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
2021-12-04 11:05:22	ga_ls9c_ard_3-2-1_107083_2021-12-04_final.stac-item
2021-12-16 11:27:09	ga_ls9c_ard_3-2-1_111076_2021-12-16_final.stac-item
2021-12-18 09:40:18	ga_ls9c_ard_3-2-1_093087_2021-12-18_final.stac-item
2021-12-21 11:45:42	ga_ls9c_ard_3-2-1_114076_2021-12-21_final.stac-item
2022-01-07 10:50:28	ga_ls9c_ard_3-2-1_105077_2022-01-07_final.stac-item
2022-01-08 09:56:50	ga_ls9c_ard_3-2-1_096082_2022-01-08_final.stac-item
2022-01-24 09:52:51	ga_ls9c_ard_3-2-1_096072_2022-01-24_final.stac-item
2022-01-24 09:53:39	ga_ls9c_ard_3-2-1_096074_2022-01-24_final.stac-item
2022-01-30 09:20:34	ga_ls9c_ard_3-2-1_090084_2022-01-29_final.stac-item
2022-01-30 09:22:34	ga_ls9c_ard_3-2-1_090089_2022-01-29_final.stac-item
2022-01-31 10:01:50	ga_ls9c_ard_3-2-1_097079_2022-01-31_final.stac-item
2022-02-06 09:26:44	ga_ls9c_ard_3-2-1_091084_2022-02-05_final.stac-item
2022-02-11 11:18:56	ga_ls9c_ard_3-2-1_110071_2022-02-11_final.stac-item
2022-02-15 10:55:23	ga_ls9c_ard_3-2-1_106074_2022-02-15_final.stac-item
2022-02-27 09:45:52	ga_ls9c_ard_3-2-1_094086_2022-02-27_final.stac-item
2022-03-09 10:20:08	ga_ls9c_ard_3-2-1_100079_2022-03-09_final.stac-item
2022-03-10 09:28:06	ga_ls9c_ard_3-2-1_091088_2022-03-09_final.stac-item
2022-03-10 11:00:12	ga_ls9c_ard_3-2-1_107071_2022-03-10_final.stac-item
2022-03-19 10:53:35	ga_ls9c_ard_3-2-1_106070_2022-03-19_final.stac-item
2022-03-30 10:38:35	ga_ls9c_ard_3-2-1_103079_2022-03-30_final.stac-item
2022-04-03 10:14:16	ga_ls9c_ard_3-2-1_099080_2022-04-03_final.stac-item
2022-04-09 11:17:14	ga_ls9c_ard_3-2-1_109083_2022-04-09_final.stac-item
2022-04-18 11:10:56	ga_ls9c_ard_3-2-1_108083_2022-04-18_final.stac-item
2022-04-25 09:37:47	ga_ls9c_ard_3-2-1_093082_2022-04-25_final.stac-item
2022-05-01 10:33:59	ga_ls9c_ard_3-2-1_103068_2022-05-01_final.stac-item
2022-05-06 10:53:41	ga_ls9c_ard_3-2-1_106071_2022-05-06_final.stac-item
2022-05-18 09:40:10	ga_ls9c_ard_3-2-1_094073_2022-05-18_final.stac-item
2022-05-22 09:19:48	ga_ls9c_ard_3-2-1_090084_2022-05-21_final.stac-item
2022-05-26 10:27:58	ga_ls9c_ard_3-2-1_102069_2022-05-26_final.stac-item
2022-05-26 10:29:58	ga_ls9c_ard_3-2-1_102074_2022-05-26_final.stac-item
2022-05-27 11:12:02	ga_ls9c_ard_3-2-1_109071_2022-05-27_final.stac-item
2022-05-29 11:00:53	ga_ls9c_ard_3-2-1_107074_2022-05-29_final.stac-item
2022-06-14 10:59:46	ga_ls9c_ard_3-2-1_107071_2022-06-14_final.stac-item
