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
2021-11-22 09:30:26	ga_ls9c_ard_3-2-1_091089_2021-11-22_final.stac-item
2021-11-23 10:02:26	ga_ls9c_ard_3-2-1_098069_2021-11-23_final.stac-item
2021-12-04 09:27:17	ga_ls9c_ard_3-2-1_091085_2021-12-03_final.stac-item
2021-12-13 09:22:36	ga_ls9c_ard_3-2-1_090089_2021-12-12_final.stac-item
2021-12-19 10:19:11	ga_ls9c_ard_3-2-1_100076_2021-12-19_final.stac-item
2021-12-21 11:45:42	ga_ls9c_ard_3-2-1_114076_2021-12-21_final.stac-item
2021-12-28 11:52:18	ga_ls9c_ard_3-2-1_115077_2021-12-28_final.stac-item
2022-01-14 09:21:43	ga_ls9c_ard_3-2-1_090087_2022-01-13_final.stac-item
2022-01-28 09:29:44	ga_ls9c_ard_3-2-1_092076_2022-01-27_final.stac-item
2022-02-03 10:28:44	ga_ls9c_ard_3-2-1_102069_2022-02-03_final.stac-item
2022-02-03 10:29:08	ga_ls9c_ard_3-2-1_102070_2022-02-03_final.stac-item
2022-02-05 10:20:22	ga_ls9c_ard_3-2-1_100079_2022-02-05_final.stac-item
2022-02-07 11:45:17	ga_ls9c_ard_3-2-1_114075_2022-02-07_final.stac-item
2022-02-12 10:26:06	ga_ls9c_ard_3-2-1_101078_2022-02-12_final.stac-item
2022-03-08 09:40:27	ga_ls9c_ard_3-2-1_093088_2022-03-08_final.stac-item
2022-03-26 11:04:54	ga_ls9c_ard_3-2-1_107083_2022-03-26_final.stac-item
2022-04-02 09:29:24	ga_ls9c_ard_3-2-1_092076_2022-04-01_final.stac-item
2022-04-05 10:00:42	ga_ls9c_ard_3-2-1_097077_2022-04-05_final.stac-item
2022-05-04 11:05:40	ga_ls9c_ard_3-2-1_108070_2022-05-04_final.stac-item
2022-05-29 09:24:47	ga_ls9c_ard_3-2-1_091081_2022-05-28_final.stac-item
2022-05-30 10:07:39	ga_ls9c_ard_3-2-1_098080_2022-05-30_final.stac-item
2022-06-10 11:29:13	ga_ls9c_ard_3-2-1_111083_2022-06-10_final.stac-item
2022-06-21 11:05:43	ga_ls9c_ard_3-2-1_108070_2022-06-21_final.stac-item
2022-07-04 10:39:18	ga_ls9c_ard_3-2-1_103081_2022-07-04_final.stac-item
2022-07-17 10:04:23	ga_ls9c_ard_3-2-1_098071_2022-07-17_final.stac-item
2022-07-21 09:44:55	ga_ls9c_ard_3-2-1_094084_2022-07-21_final.stac-item
2022-07-30 11:16:09	ga_ls9c_ard_3-2-1_109080_2022-07-30_final.stac-item
2022-08-02 10:04:37	ga_ls9c_ard_3-2-1_098071_2022-08-02_final.stac-item
2022-08-08 09:28:48	ga_ls9c_ard_3-2-1_092074_2022-08-07_final.stac-item
2022-08-22 09:40:51	ga_ls9c_ard_3-2-1_094073_2022-08-22_final.stac-item
2022-08-29 11:26:19	ga_ls9c_ard_3-2-1_111074_2022-08-29_final.stac-item
2022-08-30 10:30:18	ga_ls9c_ard_3-2-1_102073_2022-08-30_final.stac-item
2022-08-31 09:39:52	ga_ls9c_ard_3-2-1_093086_2022-08-31_final.stac-item
