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
2021-11-11 10:20:39	ga_ls9c_ard_3-2-1_100080_2021-11-11_final.stac-item
2021-11-12 09:19:57	ga_ls9c_ard_3-2-1_091075_2021-11-11_final.stac-item
2021-11-18 09:59:11	ga_ls9c_ard_3-2-1_097067_2021-11-18_final.stac-item
2021-12-06 10:50:11	ga_ls9c_ard_3-2-1_105076_2021-12-06_final.stac-item
2021-12-12 10:11:03	ga_ls9c_ard_3-2-1_099071_2021-12-12_final.stac-item
2021-12-22 10:50:05	ga_ls9c_ard_3-2-1_105076_2021-12-22_final.stac-item
2022-01-10 09:40:52	ga_ls9c_ard_3-2-1_094073_2022-01-10_final.stac-item
2022-01-14 09:17:44	ga_ls9c_ard_3-2-1_090077_2022-01-13_final.stac-item
2022-01-15 11:38:41	ga_ls9c_ard_3-2-1_113074_2022-01-15_final.stac-item
2022-01-19 11:14:23	ga_ls9c_ard_3-2-1_109075_2022-01-19_final.stac-item
2022-02-04 11:13:36	ga_ls9c_ard_3-2-1_109073_2022-02-04_final.stac-item
2022-02-04 11:14:23	ga_ls9c_ard_3-2-1_109075_2022-02-04_final.stac-item
2022-02-04 11:14:47	ga_ls9c_ard_3-2-1_109076_2022-02-04_final.stac-item
2022-02-08 10:49:39	ga_ls9c_ard_3-2-1_105075_2022-02-08_final.stac-item
2022-02-17 09:07:43	ga_ls9c_ard_3-2-1_088083_2022-02-16_final.stac-item
2022-02-24 10:49:54	ga_ls9c_ard_3-2-1_105076_2022-02-24_final.stac-item
2022-03-04 09:56:47	ga_ls9c_ard_3-2-1_097067_2022-03-04_final.stac-item
2022-03-11 10:09:46	ga_ls9c_ard_3-2-1_098084_2022-03-11_final.stac-item
2022-04-28 10:02:42	ga_ls9c_ard_3-2-1_098067_2022-04-28_final.stac-item
2022-05-13 09:27:17	ga_ls9c_ard_3-2-1_091087_2022-05-12_final.stac-item
2022-05-13 09:27:41	ga_ls9c_ard_3-2-1_091088_2022-05-12_final.stac-item
2022-05-18 11:19:27	ga_ls9c_ard_3-2-1_110074_2022-05-18_final.stac-item
2022-05-22 10:55:29	ga_ls9c_ard_3-2-1_106076_2022-05-22_final.stac-item
2022-05-25 11:23:36	ga_ls9c_ard_3-2-1_111069_2022-05-25_final.stac-item
2022-05-31 10:50:55	ga_ls9c_ard_3-2-1_105080_2022-05-31_final.stac-item
2022-06-03 11:19:26	ga_ls9c_ard_3-2-1_110074_2022-06-03_final.stac-item
2022-06-22 10:09:20	ga_ls9c_ard_3-2-1_099068_2022-06-22_final.stac-item
2022-06-23 09:17:20	ga_ls9c_ard_3-2-1_090077_2022-06-22_final.stac-item
2022-07-05 11:20:10	ga_ls9c_ard_3-2-1_110075_2022-07-05_final.stac-item
2022-07-16 09:22:18	ga_ls9c_ard_3-2-1_091074_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
2022-07-28 09:52:24	ga_ls9c_ard_3-2-1_095087_2022-07-28_final.stac-item
2022-08-01 09:21:45	ga_ls9c_ard_3-2-1_091072_2022-07-31_final.stac-item