2022-06-15 10:04:34	ga_ls9c_ard_3-2-1_098072_2022-06-15_final.stac-item
2022-06-21 09:28:49	ga_ls9c_ard_3-2-1_092075_2022-06-20_final.stac-item
2022-06-23 09:20:31	ga_ls9c_ard_3-2-1_090085_2022-06-22_final.stac-item
2022-06-28 09:39:07	ga_ls9c_ard_3-2-1_093085_2022-06-28_final.stac-item
2022-07-09 09:20:08	ga_ls9c_ard_3-2-1_090084_2022-07-08_final.stac-item
2022-07-17 10:07:34	ga_ls9c_ard_3-2-1_098079_2022-07-17_final.stac-item
2022-07-22 10:25:48	ga_ls9c_ard_3-2-1_101078_2022-07-22_final.stac-item
2022-07-23 09:31:48	ga_ls9c_ard_3-2-1_092082_2022-07-23_final.stac-item
2022-07-28 11:25:18	ga_ls9c_ard_3-2-1_111072_2022-07-28_final.stac-item
2022-08-11 09:58:32	ga_ls9c_ard_3-2-1_097071_2022-08-11_final.stac-item
2022-08-27 10:02:11	ga_ls9c_ard_3-2-1_097080_2022-08-27_final.stac-item
2022-08-31 09:37:04	ga_ls9c_ard_3-2-1_093079_2022-08-31_final.stac-item
2022-09-27 10:55:32	ga_ls9c_ard_3-2-1_106074_2022-09-27_final.stac-item
2022-09-30 09:52:45	ga_ls9c_ard_3-2-1_095087_2022-09-30_final.stac-item
2022-10-03 11:58:09	ga_ls9c_ard_3-2-1_116076_2022-10-03_final.stac-item
2022-10-29 10:54:50	ga_ls9c_ard_3-2-1_106072_2022-10-29_final.stac-item
2022-10-30 11:41:17	ga_ls9c_ard_3-2-1_113080_2022-10-30_final.stac-item
2022-11-01 09:46:26	ga_ls9c_ard_3-2-1_095071_2022-11-01_final.stac-item
2022-11-23 10:47:52	ga_ls9c_ard_3-2-1_105070_2022-11-23_final.stac-item
2022-11-26 11:21:33	ga_ls9c_ard_3-2-1_110077_2022-11-26_final.stac-item
2022-12-01 09:59:34	ga_ls9c_ard_3-2-1_097073_2022-12-01_final.stac-item
2022-12-01 10:04:22	ga_ls9c_ard_3-2-1_097085_2022-12-01_final.stac-item
2022-12-04 10:28:53	ga_ls9c_ard_3-2-1_102069_2022-12-04_final.stac-item
2022-12-06 10:19:20	ga_ls9c_ard_3-2-1_100076_2022-12-06_final.stac-item
2022-12-08 10:03:48	ga_ls9c_ard_3-2-1_098068_2022-12-08_final.stac-item
2022-12-12 09:45:04	ga_ls9c_ard_3-2-1_094083_2022-12-12_final.stac-item
2022-12-29 10:27:07	ga_ls9c_ard_3-2-1_101080_2022-12-29_final.stac-item
2023-01-16 10:13:05	ga_ls9c_ard_3-2-1_099076_2023-01-16_final.stac-item
2023-01-24 09:28:49	ga_ls9c_ard_3-2-1_091089_2023-01-23_final.stac-item
2023-01-25 10:07:19	ga_ls9c_ard_3-2-1_098077_2023-01-25_final.stac-item
2023-01-27 09:53:23	ga_ls9c_ard_3-2-1_096073_2023-01-27_final.stac-item
2023-01-27 11:35:04	ga_ls9c_ard_3-2-1_112080_2023-01-27_final.stac-item
2023-02-07 11:13:26	ga_ls9c_ard_3-2-1_109072_2023-02-07_final.stac-item
2023-02-10 11:45:08	ga_ls9c_ard_3-2-1_114074_2023-02-10_final.stac-item