2022-09-04 10:46:27	ga_ls9c_ard_3-2-1_105067_2022-09-04_final.stac-item
2022-09-07 11:18:56	ga_ls9c_ard_3-2-1_110071_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
2022-10-02 11:14:53	ga_ls9c_ard_3-2-1_109076_2022-10-02_final.stac-item
2022-10-04 09:29:13	ga_ls9c_ard_3-2-1_091090_2022-10-03_final.stac-item
2022-10-13 10:54:00	ga_ls9c_ard_3-2-1_106070_2022-10-13_final.stac-item
2022-10-15 10:46:27	ga_ls9c_ard_3-2-1_104082_2022-10-15_final.stac-item
2022-10-25 09:44:16	ga_ls9c_ard_3-2-1_094081_2022-10-25_final.stac-item
2022-10-30 09:57:12	ga_ls9c_ard_3-2-1_097067_2022-10-30_final.stac-item
2022-11-05 09:28:29	ga_ls9c_ard_3-2-1_091088_2022-11-04_final.stac-item
2022-11-11 10:27:56	ga_ls9c_ard_3-2-1_101082_2022-11-11_final.stac-item
2022-11-12 09:33:55	ga_ls9c_ard_3-2-1_092086_2022-11-12_final.stac-item
2022-11-15 10:03:38	ga_ls9c_ard_3-2-1_097083_2022-11-15_final.stac-item
2022-11-20 10:22:10	ga_ls9c_ard_3-2-1_100083_2022-11-20_final.stac-item
2022-11-22 10:03:49	ga_ls9c_ard_3-2-1_098068_2022-11-22_final.stac-item
2022-11-30 10:55:12	ga_ls9c_ard_3-2-1_106073_2022-11-30_final.stac-item
2022-12-06 10:19:20	ga_ls9c_ard_3-2-1_100076_2022-12-06_final.stac-item
2022-12-09 10:49:03	ga_ls9c_ard_3-2-1_105073_2022-12-09_final.stac-item
2022-12-13 10:23:56	ga_ls9c_ard_3-2-1_101072_2022-12-13_final.stac-item
2022-12-16 09:18:20	ga_ls9c_ard_3-2-1_090078_2022-12-15_final.stac-item
2022-12-17 11:38:53	ga_ls9c_ard_3-2-1_113074_2022-12-17_final.stac-item
2022-12-19 09:52:49	ga_ls9c_ard_3-2-1_095087_2022-12-19_final.stac-item
2022-12-23 11:02:09	ga_ls9c_ard_3-2-1_107075_2022-12-23_final.stac-item
2022-12-24 10:09:43	ga_ls9c_ard_3-2-1_098083_2022-12-24_final.stac-item
2022-12-24 11:45:25	ga_ls9c_ard_3-2-1_114075_2022-12-24_final.stac-item
2022-12-26 11:36:16	ga_ls9c_ard_3-2-1_112083_2022-12-26_final.stac-item
2022-12-29 10:25:07	ga_ls9c_ard_3-2-1_101075_2022-12-29_final.stac-item
2022-12-30 09:33:05	ga_ls9c_ard_3-2-1_092084_2022-12-30_final.stac-item
2023-01-02 10:02:01	ga_ls9c_ard_3-2-1_097079_2023-01-02_final.stac-item
2023-01-03 10:44:52	ga_ls9c_ard_3-2-1_104078_2023-01-03_final.stac-item
2023-01-08 09:26:31	ga_ls9c_ard_3-2-1_091083_2023-01-07_final.stac-item
2023-01-14 10:23:29	ga_ls9c_ard_3-2-1_101071_2023-01-14_final.stac-item
2023-01-14 10:24:41	ga_ls9c_ard_3-2-1_101074_2023-01-14_final.stac-item
2023-01-14 10:25:53	ga_ls9c_ard_3-2-1_101077_2023-01-14_final.stac-item