2022-08-15 09:33:50	ga_ls9c_ard_3-2-1_093071_2022-08-15_final.stac-item
2022-09-14 11:24:22	ga_ls9c_ard_3-2-1_111069_2022-09-14_final.stac-item
2022-09-18 09:27:59	ga_ls9c_ard_3-2-1_091087_2022-09-17_final.stac-item
2022-09-20 10:49:20	ga_ls9c_ard_3-2-1_105074_2022-09-20_final.stac-item
2022-09-24 10:27:49	ga_ls9c_ard_3-2-1_101082_2022-09-24_final.stac-item
2022-09-28 09:57:32	ga_ls9c_ard_3-2-1_097068_2022-09-28_final.stac-item
2022-10-09 11:24:16	ga_ls9c_ard_3-2-1_110084_2022-10-09_final.stac-item
2022-10-22 10:49:52	ga_ls9c_ard_3-2-1_105075_2022-10-22_final.stac-item
2022-10-28 10:09:35	ga_ls9c_ard_3-2-1_099067_2022-10-28_final.stac-item
2022-11-05 09:22:06	ga_ls9c_ard_3-2-1_091072_2022-11-04_final.stac-item
2022-11-14 09:22:22	ga_ls9c_ard_3-2-1_090088_2022-11-13_final.stac-item
2022-11-21 11:00:14	ga_ls9c_ard_3-2-1_107070_2022-11-21_final.stac-item
2022-11-21 11:00:38	ga_ls9c_ard_3-2-1_107071_2022-11-21_final.stac-item
2022-12-22 11:58:11	ga_ls9c_ard_3-2-1_116076_2022-12-22_final.stac-item
2023-01-07 11:58:14	ga_ls9c_ard_3-2-1_116076_2023-01-07_final.stac-item
2023-01-11 11:36:41	ga_ls9c_ard_3-2-1_112084_2023-01-11_final.stac-item
2023-01-17 10:53:08	ga_ls9c_ard_3-2-1_106068_2023-01-17_final.stac-item
2023-01-19 10:40:44	ga_ls9c_ard_3-2-1_104068_2023-01-19_final.stac-item
2023-02-01 10:10:48	ga_ls9c_ard_3-2-1_099070_2023-02-01_final.stac-item
2023-02-21 11:24:02	ga_ls9c_ard_3-2-1_111068_2023-02-21_final.stac-item
2023-03-07 09:56:57	ga_ls9c_ard_3-2-1_097067_2023-03-07_final.stac-item
2023-03-10 10:33:47	ga_ls9c_ard_3-2-1_102082_2023-03-10_final.stac-item
2023-03-18 09:39:58	ga_ls9c_ard_3-2-1_094071_2023-03-18_final.stac-item
2023-04-16 10:46:27	ga_ls9c_ard_3-2-1_105068_2023-04-16_final.stac-item
2023-04-28 11:11:30	ga_ls9c_ard_3-2-1_109069_2023-04-28_final.stac-item
2023-04-30 11:01:06	ga_ls9c_ard_3-2-1_107074_2023-04-30_final.stac-item
2023-05-02 09:10:13	ga_ls9c_ard_3-2-1_089075_2023-05-01_final.stac-item
2023-05-19 11:31:02	ga_ls9c_ard_3-2-1_112072_2023-05-19_final.stac-item
2023-06-03 10:48:52	ga_ls9c_ard_3-2-1_105075_2023-06-03_final.stac-item
2023-06-05 10:38:53	ga_ls9c_ard_3-2-1_103081_2023-06-05_final.stac-item
2023-06-12 09:06:54	ga_ls9c_ard_3-2-1_088083_2023-06-11_final.stac-item
2023-06-14 10:27:24	ga_ls9c_ard_3-2-1_102068_2023-06-14_final.stac-item
2023-07-12 10:55:10	ga_ls9c_ard_3-2-1_106075_2023-07-12_final.stac-item
2023-07-19 09:28:28	ga_ls9c_ard_3-2-1_091090_2023-07-18_final.stac-item