2023-02-26 10:08:00	ga_ls9c_ard_3-2-1_098079_2023-02-26_final.stac-item
2023-02-27 10:49:40	ga_ls9c_ard_3-2-1_105075_2023-02-27_final.stac-item
2023-03-07 10:01:45	ga_ls9c_ard_3-2-1_097079_2023-03-07_final.stac-item
2023-03-31 09:12:52	ga_ls9c_ard_3-2-1_089081_2023-03-30_final.stac-item
2023-04-06 11:51:57	ga_ls9c_ard_3-2-1_115077_2023-04-06_final.stac-item
2023-04-07 10:54:19	ga_ls9c_ard_3-2-1_106072_2023-04-07_final.stac-item
2023-04-07 10:54:43	ga_ls9c_ard_3-2-1_106073_2023-04-07_final.stac-item
2023-04-13 10:17:58	ga_ls9c_ard_3-2-1_100074_2023-04-13_final.stac-item
2023-04-15 11:44:28	ga_ls9c_ard_3-2-1_114074_2023-04-15_final.stac-item
2023-05-02 10:46:42	ga_ls9c_ard_3-2-1_105069_2023-05-02_final.stac-item
2023-05-05 09:40:40	ga_ls9c_ard_3-2-1_094074_2023-05-05_final.stac-item
2023-05-05 11:18:21	ga_ls9c_ard_3-2-1_110071_2023-05-05_final.stac-item
2023-05-12 09:50:50	ga_ls9c_ard_3-2-1_095084_2023-05-12_final.stac-item
2023-05-14 11:16:56	ga_ls9c_ard_3-2-1_109083_2023-05-14_final.stac-item
2023-05-19 09:51:21	ga_ls9c_ard_3-2-1_096070_2023-05-19_final.stac-item
2023-05-31 10:20:22	ga_ls9c_ard_3-2-1_100081_2023-05-31_final.stac-item
2023-06-03 09:11:59	ga_ls9c_ard_3-2-1_089080_2023-06-02_final.stac-item
2023-06-03 09:12:23	ga_ls9c_ard_3-2-1_089081_2023-06-02_final.stac-item
2023-06-21 10:33:35	ga_ls9c_ard_3-2-1_103068_2023-06-21_final.stac-item
2023-06-22 11:22:49	ga_ls9c_ard_3-2-1_110083_2023-06-22_final.stac-item
2023-07-18 10:16:55	ga_ls9c_ard_3-2-1_100072_2023-07-18_final.stac-item
2023-07-27 11:51:37	ga_ls9c_ard_3-2-1_115077_2023-07-27_final.stac-item
2023-07-28 09:19:56	ga_ls9c_ard_3-2-1_090084_2023-07-27_final.stac-item
2023-07-31 09:51:17	ga_ls9c_ard_3-2-1_095085_2023-07-31_final.stac-item
2023-10-19 11:25:32	ga_ls9c_ard_3-2-1_111072_2023-10-19_final.stac-item
2023-10-24 10:07:11	ga_ls9c_ard_3-2-1_098077_2023-10-24_final.stac-item
2023-10-24 11:47:16	ga_ls9c_ard_3-2-1_114080_2023-10-24_final.stac-item
2023-10-26 09:52:01	ga_ls9c_ard_3-2-1_096070_2023-10-26_final.stac-item
2023-10-26 11:36:05	ga_ls9c_ard_3-2-1_112083_2023-10-26_final.stac-item
2023-11-01 09:19:14	ga_ls9c_ard_3-2-1_090081_2023-10-31_final.stac-item
2023-11-02 09:58:29	ga_ls9c_ard_3-2-1_097071_2023-11-02_final.stac-item
2023-11-15 11:05:43	ga_ls9c_ard_3-2-1_108069_2023-11-15_final.stac-item
2023-11-25 10:06:03	ga_ls9c_ard_3-2-1_098074_2023-11-25_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