2023-01-15 11:07:32	ga_ls9c_ard_3-2-1_108073_2023-01-15_final.stac-item
2023-02-17 10:14:45	ga_ls9c_ard_3-2-1_099080_2023-02-17_final.stac-item
2023-03-08 09:07:42	ga_ls9c_ard_3-2-1_088083_2023-03-07_final.stac-item
2023-03-12 11:57:56	ga_ls9c_ard_3-2-1_116076_2023-03-12_final.stac-item
2023-03-13 09:28:37	ga_ls9c_ard_3-2-1_091089_2023-03-12_final.stac-item
2023-03-13 09:29:01	ga_ls9c_ard_3-2-1_091090_2023-03-12_final.stac-item
2023-04-03 11:20:16	ga_ls9c_ard_3-2-1_110075_2023-04-03_final.stac-item
2023-04-05 11:11:05	ga_ls9c_ard_3-2-1_108083_2023-04-05_final.stac-item
2023-04-26 09:52:12	ga_ls9c_ard_3-2-1_095087_2023-04-26_final.stac-item
2023-05-09 10:53:14	ga_ls9c_ard_3-2-1_106070_2023-05-09_final.stac-item
2023-05-15 10:16:55	ga_ls9c_ard_3-2-1_100072_2023-05-15_final.stac-item
2023-05-21 09:44:33	ga_ls9c_ard_3-2-1_094084_2023-05-21_final.stac-item
2023-06-01 09:21:09	ga_ls9c_ard_3-2-1_091072_2023-05-31_final.stac-item
2023-06-24 09:30:22	ga_ls9c_ard_3-2-1_092080_2023-06-24_final.stac-item
2023-06-25 10:15:14	ga_ls9c_ard_3-2-1_099084_2023-06-25_final.stac-item
2023-06-29 09:49:01	ga_ls9c_ard_3-2-1_095080_2023-06-29_final.stac-item
2023-07-05 10:46:32	ga_ls9c_ard_3-2-1_105069_2023-07-05_final.stac-item
2023-07-20 10:02:57	ga_ls9c_ard_3-2-1_098068_2023-07-20_final.stac-item
2023-07-24 11:18:41	ga_ls9c_ard_3-2-1_110072_2023-07-24_final.stac-item
2023-07-27 11:52:49	ga_ls9c_ard_3-2-1_115080_2023-07-27_final.stac-item
2023-07-30 09:06:00	ga_ls9c_ard_3-2-1_088080_2023-07-29_final.stac-item
2023-08-04 10:59:54	ga_ls9c_ard_3-2-1_107071_2023-08-04_final.stac-item
2023-08-15 10:42:12	ga_ls9c_ard_3-2-1_104073_2023-08-15_final.stac-item
2023-10-15 10:11:21	ga_ls9c_ard_3-2-1_099072_2023-10-15_final.stac-item
2023-10-16 09:17:44	ga_ls9c_ard_3-2-1_090077_2023-10-15_final.stac-item
2023-10-16 10:54:13	ga_ls9c_ard_3-2-1_106071_2023-10-16_final.stac-item
2023-10-23 11:00:49	ga_ls9c_ard_3-2-1_107072_2023-10-23_final.stac-item
2023-11-01 10:54:56	ga_ls9c_ard_3-2-1_106073_2023-11-01_final.stac-item
2023-11-04 11:29:48	ga_ls9c_ard_3-2-1_111083_2023-11-04_final.stac-item
2023-11-05 10:29:25	ga_ls9c_ard_3-2-1_102071_2023-11-05_final.stac-item
2023-11-17 09:19:41	ga_ls9c_ard_3-2-1_090082_2023-11-16_final.stac-item
2023-11-22 09:35:07	ga_ls9c_ard_3-2-1_093074_2023-11-22_final.stac-item
2023-11-26 10:47:19	ga_ls9c_ard_3-2-1_105069_2023-11-26_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