2023-08-18 09:33:24	ga_ls9c_ard_3-2-1_093071_2023-08-18_final.stac-item
2023-08-29 09:16:37	ga_ls9c_ard_3-2-1_090075_2023-08-28_final.stac-item
2023-09-04 11:57:45	ga_ls9c_ard_3-2-1_116076_2023-09-04_final.stac-item
2023-09-06 11:47:25	ga_ls9c_ard_3-2-1_114081_2023-09-06_final.stac-item
2023-09-23 09:10:10	ga_ls9c_ard_3-2-1_089074_2023-09-22_final.stac-item
2023-10-05 11:13:50	ga_ls9c_ard_3-2-1_109074_2023-10-05_final.stac-item
2023-11-04 11:24:37	ga_ls9c_ard_3-2-1_111070_2023-11-04_final.stac-item
2023-11-06 09:34:36	ga_ls9c_ard_3-2-1_093073_2023-11-06_final.stac-item
2023-11-18 09:56:59	ga_ls9c_ard_3-2-1_097067_2023-11-18_final.stac-item
2023-11-26 10:49:19	ga_ls9c_ard_3-2-1_105074_2023-11-26_final.stac-item
2023-11-27 09:52:54	ga_ls9c_ard_3-2-1_096072_2023-11-27_final.stac-item
2023-11-29 09:40:32	ga_ls9c_ard_3-2-1_094072_2023-11-29_final.stac-item
2023-12-01 09:29:22	ga_ls9c_ard_3-2-1_092075_2023-11-30_final.stac-item
2023-12-02 10:14:13	ga_ls9c_ard_3-2-1_099079_2023-12-02_final.stac-item
2023-12-03 10:55:52	ga_ls9c_ard_3-2-1_106075_2023-12-03_final.stac-item
2023-12-12 10:50:05	ga_ls9c_ard_3-2-1_105076_2023-12-12_final.stac-item
2023-12-14 10:34:33	ga_ls9c_ard_3-2-1_103068_2023-12-14_final.stac-item
2023-12-17 09:33:23	ga_ls9c_ard_3-2-1_092085_2023-12-17_final.stac-item
2023-12-19 09:22:13	ga_ls9c_ard_3-2-1_090088_2023-12-18_final.stac-item
2023-12-28 10:49:20	ga_ls9c_ard_3-2-1_105074_2023-12-28_final.stac-item
2024-01-04 10:55:50	ga_ls9c_ard_3-2-1_106075_2024-01-04_final.stac-item
2024-01-11 09:23:09	ga_ls9c_ard_3-2-1_091075_2024-01-10_final.stac-item
2024-01-12 10:03:37	ga_ls9c_ard_3-2-1_098068_2024-01-12_final.stac-item
2024-01-18 09:29:44	ga_ls9c_ard_3-2-1_092076_2024-01-17_final.stac-item
2024-01-29 10:49:16	ga_ls9c_ard_3-2-1_105074_2024-01-29_final.stac-item
2024-02-11 10:17:36	ga_ls9c_ard_3-2-1_100072_2024-02-11_final.stac-item
2024-02-11 10:20:00	ga_ls9c_ard_3-2-1_100078_2024-02-11_final.stac-item
2024-02-13 10:03:14	ga_ls9c_ard_3-2-1_098067_2024-02-13_final.stac-item
2024-02-13 10:09:37	ga_ls9c_ard_3-2-1_098083_2024-02-13_final.stac-item
2024-02-15 09:52:26	ga_ls9c_ard_3-2-1_096071_2024-02-15_final.stac-item
2024-02-26 11:13:50	ga_ls9c_ard_3-2-1_109074_2024-02-26_final.stac-item
2024-03-24 09:22:00	ga_ls9c_ard_3-2-1_090088_2024-03-23_final.stac-item
2024-03-24 10:52:54	ga_ls9c_ard_3-2-1_106068_2024-03-24_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