c_ard_3-2-1_115080_2023-03-05_final.stac-item
2023-03-27 11:12:56	ga_ls9c_ard_3-2-1_109072_2023-03-27_final.stac-item
2023-04-01 11:35:49	ga_ls9c_ard_3-2-1_112083_2023-04-01_final.stac-item
2023-04-08 11:39:34	ga_ls9c_ard_3-2-1_113077_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
2023-04-19 11:19:22	ga_ls9c_ard_3-2-1_110073_2023-04-19_final.stac-item
2023-05-17 10:03:44	ga_ls9c_ard_3-2-1_098070_2023-05-17_final.stac-item
2023-05-17 10:04:32	ga_ls9c_ard_3-2-1_098072_2023-05-17_final.stac-item
2023-05-31 10:16:23	ga_ls9c_ard_3-2-1_100071_2023-05-31_final.stac-item
2023-06-01 09:22:21	ga_ls9c_ard_3-2-1_091075_2023-05-31_final.stac-item
2023-06-02 10:08:00	ga_ls9c_ard_3-2-1_098081_2023-06-02_final.stac-item
2023-06-03 09:15:58	ga_ls9c_ard_3-2-1_089090_2023-06-02_final.stac-item
2023-06-09 10:13:20	ga_ls9c_ard_3-2-1_099079_2023-06-09_final.stac-item
2023-06-13 11:29:02	ga_ls9c_ard_3-2-1_111083_2023-06-13_final.stac-item
2023-06-22 09:39:09	ga_ls9c_ard_3-2-1_094071_2023-06-22_final.stac-item
2023-09-14 10:55:15	ga_ls9c_ard_3-2-1_106074_2023-09-14_final.stac-item
2023-09-23 10:46:16	ga_ls9c_ard_3-2-1_105067_2023-09-23_final.stac-item
2023-09-23 10:46:40	ga_ls9c_ard_3-2-1_105068_2023-09-23_final.stac-item
2023-10-05 09:38:32	ga_ls9c_ard_3-2-1_093083_2023-10-05_final.stac-item
2023-10-09 10:52:44	ga_ls9c_ard_3-2-1_105083_2023-10-09_final.stac-item
2023-10-15 10:15:45	ga_ls9c_ard_3-2-1_099083_2023-10-15_final.stac-item
2023-10-25 10:52:26	ga_ls9c_ard_3-2-1_105082_2023-10-25_final.stac-item
2023-10-28 09:40:02	ga_ls9c_ard_3-2-1_094071_2023-10-28_final.stac-item
2023-10-30 09:33:38	ga_ls9c_ard_3-2-1_092086_2023-10-30_final.stac-item
2023-11-13 11:19:41	ga_ls9c_ard_3-2-1_110073_2023-11-13_final.stac-item
2023-11-15 09:29:38	ga_ls9c_ard_3-2-1_092076_2023-11-14_final.stac-item
2023-11-18 09:57:22	ga_ls9c_ard_3-2-1_097068_2023-11-18_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years